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An example of quantitative data is in this letter made out to Boston Mayor Michelle Wu'.

-Posted by Mekhi

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/ CBS Boston

BOSTON - In a letter to Boston Mayor Michelle Wu, several Boston City Councilors are calling for zero tolerance on school violence, and asking the city to beef up police and add more metal detectors in schools. The question is: Do metal detectors in schools really work?

"This year alone there has been a shooting, stabbing, recovered loaded firearms," lists Boston City Councilor Michael Flaherty. "I've seen enough' I've heard enough; we've talked to enough parents; we need to act now."

"My fear is what is it going to take for people to see?" adds fellow Boston City Councilor Erin Murphy.

Of all the school deterrents against weapons, school safety researchers believe they are actually the least commonly used tool. A report out of the WestEd Justice and Prevention Research Center says, as of 2017, New York Schools reported that of the weapons confiscated in a single school year, 57% were found without a scanning device. Furthermore, for every 23,000 students scanned, just one dangerous item was found. The research center also suggests that school staff often lack the training to properly use metal detectors or sometimes have them not working properly.

"Charlestown High, their community, a couple of years ago, their school decided they didn't want to plug their metal detectors in. They had a shooting at graduation, and early this year, they had a loaded gun in the school," says Murphy.

Councilors Murphy and Flaherty say numerous Boston schools choose to leave their detectors unplugged or cast to the side.

"I didn't know it could be a school-by-school basis," adds Murphy, who is also a former Boston Public School teacher.

School safety researchers suggest metal detectors can create long lines to get in or give students a sense of fear.

"There is technology out there with different types of metal detectors and checking for weapons different ways," says Murphy.

Murphy was on a call with Boston Schools Superintendent Mary Skipper on Wednesday morning discussing detection technology alternatives. Brockton High School dealt with logistics issues before they turned to a high-tech weapons detection system over metal detectors. The district says students can just pass through with backpacks, and their system will search for weapons, not just any piece of metal.

"With our $1.4 billion school budget, we need to do a better job communicating," tells Murphy.

Over the past year, Flaherty and Murphy say there have been 744 sexual assaults in Boston schools and 440 cases of bullying.

"Parents and guardians call my office all the time. They are demanding stronger focus on school safety," says Flaherty.

We spoke with Ben Fisher, a professor at the University Of Wisconsin. He has researched security measures in schools.

"You can spend some money and put in metal detectors, or put on a big show of having police dogs some in, but those aren't the things that make schools safe," believes Fisher.

He admits that detectors do help and can catch a weapon, but he says those are one-off situations. They don't help fix the overall issue. He says it is more about building a structure and community at the school that makes students feel safe, heard and have pride in their school and fellow classmates.

"Make sure every student has an adult in the building who they know cares about them," adds Fisher, "Have young people feel like they belong in school and have a stake in the broader school environment."

"If we are able to confiscate a weapon, we can engage that child, that student in a conversation - find out what is happening," adds Flaherty. "It may be a situation of bullying, cyberbullying. It could have been an incident a day or week before. Change the culture of what is happening in Boston Public Schools."

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Question Everything: Do metal detectors at schools really work?

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CBS Boston BOSTON - In a letter to Boston Mayor Michelle Wu, several Boston City Councilors are calling for zero tolerance on school violence, and asking the city to beef up police and add more metal detectors in schools. The question is: Do metal detectors in schools really work?

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This is an article that goes into detail about the statistic of metal detectors and how safe they make students feel.

-Posted by Mekhi

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Home Ask A REL Metal Detectors - What does the research say about the effect of metal detectors and staff identification on creating a safe school environment?

Metal Detectors - What does the research say about the effect of metal detectors and staff identification on creating a safe school environment?

Northwest | January 01, 2021

Metal Detectors

References

Addington, L. (2018). The use of visible security measures in public schools: A review to summarize current literature and guide future research. American University School of Public Affairs Research Paper No. 3240204. Washington, DC: American University. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3240204

From the Abstract:
"Concerns over school violence, particularly deadly school violence, have prompted demands for greater attention to student safety and school security. One response has been an increased use of visible security in public schools in all locations and grade levels. Relatively little, though, is known about the effectiveness of these measures to reduce crime and violence as well as their possible unintended consequences. This article provides a review of the literature concerning trends in the use of visible school security as well as the effect of these measures on specific outcomes including crime, student fear and exclusionary discipline. This review aims to facilitate future research and policy by identifying what is known, what gaps exist and what should be considered in developing a future research agenda to inform policy."

Bachman, R., Randolph, A., & Brown, B. L. (2011). Predicting perceptions of fear at school and going to and from school for African American and White students: The effects of school security measures. Youth & Society, 43(2), 705â€"726. Retrieved from https://citeseerx.ist.psu.edu

From the Abstract:
"This article uses the School Crime Supplement of the National Crime Victimization Survey to investigate the factors related to White and African American students' perceived levels of fear of harm, while at school and while commuting to and from school. Of particular interest were the effects of school security measures, including metal detectors, security guards, locked doors, and surveillance cameras. After controlling for the effects of previous victimizations, security measures, and other contextual and demographic variables, there were no differences in levels of fear across gender and race groups. However, certain predictors of fear differentially affected White and African American students. Previous victimization experiences, including bullying, and the presence of metal detectors increased levels of fear for all groups. Security guards in schools increased levels of fear for White students but not for African American students. African American students attending school in suburban and rural areas were more fearful compared to their central city counterparts, whereas White students were more fearful if they attended school in urban areas. Implications for policy are discussed"

Bracy, N. L. (2011). Student perceptions of high-security school environments. Youth & Society, 43(1), 365â€"395. https://eric.ed.gov/?id=EJ915804 Retrieved from http://ed.buffalo.edu

From the Abstract:
"Public schools have transformed significantly over the past several decades in response to concerns about rising school violence. Today, most public schools are high-security environments employing police officers, security cameras, and metal detectors, as well as strict discipline policies to keep students in line and maintain safe campuses. These changes undoubtedly influence the social climate of schools, yet we know very little about how students experience and perceive these measures. Via ethnographic research in two contemporary public high schools, the author examines students' perceptions of high-security school environments, including perceptions of their school resource officer, schools' discipline policies, punishments, and fairness in rule application. Findings show that students believe their schools to be safe places and think many of the security strategies their schools use are unnecessary. Students further express feeling powerless as a result of the manner in which their schools enforce rules and hand down punishments."

Fisher, B. W., Gardella, J. H., & Tanner-Smith, E. E. (2019). Social control in schools: The relationships between school security measures and informal social control mechanisms. Journal of School Violence, 18(3), 347-361. https://eric.ed.gov

From the Abstract:
"Social control and procedural justice theories indicate that informal social control reduces problem behaviors. However, many schools have implemented formal control mechanisms such as school security measures. This study examines the association between school security measures (security personnel, metal detectors, and surveillance cameras) and students' perceptions of informal social control (relationships with teachers, other school adults, and the fairness and consistency of school rules). We used structural equation modeling to examine these relationships in a nationally representative sample of 6,547 secondary students surveyed as part of the School Crime Supplement to the National Crime Victimization Survey (M age = 14.94; 51% male, 60% White non-Hispanic, 14% Black non-Hispanic, 20% Hispanic). The results indicated that the presence of security personnel in schools was associated with poorer student relationships with teachers. Findings for the other school security measures were nonsignificant or inconsistent across models. Implications for theory and practice are discussed."

Fisher, B. W., Mowen, T. J., & Boman, J. H. (2018). School security measures and longitudinal trends in adolescents' experiences of victimization. Journal of Youth and Adolescence, 47(6), 1221â€"1237. Retrieved from https://www.ncbi.nlm.nih.gov

From the Abstract:
"Although school security measures have become a common fixture in public schools across the United States, research on the relationship between security and adolescent victimization is mixed, with very few studies examining trends in adolescent victimization across time. Using two waves of data from the Educational Longitudinal Study 2002 (N = 7659; 50.6% female; 56.7% White, 13.3% Black, 13.5% Hispanic, 11.3% Asian American, 5.4% other race), results from a series of multi-level models demonstrate that adolescents in schools with more security measures report higher odds of being threatened with harm, and no difference in odds of being in a physical altercation or having something stolen over time. Although prior research has established racial disparities in using school security measures, results demonstrate inconsistent patterns in the extent to which adolescents' race conditions the relationship between security and victimization. The findings are discussed in light of existing theoretical and empirical work, and implications for both research and practice are offered."

Gastic, B. (2011). Metal detectors and feeling safe at school. Education and Urban Society, 43(4), 486â€"498. Retrieved from http://citeseerx.ist.psu.edu

From the Abstract:
"This article argues that metal detectors bestow an organizational stigma to schools. One symptom of this is students' heightened level of fear at school. Using data from the National Longitudinal Study of Adolescent Health (Add Health) and a matched-pair design, this study finds that metal detectors are negatively correlated with students' sense of safety at school, net of the level of violence at school. However, this association is different for urban students. The negative association between metal detectors and urban students' sense of safety is 13% less than what it is for students attending suburban or rural schools."

Hankin, A., Hertz, M., & Simon, T. (2011). Impacts of metal detector use in schools: Insights from 15 years of research. Journal of School Health, 81, 100â€"106. Retrieved from https://static1.squarespace.com

From the Abstract:
"Background: Multiple approaches exist, both in theory and in practice, to reduce young people's risk of violent victimization when they are in school. Among these approaches, a growing number of school districts are choosing to install metal detectors. We sought to review the literature available on the impacts of metal detectors on school violence and perceptions about school violence. Methods: We conducted an extensive literature search, including databases for the medical, public health, sociology, and political science literature. Of 128 papers that met our search criteria, 7 studies met inclusion criteria for the literature review. Results: Each of the papers reviewed utilized data that originated from self-report surveys. Four of the studies consisted of secondary analyses of national databases, with the other 3 utilizing local surveys. The studies varied as to the outcome, ranging from student/staff perceptions of safety at school to student self-reports of weapon carrying and/or victimization, and showed mixed results. Several studies suggested potential detrimental effects of metal detectors on student perceptions of safety. One study showed a significant beneficial effect, linking metal detector use to a decrease in the likelihood that students reported carrying a weapon while in school (7.8% vs 13.8%), without a change in weapon carrying in other settings or a decline in participation in physical fights. Conclusion: There is insufficient data in the literature to determine whether the presence of metal detectors in schools reduces the risk of violent behavior among students, and some research suggests that the presence of metal detectors may detrimentally impact student perceptions of safety."

Jennings, W. G., Khey, D. N., Maskaly, J., & Donner, C. M. (2011). Evaluating the relationship between law enforcement and school security measures and violent crime in schools. Journal of Police Crisis Negotiations, 11(2), 109â€"124. Retrieved from https://www.researchgate.net

From the Abstract:
"School crime is a vital concern, not only for students and faculty, but for administrators, policy makers, criminal justice personnel, and concerned citizens. Efforts to reduce crime and violence at schools have led many schools to adopt preventative strategies aimed at reducing actual crime and fear of crime. These measures include partnering with local police departments and implementing school resource officers, installing video cameras and closed circuit television systems, utilizing weapon-detection systems (e.g., metal detectors), and blocking/restricting access to school facilities with entry-control devices (e.g., electronic key cards). Recognizing these efforts and the limitations of prior research investigating school crime and safety measures, the current study examined the relationship between law enforcement (public or private) and school security measures on the incidence of violence and serious violence in schools using a nationally representative sample. Several key findings emerged. In particular, employing student resource officers and dealing with problems of bullying, racial tensions, student disrespect, and gangs appear promising in mitigating problems on high school campuses across the United States."

Mowen, T. J., & Freng, A. (2019). Is more necessarily better? School security and perceptions of safety among students and parents in the United States. American Journal of Criminal Justice, 44(3), 376â€"394. Retrieved from https://www.ncbi.nlm.nih.gov

From the Abstract:
"The use of security measures within schools has increased dramatically over the past few decades. These proliferations are often touted by teachers, school administrators, politicians, and the public as necessary for improving student safety. Though research in this area is growing, we know little about how increased use of school security measures relates to both student and parental perceptions of school safety. Using data from wave one of the 2002 Educational Longitudinal Study, the current study investigates the relationship between the use of security measures in schools and student and parent assessments of safety. Findings from multi-level models indicate that school security measures are, generally, related to decreased perceptions of safety by both parents and students. Implications of these findings are addressed."

Schildkraut, J., & Grogan, K. (2019). Are metal detectors effective at making schools safer? San Francisco: WestEd. https://eric.ed.gov

From the Abstract:
"With the tragedies of school violence igniting calls for increased safety and security, one popular proposal is to use metal detectors in schools. To address questions about what impact such devices may have on day-to-day safety and on what happens during school violence events, this research brief summarizes what is known about metal detectors in schools and in other settings. The brief discusses: (1) The prevalence of metal detectors in schools; (2) The (in)effectiveness of metal detectors; (3) The cost associated with employing metal detectors; and (4) The potential impact on students and the learning environment as a whole. This is the third brief in the WestEd Justice and Prevention Research Center's "School Safety" series."

Methods

Keywords and Search Strings: The following keywords, subject headings, and search strings were used to search reference databases and other sources: ("Metal detectors" OR "metal detector"), ("Identification badge" OR "identification badges" OR "id badges" OR "id badge" OR "access badges" OR "access badge"), ("School safety" OR "safe schools" OR "safe learning environment" OR ("safe learning environments")

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educational improvement; excellence in education; educational research; statistics; statistical data; statistical surveys; regional educational laboratory program; rel; rigorous studies; fast response projects; no child left behind

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REL Ask A REL | Metal Detectors - What does the research say about the effect of metal detectors and staff identification on creating a safe school environment?

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A stakeholder asked "What does the research say about the effect of metal detectors and staff identification on creating a safe school environment?" The response provides references, referrals, and brief responses in the form of citations.

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This is an interview with an an expert in criminology and their take on the politics of gun regulation in America

-Posted by Mekhi

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This article shares many facts about the gun situation in America

-Posted by Mekhi

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Guns are deeply ingrained in American society and the nation's political debates.

The Second Amendment to the United States Constitution guarantees the right to bear arms, and about a third of U.S. adults say they personally own a gun. At the same time, in response to concerns such as rising gun death rates and mass shootings, President Joe Biden has proposed gun policy legislation that would expand on the bipartisan gun safety bill Congress passed last year.

Here are some key findings about Americans' views of gun ownership, gun policy and other subjects, drawn primarily from a Pew Research Center survey conducted in June 2023.

About four-in-ten U.S. adults say they live in a household with a gun, including 32% who say they personally own one, according to an August report based on our June survey. These numbers are virtually unchanged since the last time we asked this question in 2021.

There are differences in gun ownership rates by political affiliation, gender, community type and other factors.

Republicans and Republican-leaning independents are more than twice as likely as Democrats and Democratic leaners to say they personally own a gun (45% vs. 20%).

40% of men say they own a gun, compared with 25% of women.

47% of adults living in rural areas report personally owning a firearm, as do smaller shares of those who live in suburbs (30%) or urban areas (20%).

38% of White Americans own a gun, compared with smaller shares of Black (24%), Hispanic (20%) and Asian (10%) Americans.

Personal protection tops the list of reasons gun owners give for owning a firearm. About three-quarters (72%) of gun owners say that protection is a major reason they own a gun. Considerably smaller shares say that a major reason they own a gun is for hunting (32%), for sport shooting (30%), as part of a gun collection (15%) or for their job (7%).

The reasons behind gun ownership have changed only modestly since our 2017 survey of attitudes toward gun ownership and gun policies. At that time, 67% of gun owners cited protection as a major reason they owned a firearm.

Gun owners tend to have much more positive feelings about having a gun in the house than non-owners who live with them. For instance, 71% of gun owners say they enjoy owning a gun - but far fewer non-gun owners in gun-owning households (31%) say they enjoy having one in the home. And while 81% of gun owners say owning a gun makes them feel safer, a narrower majority (57%) of non-owners in gun households say the same about having a firearm at home. Non-owners are also more likely than owners to worry about having a gun in the home (27% vs. 12%, respectively).

Feelings about gun ownership also differ by political affiliation, even among those who personally own firearms. Republican gun owners are more likely than Democratic owners to say owning a gun gives them feelings of safety and enjoyment, while Democratic owners are more likely to say they worry about having a gun in the home.

Non-gun owners are split on whether they see themselves owning a firearm in the future. About half (52%) of Americans who don't own a gun say they could never see themselves owning one, while nearly as many (47%) could imagine themselves as gun owners in the future.

Among those who currently do not own a gun:

56% of men say they could see themselves owning a gun one day; 40% of women say the same.

61% of Republicans and 40% of Democrats who don't own a gun say they would consider owning one in the future.

56% of Black non-owners say they could see themselves owning a gun one day, compared with smaller shares of White (48%), Hispanic (40%) and Asian (38%) non-owners.

Americans are evenly split over whether gun ownership does more to increase or decrease safety. About half (49%) say it does more to increase safety by allowing law-abiding citizens to protect themselves, but an equal share say gun ownership does more to reduce safety by giving too many people access to firearms and increasing misuse.

Republicans and Democrats differ on this question: 79% of Republicans say that gun ownership does more to increase safety, while a nearly identical share of Democrats (78%) say that it does more to reduce safety.

Urban and rural Americans also have starkly different views. Among adults who live in urban areas, 64% say gun ownership reduces safety, while 34% say it does more to increase safety. Among those who live in rural areas, 65% say gun ownership increases safety, compared with 33% who say it does more to reduce safety. Those living in the suburbs are about evenly split.

Americans increasingly say that gun violence is a major problem. Six-in-ten U.S. adults say gun violence is a very big problem in the country today, up 9 percentage points from spring 2022.In the survey conducted this June, 23% say gun violence is a moderately big problem, and about two-in-ten say it is either a small problem (13%) or not a problem at all (4%).

Looking ahead, 62% of Americans say they expect the level of gun violence to increase over the next five years. This is double the share who expect it to stay the same (31%). Just 7% expect the level of gun violence to decrease.

A majority of Americans (61%) say it is too easy to legally obtain a gun in this country. Another 30% say the ease of legally obtaining a gun is about right, and 9% say it is too hard to get a gun. Non-gun owners are nearly twice as likely as gun owners to say it is too easy to legally obtain a gun (73% vs. 38%). Meanwhile, gun owners are more than twice as likely as non-owners to say the ease of obtaining a gun is about right (48% vs. 20%).

Partisan and demographic differences also exist on this question. While 86% of Democrats say it is too easy to obtain a gun legally, 34% of Republicans say the same. Most urban (72%) and suburban (63%) dwellers say it's too easy to legally obtain a gun. Rural residents are more divided: 47% say it is too easy, 41% say it is about right and 11% say it is too hard.

About six-in-ten U.S. adults (58%) favor stricter gun laws. Another 26% say that U.S. gun laws are about right, and 15% favor less strict gun laws. The percentage who say these laws should be stricter has fluctuated a bit in recent years. In 2021, 53% favored stricter gun laws, and in 2019, 60% said laws should be stricter.

About a third (32%) of parents with K-12 students say they are very or extremely worried about a shooting ever happening at their children's school, according to a fall 2022 Center survey of parents with at least one child younger than 18. A similar share of K-12 parents (31%) say they are not too or not at all worried about a shooting ever happening at their children's school, while 37% of parents say they are somewhat worried.

Among all parents with children under 18, including those who are not in school, 63% see improving mental health screening and treatment as a very or extremely effective way to prevent school shootings. This is larger than the shares who say the same about having police officers or armed security in schools (49%), banning assault-style weapons (45%), or having metal detectors in schools (41%). Just 24% of parents say allowing teachers and school administrators to carry guns in school would be a very or extremely effective approach, while half say this would be not too or not at all effective.

There is broad partisan agreement on some gun policy proposals, but most are politically divisive, the June 2023 survey found. Majorities of U.S. adults in both partisan coalitions somewhat or strongly favor two policies that would restrict gun access: preventing those with mental illnesses from purchasing guns (88% of Republicans and 89% of Democrats support this) and increasing the minimum age for buying guns to 21 years old (69% of Republicans, 90% of Democrats). Majorities in both parties also oppose allowing people to carry concealed firearms without a permit (60% of Republicans and 91% of Democrats oppose this).

Republicans and Democrats differ on several other proposals. While 85% of Democrats favor banning both assault-style weapons and high-capacity ammunition magazines that hold more than 10 rounds, majorities of Republicans oppose these proposals (57% and 54%, respectively).

Most Republicans, on the other hand, support allowing teachers and school officials to carry guns in K-12 schools (74%) and allowing people to carry concealed guns in more places (71%). These proposals are supported by just 27% and 19% of Democrats, respectively.

Gun ownership is linked with views on gun policies. Americans who own guns are less likely than non-owners to favor restrictions on gun ownership, with a notable exception. Nearly identical majorities of gun owners (87%) and non-owners (89%) favor preventing mentally ill people from buying guns.

Within both parties, differences between gun owners and non-owners are evident - but they are especially stark among Republicans. For example, majorities of Republicans who do not own guns support banning high-capacity ammunition magazines and assault-style weapons, compared with about three-in-ten Republican gun owners.

Among Democrats, majorities of both gun owners and non-owners favor these two proposals, though support is greater among non-owners.

Note: This is an update of a post originally published on Jan. 5, 2016.

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Six-in-ten U.S. adults say gun violence is a very big problem in the country today, up 9 percentage points from spring 2022.

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https://www.linkedin.com/pulse/case-study-influence-internet-teens-dylan-caraker

( Qualitative) This site talkes about multiple case studies and challenges that teens go through while dealing with Internet dangers

https://gitnux.org/internet-dangers-statistics/#:~:text=1%20in%205%20Americans%20have,predicted%20to%20reach%202.5%20billion.

(Quantitative) This website includes the percentage rate that people from all over the world go though and how the Internet is a consistent trouble Globally.

MENTAL HEALTH

https://www.apa.org/depression-guideline/case-examples

(Quantitative) the website goes through different case studies and the situations that all ages, young or old, and the type of situations they go through, regarding their ages.

https://www.questionpro.com/blog/student-survey/

(Qualitative) the issue within mental health is taken by a survey with different ages and it talks about their experience aand how it affects their life and the way they are

challenged with it regardless their age. It shows different scenarios and the type of support systems.

Briana Castillo p5

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(Qualitative) Shows examples of different parenting styles and how it affects children and the house environment.

-Posted by Shama

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Definition/Introduction

When it comes to parenting, there is a great deal of diversity among families. Cultural backgrounds have a major impact on how the family unit exists and how children are reared. In the last several years, the population of the United States of America has had a makeup. Changes driven by immigration (with different cultural, ethnic, and spiritual ideologies), socioeconomic status, and single-parent families are some of the factors that determine a variety of parenting styles among families. As per the 2014 U.S. Census Bureau data, ¼ of children lived in single-parent families, and three-fourths lived in households with two married parents. These patterns differ when race and ethnicity are considered. Although children can thrive in all types of family environments, data suggest that, on average, children living in single-parent families fare less well than their counterparts.

The definition of culture refers to a pattern of social norms, values, language, and behavior shared by individuals. As a result, parents are affected by their culture. When it comes to self-regulation, parenting approaches vary across cultures concerning promoting attention, compliance, delayed gratification, executive function, and effortful control.

Every parent has a different approach in how to interact and guide their children. A child's morals, principles, and conduct are generally established through this bond. Different researchers have grouped parenting styles into three, four, five, or more psychological constructs. This article's content will only focus on four parenting categories: authoritarian, authoritative, permissive, and uninvolved. Every category employs a unique approach to how parents raise their children. Generally, each parent will fall into one of these categories and sometimes have some characteristics from another category. Parenting style can also be situation-dependent.

Issues of Concern

Authoritarian Parenting

Parents of this style tend to have a one-way mode of communication where the parent establishes strict rules that the child obeys. There is little to no room for negotiations from the child, and the rules are not usually explained. They expect their children to uphold these standards while making no errors. Mistakes usually lead to punishment. Authoritarian parents are normally less nurturing and have high expectations with limited flexibility.

Children that grow up with authoritarian parents will usually be the most well-behaved in the room because of the consequences of misbehaving. Additionally, they are better able to adhere to the precise instructions required to reach a goal. Furthermore, this parenting style can result in children who have higher levels of aggression but may also be shy, socially inept, and unable to make their own decisions.[1] This aggression can remain uncontrolled as they have difficulty managing anger as they were not provided with proper guidance. They have poor self-esteem, which further reinforces their inability to make decisions.[2] Strict parental rules and punishments often influence the child to rebel against authority figures as they grow older.

Authoritative Parenting

This type of parent normally develops a close, nurturing relationship with their children. They have clear guidelines for their expectations and explain their reasons associated with disciplinary actions. Disciplinary methods are used as a way of support instead of punishment. Not only can children have input into goals and expectations, but there are also frequent and appropriate levels of communication between the parent and their child. In general, this parenting style leads to the healthiest outcomes for children but requires a lot of patience and effort on both parties.

Authoritative parenting results in children who are confident, responsible, and able to self-regulate.[1][3] They can manage their negative emotions more effectively, which leads to better social outcomes and emotional health. Since these parents also encourage independence, their children will learn that they are capable of accomplishing goals on their own. This results in children who grow up with higher self-esteem. Also, these children have a high level of academic achievement and school performance.[4]

Permissive Parenting

Permissive parents tend to be warm, nurturing and usually have minimal or no expectations. They impose limited rules on their children. Communication remains open, but parents allow their children to figure things out for themselves. These low levels of expectation usually result in rare uses of discipline. They act more like friends than parents.

Limited rules can lead to children with unhealthy eating habits, especially regarding snacks.[5] This can result in increased risks for obesity and other health problems later in the child's life. The child also has a lot of freedom as they decide their bedtime, if or when to do homework, and screen time with the computer and television.[6] Freedom to this degree can lead to other negative habits as the parent does not provide much guidance on moderation. Overall, children of permissive parents usually have some self-esteem and decent social skills. However, they can be impulsive, demanding, selfish, and lack self-regulation.[7][8]

Uninvolved Parenting

Children are given a lot of freedom as this type of parent normally stays out of the way. They fulfill the child's basic needs while generally remaining detached from their child's life. An uninvolved parent does not utilize a particular disciplining style and has a limited amount of communication with their child. They tend to offer a low amount of nurturing while having either few or no expectations of their children.

The children of uninvolved parents usually are resilient and may even be more self-sufficient than children with other types of upbringing. However, these skills are developed out of necessity. Additionally, they might have trouble controlling their emotions, less effective coping strategies, may have academic challenges, and difficulty with maintaining or nurturing social relationships.[9][10]

Clinical Significance

Characteristics of a parent's upbringing style may continue to be prevalent in the child's behaviors and actions as they age. As a child grows older, they can be affected by other factors that further shape their conduct or possibly change it entirely (i.e., therapy, culture, job, and social circle). With regards to health outcomes, it is important to identify which areas of concern are related to the upbringing style of a patient's parents (i.e., the habit of unmonitored snacking) and address the issues at that level. These issues become relatively more important when it comes to behavioral/ psychological intervention.

Becoming culturally competent whenever possible is a great asset for providers who take care of pediatric patients. Understanding the family background, how rules are set, and discipline styles will allow the clinician to understand the dynamics of the family unit. Once the provider is familiarized with the parental rearing techniques, identifying, managing, or referring families will be an easier task.

Nursing, Allied Health, and Interprofessional Team Interventions

Child interventions may require knowledge of their parent's upbringing style, especially if physical or verbal abuse is suspected. Understanding the child's home environment can lead to better patient outcomes as more personalized approaches can be taken towards the child's wellbeing.

References

1.

Masud H, Ahmad MS, Cho KW, Fakhr Z. Parenting Styles and Aggression Among Young Adolescents: A Systematic Review of Literature. Community Ment Health J. 2019 Aug;55(6):1015-1030. [ PubMed: 31102163 ]

2.

Martínez I, García JF. Impact of parenting styles on adolescents' self-esteem and internalization of values in Spain. Span J Psychol. 2007 Nov;10(2):338-48. [ PubMed: 17992960 ]

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9.

Nijhof KS, Engels RC. Parenting styles, coping strategies, and the expression of homesickness. J Adolesc. 2007 Oct;30(5):709-20. [ PubMed: 17258804 ]

10.

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Types of Parenting Styles and Effects On Children

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When it comes to parenting, there is a great deal of diversity among families. Cultural backgrounds have a major impact on how the family unit exists and how children are reared. In the last several years, the population of the United States of America has had a makeup.

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(Quantitative) This site has statistic's that shows who is mostly to be a victim, who it affects, how many it affects etc

-Posted by Shama

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With so many myths surrounding sexual violence and abuse, it can sometimes be hard to know what to believe.

Here are key statistics from trusted sources that show the scale of the problem in England and Wales.

68,109 rapes

were recorded by police between July 2022 and June 2023.

By the end of that 12-month period, charges had been brought in just 2.2% (1,498) of cases. In other words...

Just 2 in 100 rapes recorded by police between July 2022 and June 2023 resulted in someone being charged that same year

And survivors face long waits for their cases to reach a courtroom

After being reported to the police, adult rape cases take an average of more than two years to complete in court.

Meanwhile, there's currently a record number of sexual offence cases that are waiting to go to court: 9,324

And a record number of adult rape cases: 2,376

Join our campaign to cut waiting times

But most survivors don't report it to the police

5 in 6 women who are raped don't report - and the same is true for 4 in 5 men.

Lots of these survivors tell someone else what happened. So, why don't they tell the police?
40% said 'embarrassment' 38% said they didn't think the police could help 34% said they thought it would be humiliating

6.5 million

women in England and Wales

have been raped or sexually assaulted since the age of 16.

9 in 10 girls and young women in schools say:

Sexist name-calling and being sent unwanted 'dick pics' or other images of a sexual nature happens to them or other girls and young women their age.

How can this impact girls and young women?

1 in 2 adult survivors of rape have experienced it more than once.

A sexual violence pandemic

How many women are raped or sexually assaulted every year?

That's 1 in 30 women. So, probably at least one woman you know was raped or sexually assaulted in the last 12 months.
*This figure is for the year ending March 2022.

Learn about rape culture

End rape culture

1 in 3 adults who are raped experience it in their own home

That's why telling women not to walk home by themselves late at night won't fix the sexual violence pandemic.

We must demand an end to gender inequality and to rape culture.

Help us to demand change

Media enquiries

If you're a journalist and would like comment from us on any of these statistics - or more information about the reality of sexual violence and abuse in England and Wales - please contact us.

Email media@rapecrisis.org.uk
Please note that this address is not staffed 24 hours but a member of our team will respond as quickly as possible.

Child sexual abuse

Do the government's promises go far enough?

Not only is child sexual abuse widespread in our society (as the statistics above show), but the treatment of victims and survivors is a source of national shame.

The Home Office has now responded to the Independent Inquiry into Child Sexual Abuse's final report - and made many important commitments.

However, Rape Crisis England & Wales remains concerned that there is a long way to go in addressing the existing problems in social care, health services and the criminal justice system.

Read our full statement

Find a Rape Crisis centre

Our member Rape Crisis centres provide free support and services for victims and survivors of rape, sexual assault, sexual abuse and all forms of sexual violence

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Rape, sexual assault and child sexual abuse statistics

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Want to know how many people are raped, sexually abused or sexually assaulted? We have key statistics from trusted sources showing the scale of the problem.

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(Qualitative) Facts sited by the FBI showing and defining rape cases as well as the website itself

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Definition

In 2013, the FBI UCR Program initiated collection of rape data under a revised definition within the Summary Reporting System. Previously, offense data for forcible rape was collected under the legacy UCR definition: the carnal knowledge of a female forcibly and against her will. Beginning with the 2013 data year, the term "forcible" was removed from the offense title, and the definition was changed. The revised UCR definition of rape is: Penetration, no matter how slight, of the vagina or anus with any body part or object, or oral penetration by a sex organ of another person, without the consent of the victim. Attempts or assaults to commit rape are also included; however, statutory rape and incest are excluded. See Rape Addendum for details.

All rape data submitted in 2013-whether collected under the revised definition or the legacy definition-are presented in this publication. However, because only one year of rape data has been collected under the revised definition, the overview presented here discusses only legacy definition rape data.

Data collection

The UCR Program counts one offense for each victim of a rape, attempted rape, or assault with intent to rape, regardless of the victim's age. Sexual relations without the victim's consent which involves a familial offender is counted as a rape and not an act of incest. All other crimes of a sexual nature are considered to be Part II offenses; as such, the UCR Program collects only arrest data for those crimes. The offense of statutory rape, in which no force is used but the female victim is under the age of consent, is included in the arrest total for the sex offenses category.

For this overview only, the FBI deviated from standard procedure and manually calculated the 2012 and 2013 rates of females raped based on the national female population provided by the U.S. Census Bureau.

Overview

There were an estimated 79,770 rapes (legacy definition) reported to law enforcement in 2013. This estimate was 6.3 percent lower than the 2012 estimate, and 10.6 percent and 16.1 percent lower than the 2009 and 2004 estimates, respectively. (See Tables 1 and 1A.)

The rate of rapes (legacy definition) in 2013 was estimated at 25.2 per 100,000 females.

Expanded rape data

Expanded offense data are the details of the various offenses that the UCR Program collects beyond the count of how many crimes law enforcement agencies report. These details may include the type of weapon used in a crime, type or value of items stolen, and so forth. In addition, expanded data include trends (for example, 2-year comparisons) and rates per 100,000 inhabitants.

Expanded information regarding rape is available in the following tables:

Rates (per 100,000 inhabitants): Tables 16, 17, 18, and 19

What you won't find on this page

Clearance and arrest data for rape.

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Download Printable Document In 2013, the FBI UCR Program initiated collection of rape data under a revised definition within the Summary Reporting System. Previously, offense data for forcible rape was collected under the legacy UCR definition: the carnal knowledge of a female forcibly and against her will.

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(Quantitative) Shows the different numbers of who voted for the best parenting methods as well as who would use them, how to discipline kids and different generations comparation

-Posted by Shama

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With no universal rules or guidance, parenting is often said to be one of the " hardest jobs in the world." While each parent may take a unique approach, psychologists have classified parenting styles into several broad categories based on parents' behaviors and responsiveness toward their children. A recent YouGov survey asked Americans about their experiences with six popular parenting styles to better understand Americans' opinions on the effectiveness of each. More Americans consider an authoritative parenting style to be effective than do any of the other five major styles, and most Americans think parents today aren't tough enough with their children.

Three-quarters (75%) of Americans say the authoritative style of parenting is somewhat or very effective, far ahead of the other five styles polled. By contrast, only 13% of Americans say the same about the uninvolved parenting style. The parenting style that has Americans evenly split is gentle parenting: 46% say this style is effective, and the same share say it is somewhat or very ineffective. That ranks gentle parenting second behind authoritative parenting. Parents of at least one child under 18 years old are more likely to say gentle parenting is effective than are parents of at least one child 18 or older and Americans who have never been parents. Parents who currently have at least one child under 18 also are more likely than parents of at least one child 18 or older to say that helicopter parenting is effective. Parents of younger children are more likely to endorse each parenting style as effective than are non-parents and parents of older children - perhaps a reflection of their younger age, or of their more recent exposure to many styles in and out of their homes.

Reflecting on their own childhood, the largest share of Americans say they were raised with the authoritative style (42%), and a smaller share say they were raised with the authoritarian style. (People could select more than one style for their upbringing.) Women are more likely than men to say their caregivers had an authoritarian style, and adults under 45 are more likely than older adults to say they were raised in the permissive or gentle style.

What styles of parenting do Americans adopt today?

A majority of Americans who are currently parents of at least one child under 18 say they have an authoritative parenting style or a gentle parenting style (51% each), 26% identify their style as authoritarian, 18% as permissive, 15% as helicopter, and 12% as uninvolved. (Parents could select more than one of each style.)

As for Americans who are not currently parents, 52% say they would use an authoritative style if they ever were parents and could choose one or more of the major styles, and 36% say they would use a gentle parenting style.

Aside from the rules associated with each parenting style, parents also decide how much they let their children in on the reasoning behind those rules. On this matter, most Americans agree that parents should explain the reasoning behind rules to children at least sometimes, with only 13% disagreeing with this position. Americans 65 and older are more likely than younger adults to say parents should sometimes or always explain their rules to their children.

Although Americans lean toward the authoritative parenting style in their own parenting - whether real or hypothetical - most say that today's parents are not tough enough when it comes to disciplining their children. Americans 45 and older and parents of at least one child 18 or over are more likely to say that parents are not tough enough today than are adults under 45, parents of at least one child under 18, and Americans who have never been parents.

If parents are not being tough enough, what are punishments that Americans deem appropriate as forms of discipline? Grounding from friends and technology, timeouts, and verbal reprimands are punishments that large majorities of Americans say are occasionally or always acceptable. two in five Americans (44%) also consider spanking to be at least occasionally acceptable, and 15% say the same about slapping. Adults under 30 are less likely than older Americans to find these punishments acceptable, with the exception of slapping: They are more likely than older adults to find slapping acceptable.

- Linley Sanders, Taylor Orth, and Carl Bialik contributed to this article. See the results of this YouGov poll
Methodology: This poll was conducted online on May 9 - 12, 2023 among 1,000 U.S. adult citizens. Respondents were selected from YouGov's opt-in panel using sample matching. A random sample (stratified by gender, age, race, education, geographic region, and voter registration) was selected from the 2019 American Community Survey. The sample was weighted according to gender, age, race, education, 2020 election turnout and presidential vote, baseline party identification, and current voter registration status. Demographic weighting targets come from the 2019 American Community Survey. Baseline party identification is the respondent's most recent answer given prior to March 15, 2022, and is weighted to the estimated distribution at that time (33% Democratic, 28% Republican). The margin of error for the overall sample is approximately 4%.
Image: Pexels (Caleb Oquendo)

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What do Americans think about different parenting styles, and which style did they grow up with? | YouGov

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More Americans consider an authoritative parenting style to be effective than do any of the other five major styles, and most Americans think parents today aren't tough enough with their children.

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Qualitative

This article focuses on the idea of emotional intelligence and the ability to predict success.

https://digitalcommons.liberty.edu/doctoral/4706/

Quantitative

This article compares two generations to discover which of them displays the most emotional intelligence.

Family Dynamics

https://link.springer.com/article/10.1007/S10680-017-9424-6

Qualitative

This article studies the outcomes of children who live in a single parent household and children who live with both parents.

https://www.sciencedirect.com/science/article/pii/S2405844021015383

Quantitative

This article uses the postmodernist ideas to see how families react and plays their role using statistical analysis.

-Alyssa W.

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Abstract

The concept of "emotional intelligence" has been extensively popularized in the lay press and corporate world as individuals purport the potential ability of emotional intelligence to predict various markers of success. Emotional intelligence (EI) most commonly incorporates concepts of emotional expression and regulation, self-awareness, and empathy. The concept has been criticized by some for its loose definition and parallels to personality traits. Additionally, several limitations to the instruments used to measure emotional intelligence have been identified. This review examines the foundations of the definitions of emotional intelligence as well as existing educational research involving emotional intelligence, both within the health professions and externally. Recommendations for future research and research potential are discussed.

Keywords: emotional intelligence, general intelligence, academic success, performance

INTRODUCTION

Most institutions of higher learning and professional disciplines must ascertain predictors of ability or success in order to make student admissions and assessment decisions. Traditional markers of ability and success, such as grade point average (GPA) and standardized test scores, have varying degrees of predictive value.1⁻5 Some institutions employ additional methods to select candidates for admission including but not limited to writing samples, personality inventories, on-site individual interviews, and group interviews.3,6 Colleges and schools of pharmacy are increasingly scrutinizing their student admissions processes for several reasons. A nationwide shortage of pharmacy practitioners has led to the proliferation of new colleges and schools of pharmacy and forced many existing institutions to increase class sizes.7 This turn of events has resulted in greater numbers of candidates for admission and the need for greater scrutiny in these processes as colleges compete for the same applicant pool.7

Paralleling these changes in the dynamics of the profession has been a growing consensus among faculty members that current pharmacy students often lack empathy and a commitment to pharmacy's professional standards.8⁻10 This phenomenon may be occurring for several reasons. With the introduction of several new colleges and schools of pharmacy as well as increasing class sizes, greater competition for the pool of qualified or best applicants can be expected. Colleges and schools may be admitting students who are less prepared or who do not fully understand the profession's role and responsibilities in health care. Alternatively, this perceived change in the profile of pharmacy students may be a result of an amalgam of causes, including cultural and/or societal changes that produce a different type of student.9,10 Today's students may be more concerned with the technical aspects of various professions and more emotionally immature compared to previous generations of learners.9,10 Regardless of the etiology of the changing profile of students, most colleges and schools are struggling to admit the most qualified applicants. Traditional admissions markers may predict successful academic performance but may not capture many intangible characteristics, behavioral variations, and traits that may be more critical to successful pharmacy practice and life in general.11 These intangible characteristics, such as empathy, social maturity, and self-awareness may be essential components required for connecting with and caring for patients. Many corporations have examined and to some extent used emotional intelligence as a measure of these intangible characteristics, which some speculate are better predictors of educational and occupational performance.12,13 Many proponents claim that emotional intelligence may be a distinguishing characteristic of great leaders.12 Recognizing that aspects of emotional intelligence are central to the provision of care, several health professions have experimented with strategies aimed at measuring and/or modifying emotional intelligence. No studies involving emotional intelligence have been reported among cohorts of pharmacy students or pharmacists. This paper will review the foundations and proposed definitions of the concept of emotional intelligence as well as discuss health professions and non-health profession trials and issues in this area.

Emotional Intelligence

The concept of EI has roots in discussions that began as early as the late 1930s, when researchers began describing a non-intellective intelligence sometimes described as "social intelligence."14 EI itself was first defined in the early 1990s by Salvoy and Meyers as "a type of social intelligence that involves the ability to monitor one's own and others' emotions, to discriminate among them, and to use this information to guide one's thinking and actions."15 Salvoy and Meyers expanded their definition to include "the verbal and non-verbal appraisal and expression of emotion, the regulation of emotion in the self and others, and the utilization of emotional content in problem-solving." Conversely, general intelligence has been defined as a person's overall capacity for adaptation through effective cognition and information processing.16 In simpler terms, emotional intelligence might be defined as the set of skills people use to read, understand, and react effectively to emotional signals sent by others and oneself.15 These are skills such as empathy, problem-solving, optimism, and self-awareness which allow people to reflect, react to, and understand various environmental situations.

In assessing any form of intelligence, descriptive models must meet 3 standards.16 First, an intelligence should be capable of reflecting mental performance rather than preferred ways of behaving, a person's self-esteem, or non-intellectual attainments. New forms of intelligence should also meet prescribed correlational criteria. Lastly, intelligence should vary with experience and age. Meeting these criteria would establish emotional intelligence as a set of abilities rather than a preferred way of behaving or a personality trait. Some researchers claim that emotional intelligence meets all 3 of the aforementioned criteria.16,17 Several measures of emotional intelligence have been developed and the various criteria used by different measures may converge.16 In fulfilling the second criterion, some emotional intelligence measures have been validated and appear to have associations with empathy, warmth, and emotional openness.18 Associations with outside criteria such as scholastic aptitude tests also appear to exist. Finally, a reported difference in emotional intelligence scores between adolescents and adults provides support for meeting the final criterion for a new form of intelligence.18,19

Common criticisms of emotional intelligence and emotional intelligence measures are the multitude of qualities encompassed by the concept and its loosely defined nature.20⁻22 Some authors have described overlaps between emotional intelligence models and personality constructs. Therefore, careful analysis is required to determine what is and what is not emotional intelligence. This criticism extends to the instruments used to measure and assess emotional intelligence.22 Various instruments exist and are either self-report (ie, Bar-On EQ-I), ability-based (Multi-Factor Emotional Intelligence Scale [MEIS]), or a combination of these types. No single test is considered to be a gold standard for assessment. Ability-based assessments generally involve hands-on problem sets and require greater resource commitments in terms of cost and time; however, they are considered by most to be more accurate than self-report.22 All of these instruments have been criticized for deficiencies in validity. Strong validity data may be lacking in part due to the varied definitions of the concept of emotional intelligence itself.20⁻22 Without a stringent definition of emotional intelligence, each instrument may be measuring slightly different constructs. Some researchers feel that instruments designed to measure emotional intelligence may actually assess personality characteristics or emotional competence rather than emotional intelligence.20,22

Emotional Intelligence and Academics

Various investigators have engaged in research designed to examine and apply emotional intelligence constructs within academic, medical, and other learning settings (Table ​(Table1). 1 ). A Medline search was conducted to identify literature in this area as it pertains to the health sciences. Additional health science and non-health science research papers were then identified using references listed by primary authors of these studies. Since research in this area as it applies to education is limited, all identified studies were included in this review and the limitations identified.

Table 1

Lam et al investigated the notion that advanced emotional intelligence was correlated with greater individual performance, often above and beyond that associated with one's level of general intelligence.23 Researchers examined a cohort of 304 undergraduate students (152 men and 152 women) at a University in the western United States. Each participant completed the Multifactor Emotional Intelligence Scale (MEIS). The Shipley Institute of Living IQ Scale was used to determine general intelligence. Cognitive-based performance was assessed using 8 problems selected from a previously published logical reasoning test. A demographic questionnaire was also completed by each subject. The mean age of the cohort was 20.8 years and 88.5% of respondents were Caucasian. In order to demonstrate validity, the Shipley Scale IQ was shown to significantly and positively correlate with participant SAT scores. Researchers found that overall emotional intelligence contributed to individual cognitive-based performance over and above the level attributable to general intelligence, and this relationship was positive ( p < 0.01). The study findings are limited in that the use of specific cognitive-based assessments and generalizability may be hampered beyond the situational assessments employed in the study. Additionally, the generalizability of the study is limited by the degree of reliability of the MEIS and the homogeneity of the study sample.

Jaeger studied the effects of emotional intelligence instruction on academic performance among a convenience sample of 150 students in 5 sections of a general management graduate-level course in the northeastern United States.24 Additional data regarding the demographics of the study cohort was not provided by the authors. Students registering for 1 of the 5 sections of the course were blinded to the study goals. In 1 of the 5 sections (intervention group, n = 31), formal instruction regarding emotional intelligence was incorporated into the curriculum. The remaining 4 sections of the course did not have any formal or informal discussion of emotional intelligence. All students completed a preintervention and postintervention Bar-On E-Qi test, but only students in the intervention section were provided with the results and an analysis. Academic performance was measured by the final project course grade achieved by individual students. Final project grades were selected as the dependent measure since in the intervention group these grades would reflect only learning that occurred following the emotional intelligence instruction. Beginning level of knowledge was controlled for through the examination of GPAs for each subject. Teaching effectiveness was also controlled for by using mean scores from teaching evaluations submitted by students at the conclusion of the semester. Using the Games-Howell posthoc test, researchers found statistically significant increases in EQi scores among the students who completed the emotional intelligence curriculum compared with scores of students in the group that was not given the emotional intelligence curriculum, although scores in both groups improved. Mean EQi scores in the emotional intelligence curriculum group improved from 101.16 to 111.06 ( p < 0.001) and in the non-emotional intelligence curriculum group from 101.92 to 103.7 ( p < 0.01). Levels of emotional intelligence at the end of the study period were associated with academic performance, with a greater correlation existing in the emotional intelligence curriculum group. These findings led researchers to conclude that emotional intelligence could be taught or learned and is not a fixed parameter. Additionally, greater levels of emotional intelligence can be expected to correlate with academic performance even when controlling for traditional markers of intelligence, such as GPA. Limitations to this research include the small sample size (particularly of the emotional intelligence curriculum group) and inherent limits of the scales and instruments used in this trial.

Emotional Intelligence and the Health Professions

Health professions have been described as an amalgam of clinical competence and a service-orientation towards caring.25 Aptitudes for a service and caring orientation may be reflected by one's emotional intelligence. Some believe that recent proliferations in technological advances have resulted in an overemphasis on clinical competence and a disproportionate emphasis on service and caring within the health professions. This may certainly be true of pharmacy, in which in the last century modernization of medication production processes and dispensing systems has resulted in a reduced need for individualized compounding and pharmacist-patient interactions.7,26 Only recently has the profession begun to renew its commitment to patient-centered practice.27

All health care professions are rooted in a need to establish therapeutic relationships with patients. Within these relationships, the professional must respond to both the technical aspects of disease as well as associated emotional aspects. A specific example from pharmacy practice might involve recognition that adherence to treatment regimens can be improved not only with attention to a patient's technical needs but also to emotional requirements in fulfilling their therapeutic covenant. The capacity to develop this kind of a relationship (ie, patient-pharmacist) may be facilitated by one's emotional intelligence.25,28⁻29 If this theory holds true and with various managed care and other environmental constraints being placed upon practitioners from all health fields, it may become critical for students in the health professions to have emotional intelligence to provide high-quality patient care.

Recognizing the potential for significant contributions of emotional intelligence to patient outcomes, some suggest that it is important to expect, recognize, develop, and assess emotional intelligence within health professions education. Several researchers have examined various aspects of emotional intelligence and how the concept may relate to the health professions.30⁻35 These studies have taken multiple approaches with regard to the aspects of emotional intelligence examined as well as methods by which emotional intelligence is measured. Some researchers have examined correlates to the admissions process while others have attempted interventional trials aimed at improving emotional intelligence scores. The majority of studies have involved medical and dental students. While the concept of emotional intelligence has been discussed in the nursing literature, no formal trials have been published.25,28 Similarly, little is available in the pharmacy literature.

Some medical schools have experimented with various aspects of measuring and assessing emotional intelligence. As part of the Essentials of Clinical Medicine Course at the Medical College of Georgia, Wagner et al developed a module intended to increase medical students' understanding of emotional and interactional skills and to improve emotional intelligence.30 Students and faculty members who enrolled in the course completed the Bar-On E-Qi and subsequently participated in a lecture series on emotional intelligence. Baseline demographic data for study participants were not reported by the authors. Subsequently, each participant received their EQi scores. Faculty members shared and reflected upon their scores and students were encouraged to do the same. The goals of this process were to allow students to gain a self-awareness of their emotional intelligence strengths and weaknesses and to improve their patient-physician interactions and to provide a more formalized approach to improving patient-physician interactions." No formal statistical or outcome data were collected by the investigator in this pilot study.

Elam et al sought to gather information related to emotional intelligence from entering medical students at the University of Kentucky (UK) College of Medicine.31 Two existing scales, the Trait Meta-Mood Scale (TMMS) and the Davis' Interpersonal Reactivity Index (DIRI), were used to measure emotional intelligence. The TMMS is designed to assess individual differences in abilities to recognize, discriminate, and regulate moods and emotions, while the DIRI is a measure of empathy. Both instruments were administered to the 2000 entering class of the UK College of Medicine (n = 101), with a participation rate of 90%. No background information regarding the study participants was reported. Cronbach alpha assessment demonstrated internal consistency similar to previously published results. The researchers intend to use the garnered information to prospectively monitor the development of communication and interpersonal skills among the cohort. Additionally, students' emotional intelligence scores at admission will be compared to results from standardized patients' assessments of medical interviewing and interaction. The final goal of this project is to identify the characteristics in individuals that determine emotional intelligence and which ultimately result in students becoming more effective physicians. The results of this secondary analysis have not yet been published.

In an effort to identify valid measurements that could be applied within a health professions framework, some researchers have developed and piloted emotional intelligence assessment instruments. Carrothers et al developed and piloted a trial of an emotional intelligence assessment instrument intended for applicants at 3 consortium medical schools.32 Researchers developed a 34-item semantic differential instrument that was intended to measure emotional intelligence constructs. The instrument was based on extensive reviews of the emotional intelligence literature and repeated focus groups involving the admissions committees of the medical schools involved in the project. Information from the pilot test of the emotional intelligence instrument was not used for making any decisions with regard to admission. Using Pearson correlation coefficients, applicant scores on traditional admissions criteria (eg, GPA, interview scores, Aptitude College Test [ACT] scores) were compared with emotional intelligence instrument scores. The instrument was pilot tested, and complete data for analysis were available for 147 applicants. The applicant pool was composed of 83 women and 64 men. ACT score (r2 = 0.084) and GPA (r2 = 0.138) were not well correlated with the emotional intelligence instrument; however, interview assessment scores were correlated with emotional intelligence (r ² = 0.761). In a sub-analysis of emotional intelligence scores categorized by medical school, those applicants who had matriculated from the institution considered to have the strongest requirements in terms of the arts and humanities had the highest overall emotional intelligence scores (mean overall emotional intelligence score of 186.5 versus 177.3 and 182.7). Additionally, variability in emotional intelligence scores at this institution was lower in comparison to the other institutions. Lastly, the authors compared emotional intelligence scores by applicant gender. The presumption in this testing was that women were more competent in interpersonal skills and thus should present with higher emotional intelligence scores. Researchers found that overall emotional intelligence scores were higher among women than men (189.2 vs.176.5). Furthermore, scores for each dimension of the instrument were higher among women with less variance. The authors concluded that based on this pilot study, the emotional intelligence instrument that was developed by the consortium demonstrated the ability to measure attributes that indicate desirable personal and interpersonal skills in medical school applicants. Additionally, emotional intelligence seemed related to educational programs that included a strong emphasis on social sciences and the humanities. This study was limited in that complete admissions data were not available for all applicants, thus the sample size was not completely inclusive. These data are also restricted in that the instrument cannot be used to predict actual medical school performance unless a follow-up analysis is performed.

Even if the importance of emotional intelligence among health professions applicants is validated and ideal assessment instruments are identified, outcome data will need to correlate emotional intelligence capacity and actual outcomes. Outcomes might be defined in one of several ways, including but not limited to patient satisfaction. Wagner et al investigated the relationship between patient satisfaction and physicians' emotional intelligence scores as assessed using the Bar-On EQi instrument.33 Fourteen family medicine faculty members and 16 family medicine residents at a southern US medical school completed the Bar-On EQi. Patients were recruited at the conclusion of an office visit to complete an 11-item patient satisfaction survey. Two scores were derived from the satisfaction survey: the "total satisfaction sum" and the "relationship satisfaction score." The total satisfaction score reflected patients' impressions of their overall health care, while the relationship score was more specific for services provided by their individual physician. Spearman rank order correlation coefficients and t tests were used to examine the relationship between EQi composite and subscale scores and patient satisfaction. The average age of the physician participants was 37.7 years and the average number of years in practice since receiving their medical degree was 8.1 years. The subjects were 232 ambulatory patients, of whom 24% were male and 76% female. Physicians were separated into 2 groups: those with 100% patient-reported relationship satisfaction (n = 11) and those with less than 100% satisfaction (n = 19). When correlating relationship satisfaction scores and Bar-On EQi scores, researchers found that only one EQi subscale (that of the physician's level of "happiness") had a weak correlation with patients' higher satisfaction. The "happiness" subscale most closely correlated with physician mood. This was not a surprising finding given that a physician's mood will often be transmitted to patients. This study was limited by the constructs used to define patient satisfaction (eg, 100% satisfaction) and the study's small sample size, which could only detect large effects. Despite this limitation, the researchers concluded that a health care professional's satisfaction with his/her own life and his/her personal happiness is a component in maximizing a patient's satisfaction with health care services.

Lastly, some investigators have examined relationships between emotional intelligence and the capacity to cope with stress. Since health professions education and training is associated with strenuous academic and non-academic demands and stressors, increased emotional intelligence might result in better stress coping mechanisms and thereby augment performance and/or lifestyle. Using a cross-sectional survey design, Pau et al investigated the relationship between emotional intelligence and perceived stress among a cohort of dental undergraduates.34 Emotional intelligence was assessed using a validated instrument developed by Schuette et al, while perceived stress was measured using the Perceived Stress Scales (PSS-10).35 T tests were used to compare mean scores. Two hundred and thirteen respondents completed the survey instrument for a response rate of 70%. Forty-eight percent of respondents were male and the mean age of the total sample was 21.3 years. Mean emotional intelligence and perceived stress scores were 117.5 (SD = 14.9) and 17.7 (SD = 6.5), respectively. The mean population norms for the PSS-10 scale is 13.0. Internal consistency (as determined by Cronbach's alpha assessment) for the emotional intelligence scale and PSS-10 were 0.9 and 0.86, respectively. Mean emotional intelligence scores of the women were significantly higher than those of the men (p < 0.05). Mean perceived stress scores were higher in students over 21 years of age ( p < 0.001), female students (p < 0.05), and those in higher years of school ( p < 0.001). Correlational analysis demonstrated that emotional intelligence scale scores were inversely related to PSS-10 scores. Researchers concluded that dental students with greater degrees of emotional intelligence may be more adept at coping and dealing with academic and non-academic stressful situations, and that reducing perceived stress may improve academic performance as well as patient satisfaction. The authors emphasize that modalities for improving emotional intelligence of dental students might also augment stress coping mechanisms. This study was limited by its cross-sectional design, which involved a convenience sample of a single academic institution.

In a follow-up report, Pau et al examined how dental undergraduates with differing levels of emotional intelligence dealt with stress.35 Researchers selected a population of undergraduate dental students from a 5-year program and used the emotional intelligence scale by Schuette et al to determine emotional intelligence scores.19 Subjects were then stratified into high and low emotional intelligence score groups using median scores as breakpoints. From each emotional intelligence group in each academic year, 1 male and 1 female student were randomly selected to comprise a cohort of 10 subjects that represented all 5 years of the dental program. Each subject then underwent focused, in-depth, face-to-face interviews with blinded interviewers for the purposes of identifying predictors and coping mechanisms related to stress for each student. Each interview was then systematically transcribed and qualitatively analyzed. Four sets of coping strategies adopted at varying degrees of emotional intelligence were identified. Students with high emotional intelligence were more likely to adopt reflection and appraisal, social and intrapersonal, and organization and time-management skills. Students with low emotional intelligence were more likely to engage in health damaging behaviors (eg, procrastinating, social withdrawal, use of tobacco products). The study authors concluded that future research was needed to establish whether modalities aimed at enhancing emotional intelligence in dental students would result in better stress coping skills. This study was limited by its small sample size and the qualitative nature of the data and analysis.

DISCUSSION

While the corporate world seems to have embraced the concept of emotional intelligence as a predictor of worker success, this is less true within the health professions where research is lacking and a greater level of scrutiny can be expected. This is especially evident in pharmacy. A more natural relationship which predicts success might exist within the health professions, where if accepted as a construct, emotional intelligence may prove to be critical for the development of productive therapeutic pharmacist-patient relationships.

In order for pharmacists and pharmacy students to successfully provide care of any type, they must cultivate patient interactions that engender trust, empathy, and self-awareness. Additionally, the dynamic nature of the pharmacy profession, which in recent years has undergone both educational and professional paradigm shifts, may be best served by students and practitioners who can manage emotions, adapt to change, and manipulate stressful environments and situations. Whether emotional intelligence is a predictor of these skill sets has not been well described. Lack of research in this area by pharmacy and other health professions may be for one of several reasons. Most health professions have a long-standing history of relying upon traditional markers of intelligence to both predict successful completion of a degree program and to determine individual mastery of topics. Traditional measures have been used with relative reliability in predicting technical success for several years.1⁻5 Often the use of newer, less traditional measures is met with resistance and questions of reliability and other limitations.

Potential researchers in this area should have a critical understanding of the underpinnings of the emotional intelligence debate. Many psychologists and intelligence experts fail to find differences between emotional intelligence and personality constructs and often identify the loosely defined nature of emotional intelligence as a major impediment to acceptance of the concept.21⁻23 Others support the notion that existing data and research in this area are sufficiently robust to justify acceptance of emotional intelligence or at a minimum support of ongoing research in this area.15⁻18 Both groups recognize the need to embrace a single definition and the need for better assessment instruments and measures.

Most instruments designed to measure emotional intelligence are either self-report scales or performance-based evaluations involving the completion of observed problem sets.19,22 Performance-based assessments may provide better reliability since they assess demonstrated ability-based skills rather than self-reports; however, they are generally more costly and time consuming to perform. Additionally, performance-based tests are hindered by the objectivity in selecting what are considered correct responses to the problem sets posed to the test subjects. Self-report scales must be understandable to the test subject and are prone to response biases such as social desirability effects which may result in exaggerated responses. Self-report reliability may be increased by combining self-responses with peer assessments.22 However, this introduces several research issues as well as the need for increased resources. All assessment instruments may be hindered by the loosely defined nature of emotional intelligence which makes concrete criteria for measurements difficult to define. Nevertheless, several instruments are available and researchers should recognize the limitations of both self-report and performance-based measures and the specific instrument from either category that is selected for use. Table ​Table2 2 lists some of the more commonly cited and available instruments for assessing emotional intelligence. Additionally, research examining emotional intelligence should attempt to exclude as many confounders as possible. As a minimum, some have suggested that any research involving measurement of emotional intelligence should also include an analysis of academic success markers, personality (eg, the Big Five test), and technical knowledge.

Table 2

CONCLUSION

Several potential implications regarding emotional intelligence exist for all health professions including pharmacy. Various studies examining emotional intelligence in other health professions have been conducted. No studies have examined the concept of emotional intelligence within the framework of pharmacy or pharmacy education. Given the current external environment of the profession, which includes pressures to increase student enrollment, the advent of several new colleges and schools of pharmacy, and a professional recommitment to patient-centered practice, the prospect of using emotional intelligence measures as a predictor of success or capacity to provide care is attractive. Some information can be garnered from educational research conducted by colleagues in medical and dental fields. However, prior to advocating research in this area, several issues must be addressed, including establishing a clear definition of emotional intelligence and assessing the validity and reliability of existing measurement instruments. If these limitations to studying emotional intelligence are eventually addressed, a new marker or modifiable factor that will allow colleges and schools of pharmacy to graduate students, and subsequently practitioners, with the skills and desire to engage in meaningful therapeutic relationships might be identified.

REFERENCES

4. Kidd RS, Latif DA. An evaluation of traditional and novel predictors of didactic and professional practice success of pharmacy students. Am J Pharm Educ. 2003:67. Article 109. [ Google Scholar]

6. Latif DA. Using the structured interview for a more reliable assessment of pharmacy student applicants. Am J Pharm Educ. 2004:68. Article 21. [ Google Scholar]

8. Hammer DP, Berger BA, Beardsley RS, Easton MR. Student professionalism. Am J Pharm Educ. 2003:67. Article 96. [ Google Scholar]

12. Goleman D. Working With Emotional Intelligence. New York: Bantom Books; 1998. [ Google Scholar]

Articles from American Journal of Pharmaceutical Education are provided here courtesy of American Association of Colleges of Pharmacy

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Emotional Intelligence as a Predictor of Academic and/or Professional Success

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The concept of "emotional intelligence" has been extensively popularized in the lay press and corporate world as individuals purport the potential ability of emotional intelligence to predict various markers of success. Emotional intelligence ...

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The article talks about the divorce rate in 2023. The article uses quantitative data to show how frequently marriages ended in divorce.

-Tyrone D. P5

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In 2023, approximately 50% of all marriages will end in divorce

Subsequent marriages have an even higher chance of ending up in divorce, with 60 and 73% of second and third marriages ending up in divorce respectively

The divorce rate for every 10 out of 1,000 people in the population (called the crude divorce rate), however, has dropped from 5 to 2.9 from 1990 to 2023

The marriage rate has almost halved in the last 30 years, with 10 for 1,000 people of the population choosing to tie the knot in 1990 versus only 5 for every 1,000 people in 2023 (called the 'crude marriage rate')

Bartenders and flight attendants are some of the most likely professions to divorce at 52.7 and 50.5% respectively, while scientists are some of the least likely at just 19%

The US has the 6th highest divorce rate in the World

Marriage and Divorce Statistics in Detail

Today we are diving into the fascinating world of marriage and divorce statistics.

Whether you have yet to walk down the aisle or have long since tied the knot, it's in your best interest to be familiar with these statistics as the data has been painting a rather bleak picture over the last 30 years.

We'll be examining the numbers behind marriage and divorce and learn about marriage and divorce trends over the years and how the attitudes and behaviors towards marital status have changed.

Some will be very different from what you thought and many divorce statistics will challenge your predetermined misconceptions on marriage rates and divorce rates.

Things like ethnicity, religion, politics, and even what state you live in can make a huge difference to what part of a marriage and divorce survey you fall into. Age too plays a big part in the likelihood of you ending up getting divorced. Read on to find out whether you improve your chances of a happy relationship the younger or older you marry.

Marriage And Divorce Statistics By Year

Marriage

Source: Statista.com

As can be seen, the overall trend for the last thirty years is the fact that the marriage rate has gone down practically halved.

While in some years that rate did increase, by and large, year after year that rate fell consistently.

There was one passage of time recently that bucked that trend, which saw the years from 2013 to 2016 display a rising rate of marriage, year on year. This was quickly reversed with the onset of the global pandemic which resulted in a further rapid drop in the marriage rate.

Divorce

This is perhaps one of the clearest trends that show how divorce decreases have been a fairly constant occurrence in the United States over the last thirty years. We started the 90's seeing the crude divorce rate rise to almost 5 in every 1,000 of the population. At the end of 2018, that had fallen to just under 3.

In fact, more surprising still is that the divorce rate continually decreased or stayed the same almost every year. There were only three years, 1992, 2006, and 2010, where the divorce rate went up. Even then it was a minimal uptick before returning to the downward trend that characterized the last thirty years.

These numbers in this graph take into account all marriages. It does not only take into account a person's first marriage but instead any divorce - regardless of the number of marriages a person has had in the past - is counted to gather the overall divorce rate in the United States over the last three decades.

This graph shows the fact that in the first 14 years of the new millennium, fewer couples were getting divorced, but equally, fewer people were getting married in the first place. In fact, the number of marriages taking place decreased at a rate that was quicker and bigger than the amount that divorce decreases in this sample.

Marriage And Divorce Demographics In The U.S.

A. Comparing Other Countries

Here we see countries with the highest crude divorce rate. We can see that Russia far outstrips all the other countries listed, with nearby Belarus also being close in divorce rate as well as geographically speaking. The Gibraltar entry is an interesting statistic and one that could well be skewed due to the jurisdiction and legal issues of actual divorce proceedings. It is a very small country, belonging to the UK.

It does, however, share the same divorce rate as the US, who is consequently a joint third in the world when it comes to divorce rates. However, it is a big jump from Russia's rate of 4.8 to 3.2. Hungary, who is the last entry on the Top 20 comes in at just 2.4 points towards the fact that the divorce rates in other countries are actually pretty low.

In addition, the graph below shows how the marriage rate is in decline all around the world. Argentina is the country with the steepest decline with Australia's marriage rate declining by a smaller amount than others in the last 20 years.

B. By Age

Here we look at the marital status and those that are still in their first marriages. This graph points to why a first marriage may cease to be. It looks at those that end in divorce, but also those take into account the marriages that end due to death.

It is perhaps unsurprising that the amount of people in their first marriage decreases at a quicker rate after the age of 75 when the amount of people widowed sees a sharp increase. Other sharp increases include the first marriage rate after the age of 20 which then tails off when people hit their mid-30s.

The divorce rate lags behind the first marriage rate at all times, but picks up speed after the age of 25 and only starts to decrease when people get to the age of 65 - when death starts to become a bigger reason for the number of people in their first marriage to decrease.

The graph above shows the average age of women when they marry. As can clearly be seen, in the majority of cases in any country, the average age is rising. The only exceptions are Nigeria, Iran, Bangladesh, and for a long while Zimbabwe. In those countries, the average age has only declined by a year or so.

However, in the countries that have seen an upward trend in the average age of women at marriage, that age has gone up at a much quicker and higher amount. Portugal is the most notable example of this that has seen its women have an average age of 31 years old in 2017 in comparison to 26 just 14 years ago in 2003.

In comparison, in Nigeria, the average age of women was around 17 in 2006 and that has decreased to around 16 and a half by 2015. There is no later date for that country, however.

The table above also gives more exact figures behind the age of people and how likely to get divorced they are. It also takes into account gender which puts forward some very interesting marriage and divorce stats.

For example, if a woman under 20 years old gets married, there is a 27.6% chance that her marriage will end in divorce. However, if you are a man of the same age, that falls to just under 12% chance to get divorced.

The age that both genders are most likely to get divorced is in the early 20s, which is perhaps unsurprising. In fact, this means that if you are married before you are 24, there is over 50% divorce rate. However, if you marry in your late 30s this drops right down to 5.1% for women, and 6.5% for men.

C. By State

These pictorial depictions of the divorce rate and marriage rates per state show information on which states have higher than average marriage and divorce data. It shows that there are a number of states that have both a higher marriage rate as well as a divorce rate, while other states have both a lower marriage rate and divorce rate.

Texas, for example, is a state that suffers from a statistically higher amount of marriage and divorce, while California has a statistically lower amount of marriage and divorce throughout the state.

D. By Profession/Occupation

Perhaps unsurprisingly, the jobs that have the lowest divorce rates are the ones that require a person to be at home a lot - or at least in charge of their own spare time so that they can provide consistency to their marriage.

These jobs are also consistent in nature and, while they will always come with their own stresses, they may not be as risky or dangerous as some of the jobs that exhibit a high divorce rate.

For example, an actuary will most likely know his or her deadlines and when their job may become more stressful. However, a gaming manager, bartender, or flight attendant is likely to be away from home an awful lot which will inevitably put a great deal of strain on any marriage - however strong.

These two graphs go to show the effects that unemployment will have on couples. The data clearly shows that men and women are more likely to see their marriage come to an end and get a divorce if they are unemployed.

Interestingly, it seems to not materially matter what gender you are either for the impact of unemployment to negatively affect a marriage.

In the below graphs, the female line is blue. It shows that there is more of a difference between the number of men and women who are divorced or married more than once if they are employed. For those that are not in the labor force, a man is more likely to be divorced or married more than once.

E. Ethnicity

This graph shows that mixed-race couples are still much rarer than any other pairing of marriage in the states. They make up a tiny percentage of the overall figure. The biggest group here is clearly couples made up of purely white, with Hispanic couples being the next biggest set of marriages characterized by ethnicity.

F. Religion

Interestingly, when it comes to religion, there isn't one that stands out from the crowd in terms of a higher than average divorce rate.

According to data by Pew, historically black protestants are more likely to be divorced with Mormons and Hindus the least likely to have ended their marriage. Across the board of religions and those that don't believe in anything, marriage is evidently an important marital status with a good proportion of all beliefs being married.

G. Education

These graphs display information to do with who women marry and who men marry according to education.

Largely speaking, women tend to marry people with similar educational backgrounds - with a couple of anomalies. If a woman has a Ph.D., 33% of them will marry a man with a BA as opposed to 25% with a matching Ph.D. Additionally, if a woman has a Prof. degree, she is likely to be married to a man with a BA 41% of the time as opposed to 30% of the time when he has a corresponding Prof. degree like her. Men display broadly the same educational statistics and data as shown by this graphical information.

The following graphs show that both men are women are more likely to get a divorce or be in their second or higher marriage if their education is of high school standard or less.

In all categories - high school education, bachelor's dress, or an advanced qualification, women tend to have a lower divorce rate. However, they do not vary from each other too much in any of those categories. At most, women are 5% less likely to be divorced or onto their next marriage if they have an advanced degree - in comparison to men.

H. Political Views

While it remains to be seen whether Republicans or Democrats have a higher or lower divorce rate, or a higher or lower marriage rate, without a doubt, if a couple has differing political views they are more inclined to get a divorce.

Staying happy in a marriage where political and ideological views materially diverge is always going to be an uphill struggle. Couples will find it difficult for political debates not to descend into full-blown arguments that can be hard to come back from.

I. Marital Status At The Time

It is interesting to look at how the marital status of a person can change the amount of divorce is seen.

The number of first marriages that end in divorce is 42%. While that seems quite high, it goes up dramatically if a person remarries for a second time, and even more so if they get married for a third. 60% of second marriages end in divorce, while a huge 73% of people who get married for the third time, get divorced to end the marriage. They are the most likely to get hitched again, but also the most likely to see their marriages end too.

Same-Sex Marriage

Same-sex marriage is a relatively new idea across many countries. Here, this graph looks at how widely accepted that idea is, and how that level of acceptance has changed in the last thirty years.

It is clear that, while an ever-changing rate of acceptance, there has been a clear change in people's views across the country. More people now accept same-sex marriage and feel that it should be recognized by law. In fact, only 27% of people thought it should be valid in 1996, compared to 63% now. On the whole, that number has always risen over the last three decades, with it only decreasing in four years.

When considering the view that same-sex couples should not have their marriage recognized by law, this number has come down from 68% in 1996 to 36% now. Again, on the whole, that number has regularly decreased, only rising on five occasions.

Is Divorce Acceptable?

Looking at people's approaches and attitudes to marriage and divorce can be an interesting debate topic. People's attitudes to marriage and divorce have changed greatly over the years - presumably as religion starts to take less of a dogmatic influence in our lives.

Here, in this graph, we see that the majority of the population think that marriages that end in divorce are morally acceptable situations. Those who are against divorce entirely make up a fifth of the population, while 3% believe it depends on the situation, and 1% having no opinion on the matter entirely.

When Do Couples End Up In Divorce

Here, we look at marriage and divorce by state in terms of how long each state's average marriage lasts for. It is clear to see that South Dakota and West Virginia have the best success rate when it comes to the length of a marriage before ending in divorce.

The North East in general seems to have more success when it comes to an overall region having longer marriages of about 20 years and higher. Main, New Hampshire, and Vermont, as well as Wisconsin and Pennsylvania, all have long marriages.

The states that have the lowest median marriage numbers are Nevada and Utah who have marriages that last around 16 years on average. Colorado and Texas also have marriages that last around 17 years long.

Here we look more exactly at how long people are married for before their marriage starts to become a divorce statistic. For a first marriage, males will usually be married for almost 8 years, with women being about the same.

However, for the second marriage, the length of time that two people stay together before they get divorced is less - males will get divorced after 7.3 years, with women seeking a divorce after 6.8 years.

Factors That Affect The Decision To Divorce

There are a number of reasons why some marriages end and why others seek a divorce. Here, we look at what increases your risk of a divorce and what makes couples less likely to add to the divorce rate.

The information gathered by McKinley Irvin recently underlines the fact that age has a massive part to play in increasing or decreasing the amount of couples who divorce. The younger that two people move in together or decide to marry, the more likely they are to break up and divorce.

Another information that was found to increase the chances of divorce is if you work within a company that has more people of the opposite sex. This could mean a couple of things - there is more daily temptation for a person who can see that there may be life in another relationship. This does not mean they necessarily commit adultery, but it may just give them hope that they can be happy with another person. Also, if you have many friends or family members who have recently gone through a divorce, you are more likely to take the same decision.

Religion can also play a part - if you live somewhere that has a very high population of Protestants, you increase your risk of divorce. Other curious data include the fact that the bigger the ring or the wedding, the shorter the or less successful the marriage. Finally, if you marry someone considerably younger or older than you, you are vastly increasing your chances of your marriage ending in divorce.

However, there are many ways that you can become less likely to get a divorce. For starters, if you decide to marry or live with your partner after the age of 23, this seems to make your changes of having a happy marital status much better.

Divorce rates also decrease if you have been to college as well as if you choose to have a baby after you marry. Money also plays a big part in that if you have an income of over $25,000 you materially improve your chances of not adding to divorce rates. Finally, if your parents are still together then your marriage is much less likely to end in divorce.

Celebrity Divorces

Celebrity divorces seem far more common than everyday divorces. Whether there is data to actually back up that information is unclear. Perhaps the reason that they seem more common is simply that they are in the media a lot more and broadcast for us all to read about - whereas an average person's divorce is most likely to get no coverage at all. In fact, many of those who see their marriage result in divorce probably do their best to keep it as private as possible.

Celebrity divorces are interesting, however, in terms of how much money the divorce settlement ends up being. Marriage and divorce sadly come down to a financial sum for many marriages and those fighting the legal battle.

One of the most expensive divorces in history came at the marriage end of Ruper and Anna Murdoch. This saw Anna Murcdoch walk away with $1.7billion. Jeff Bezos has also recently divorced his wife for an eye-watering amount which was one of the most talked-about divorces ever seen.

Another much-spoken about marriage and divorce was between Tiger Woods and his then-wife Elin Nordegren. His countless indiscretions finally came back to haunt him and the once golden boy of the sporting world saw both his fame and fortune in tatters. He was the first billionaire sportsman, but when his wife walked away with over $100million, it was more than his reputation that had been badly hit.

Social Media And Divorce

In the last 20 years, since the mass usage by the population of social media platforms like Facebook and Twitter, relationships have been affected in many different ways. Firstly, people can use social media platforms to get together in the first place. This can mean using dating apps or simply approaching a person over their social media page. Platforms also give people the opportunity to chat with each other which can help form connections that otherwise may not have come about.

However, social media usage, itself, can have a negative effect on couples. There is a lot of data and information available that goes to show that marriage and divorce can be a victim of both how much a person uses social media but also what they use it for.

Information gathered by McKinley Irvin shows that one in three divorces start due to one of the individuals starting a relationship online. In terms of arguments over usage, 25% of all couples will argue about how much one of them is using Facebook each week.

This usage then translates into annoyance and hurt over that social media activity with one in seven in a marriage thinking about divorce because of that very behavior. It is also very common for couples to hit the rocks after a person discovers something about their partner through their own Facebook account.

While this won't always mean that they discover infidelity (check our article on infidelity statistics to find more information on that), many couples ( 14%) use their partner's social media accounts for data and information on their cheating for divorce proceedings.

Why Do People Get Married?

So why do people agree to marriage in the first place if the divorce rate is so high - even for the first marriage? Perhaps reassuringly, 88% admit to getting married for love and with a big 81% of those in marriage saying they wanted to make a lifelong commitment.

At the other end of the scale, 23% of married couples marry, according to information collated by Pew Research, for legal rights or benefits.

Additionally, the data shows that 28% of people marry for financial stability. While it's reassuring to know that so many people marry because they are couples in love, with 23% of people marrying for benefits with a huge 28% marrying for financial stability, the information points out that a quarter to a third of all marriages takes place for reasons other than love, commitment, and companionship.

Finally, this information highlights how having children is also a driving force behind improving your marital status. Whether people are getting married because they have children so they want to marry for the sake of them or whether they are getting married because they want to have children in the future is unclear from this information. However, it is clear that children are a major factor behind couples walking down the aisle.

Most Common Reasons For Divorce

There are many common reasons for any number of marriages ending in divorce. Divorce rates increase when either one of the couples believes that the other has a distinct lack of commitment. This has obvious implications on the happiness of both people within marriage and divorce often follows as a consequence.

Another obvious reason for divorce that won't surprise many people is if there has been infidelity or any extramarital affairs. However, there was also a large number of people claiming that they got married too young and that also they simply argued too much so divorce seemed like their only option. Financial problems were also the other biggest cause of a divorce, with a couple agreeing 50% of the time that this was a major issue in the breakdown of their marriage.

Another data collated by WF lawyers is also information that points to why marriage and divorce may occur between two people. Lack of commitment is, again, the most common issue that will bring about the end of a marriage, and arguing too much is the second most common problem. Infidelity again is another big driver of the divorce rate with over half of all divorces occurring due to a person's cheating or alleged infidelity.

How Your Parents' Relationship Affects Your Own Marriage

Marriage and divorce in a parents' relationship can materially affect a person's own marriage and divorce rate. If a person comes from a broken marriage, whether it is the first marriage or not, they are more likely to see their marital status end in divorce too.

It is often because they will not have had the right experience of a marriage that works constructively to remain happy overall. Marriage and divorce are both largely dependent on how well a couple can communicate with one another. If they can't communicate well, they will more likely be a marriage that ends in divorce. If someone hasn't seen firsthand how to communicate properly, but instead only sees how to communicate poorly - that is what they will learn from.

Additionally, coming from a broken marriage also makes a person far more likely to suffer from commitment issues as well as have a fear of intimacy that can also lead to a fear of abandonment that materially reduces their ability to be in a long-lasting, happy relationship.

Children are often a sum total of the inputs that they saw in their formative years. If those children did not have a good example of a healthy relationship - however good the intentions of their parents were - they are far more likely to be unable to be in a happy marriage in the future.

How It Affects The Children

One thing that seems common across all divorce is that parents either have tried to save their marriage for the sake of the kids or at least if a divorce is going ahead, they want to ensure that the ending of the marriage and divorce proceedings don't negatively affect their children.

Here we look at some of the effects that marriage and divorce can have on children. The first being what the information is on children who have had to repeat a grade.

Data collated by the National Center for Health Statistics have shown that while a child whose family structure includes two biological or two adoptive parents are 6.5% likely to have to repeat a grade, that goes up to around 20% or more if they have any other home life. This structure could mean either living or having stepparents or simply living only with a mother.

This graph shows the effects on a child's ability to achieve the highest grades at school. Bearing this in mind, a child who is living with both their parents will achieve mostly As around 30% of the time. This falls to 9% if children is always living with a single parent.

Impact On Your Finances

Another one of the reasons that people may delay marriage and divorce is down to finances. Some will put off marrying as they save up for an expensive wedding, while some couples delay divorce owing to the sky-high legal fees. Here, we break down those financial marriage and divorce costs a little more closely.

When it comes to marriage, the average expenditure for a wedding is high, wherever you live. Couples that are marrying in the state of Rhode Island can expect to pay over $52,000 for their wedding. However, for those that live in Utah, that figure goes right down to $18,516. While this is still a lot of money, the information shows that this is over 50% less of a Rhode Island wedding.

For divorce, the costs can really rack up very quickly, depending on what legal proceedings you have to carry out to finalize the end of your marital status.

Court fees for a short, two-day trial will cost couples $25,000. The cheapest divorce, however, is one that sees collaborative law negotiations which will cost each individual $3,000. However, the information extrapolates what the average minimum amount is for each divorce is $15,000.

Child Support And Divorce

One of the biggest issues that couples have to contend with when they split and divorce is what happens to the children that they have.

Here, we look at the data behind child support and divorce and how the numbers have varied over the time between 1993 and 2011. While there was a large dip in 2009 for the amount of custodial parents, the number tends to stick around the same 5 million mark. However, it went to just over 4 million in 2009 and has yet to go back up to its peaks of 5.5 million in 2003.

Child custody is obviously a big problem that couples face when they start to seek the help of a divorce lawyer. So it's interesting to see that while the divorce rate is dropping, the number of marriages that end up with a custody battle on their hands by and large stays the same, with only a dip being seen in very recent years.

This could be to do with the balancing out of gender roles so that children are less likely to only be given full custody under their mothers.

Other Separation Arrangement

Of course, all these statistics do not take into account the men and women who don't fall into this information collation. Those will be people whose marital status is separation or even something even more modern.

Not everyone who breaks up with their marriage partner will automatically get divorced. This can skew the information on the men and women who are in their first marriage or later, but actually are no longer with their partner.

Remarrying

Getting remarried is becoming a far more common thing to do after a first marriage has broken down. Marriage and divorce have changed in people's opinion culturally speaking so that getting married to someone who has previously been married is no longer stigmatized or frowned upon. For that reason, divorce (as we have seen) is common even if the rate is falling.

However, remarriage is on the rise - particularly with those that are the baby boomers' age.

According to information found by the Pew Research Center, while 42% of divorcees above 50 remarried in 1980, that number has risen to 57% by 2013. Other age groups saw a decline in that time. Those between the age of 18-34 saw a decrease from 72% in 1980 to 42% in 2013, with 35-54 years olds' age bracket going from 72% to 60% in the same time frame.

Interestingly, the same study showed information data that displayed that men have always been more likely to remarry than women - whatever their age.

FAQs

Marriage And Divorce - In Numbers

Seeing marriage and divorce data investigated in the round like this is an interesting way to look at how both have changed over the years.

However, marriage and divorce are also clearly affected by a person's age, a person's age when they married, and what a person does for a living - in addition to a whole host of other factors. These can include where they live, what their education was, and if their parents' are divorced or still together.

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Divorce Rate & Statistics (2023) - How Many Marriages End In Divorce? - Her Norm

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In the article, it is mainly comprised of qualitative data. The data is based on predictions on how high or low the divorce rate will be in 2024.

-Tyrone D. P5

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Here are 10 short statistics about the US divorce rates in 2024:

The US divorce rate is expected to reach an all-time high in 2024.

Over 50% of marriages in the US end in divorce.

The average length of a marriage before divorce is 8 years.

Divorce rates are higher among couples who marry at a young age.

Financial issues are one of the leading causes of divorce.

Infidelity is another major factor contributing to divorce.

The divorce rate is higher for second and third marriages.

Divorce rates vary by state, with some states having higher rates than others.

Children of divorced parents are more likely to experience emotional and behavioral problems.

Divorce can have long-term negative effects on individuals' mental and physical health.

1. US Divorce Rates in 2024

1.1 Factors Contributing to High Divorce Rates

Marriage at a young age is also associated with higher divorce rates.

Couples who marry in their late teens or early twenties may not have fully developed their individual identities or acquired the necessary skills to navigate the challenges of married life.

Lack of maturity and life experience can strain the relationship and increase the likelihood of divorce.

1.2 Regional Variations in Divorce Rates

For example, states with higher poverty rates tend to have higher divorce rates.

Financial instability and limited resources can put significant strain on marriages, increasing the likelihood of divorce.

Additionally, states with higher levels of education and income tend to have lower divorce rates, suggesting that socioeconomic factors play a role in marital stability.

2. Average Length of Marriages Before Divorce

2.1 Factors Affecting the Duration of Marriages

Several factors can affect the duration of marriages before divorce.

One of the key factors is the age at which couples marry.

Research has shown that couples who marry at a young age are more likely to divorce compared to those who marry later in life.

This may be due to the lack of maturity and life experience, as well as the increased likelihood of financial instability among young couples.

3. Impact of Divorce on Children

Divorce can have significant negative effects on children.

Research has consistently shown that children of divorced parents are more likely to experience emotional and behavioral problems compared to children from intact families.

3.1 Emotional Effects on Children

Children of divorced parents often experience a range of emotions, including sadness, anger, confusion, and guilt.

They may blame themselves for their parents' divorce and feel a sense of loss and abandonment.

These emotional effects can have long-lasting consequences on their mental health and well-being.

Additionally, children of divorced parents may struggle with forming and maintaining healthy relationships in the future.

They may have difficulty trusting others and fear commitment due to their parents' failed marriage.

These challenges can impact their ability to form intimate and fulfilling relationships as adults.

3.2 Behavioral Effects on Children

Divorce can also lead to behavioral problems in children.

They may exhibit aggression, defiance, and conduct disorders as a result of the stress and disruption caused by the divorce.

These behavioral issues can manifest both at home and in school, affecting their academic performance and social interactions.

Furthermore, children of divorced parents are more likely to engage in risky behaviors such as substance abuse and early sexual activity.

The lack of parental supervision and support, coupled with the emotional turmoil caused by the divorce, can increase their vulnerability to these negative behaviors.

4. Long-Term Effects of Divorce on Individuals

Divorce can have long-term negative effects on individuals' mental and physical health.

The emotional trauma and stress associated with divorce can lead to a range of psychological and physical problems.

4.1 Mental Health Effects

Individuals who have gone through a divorce are at a higher risk of developing mental health disorders such as depression and anxiety.

The loss of a significant relationship and the accompanying emotional upheaval can trigger or exacerbate existing mental health issues

Divorce can also lead to a decrease in self-esteem and self-worth.

Individuals may question their own value and desirability, leading to feelings of inadequacy and insecurity.

These negative self-perceptions can impact their overall well-being and quality of life.

4.2 Physical Health Effects

The stress and emotional toll of divorce can also have physical health consequences.

Research has shown that divorced individuals are more likely to experience chronic health conditions such as heart disease, hypertension, and diabetes.

The physiological effects of stress and the disruption of social support networks can contribute to these health problems

Furthermore, divorced individuals may engage in unhealthy coping mechanisms such as excessive alcohol consumption, smoking, and poor dietary habits.

These behaviors can further compromise their physical health and increase their risk of developing chronic diseases.

5. Divorce Rates for Second and Third Marriages

Divorce rates are higher for second and third marriages compared to first marriages.

This suggests that individuals who have been through a divorce are more likely to experience subsequent relationship breakdowns.

5.1 Factors Contributing to Higher Divorce Rates in Second and Third Marriages

Additionally, individuals who have been through a divorce may carry emotional baggage and unresolved issues into their subsequent marriages.

These unresolved issues can create conflict and hinder the development of a healthy and stable relationship.

6. The Role of NLP in Understanding Divorce Rates

Natural Language Processing (NLP) can play a significant role in understanding divorce rates.

NLP is a branch of artificial intelligence that focuses on the interaction between computers and human language.

By analyzing large amounts of text data, NLP algorithms can extract valuable insights and patterns related to divorce rates.

I use AtOnce's AI language generator to write fluently & grammatically correct in any language:

6.1 Analyzing Social Media Data

For example, NLP algorithms can detect keywords and phrases related to divorce, such as "separation," "custody battle," or "divorce lawyer." By analyzing the frequency and context of these terms, researchers can gain a better understanding of the prevalence and nature of divorce discussions on social media

Example of me using AtOnce's AI SEO optimizer to rank higher on Google without wasting hours on research:

6.2 Predictive Modeling

For example, certain linguistic markers, such as negative emotion words or frequent use of pronouns indicating distance and detachment, may be indicative of a troubled marriage.

By analyzing these linguistic markers in large datasets, NLP algorithms can develop models that accurately predict the likelihood of divorce.

Latent Semantic Indexing (LSI) is a technique used in information retrieval and natural language processing to identify relationships between terms and concepts.

LSI can help uncover related terms and topics that are semantically similar to the main topic of divorce rates.

7.1 LSI Terms

Some LSI terms related to divorce rates include:

Marital dissolution

Relationship breakdown

Marriage dissolution

Divorce statistics

Marital satisfaction

Marital stability

Divorce trends

Divorce causes

Divorce consequences

Divorce prevention

8. The Impact of Divorce on Society

Divorce has far-reaching implications for society as a whole.

It affects not only the individuals involved but also their families, communities, and the economy.

8.1 Economic Consequences

8.2 Social Consequences

Divorce can also have social consequences, affecting the fabric of families and communities.

Children from divorced families may experience a sense of instability and disruption in their lives, which can impact their social development and relationships with peers.

Furthermore, divorce can strain social support networks, as friends and family members may feel compelled to take sides or distance themselves from the divorcing couple.

This can lead to feelings of isolation and loneliness for individuals going through a divorce.

9. Strategies for Reducing Divorce Rates

Reducing divorce rates requires a multifaceted approach that addresses the underlying causes of marital dissatisfaction and provides support and resources for couples in crisis.

9.1 Pre-marital Education and Counseling

9.2 Relationship Education and Support

Providing ongoing relationship education and support can help couples navigate the challenges and transitions of married life.

Couples can benefit from workshops, support groups, and counseling services that address common issues faced by married couples, such as financial management, parenting, and maintaining intimacy.

9.3 Access to Mental Health Services

9.4 Policy Changes

In conclusion, the US divorce rate is expected to reach an all-time high in 2024.

Financial issues, infidelity, and marriage at a young age are some of the factors contributing to high divorce rates.

Divorce can have significant negative effects on children and individuals' mental and physical health.

NLP and LSI techniques can help analyze and understand divorce rates, while strategies such as pre-marital education, counseling, and access to mental health services can help reduce divorce rates and support healthy marriages.
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What percentage of US marriages end in divorce?

Has the percentage of US marriages ending in divorce increased over the years?

Are there any factors that can influence the likelihood of divorce in a marriage?

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50 Shocking Facts: US Divorce Rates Unveiled - 2024

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Here are 10 short statistics about the US divorce rates in 2024: The US divorce rate is expected to reach an all-time high in 2024. Over 50% of marriages in the US end in divorce. The average length of a marriage before divorce is 8 years.

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The article talks about where employment could be in 2024. The article also talks about predictions about the market as well.

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Employers slowed hiring and handed out smaller raises in recent months, signs of fading momentum in the job market that have some forecasters expecting unemployment to rise in 2024.

And that might be OK. The key for American workers and Federal Reserve policymakers is to have the labor market cool without collapsing. That would support household incomes while helping inflation drift lower, putting the economy on a glide path to a soft landing -as long as the slowdown isn't too severe.

Copyright ©2024 Dow Jones & Company, Inc. All Rights Reserved. 87990cbe856818d5eddac44c7b1cdeb8

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Where the Job Market Is Heading in 2024, in Six Charts

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Forecasters expect unemployment to edge higher and hiring to slow, which could aid the economy's soft landing.

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Topic: Feral Children

The Qualitative data for this topic is the case study of Kamala and Amala, who were captured by wolves at a young age and were then raised by them. A witness account shows that they saw the "cubs" with a mother wolf, but they seemed to have long matted hair and certain human features. Once they were rescued, the two young girls were taken to an orphanage where they were described to have "wolfish" tendencies and overall lack the ability to behave themselves as a human should. The quantative data regarding this topic is a case study of the feral child "Genie". Genie's social worker and a team of psychologists began to run multiple tests on Genie to see if the isolation she received had major impacts on her language development. https://www.verywellmind.com/genie-the-story-of-the-wild-child-2795241https://www.edubloxtutor.com/amala-kamala/

Topic: Police Brutality

The Qualitative data for this topic is the known fact that attitudes towards police officers vary from different ranges based upon who you talk to. Multiple generations have a generational trauma of the simple fact that an officer has killed or injured someone they love close to them, typically in communities where the economy is set up for failure. In 2014, a young African American man, 18 year old Michael Brown life was cut short by a Ferguson police officer. Quantitive data on this topic is the different groups of people who were surveyed on what they believe regarding police brutality. https://pro.morningconsult.com/articles/most-voters-see-police-violence-as-problem# https://abcnews.go.com/US/half-us-killings-police-unreported-study/story?id=80303407 ( Kimesa A. )

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How does divorce affect children? Michael A. Glover Period 5 (Quantitative Data)

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How does divorce affect children? Michael A. Glover Period 5 (Quantitative Data)

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academicworks.cuny.edu/cgi/viewcontent.cgi?article=3353&context=gc_etds |

Quantitative Data:

This document show how the divorce can have a impact on children's behavior. To continue, it has show the number of divorces have been steadily going up over the past few decades and impacting over 1 million children every year in the USA. Furthermore, divorce can impact children behavior in many different ways depending on certain factors such as their age, relationships with parents and coping strategies. Also, the document suggest the hardest time is when the parents separate to separate living arrangements and after the divorce. Causing it to be the most difficult time emotionally and behavioral for the children.

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How does divorce affect children? Michael Glover Period 5  (Qualitative Data)  

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How does divorce affect children? Michael Glover Period 5  (Qualitative Data)  

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https://link.springer.com/article/10.1007/s11205-020-02428-2

Qualitative Data:

This UK study wanted to know if parents divorcing or separating has a impact on 5 year-olds. They used information from the Millennium Cohort Study, to find out that divorce is tougher for kids from happier parent relationships, causing behavior issues for the children. This can also be found in temporary separation has linked behavior changes for kids as well.

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The Causal Effects of Parental Divorce and Parental Temporary Separation on Children's Cognitive Abilities and Psychological Well-being According to Parental Relationship Quality

Abstract

We explore the effects of parental divorce and parental temporary separation on well-being of children at a specific stage of their development according to the parental relationship quality. Despite the importance of this subject, among previous studies only few consider very young children and are based on statistical methods properly tailored to enhance causal evaluations. We attempt to establish the effects on both cognitive abilities and psychological dimensions of children at age five by using data drawn from the first three waves of the UK Millennium Cohort Study. Using an appropriate imputation method, we apply the augmented inverse propensity treatment weighted estimator to infer causality. Overcoming some of the limitations of previous research, we find that the dissolution of high-quality parental unions has the most harmful effects on children, especially concerning conduct problems. We demonstrate the substantial variation on consequences of parental divorce depending on the level of parental relationship quality. We show that parental temporary separation is a type of family disruption that has significant negative effects on young children. In fact, we infer that they have more conduct and hyperactivity problems than children from stable or divorced families. Our results also suggest children to be targeted with appropriate policies aimed to reduce the adverse effect of family disruption.

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1 Introduction

Parental divorce and union dissolution is an increasingly common experience for children in all developed countries. It has raised the debate on whether parental divorce is damaging for children's well-being and to what extent parents should remain together for the sake of the children. In accordance with this social concern, one of the most extensively discussed topics in the literature has been the average effects of divorce on children well-being. Many social surveys have been considered and various statistical methods have been used putting special emphasis on controlling for parental relationship quality and conflict prior to separation but often without considering that parental conflict does not always precede separation. In fact, a large percentage of low-distress couples divorce, a phenomena that has increased substantially in recent decades (Gähler and Palmtag 2015).

For this reason, some studies in the last two decades have offered a more nuanced explanation of the causality of divorce that focuses on the heterogeneity of divorce effects by parental relationship quality (Amato et al. 1995; Jekielek 1998; Hanson 1999; Strohschein 2005). They take into account in which way divorce affects different children, either positively or negatively, instead of concentrating on the average causal effect of divorce across the board (Amato 2010). These studies suggest that divorce may be a positive experience for children from high-distress marriages, while the dissolution of low-distress marriages may have opposite effects (Amato et al. 1995; Booth and Amato 2001). Despite the significant ramifications of these findings, to the best of the author's knowledge only few studies have examined the heterogeneity of the consequences of parental divorce by the level of parental relationship quality. These studies (for instance, see: Amato et al. 1995; Jekielek 1998; Hanson 1999; Morrison and Coiro 1999; Booth and Amato 2001; Strohschein 2005; Fomby and Osborne 2010; Yu et al. 2010; Kalmijn 2015) present the following characteristics: a) only two are based on non-US data, and only few use nationally representative samples or methods to infer causality; b) they have mainly analyzed children's psychological well-being while evidence on other children's outcomes such as cognitive development is scarce; c) the most of them focus solely on children in middle childhood or older. Amato ( 2010), in his most recent review of the literature, encourages more research concerning this issue. We use a national large sample with several cases of divorce and temporary separations among parents and cohabiting couples representing the current trend in the Western societies. We explore the effects both on the psychological well-being and cognitive development of the children. We investigate if and how these effects are different according to parental relationship quality. The latter is measured in a way to capture not only parental conflicts before separation but also communication, affection and emotions among the couple. We use the first three waves of the Millennium Cohort Study (MCS) which is a nationally representative longitudinal study of a cohort of British children born from 2000 to 2002 in the UK. We move forward from previous work and contribute in respect to the analysis of the interrelationships between family disruption, parental relationship quality and children's psychological well-being and cognitive development. First, we test whether the hypothesis of heterogeneity of divorce effects by parental relationship quality is also true for children from UK. Second, we aim to assess whether this hypothesis is also valid for young children since only Fomby and Osborne ( 2010) account for very young children and do not find evidence of heterogeneity of divorce by parental relationship quality. We have specifically focused on a salient period of children's lives, namely the transition to school. It is well-demonstrated that children who enter school without the necessary cognitive or socio-emotional skills have greater academic and behavioral difficulties during their school years and beyond than their more "school-ready" counterparts (Romano et al. 2010). Third, we aim to assess the heterogeneity hypothesis by improving and extending the methodological and analytical approach proposed in the literature. We focus on many of children's outcomes rather than just on one or two since we consider the following multiple dimensions of children's school readiness: three different cognitive abilities (verbal, problem-solving and spatial abilities) and five psychological dimensions (conduct, hyperactivity, internalizing and peer problems, and pro-social behavior). Unlike previous research on parental divorce, we use the Augmented Inverse Propensity Treatment Weighted (AIPTW, Robins et al. 2000) estimator in order to yield robust estimates of the effects of interest and an imputation method based on the statistical methodology of chained equations (Raghunathan et al. 2001), which allows us to jointly impute missing data for different types of variables. Furthermore, in previous research on the interplay between parental divorce, parental relationship quality and children's outcomes, the fact that a significant proportion of parents separate only temporarily was not considered. Little is known about the level of relationship quality of these parents before separation and the risks children experience when they face this type of family disruption (Kiernan et al. 2011; Nepomnyaschy and Teitler 2013).

In sum, by using cohort data similar to that used by Fomby and Osborne ( 2010), we aim to test the following three hypotheses: i) parental relationship quality and family disruption are unrelated processes that have independent effects on children (the independent hypothesis); ii) the negative association between family disruption and children's well-being may be spurious because poor relationship quality is related to both family disruption and poor children well-being (the selection hypothesis); iii) the consequences of family disruption on children are contingent on the level of parental relationship quality experienced prior to this event (the heterogeneity hypothesis). To test this third hypothesis about the heterogeneity of the effects of family disruption by parental relationship quality is the main contribution of our study.

The paper is structured as follows. In Sect. 2 we provide a background section considering the effects of family disruption on children well-being, then we focus on the conceptual framework. In Sect. 3 we describe data and methods. In Sect. 4 we show the main results. In Sect. 5 we provide a discussion. The supplementary material provides further details on data, missing data imputation and additional tables with results.

2 Background

2.1 Family Disruption on Children Well-being

Studies on the effects of parental divorce on children's well-being that use ordinary least squares (OLS) and logistic models show that part of this effect is spurious and it is only partially explained by parental relationship quality (Hanson 1999). Since the late 1990s, several studies have used more innovative research designs to identify the independent effects of parental divorce and father absence such as lagged dependent variable models, growth curve models, individual and sibling fixed effects models, natural experiments and instrumental variables, and propensity score matching. McLanahan et al. ( 2013) review these studies and find consistent evidence that parental divorce exerts negative effects on the well-being of offspring. They also show that this evidence is stronger for children's socio-emotional development, especially in externalizing problems, than for children's cognitive ability. Nevertheless, they present the following features: a) most studies of the effect that of parental divorce on cognitive and psychological development are based on US samples b) very few studies focus on children who experience parental divorce in early childhood, and c) only one (Strohschein 2005) explores the heterogeneity of divorce effects by the quality of the parental relationship prior to separation.

A weakness of existing research is that it does not consider parents who separate only temporarily. Recent studies observe that a non-negligible proportion of parents separate for a short time period and then re-partner with the same person (Kiernan et al. 2011; Nepomnyaschy and Teitler 2013). However, as stated by Nepomnyaschy and Teitler ( 2013, 3) "in most studies, this family 'type' is usually classified as either intact or separated (depending on when cohabitation status is ascertained), but it may differ in many respects from both of those groups". The reason this type of family disruption is scarcely considered in previous research is that most studies only use two waves of survey data, and at least three waves are necessary to detect it. The existing research on the characteristics of parents who only separate temporarily show that such couples have a more disadvantaged socio-demographic background than with continuously intact relationships (Kiernan et al. 2011; Nepomnyaschy and Teitler 2013). Despite that, the only two studies that analyze the consequences of temporary separation on children well-being find evidence of a negative effect, even when controlling for several socio-demographic characteristics (Kiernan et al. 2011; Nepomnyaschy and Teitler 2013). However, no study controls for the relationship quality of parents before separation and some evidence suggest that couples who separate temporarily have a lower relationship quality than stable couples long before separation occurs (Vennum et al. 2014). Thus, if poor parental relationship quality may cause temporary separation, then it is difficult to rule out the possibility that the negative association between parental temporary separation and children's outcomes may be due to relationship quality rather than this event per se.

2.2 Heterogeneity of the Effects of Parental Divorce by Parental Relationship Quality

2.2.1 Conceptual Framework

Two main explanations are provided regarding the heterogeneity of the effects of parental divorce1 by parental relationship quality. One is the stress relief hypothesis (Wheaton 1990) which concerns the consequences of transitions in life roles. Wheaton ( 1990, 210) stated that "...instead of being stressful, life events may at times be either non-problematic or even beneficial, offering escape from a chronically stressful role situation, creating the apparent paradox of more 'stress' functioning as stress relief". According to this perspective, the stressful event of parental divorce may be beneficial for children whose parental relationship prior to divorce has been poor, as it takes them away from an aversive and stressful home environment. After divorce, these children should enjoy an improvement in their well-being since they no longer experience the parental conflict (Booth and Amato 2001; Strohschein 2005).

By contrast, the dissolution of low-distress parental relationships may be detrimental to children's development. Children from relatively harmonious families may not benefit from divorce, since it is unlikely that they experience this event as stress relief. For these children, divorce may instead give rise to stressful situations such as a decline in their standard of living, moving to a poorer neighborhood, changing schools, and losing contact with the non-custodial parent (Amato 2010). Children from non-dysfunctional families may also begin to experience parental discord after separation, since issues such as custody, childrearing, visitation, and child support are potentially conflictual (Booth and Amato 2001).

In addition to changes in stress, children's understanding and perceptions of divorce depend on the level of their parents' pre-divorce relationship problems, another factor related to children's adjustment after separation. Children who have witnessed parental disputes may anticipate their parents' divorce and attribute it to external reasons, such as parental conflict, as argued by Booth and Amato ( 2001). For children from low-distress families, by contrast, divorce might come as more of a surprise and they might see divorce as a threat to their happiness. Booth and Amato ( 2001) give possible reasons as to how an unexpected divorce may adversely impact on children. First, for these children, it is more difficult to comprehend and accept the reasons for their parents' separation. As Maes et al. ( 2012, 276) state: "if children do not understand why their parents have divorced, they make up their own story around things they do know, increasing the danger that children will blame themselves". Second, children who do not anticipate parental divorce may feel that they have little control over events in their lives (Booth and Amato 2001). Children's self-blame and locus of control are, in turn, negatively related to their adjustment after divorce (Bussell 1996; Kim et al. 1997).

Are these useful in explaining the heterogeneity of parental divorce for infants and very young children? The explanation of children's understanding and perceptions of divorce is unlikely to be valid for very young children due to the kind of reasoning needed for children to be able to anticipate this event and blame themselves for it. The stress relief explanation developed for older children and adults, however, can also be applied to infants and very young children. There is a growing and consistent body of research documenting that the exposure to poor parental relationship quality during infancy affects children's well-being cross-sectionally during infancy and longitudinally during their pre-school years (Fitzgerald 2010; Graham et al. 2013; Zhou, Cao and Leerkes 2017). For example, a possible mechanism is that parental conflict experienced by infants is associated with neural responses to emotional tone of voice, particularly very angry speech (Graham et al. 2013). With the existing evidence, it is reasonable to assume that if parental conflict produces stress in infants, then when parental divorce occurs this source of stress will disappear and their well-being will improve.

The second explanation does not focus on the consequences of direct exposure of infants to parental conflict but highlights an indirect pathway through parental well-being: parental relationship quality moderates the effect of parental divorce on very young children because parental relationship quality also moderates the effect of divorce on parent's well-being. To our knowledge, this explanation has not been mentioned by previous research and is based on two main premises. First, it has been largely demonstrated that parents' emotional adjustment after divorce is an important predictor of children's well-being (Amato 1993) and that parents' emotional problems are also clearly associated with adverse children's outcomes during infancy and early childhood (Petterson and Albers 2001; Kiernan and Huerta 2008). In addition to that, few empirical studies that have focused on this topic predominantly show that people who enjoyed a high relationship quality prior to divorce suffer the most harmful negative effects on their emotional well-being (for instance, see Wheaton 1990; Booth and Amato 2001; Williams 2003; Waite et al. 2009; Ye et al. 2017). For people with low levels of relationship quality, the findings are mixed. Some studies give support to the hypothesis that divorce is beneficial for the emotional well-being of people in highly conflictual or unsatisfactory relationships (for instance, see: Wheaton 1990; Williams 2003; Amato and Hohmann-Marriott 2007; Ye et al. 2017). Others find evidence that when people divorce from an unsatisfactory relationship, they experience a decrease in their emotional well-being but to a lesser extent than those who divorce from satisfactory relationships (Kalmijn and Monden 2006; Waite et al. 2009). For these reasons, it seems plausible to hypothesize that if divorce has the most harmful effects on parents who enjoyed a high level of relationship quality, their children would also experience the most harmful effects of this event.

2.2.2 Previous Research

To the extent of our knowledge the current research is based on the possible data according to the characteristics of the sample at the time and on the best method of analysis. Confidence in research findings increases when studies are based on a nationally representative sample with a large sample size. Some studies have less than 300 cases in the divorce group, and only three (Hanson 1999; Strohschein 2005; Kalmijn 2015) use nationally representative surveys. The majority of samples are based on American children, with the exception of Kalmijn ( 2015) and Strohschein ( 2005), and there is not enough evidence to conclude the hypothesis of heterogeneity of divorce effects is valid in all Western countries or if this hypothesis is country-specific. With exception of Fomby and Osborne ( 2010), all relevant studies examine only children whose parents are married; they exclude the large and increasing proportion of children who are living with their biological cohabiting parents (Kiernan et al. 2011).

Concerning the characteristics of the outcomes and focal variables we observe that seven of the nine studies in this field used the psychological well-being of offspring; there is less consistent evidence of variation in divorce effects in other important outcomes. Among studies concerning the heterogeneity of divorce, only one focus on educational achievement (Hanson 1999). For this reason, with the existing research, it is not possible to say whether the hypothesis about the heterogeneity of divorce effects is valid for most children's outcomes, or only for psychological ones.

In addition, existing research does not focus on a specific stage of children's development. Instead, samples are used with great variation in the children's ages at the time of divorce, and the age when response variables are measured. Most studies look at children who experienced parental divorce over a wide range of ages (Booth and Amato 2001; Hanson 1999; Kalmijn 2015). In some of them, divorce occurred any time from when the children were born to when they were adults. Only Fomby and Osborne ( 2010) focus on a specific stage of children's development namely parental divorce that occurs before age 3, and the response variable is measured at age 3. Second, as mentioned, studies finding evidence in favor of the heterogeneity hypothesis analyze children's outcomes measured during middle childhood and/or adolescence (Hanson 1999; Jekielek 1998; Morrison and Coiro 1999; Strohschein 2005) or adulthood (Amato et al. 1995; Booth and Amato 2001; Yu et al. 2010; Kalmijn 2015) and the only paper that does not support this hypothesis focuses on outcomes in very young children (Fomby and Osborne 2010). These contradictory results may suggest that the effects of divorce only vary by parental relationship quality for children in middle childhood or older. However, with only one study on very young children, there is not enough evidence to conclude whether divorce effects are heterogeneous depending on the age of the child at the time of divorce and/or the age when the outcomes were measured.

3 Materials and Methods

3.1 Data

The data correspond to the first three waves of Millennium Cohort Study (MCS) which is a high-quality profile survey representative for the UK (Plewis et al. 2000; Hansen and Joshi 2007; Plewis 2007; Hansen et al. 2012). The first sweep was carried out between September 2000 and January 2002. It contains information on 18,819 babies from 18,533 families, collected from the parents when the babies were 9-11 months old. The families were contacted again when the children were aged 3 and 5 years. The response rates achieved for the second (2004/05) and third (2006) waves were 78% and 79% of the target sample, respectively. More than two-thirds of the sample (around 69% representing 13,234 families) responded in all three waves (Ketende 2010). The MCS sample design allowed for over-representation of families living in areas with high rates of child poverty and/or high proportions of ethnic minorities. Survey methods were used to take account of the initial sampling design, and adjustments were made for non-response in the recruitment of the original sample and sample attrition over the follow-up period to age five.2

We consider children whose family structure is available for all the first three waves of the MCS. The sample includes only singleton children and families where the mother is the main respondent at the first wave. More details on the data and on how we handle missing values are available in Section A1 of the supplementary material.

3.2 Variables

3.2.1 Response Variables

The variables of interest for school readiness are measured when children are 5 years old, at the third wave. The Strengths and Difficulties Questionnaire (SDQ) (Goodman 1997) assesses children's behavioral adjustment and is answered by the mother. The SDQ is made up of five subscales assessing emotional symptoms, conduct problems, hyperactivity or inattention problems, peer problems, and pro-social behavior. Each subscale has five items with scores ranging from 0 to 2. Children's cognitive development is assessed by using the British Ability Scales (BAS II) (Elliott et al. 1997). The following BAS subscales were used to measure different domains of cognitive development: the naming vocabulary test, which assesses expressive language; the picture similarities test, which measures pictorial reasoning; and the pattern construction test, which assesses spatial ability. These were conducted by an interviewer at home. The three tests assess the three most significant information-processing skills: verbal reasoning, non-verbal reasoning and spatial abilities (Hill 2005). A standardized score is computed for each cohort member according to his/her age band considered every three months. Table 1 shows the average scores for the response variables stratified according to the family situation at age 5 as defined in the following section. Children experiencing parental temporary separation or parental divorce shows lightly more psychological problems and lower scores for cognitive development with respect to children with stable family.

Table 1 Descriptive statistics of the children's outcomes according to the family situation

3.2.2 Focal Variables

We use the first three waves of the survey to create the following main family situations: children that experience parental divorce are those whose parents were together (married or cohabiting) until they were at least 9 months old, but who divorced when they were aged between 9 months and 5 years (N = 1177); children that experience parental temporary separation are those whose parents were together (married or cohabiting) when they were born and when they were 9 months and 5 years old (N = 277); however, on one or more occasions, their parents spent more than one month living apart; children in stable families are those whose parents remained in stable married or cohabiting unions from their birth until age 5 (N = 9001).

Partnership quality was derived from the Golombok Rust Inventory of Marital State (GRIMS, Rust et al. 1990) which is a psychometric instrument for the assessment of marital discord and the overall quality of a couple's relationship. We only used the GRIMS scale for responses from the mother, as the fathers' questionnaire showed a high percentage of missing cases. We use this scale at the first wave (9 months) since it has seven items, as opposed to four items in the subsequent waves.

The following four items, the responses to which were collected at the first wave assess the negative aspects of relationship quality: (1) "my partner doesn't seem to listen to me"; (2) "sometimes I feel lonely even when I am with my partner"; (3) "I wish there was more warmth and affection between us"; and (4) "I suspect we may be on the brink of separation". The other three items assess the positive aspects of relationship quality: (1) "my partner is usually sensitive to and aware of my needs"; (2) "our relationship is full of joy and excitement"; and (3) "we can always make up quickly after an argument". The item responses consist of the following: strongly agree (0); agree (1); neither agree nor disagree (2); disagree (3); strongly disagree (4) and can't say (5). "Can't say" responses were considered as missing information. To create an ordinal scale, we included both the positive and the negative items, which involved reversing the answers to the positive items. For these items the answers were: strongly disagree (0); disagree (1); neither agree nor disagree (2); agree (3); strongly agree (4). We then added up respondents' answers to the seven items, which produced a scale with a minimum of 0 and a maximum of 28.

Most studies, also due to few observed divorced couples, consider the heterogeneity of divorce by accounting for an interaction between parental divorce and the continuous variable measuring parental relationship quality. They assume that the magnitude and sign of the interaction effect is the same across any value of the relationship quality and they do not allow the extent to which the effect of parental divorce diverges in according to the intensity of the relation to be examined. Only Fomby and Osborne ( 2010) use a binary variable to identify couples with a low relationship quality if the reported value is below the 25th percentile of the sample distribution. We consider the quartiles of the empirical distribution and we account for the following ordered categories of decreasing union quality: very good, good, poor and very poor. We choose this specification to obtain a more accurate portrayal of children who experience especially poor and very poor parental relationship quality.

Table 2 shows the descriptive statistics of the family situation according to parental relationship quality. In the sample 86% belong to stable family, 11% experience parental divorce and around 3% experience parental temporary separation. The percentages of those reporting different levels of relationship quality are quite similar: 28% and 20% reported high and low quality relationships, respectively. The data reveal that parents who remained together from wave 1 (children were 9 months old) to wave 3 (children were 5 years old) had better relationship quality on average than those who divorced or experienced some period of separation. Comparing the two types of family disruption, parents who subsequently divorce exhibit worse relationship quality than those who only temporarily separate. At wave 1, around 18% of parents in stable family reported the lowest relationship quality compared with 32% of those who later separated temporarily and 39% of those who later divorced. Hence, in accordance with the selection hypothesis, a large number of children with divorced parents were exposed to poor union quality before parental separation. However, contrary to this hypothesis, Table 2 also shows that a considerable proportion of parents who divorced had not experienced poor relationship quality prior to ending their relationship. Among children whose parents divorced, around 17% and 22% belonged to families with the highest (q ₁) and high (q ₂) relationship quality, respectively. It is important to acknowledge that children whose parents had the highest relationship quality at wave 1 could experience poor parental relationship quality after this wave and prior to their parents' divorce since this event occurs between wave 1 and wave 3 of the survey.

Table 2 Descriptive statistics of the family situation according to the levels of the parental Relationship Quality (RQ)

Although the percentages show that a large proportion of divorced parents reported the lowest level of relationship quality before separation, the row percentages demonstrate that the majority of parents with poor-quality relationships do not separate. Approximately three-quarters (73%) of mothers with the lowest level of relationship quality at wave 1 remained in a relationship with the father of their child four years later.

Overall, considering only values from Tables 1 and 2, we cannot say whether the observed differences on school readiness between children from different family situations are explained by differences in parental relationship quality pre-dating the experience of family disruption.

3.2.3 Control Variables

The control variables illustrated in Table 3 are measured when children were 9 months old (wave 1), namely before parental separation took place, and took into account several socio-demographic characteristics related to family disruption and children's well-being (Booth and Amato 1991, 2001; Wilson and Waddoups 2002; Amato and Hohmann-Marriott 2007; Kiernan and Huerta 2008; Brown 2004; Kiernan and Mensah 2009; Brooks-Gunn et al. 2010; Muluk et al. 2014; Idstad et al. 2015; Karraker and Latham 2015; Oláh and Gähler 2014; Sabates and Dex 2015).

Table 3 Descriptive statistics of the socio-demographic characteristics

Concerning the social exchange theory (Levinger 1976) we include into the rewards and costs the following variables to control for the selection into family disruption: family income, housing tenure, mother's educational attainment and ethnicity, mother's health (depression and longstanding illness) and the presence of half- or step-siblings at home. We consider the following variables as barriers to family disruption: paid work status of the mother; whether the mother lived with someone else as a couple before living with the father of the child; type of parental union (married directly, cohabitation before marriage, or cohabitation); year that parents began living together as a couple; whether parents grew up in a non-stable family and mother's attitudes to single-parent upbringing. Instrumental support is measured by the following response provided by the mother: "If I had financial problems, I know my family would help if they could". Finally, another group of control variables is related to the division of unpaid work, which is associated with the probability of divorce: who is mostly responsible for household tasks and who is generally with and looking after the children.

3.3 Methods and Analytical Strategy

The effect of parental divorce (or parental temporary separation) on children's outcomes is evaluated under the framework of counterfactual reasoning or Potential Outcomes (POs) (Rubin 1974, Holland and Rosenbaum 1986). In this context, we are interested to estimate the Average Treatment Effect (ATE) that is conceived as the difference between the expected values of the POs of the children in the treated and untreated condition. We refer to the POs of individual exposed to treatment as \( Y_{i}^{\left( 1 \right)} \) and not exposed as \( Y_{i}^{\left( 0 \right)} \) for each i, i = 1,..., n. The treatment is provided only to a fraction of the units, and it is denoted by a binary variable Z i that is equal to 1 if the individual i is treated and to 0 if he/she is not treated. The treatment effect is defined as the difference \( Y_{i}^{\left( 1 \right)} - Y_{i}^{\left( 0 \right)} \) and the same value over the population is the ATE defined as the expected value of the POs as follows

$$ {\text{ATE}} = {\text{E}}[ {Y_{i}^{\left( 1 \right)} - Y_{i}^{\left( 0 \right)} } ]. $$

The realized outcome for individual i is given by

$$ Y_{i} = Z_{i} Y_{i}^{\left( 1 \right)} + \left( {1 - Z_{i} } \right)Y_{i}^{\left( 0 \right)} . $$

In this framework, the outcomes of the children whose parents are divorced or temporary separated are only observed in the presence of the treatment conditions and the outcomes of the children in stable families are only observed in the absence of treatment. That is, a child can experience parental divorce or can live in a stable family from 9 months to age 5. As recently stated by Kim ( 2011) the ATE joints the realized developmental outcomes for children had experienced divorce or temporary separation and the counterfactual outcomes for these children had their parents remained together. The effects of family disruption on children's outcomes can be assessed only on average in this non-experimental study, since each child belongs to one of the treatment or to the control group and one PO is always not realized. Children experiencing family disruption may be not randomly selected, and the family characteristics that determine the disruption may also affect the child's well-being through other pathways (McLanahan et al. 2013).

The Propensity Score (PS, Rosenbaum and Rubin 1983) is a multivariate statistical matching method proposed for data collected in non-experimental contexts aimed to reduce the bias of the estimator of the treatment effect by considering the observed pre-treatment covariates (Rosenbaum 2020). The PS concerns the conditional probability of the treatment (the probability of experiencing parental divorce or parental temporary separation) given the observed pre-treatment covariates. This aims to mimic an experimental context especially when the observational data are rich as in the context of this application where similar questionnaires are administered to the participants. For estimating the ATE the weighted regression estimator (Rosenbaum 1987) defined as the Inverse Propensity Treatment Weighted (IPTW) estimator (Robins et al. 2000) weights each unit according to the estimated inverse probability of receiving the treatment actually received. The weights are obtained as the inverse of the estimated PS and in this context they allow us to compare children exposed to divorce despite their low probability of exposure and children not-exposed to divorce. We use observable pre-treatment covariates collected into the column vector \( \varvec{X}_{i} \) whose realized values are denoted with \( \varvec{x}_{i} \) for i = 1, ..., n. We assume that conditional to the pre-treatment covariates the average outcomes in the treated and control groups in the absence of treatment would be the same. Another assumption is defined as strong ignorability (Rosenbaum and Rubin 1983) and postulates that given the pre-treatment covariates the treatment choice is independent of the POs. The positivity assumption is also required meaning that each treatment level occurs with some positive probability. This is also defined overlap assumption since it implies that the support of the conditional distribution of the covariates x i given Z i = 0 overlaps completely with the conditional distribution of x i given Z i = 1 (Imbens and Wooldridge 2009).

Disposing of a sample of n independent units, the IPTW estimator uses weights estimated through the maximum likelihood estimates of the parameters of the multiple logistic regression model given by

$$ \hat{w}_{i} = \frac{1}{{\hat{p}(z_{i} = 1|\varvec{x}_{i} )}}, \quad i = 1, \ldots ,n. $$

In this way it is possible to mimic a pseudo-population in which the covariates are balanced between treated and untreated individuals. The Augmented IPTW (AIPTW) estimator has the smallest asymptotic variance among the class of the IPTW estimators (Robins et al. 1994) and it is obtained according to the proposal of Lunceford and Davidian ( 2004) as follows:

$$ \hat{\tau }_{aiptw} = \frac{1}{n}\mathop \sum \limits_{i = 1}^{n} \frac{{Z_{i} Y_{i} }}{{\hat{p}(z_{i} = 1|\varvec{x}_{i} )}} - \frac{1}{n}\mathop \sum \limits_{i = 1}^{n} \frac{{Z_{i} - \hat{p}\left( {z_{i} = 1 |\varvec{x}_{i} } \right)}}{{\hat{p}\left( {z_{i} = 1 |\varvec{x}_{i} } \right)}}\hat{f}\left( {Y_{i} = y_{i} |\varvec{v}_{i} } \right), $$

where \( \hat{f}\left(Y_i= {y_{i} |\varvec{v}_{i} } \right) \) denotes the multiple linear regression model estimated for the observed responses by using ordinary least squares or robust inferential methods with \( \varvec{v}_{i} \) denoting the vector of the observed covariates. All the relevant covariates should be included in the sets \( \varvec{x}_{i} \) and \( \varvec{v}_{i} \). We propose to apply the AIPTW estimator since it corrects for possible mis-specifications in the PS model or in POs model and it is statistically more robust with respect to other methods. The so-called "double robustness" property (Bang and Robins 2005; Neugebauer and van der Laan 2005) implies that the estimator remains consistent if the POs or PS model are incorrectly specified, see among others, Cao et al. ( 2009) and Glynn and Quinn ( 2010). When the estimated weights are too large Robins et al. ( 2000) propose to truncate such weights up to a specified threshold, preventing to some units being highly influential.

The analytical strategy we follow is to consider the three hypotheses illustrated in the introduction and to show the results according to the following steps. First, we estimate the ATEs of parental divorce and parental temporary separation including the available covariates in the PS model shown in Table 3 and accounting also for the overall weights to consider attrition and the initial sampling design. We estimate the POs model by considering all the variables most directly related to the children's living conditions selected according to the knowledge in the field. They are the following: sex of the child; number of children at home; mother's education, ethnicity and labor force participation; household income; housing tenure; mother's longstanding illness and depression, and type of parental union. Second, to evaluate the selection hypothesis we estimate the ATE including the parental relationship quality in the POs and PS models. Third, to evaluate the heterogeneity for parental divorce we estimate the ATE by considering the quartiles of the variable relationship quality in the POs and PS models. The heterogeneity hypothesis is not considered for children experiencing parental temporary separation. The three steps are repeated for every outcome by considering each time five imputed datasets in order to account for missing values. More details are provided in Section A1 of the supplementary material.

4 Results

4.1 Average Effects of Family Disruption on Children's Well-being

In order to evaluate i) the independent and ii) the selection hypotheses, we compare the following two models: Model 1, which only includes control variables, and Model 2, which also considers parental relationship quality in both outcome and treatment models. Table 4 reports the results for each psychological and cognitive dimension. As expected, this covariate is significant in predicting the probability of parental divorce and parental temporary separation for each dimension. We refer to Section A2 of the supplementary material for some additional results for conduct problems where we show the estimated regression coefficients of the covariates included in the PO and PS models (Table A1 and A2, respectively). Concerning the results showed in Table 4 we notice that the estimated ATE of parental divorce is significant for all the psychological dimensions and except for the picture similarity test in Model 1 for all the other cognitive dimensions. However, when parental relationship quality is introduced among the control variables (Model 2), the effect of parental divorce is not significant for internalizing problems and peer problems. For conduct and hyperactivity problems, the magnitude of the effect of parental divorce is still significant but is considerably reduced. For conduct problems, parental divorce increases the average score of 0.244 points (Model 1) with respect to the score of children in stable family but this average score decreases to 0.162 when parental relationship quality is included (Model 2). For hyperactivity, the effect of parental divorce is 0.407 in Model 1 and 0.241 in Model 2. By considering parental relationship quality the ATE is reduced of around 34% for conduct problems and around 41% for hyperactivity problems3. Unexpectedly, the effect of parental divorce on pro-social behavior becomes significant in Model 2. For the cognitive dimension, the estimated effect of parental divorce in Model 1 is significant for all cognitive variables with the exception of the picture similarity test. Unlike the results for the most psychological variables, when parental relationship quality is included (Model 2), the effect of parental divorce does not decrease for the pattern construction test, and even increases slightly for the vocabulary test.

Table 4 Estimated average causal effects (ATE) and potential-outcome means (POs) according to the family situation (p-values in parentheses)

The effect of parental temporary separation is not significant in any model for internalizing, peer problems and pro-social behavior. In contrast, parental temporary separation has a significant negative effect on children's hyperactivity and conduct in both models. For parental divorce, parental relationship quality does not reduce the effect of parental temporary separation in any of these psychological dimensions. It is also important to point out that for conduct and for hyperactivity problems, the magnitude of the effect of parental temporary separation is greater than the effect of parental divorce. The results of Model 2 show that the estimated PO mean for the conduct scores of children in stable family is 1.287. Parental temporary separation increases this score by an average of 0.384 while parental divorce increases it by an average of 0.162. In other words, the effect of parental temporary separation increases conduct problems by around 30% while parental divorce only increases conduct problems by around 16%. Similar differences result for hyperactivity problems. Turning to cognitive variables, the effect of parental temporary separation is not significant in any model for the pattern construction and vocabulary tests and this effect is only significant in Model 1 for the picture similarity test.

4.2 Heterogeneous Effects of Parental Divorce According to Parental Relationship Quality

The third hypothesis is evaluated according to the results showed in Table 5 reporting the ATE estimated according to the relationship quality. With regard to the psychological dimension, the effect of parental divorce on conduct problems is only significant for children that experienced extreme levels of parental relationship quality. Among children whose parents reported the highest relationship quality (q ₁), the PO mean in stable family is 0.960, with parental divorce increasing it by 0.349. In other words, children with parental divorce experiencing good relationship quality show more conduct problems than children in stable family. The difference in percentage is lower among children whose parents had a very poor relationship quality (q ₄).

Table 5 Estimated average causal effects (ATE) of parental divorce (PD) and potential-outcome (PO) means on children's outcomes according to the quartile of parental relationship quality (p-values in parentheses)

For hyperactivity problems, the effect of parental divorce is significant only for those whose parents had a very poor relationship. Children with parental divorce experiencing very poor relationships among parents, have a higher probability of reporting hyperactivity problems compared to children with a stable family; the difference in percentage is around 11%.

As it can be seen, for internalizing problems the average effect of parental divorce is not significant once parental relationship quality is considered. However, when this effect is analyzed according to the quartiles of parental relationship quality, we get similar results to those obtained for conduct problems. The effect of parental divorce is significant in the extreme level of the relationship quality: within the group of children whose parents showed very good relationships, those who experience parental divorce have a higher probability of manifesting internalizing problems compared to children from stable family; the difference in percentage is around 20%4. Within the group of children whose parents had very poor relationships, the difference in percentage is lower, at around 12%. For peer problems, the effect of parental divorce is only significant for children whose parents had a good relationship (q ₂) and, for pro-social behavior, the effect is only significant for those with bad relationships (q ₃).

With regard to the cognitive dimension of children's school readiness, although the average effect of parental divorce on the picture similarity tests is not significant Table 4, the results are different in Table 5. The effect of parental divorce is significant and equal to − 1.326 among children with parents reporting very poor relationships (q ₄). The effect for those experiencing very good relationships (q ₁) among parents is not significant. For the vocabulary test, it is interesting to note that the estimated ATE is significant and negatively large for those children exposed to a very good relationship (q ₁) among parents. In this category, parental divorce decreases the score of the vocabulary test by an average of 3.319 points. It is also significant but lower in magnitude for those whose parents had a bad relationship (q ₃). For the pattern construction test the estimated ATE is significant and negative for children experiencing poor and very poor relationships.

5 Discussion

This work is an attempt to elucidate the interrelationships between family disruption and parental relationship quality by testing the following three main hypotheses: i) parental relationship quality and family disruption are unrelated processes that have independent effects on children (the independent hypothesis); ii) the apparent effect of family disruption is explained according to the parental relationship quality (the selection hypothesis); iii) the effect of family disruption on children depends on the quality of the parental relationship (the heterogeneity hypothesis).

We advance previous research in several ways. First, we evaluate the importance of these hypotheses using a comprehensive view of child development rather than focusing on a single outcome. We analyze multiple domains of children's school readiness: cognitive and psychological well-being. Second, we focus on very young children who are at a key point in their development, namely the transition to school, while most research focuses on children in middle childhood or older. Third, we also analyze parental temporary separation which is a type of family disruption that is only scarcely covered in previous literature. Fourth, unlike most previous research, our study examines the heterogeneity of divorce effects by parental relationship quality outside of the US by using a UK nationally representative sample. Fifth, we use a proper multivariate method to impute the missing values and we employ the augmented inverse propensity treatment weighted estimator to infer the causal effects in each imputed dataset and we combine the results. Up to our knowledge this estimator has not been used by previous studies to assess the effect of parental divorce on children well-being.

We find mixed support for the i) independent and the ii) selection hypotheses, obtaining a different pattern for each outcome and type of family disruption. The selection hypothesis is supported by the potential outcome models regarding the average effect of parental divorce on pro-social behavior, internalizing and peer problems. Nevertheless, there is evidence in favor of the independent hypothesis in five of the eight outcomes.

Parental temporary separation only has a significant effect on conduct and hyperactivity problems; however, the magnitude of the effect of this type of family disruption is greater than the magnitude of the effect of divorce. These results indicate that, although children experiencing parental temporary separation have been invisible in most previous research and family policies, they are also at risk, and more research on this type of family disruption is needed (Nepomnyaschy and Teitler 2013; Halpern-Meekin and Turney 2016).

With regard to the third hypothesis related to the heterogeneity of divorce effects, this study shows that the average independent effects mask the substantial variation of the effect of parental divorce. First, we find that a non-negligible proportion of children from divorced families did not experience parental relationship problems. For this group of children, the idea that the negative effects of parental divorce are explained by parental relationship quality is not valid. In addition, our findings clearly support the hypothesis that the dissolution of high-quality parental unions has the most harmful effects on children's lives. We find that among children whose parents had a very good relationship quality, there are substantial differences between those whose parents divorce and those that remain together in six of the eight analyzed dimensions. In four outcomes, the effect of parental divorce is greater for them with respect to the others.

Our findings for children of non-distressed families are in accordance with the existing literature on the heterogeneity of divorce effects based on children in middle childhood, adolescence or adulthood using US and Canadian data. However, it is important to point out that our results based on children at age 5 clearly diverge from those obtained by Fomby and Osborne ( 2010) with children at age 3, which find that parental divorce is not harmful for children in high- and low-conflict families. This discrepancy is probably due to the fact that these authors categorize three-quarters of the unions as high-quality, while we consider of very good quality only those unions above the 75th percentile (highest relationship quality) of the sample distribution. This result is consistent with research on the heterogeneity of divorce effects in adults which shows that divorce has the most harmful emotional effects among those who had satisfactory relationships prior to separation. Therefore, it is reasonable to assume that the children of these parents, especially the very young, are also affected more strongly.

We do not find any evidence that corroborates the hypothesis that the effect of parental divorce is positive for children who experienced poor parental relationship quality (see also Booth and Amato 2001; Hanson 1999). It is also important to acknowledge that we do not expect to obtain this finding in a country such as the UK where fewer children are living in poor families compared to the US (OECD 2017). Comparative research on the heterogeneity of the effects of parental divorce is needed in order to determine to what extent this hypothesis varies by country and the mechanisms that may explain this variation such as the generosity of family policies.

In addition to that, we explain why we find a divergence between our result and the one obtained by previous studies. First, as mentioned, these studies have used a continuous measure of parental relationship quality and they consider the interaction effect between parental divorce and parental relationship quality instead we evaluate to what extent the effect of divorce differs between very good, good, poor and very poor relationship quality. This allow us to detect a non-linear pattern in some of our outcomes: children whose parental relationship lay in the extremes (very good or very poor) are those most affected by divorce while children whose parental relationship was moderately good or bad are the least affected. Making a comparison with adult data, our results are in line with the findings of Williams ( 2003). Second, the proposed model specification based on the augmented inverse probability weighted estimator which requires to specify a potential outcome model along with the propensity score model, has never been proposed in this context. Third, most previous research has focused on parental conflict measured in terms of the frequency of disagreements, rather than on a measure of overall marital discord and quality, the millennium cohort study does not, however, provide a direct measure of the disagreement among parents. Also, our measure of parental relationship quality is derived from the mother's perceptions and therefore misses the father perceptions. Due to these limitations, we are not able to capture the overall level of relationship quality that children experience at home. For this reason, we cannot rule out the possibility that if we had better measures to assess disharmonious families, we may have found positive effects of parental divorce for children living in them. Future research may be improved by using more subtle measurements of relationship quality and focusing on the heterogeneity effects of divorce on very young children.

Another reason that could explain why parental separation is not beneficial for children who experienced poor parental relationship quality is that we are not able to capture its duration. Research shows that there are different trajectories of parental relationship quality over time and that experiencing persistent poor parental relationship quality has more negative effects on children's well-being than experiencing temporary poor parental relationship quality. Hence, it is reasonable to hypothesize that parental separation can be positive for children whose parents experienced a chronically poor parental relationship quality while the same event can be damaging for children that only experienced temporary poor parental relationship quality prior to separation. An important contribution of future research would be to include the measurement of the duration and trajectories of parental relationship quality in the studies of the heterogeneity effects of parental divorce. In addition to that, future studies should not only analyze the heterogeneity effects of parental divorce but also the heterogeneity effects of other forms of family transitions such as parental temporary separation. Children experience an increase in the number and types of family dissolution experiences during childhood: parents separate and then they may get back together or have a new partner and may separate again (Amato 2010).

Overall, the present study makes two main contributions to the literature by employing a suitable model to infer causality by reporting that parental temporary separation has detrimental effects for children, and that parental divorce exerts the most harmful effects among children whose parents enjoyed a very good parental relationship quality prior to separation. Our results can be used also to define policies targeted to those children for whom the detrimental effect of divorce might be stronger.

Notes

1. We are only able to empirically study the heterogeneous effects of parental divorce and not the heterogeneous effects of parental temporary separation due to data limitations. For this reason, we only theoretically discuss the heterogeneous effects of parental temporary separation in this section. In addition to that, the literature does not provide any theoretical explanation about the heterogeneity of the effects of parental temporary separation.

2. Details on the survey, its origins, objectives, and sampling, as well as the content of the survey waves, are contained in the documentation attached to the data deposited at the UK Data Archive at Essex University.

3. These percentages are calculated by considering the estimated ATE multiplied by 100 and divided by the estimated PO referred to stable family.

4. The percentages are computed as explained in the previous footnote.

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Acknowledgements

Open access funding provided by Università degli Studi di Milano - Bicocca within the CRUI-CARE Agreement. Garriga thanks the grants of the Spanish Ministry of Economy and Competitiveness (Grants CSO2012-33476 and CSO2015-69439-R). Pennoni thanks the grant "Finite mixture and latent variable models for causal inference and analysis of socio-economic data" (FIRB-Futuro in Ricerca) funded by the Italian Government (RBFR12SHVV). The authors thank Isabella Romeo for her contribution to preliminary data analyses.

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1. Department of Political and Social Science, Pompeu Fabra University, Barcelona, Spain

Anna Garriga

2. Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy

Fulvia Pennoni

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Correspondence to Fulvia Pennoni.

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Garriga, A., Pennoni, F. The Causal Effects of Parental Divorce and Parental Temporary Separation on Children's Cognitive Abilities and Psychological Well-being According to Parental Relationship Quality. Soc Indic Res 161, 963-987 (2022). https://doi.org/10.1007/s11205-020-02428-2
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The Causal Effects of Parental Divorce and Parental Temporary Separation on Children's Cognitive Abilities and Psychological Well-being According to Parental Relationship Quality - Social Indicators Research

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We explore the effects of parental divorce and parental temporary separation on well-being of children at a specific stage of their development according to the parental relationship quality. Despite the importance of this subject, among previous studies only few consider very young children and are based on statistical methods properly tailored to enhance causal evaluations.

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Is there Gender Inequality on the Job? Michael Glover Period 5th Quantitative data: 

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Is there Gender Inequality on the Job? Michael Glover Period 5th Quantitative data: 

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Quantitative data: This study of 15 countries uses the employer- employee data to illustrate the gender gap. This can be seen with job differences can play a part in the pay gap on other hand in the same job, men and women still face unequal pay. Fortunately, over time the overall pay gap and within-job gap has seen notable decline while some countries have seen some increases. The results highlight the need to have fair pay compensation for workers for both genders and make sure hiring and promotions are done fairly to achieve equal pay for men and women to stop the economic division between genders to keep on persisting.

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Despite great advances in gender equality, women earn less than men in all advanced industrialized countries. These gender gaps are strongly related to the occupations and establishments in which women and men work. Germinal research highlights that, although there are substantial differences in the overall wages men and women receive, women and men who do the same work for the same employer receive very similar wages1,2,3. The processes involved in sorting women and men into different jobs, and particularly into differentially remunerated male- and female-dominated occupations, are thus viewed as central to understanding gender pay inequality4,5,6.

This understanding of the gender gap has far-reaching policy implications. If there are sizeable differences between the pay that women and men receive when they do the same work for the same employer (that is, within-job inequality), policies mandating equal pay have an important role to play in creating gender equality in the labour market. If, however, differences arise overwhelmingly through sorting women and men into different jobs, policies should focus on the organizational hiring and promotion practices that match people to jobs, as well as on broader societal views regarding whose work is defined as valuable7,8,9.

Most evidence regarding gender pay inequality comes from surveys of individuals that contain occupational data but lack good indicators of firms and jobs. Data that contain detailed occupational information and link individuals to others working for the same employer (that is, linked employer-employee data) are rarely available, so that data that can examine gender differences among those with the same occupation and employer (that is, within-job inequality) are difficult to access. The best evidence on within-job gender pay differences comes from a limited number of countries using linked employer-employee data ranging from 1980 through 1990 to examine within-job gender wage differences1,2,3. In this Article, we contribute to this literature by using linked employer-employee data to provide recent estimates of the levels and change in within-establishment, within-occupation and within-job differences in earnings across 15 countries: Canada, Czechia, Denmark, France, Germany, Hungary, Israel, Japan, the Netherlands, Norway, Slovenia, South Korea, Spain, Sweden and the United States. We show that although much of the gender inequality we observe is accounted for by sorting into establishments, occupations and jobs, within-job gender gaps in earnings remain an important source of differences in all 15 countries. Analyses for the six countries where we can examine the contractual hourly wage rate show that sorting is similarly important for gender differences in wages, suggesting that equal pay policies have an important role to play in creating gender pay equity.

Our core analyses focus on four sets of ordinary least squares regression models. The first model adjusts only for basic individual-level covariates, and provides our baseline estimate of the overall gender pay gap in each country. In subsequent models, we introduce a series of fixed effects so that we compare women and men working in the same establishment (model 2), the same occupation (model 3) and the same job (that is, occupation-establishment unit; model 4). Comparing the results of these four models enables us to see the degree to which gender differences in pay in any given year are accounted for by sorting across establishments, occupations and occupation-establishment units.

Table 1 presents information on gender differences in earnings in our 15 countries. After making basic adjustments for differences in age, education and part-time status, the gender gap in earnings among those aged 30-55 years ranges from 10% in Hungary to 41% in South Korea. Within-job gender gaps are smaller but still substantial, ranging from 7% in Denmark and France to 26% in Japan. Comparing the results in the first and fourth columns (basic adjustment and within-job), we see that within-job gender differences remain a substantial source of the overall earnings gaps in all of our 15 countries. As is visible in the final column, within-job differences typically account for about half of the overall gender differences that we observe in our countries, ranging from just over a third of the overall gap (Israel) to over nine-tenths of the gender earnings gap in Hungary.

The results in the second and third columns of Table 1 report within-establishment and within-occupation gender differences in earnings. Comparing these columns with the results with only basic adjustments highlights the role of sorting into establishments and occupations in creating gender pay differences. Where previous research1,2,3 found that sorting into occupations is substantially more important for gender inequality than sorting into establishments, we find evidence that sorting into both occupations and establishments plays an important role in producing gender differences. Our findings thus not only underscore the salience of within-job differences, but also document the importance of processes that differentially sort women and men into high-paying establishments and occupations.

Figure 1 depicts how the within-job and overall gender gaps have changed from 2005 to our most recent year of data (for most countries this represents approximately 10 years; for information on the most recent year that we have data from each country, see Table 1). The x axis plots the average annual change in the within-job gender gap for each country, and the y axis plots each country's average annual change in overall gender gap over this period. In most countries, both the overall gender gap and the within-job gender gap have fallen over time. However, this is not the case in the three Central and Eastern European countries. In Czechia, within-job gender differences decline, but overall gender differences in earnings increase, suggesting that gender differences in earnings in Czechia are increasingly due to processes sorting women and men into different jobs. Gender differences also increase in Hungary and Slovenia, where the increase is due not only to sorting processes, but also to an increase in within-job gender gaps. Of particular note, none of our 15 countries exhibits a decrease in the overall gender earnings gap coupled with an increase in within-job gender earnings gaps (as would be the case if egalitarian sorting processes counteracted rising within-job inequality); this suggests that the processes sorting women and men into different jobs are rarely gender egalitarian.

CA, Canada; CZ, Czechia; DK, Denmark; DE, Germany; ES, Spain; FR, France; HU, Hungary; IL, Israel; JP, Japan; KR, South Korea; NL, the Netherlands; NO, Norway; SI, Slovenia; SE, Sweden; US, United States. The y axis represents the average annual change in the overall gender gap in earnings (accounting only for basic adjustments, and corresponding to the first column of results in Table 1), and the x axis reports the average annual change in the within-job gender gap in earnings (corresponding to the fourth column of results in Table 1). Larger positive numbers correspond to larger increases in the gender earnings gap across years, while negative numbers correspond to decreases in the gap. We use data from approximately 10 years in each country, beginning in 2005 where possible and continuing through the most recent year available (for information on the most recent year available to us in each country, see Table 1). In three countries (the Netherlands, South Korea and Spain), we do not have data from 2005 and so use 2006 as our initial year. See the tables presented in Supplementary Information for the underlying coefficients reporting gender differences for each year. Supplementary figures depict country-specific trends for overall, within-establishment, within-occupation and within-occupation-establishment gender differences in earnings for each country.

Given the rapid expansion of women's rights around the world, one might expect uniform improvement in women's pay via both reduced sorting into different jobs and lower levels of within-job inequality. The empirical record is more mixed, with nearly universal improvements in education and labour force participation, continued and sometimes even increased segregation, and little information on what happens within jobs10.

Our analyses of linked employer-employee data from 15 countries show that currently both within-job differences and sorting into jobs make substantial contributions to gender pay gaps. Interestingly, the trends we document highlight that sorting is increasingly important, and that within-job differences are shrinking in importance in most countries. Thus, while the conclusions drawn by previous research-that sorting accounts for the vast majority of gender differences, and within job inequality is not a substantial concern-may not accurately summarize the current state of gender pay inequality, if the trends we observe hold, they may describe our future. In the current context, however, our findings suggest that policies focusing on equal pay for equal work and policies attending to hiring, promotion and other job-sorting processes are both vital to establishing gender equality in the labour market.

Limitations

Large-scale comparative analyses contain numerous challenges around data harmonization and ensuring that analytic decisions that are appropriate in some contexts are not problematic in others. Although we sought to ensure that the analyses conducted in each country are comparable, factors like parental leave policies, the availability and prevalence of part-time work, and the relevance of occupations and firms differ across our 15 countries. These differences necessarily mean that the comparisons we make across countries involve comparing contexts with different gender regimes and where paid work is organized very differently. Despite these limitations, we believe that these comparisons are informative, and in our Supplementary Information we report results from analyses where we alter variable definitions, model specifications and sample definitions, showing that the results we present here are remarkably robust.

This study uses linked employer-employee data (that is, data that link individual employees to specific employers) from 15 countries to investigate the extent to which the gender pay gap arises from women and men receiving different pay when doing the same work for the same employer (as opposed to from processes sorting women and men into different occupations and establishments). By allowing us to compare individuals to others working for the same employer, the linked employer-employee data that we use provide important insights into inequality. Below we provide information on our modelling strategy for our core analyses, and we summarize the data available in each of our 15 countries in Table 2. More information on the data used for each country and results from country-specific robustness checks are included in Supplementary Information, which also presents country-specific results on changes over time, providing a sense of each country's trends in gender inequality at the overall, establishment, occupation and job (that is, occupation-establishment) levels.

Models

As noted above, our core analyses focus on four sets of ordinary least squares regression models. Our first model adjusts only for basic individual-level covariates, and provides our baseline estimate of the overall gender pay gap in each country. In subsequent models we compare only women and men who work in the same establishment (model 2), only women and men who work in the same occupation (model 3) and only women and men who work in the same job (that is, occupation-establishment unit; model 4). We estimate these models separately by year for each country, allowing us to examine country-specific trends in these gender differences.

The equations estimated for our core models follow the same general form, using four different specifications:

where the subscripts represent i for individuals (or for each employment spell of an individual, depending on the country), f for full-time versus part-time status, o for occupations, e for establishments and t for years. The dependent variable is the logarithm of earnings (ln earningsit) for individual (or employment spell) i in year t, and the independent variables are collected in the vector x it, which includes a constant, the gender, age and age-squared of individual i, and a series of indicator variables for the education of individual i (except in countries where information on education was not available).

To address concerns regarding the comparability of full-time versus part-time workers, we consider full-time versus part-time status a defining characteristic of a job and include this axis in constructing fixed effects for all of our core models. Thus, model 1 includes the term η ft, a fixed effect (that is, indicator variable) for full-time versus part-time work, so that this basic adjustment model adjusts for age, age-squared, education and full-time versus part-time work. Model 2 includes the covariates in x it (age, age-squared and education), as well as the fixed effects η eft representing the unique units formed by combining the establishment and full-time versus part-time indicators. Model 2 thus provides estimates of the gender gap obtained from comparing women and men who work in the same establishment; for each establishment it can be thought of as estimating the gender gap separately for full-time workers and part-time workers and then taking a weighted average of these two gender gaps across all establishments. Models 3 and 4 are analogous to model 2, but contain the fixed effects η oft and η oeft that refer respectively to the unique units formed by combining full-time versus part-time status with either occupation ( η oft) or occupation-establishment units ( η oeft). The analytic sample for each model is restricted to gender-integrated fixed effect units. The subscripts to the θ parameters indicate that these are different coefficients, pertaining to different levels, basic adjustments ( B), establishment ( E), occupation ( O) and occupation-establishment ( OE).

We use the natural log of earnings as our dependent variable. Following standard conventions, these coefficients are interpreted as the relative difference between the average female and male earnings, but more formally our estimates refer to the difference in relative geometric means for unlogged earnings (which is the absolute difference in the arithmetic means of logged earnings). For an extended discussion of the interpretation of such coefficients, see Petersen11.

Data were analysed using STATA versions 14-17 and SAS version 9.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

This research was supported by the National Science Foundation (Award 0525831; D.A., A.M.P. and D.T.), the Humboldt Foundation (grant number AR8227; D.T.), the Research Council of Norway (grant number 287016; A.S.H.), European Research Council ERC Starting Grant (grant number 851149; A.S.H.), the European Research Council ERC Starting Grant (grant number 677739; T.K.), the French Agence Nationale de la Recherche (grant ANR-17-CE41-0009-01; M. Safi and O.G.), the Independent Research Fund Denmark (grant number 5052-00143b; L.H.), the European Social Fund and state budget of the Czechia (grant number CZ.03.1.51/0.0/0.0/15_009/0003702; A.K.), the Czech NPO Systemic Risk Institute (LX22NPO5101; A.K.), and institutional support (RVO: 68378025; A.K.), the Spanish Ministry of Science and Innovation (grant number PID2020-118807RB-I00/AEI /10.13039/501100011033; M.E.), the Fritz Henkel Stiftung (Endowed PhD Scholarship; HS) and Swedish Forte (grant number 2015-00807; M.H.), Z.L. received support from the European Research Council ERC Advanced Grant (grant number 340045), and A.K.M. was supported by the Slovenian Research Agency (ARRS) under grant no. P5-0193. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Research on the US data was conducted by J.K. while J.K. was working for the US Census Bureau. This paper is released to inform interested parties of research and to encourage discussion. The views expressed are those of the authors and not those of the US Census Bureau. Tabular materials presented in this paper were approved for release by the US Census Bureau's Disclosure Review Board (CBDRB-FY18-258).

Author notes

Independent Researcher.

Authors and Affiliations

1. Department of Sociology, University of California, Irvine, Irvine, CA, USA

Andrew M. Penner, Nina Bandelj & Zaibu Tufail

2. Department of Sociology, University of California, Berkeley, Berkeley, CA, USA

Trond Petersen

3. Department of Sociology and Human Geography, University of Oslo, Oslo, Norway

Are Skeie Hermansen

4. Swedish Institute for Social Research, Stockholm University, Stockholm, Sweden

Are Skeie Hermansen

5. Department of Sociology, University of Massachusetts, Amherst, Amherst, MA, USA

Anthony Rainey & Donald Tomaskovic-Devey

6. Centre for Economic and Regional Studies, Budapest, Hungary

István Boza

7. Departments of Strategic Management and Managing People in Organizations, IESE Business School, Barcelona, Spain

Marta M. Elvira

8. CRIS-CNRS, Sciences Po, Paris, France

Olivier Godechot & Mirna Safi

9. MaxPo, Sciences Po, Paris, France

Olivier Godechot

10. Department of Sociology, Stockholm University, Stockholm, Sweden

Martin Hällsten

11. Department of Organization, Copenhagen Business School, Copenhagen, Denmark

Lasse Folke Henriksen

12. Statistics Canada, Ottawa, Ontario, Canada

Feng Hou

13. Faculty of Social Sciences, University of Ljubljana, Ljubljana, Slovenia

Aleksandra Kanjuo Mrčela & Andreja Poje

14. Faculty of Economics, Meiji Gakuin University, Tokyo, Japan

Joe King, Naomi Kodama, Silvia Maja Melzer & Paula Apascaritei

15. Department of Sociology, University of Haifa, Haifa, Israel

Tali Kristal

16. Institute of Sociology, Czech Academy of Sciences, Prague, Czechia

Alena Křížková

17. Department of Sociology, University of Groningen, Groningen, the Netherlands

Zoltán Lippényi

18. School of Labor and Employment Relations, University of Illinois, Urbana-Champaign, Urbana-Champaign, IL, USA

Eunmi Mun & Jiwook Jung

19. Department of Social Sciences, Augusta University, Augusta, GA, USA

Dustin Avent-Holt

20. Department of Economics, Vienna University of Economics and Business, Vienna, Austria

Gergely Hajdu

21. Management Department, Frankfurt School of Finance and Management, Frankfurt, Germany

Halil Sabanci

22. Department of Sociology, University of Illinois, Urbana-Champaign, Urbana-Champaign, IL, USA

Matthew Soener

Contributions

A. Penner, T.P., A.S.H., A.R., I.B., M.E., O.G., M.H., L.F.H., F.H., A.K.M., J.K., N.K., T.K., A.K., Z.L., S.M.M., E.M., P.A., D.A.-H., N.B., G.H., J.J., A. Poje, H.S., M. Safi, M. Soener, D.T.-D. and Z.T. designed the analyses, interpreted the results, and wrote the paper. A.S.H. led the analyses comparing results to findings from previous work in Norway and Sweden; Z.L. led the development of weights; and I.B. and O.G. led analyses ensuring the robustness of results to the inclusion of person fixed effects. A.S.H. was responsible for conducting the Norwegian analyses; I.B. and G.H. were responsible for conducting the Hungarian analyses; M.E., H.S. and P.A. were responsible for conducting the Spanish analyses; O.G., M. Safi and M. Soener were responsible for conducting the French analyses; M.H. was responsible for conducting the Swedish analyses; L.F.H. was responsible for conducting the Danish analyses; F.H. was responsible for conducting the Canadian analyses; A.K.M. and A. Poje were responsible for conducting the Slovenian analyses; J.K. was responsible for conducting the US analyses; N.K. was responsible for conducting the Japanese analyses; T.K. was responsible for conducting the Israeli analyses; A.K. was responsible for conducting the Czech analyses; Z.L. was responsible for conducting the Dutch analyses; S.M.M. was responsible for conducting the German analyses; and E.M. and J.J. were responsible for conducting the South Korean analyses.

Corresponding author

Correspondence to Andrew M. Penner.

Competing interests

The authors declare no competing interests.

Peer review information

Nature Human Behaviour thanks David Grusky, Maria Charles and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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# data[].attributes.attachment_link.title
Within-job gender pay inequality in 15 countries - Nature Human Behaviour

# data[].attributes.attachment_link.description
Extant research on the gender pay gap suggests that men and women who do the same work for the same employer receive similar pay, so that processes sorting people into jobs are thought to account for the vast majority of the pay gap.

# data[].attributes.headline
Is there Gender Inequality on the Job? Michael Glover Period 5th (Qualitative Data)

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Is there Gender Inequality on the Job? Michael Glover Period 5th (Qualitative Data)

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https://link.springer.com/article/10.1007/s12147-020-09269-w

Qualitative Data: This study on COVID-19 had found that women inside India especially, that were unmarried and unemployed had begun taking more duties inside the home without much external help making women days more strenuous. These tasks made it almost impossible when it came to having a good work and life balance since had to more unpaid work at home. Overall, collectively many people had to more work but the study suggest women had to deal with a larger increase in the workload compared to others.

# data[].attributes.attachment_link.title
Gendering COVID-19: Impact of the Pandemic on Women’s Burden of Unpaid Work in India - Gender Issues

# data[].attributes.attachment_link.description
The COVID-19 pandemic has exacerbated the already existing gender inequalities with substantial implications on women. With the closure of offices and educational institutions, and the emerging norm of work from home and online education, along with the lack of services of domestic worker, the need to perform unpaid chores in the household has increased. Simultaneously, the requirements of social distancing and sanitization have created new unpaid chores. Owing to the sexual division of labour, and gendered roles and social norms of performing domestic and care work, the burden of unpaid work falls disproportionately on women. In this context, the objective of the paper is to study the impact of COVID-19 on time spent on unpaid work and the underlying gender differences in the urban centres in India. Specifically, the paper will do a comparative analysis of the gender differences in time spent on unpaid work before and during the lockdown, and analyse the reasons for the same.

# data[].attributes.body
(Includes both Quantitative and Qualitative)

This article sums up the causes of this disorder and how to treat it aswell, they also go into detail about many symptoms of this disorder.

https://bdd.iocdf.org/professionals/prevalence/

(Quantitative) This sections goes more into detail about how many people can be effected with this disorder. They also give a detailed explanation on the people who are more likely to get it than others.

Why Does The Abused Become The Abuser

https://www.learning-mind.com/cycle-of-abuse/

(Quantitative) This article goes into some factors that play a role into how this cycle almost always repeats itself.

https://melmagazine.com/en-us/story/why-victims-abuse-become-abusers

(Qualitative) Goes more into about certain peoples stories and about the stuff they'd hear or how they would get spoken to. They also were able to get the feed back on how this effected them in the long run , and how this tore their mental health.

-Jeniyah Mcleod 5th

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Body dysmorphic disorder is a type of obsessive-compulsive disorder. An individual with body dysmorphic disorder is overly preoccupied with what are perceived as gross imperfections in their appearance and spends an hour or more every day thinking about the way they look. In reality, the imperfectio…

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This article use quantitative data to exhibit police brutality towards different races and through the year . It utilizes statistics to show the different rate of police brutality between different races/globally .

- From Kedline

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This page has been updated with the removal of an image that was insensitive and inappropriate. We regret the image distracted from important research to better understand fatal police violence in the U.S., particularly the disproportionate burden of deaths experienced by Black, Hispanic, and Indigenous populations, as noted in the paper. Read the statement by NIMHD Director, Dr. Eliseo J. Pérez-Stable
In 2019, over 13% of global deaths due to police violence occurred in the U.S., yet the U.S. accounted for just 4% of the global population. To better understand fatal police violence in the U.S., particularly the disproportionate burden of deaths experienced by Black, Hispanic, and Indigenous* populations, a recent study supported in part by NIMHD quantified the extent of under-reporting of deaths due to police violence in the U.S. National Vital Statistics System (NVSS). The purpose of this study was to provide an updated, comprehensive analysis and framework to evaluate police violence fatalities at the state-level and accurately disaggregate mortality data by race and ethnicity.

The study investigators compared data from the NVSS (from 1980-2018) with three non-governmental, open-source databases on police violence: Fatal Encounters (from 2005-2019), Mapping Police Violence (from 2013-2019), and The Counted (from 2015-2016). They standardized age, sex, state, year of death, and race and ethnicity of each decedent from each database. Race and ethnicity were categorized as non-Hispanic Black, non-Hispanic White, non-Hispanic other races (including Indigenous* populations), and Hispanic of any race. The investigators used The Counted as the baseline from which data from all other databases were compared and database biases were assessed using network meta-regression (NMR). NMR is a mixed-effects and log-transformed linear regression model. The authors assumed that systemic biases between all databases would vary by state, race, and ethnicity and remain constant across age and sex.

The investigators estimated that the NVSS under-reported 55.5% of deaths due to police violence in the U.S., representing 17,100 (95% UI 16,600-17,600) out of 30,800 (95% UI 30,300 - 31,300) deaths from 1980 to 2018. The proportion of under-reported deaths was largest among non-Hispanic Black persons, of which 59.5% were misclassified, followed-by non-Hispanic White persons (56.1%), Hispanic persons of any race (50.0%), and non-Hispanic persons of other races (32.6%). Under-reporting also varied widely by state.

Age-standardized mortality due to police violence was 0.69 per 100,000 people for non-Hispanic Black persons. This was nearly 3.5 times higher than non-Hispanic White persons, two times higher than Hispanic persons of any race, and 4.6 times higher than non-Hispanic persons of other races. The mortality rates for non-Hispanic Black persons were higher than non-Hispanic White persons for every year included in the analysis. In the past decade (2010-2019), mortality rates for non-Hispanic Black persons increased in 42 states compared with non-Hispanic White persons. Additionally, the estimated deaths for all men were over 2000% higher than women during the same time frame.

Together, this study represents one of the most comprehensive analyses of deaths due to police violence in the U.S. The authors reported disproportionate rates of mortality by race and ethnicity that varied considerably at the state level. These results reflect the need for evidence-based strategies to address systemic racism and discrimination in policing in the U.S. and the likely direct and indirect biases in reporting to the NVSS. This study highlights the need to use a combination of open-source and governmental databases to more accurately and comprehensively evaluate deaths due to police violence and the need for disaggregation of such data by population group and area. Importantly, the authors provided a new research framework to guide future studies and provide public policy and health officials with additional data to inform policing practices and reporting within communities across the U.S.

Citation: GBD 2019 Police Violence US Subnational Collaborators. (2021). Fatal police violence by race and state in the USA, 1980-2019: a network meta-regression. The Lancet, 398, 10307. doi:10.1016/S0140-6736(21)01609-3.

*The Office of Management and Budget (OMB) uses the categories American Indian or Alaska Native to designate persons having origins in any of the original peoples of North and South America (including Central America), and who maintain tribal affiliation or community attachment. The term Indigenous is used by the investigators in this study.
Page updated December 14, 2021

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Fatal Police Violence in the United States

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NIMHD-supported study analyzes U.S. state-level mortality due to police violence from 1980 to 2019 that disaggregates by race and ethnicity.

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This article goes into depth about police brutality over the years. It uses case like what happened in Ferguson, Missouri . Also using studies like the one Gibbs and Bank-Greene did.

- Kedline

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divorce effect on a child quantitative this is quantitative because it has numbers and statistics to prove their point about divorce effect on kids

https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=3353&context=gc_etds

this is quantitative because it’s describing the effects and the research is mainly based on proving that particular point

-heidi louis

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There is no denying that going through a divorce can impact many different people. Sure, it has an obvious impact on the couple who have decided to part ways. But it also affects their family and friends. Children are the most likely to go through a difficult time.

With that in mind, we are going to take a look at some eye-opening children of divorce statistics. These children of divorce stats really help us to comprehend just how such a traumatic life event can impact children.

But before digging deep into each stat, let's have a quick look at some...

Fascinating Family Separation Statistics (Editor's Pick)

36.6% of all marriages in the US end in divorce.

Roughly one in two children will see their parent's marriage breakup.

21% of children are being raised without their fathers in America.

Children are more likely to experience behavior issues when parents divorce when the child is between the age of 7 and 14.

Children with divorced parents are twice as likely to end up dropping out of high school.

What Divorce Does to a Child

1. 36.6% of all marriages in the US end in divorce.

Before we examine the most revealing children of divorce statistics and how divorce impacts children, it's important to take a look at divorce rate statistics by year. The divorce statistics for 2018 show that one in every three marriages results in divorce.

This is a very high figure, to say the least!

Moreover, according to research published by the United Nations, the United States has the third-highest divorce rate in the world. According to the CDC, the current divorce rate in the US is 2.9 per 1,000 people.

However, while the divorce rate is dropping, the number of people getting married is also on the decline. This indicates that, for certain segments of the population, both marriage and divorce are out of reach.

2. Most people get divorced because of a lack of commitment.

There are a number of different reasons why people get divorced. Of course, everyone has their own unique situation.

However, divorced families statistics reveal that 73% of people get divorced because of a lack of commitment. After this, 56% get divorced because they argue too much, and 55% get divorced because of cheating.

Aside from this, 46% of people say the reason that they got divorced is that they got married too young. 45% had unrealistic expectations when it came to marriage, while 44% got divorced because their partnership was not equal.

Sadly, 25% of people get divorced because they're in an abusive relationship. No matter your reasons for getting divorced, there is no denying that divorce can have a huge impact on children. This is something to bear in mind, as it is imperative to keep an eye on your child during this difficult time.

3. According to statistics on children of divorce, roughly every one in two children will see their parents' marriage break up.

Now you know the divorce rate statistics, let's take a look at how many children have divorced parents. Statistics show that about 50% of all American children will witness the end of their parents' marriage. Of these children, almost half will then go on to see their parents' second marriage break up. Moreover, one in every ten children who have divorced parents will then see the break up of three or more parental marriages.

4. 21% of children are being raised without their fathers in America.

The children of divorce statistics show that it is usually the father who is absent from a child's life.

Roughly 25% of all children live with only one parent, and that's usually their mother.

These broken homes statistics show that around 21% of American kids are growing up without a father.

Statistics indicate that only 4.3% of children are being raised only by their father. It's a strikingly low number and an unusual statistic.

How Does Divorce Affect Children?

5. Children are more likely to experience behavior issues when parents divorce when the child is between the age of 7 and 14-years-old.

According to research carried out in the University College London, children are more likely to experience behavioral and emotional problems if their parents divorce when the child is between the age of 7 and 14-years-old. These children of divorce statistics 2019 reveal that there is a 16% increase in behavioral and emotional problems amongst this age range when compared to other ages.

6. Children with divorced parents are twice as likely to drop out of high school.

There are also some interesting children of divorce stats relating to the effects of divorce on teenagers. This stat from the Harvard University Press indicates that kids with divorced parents are twice as likely to end up dropping out of high school than their peers who have parents who have not divorced.

This indicates that you need to pay extra special attention to your child's performance in school if you are going through a divorce. It may even be worth talking to their teacher to explain the situation at home.

7. Children with divorced parents are more likely to get cancer.

Broken family statistics also show that children with divorced parents are more likely to get cancer. The reason for this is that they are more likely to participate in activities such as drinking too much alcohol, smoking, and having unprotected sex. These are all activities that have been shown to heighten the risks associated with developing cancer.

8. Children with divorced parents are twice as likely to attempt suicide.

This is one of the most worrying effects of divorce on children. Now, this does not mean that you should stay with someone you no longer love because of an increased risk of suicide. What it does mean, though, is that you need to pay extra special attention to your child and how they're behaving. It can be beneficial for children of divorce to see a therapist during this difficult period to help them understand the situation and talk to someone who is not directly involved in the marriage breakdown.

9. Children with divorced parents are four times as likely to have social problems.

Another of the children of divorce stats we're going to take a look at relates to how divorce impacts a child's life. This statistic indicates that children from broken homes tend to have more difficulty with their peers. It shows that growing up with divorced parents means that they are four times more likely to experience problems with their friends and peers than children whose parents are still together.

When children are frustrated, confused, or unhappy with the situation at home, they can act out and take it out on their friends. They may even feel resentment towards children whose parents are still together.

10. 70% of prison inmates incarcerated on long-term sentences grew up in a broken home, family separation statistics reveal.

More than two-thirds of prison inmates who are incarcerated on a long-term basis, which indicates more serious crimes, have grown up in a broken home.

Amongst all of the children and divorce facts, you will see that there are a lot of statistics on broken families that relate to a child's academic performance. Earlier, we mentioned that teenagers are more likely to drop out of high school when their parents get divorced. This is not simply an expression of teenagers' rebellious spirit. It can often happen because teenagers drop out of school so they can get a job and help their family to pay for rent and food.

Aside from this, children who were young when their parents separated are twice as likely to drop out of school later in life and have a fear of commitment and a low-paying job. What's more, children who have been through a number of different divorces with their parents usually have lower grade scores when compared with children who have not experienced divorce in their home life.

12. Teenagers whose parents divorce are 300% more likely to experience mental health issues.

There is no denying that there is a link between divorce and the increased risk of mental and physical health problems, as well as behavioral issues. There are a number of divorced parents statistics that show this is the case. In fact, teenagers with divorced parents are a lot more likely to experience mental health problems that will require medication, counseling, or both.

And that's not all...

There are some other divorce statistics in America that relate to children and their health that we should look at. Children living with both of their biological parents are 35% healthier than children with divorced parents. Moreover, children are 50% more likely to become seriously ill after experiencing their parents' divorce. Overall, kids that come from broken homes tend to experience more speech issues, as well as headaches, asthma, illnesses, and injuries.

13. Children are at a greater risk of living in poverty if their parents get a divorce.

This is one of those children of divorced parents statistics that may not come as a surprise when you consider the fact that getting a divorce can often mean that households have to make ends meet on a single income. Because of this, children with divorced parents are five times more likely to end up living in poverty than children who still live with both of their parents.

The Wrap-Up!

So there you have it:

Some of the most astonishing children of divorce statistics that really drive home the impact a divorce can have on a child.

You may be shocked to have learned about the sheer number of children who live in broken homes today, but the statistics on divorce and children don't lie. As a parent, you may be able to take some comfort in the knowledge that you are not alone. As a legal professional, you might want to keep this in mind for your next case.

While it can be difficult, it is vital to make sure that the issues of a divorce do not end up causing problems for your child. There is a lot of help available for you to get the support and assistance you require.

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13 Devastating Children of Divorce Statistics

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There is no denying that going through a divorce can impact many different people. Sure, it has an obvious impact on the couple who have decided to part ways. But it also affects their family and friends. Children are the most likely to go through a difficult time.

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this is considered quantitative because of the numbers and statistics

https://www.ncbi.nlm.nih.gov/books/NBK224396/#:~:text=Several%20reports%20have%20suggested%20that,larynx%2C%20pharynx%2C%20and%20esophagus.

this is qualitative because it has little number and is basically describing and doesn’t talk about date as much as the other one

heidi louis

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Past-year use of marijuana and hallucinogens by adults 35 to 50 years old continued a long-term upward trajectory to reach all-time highs in 2022, according to the Monitoring the Future (MTF) panel study, an annual survey of substance use behaviors and attitudes of adults 19 to 60 years old. Among younger adults aged 19 to 30, reports of past-year marijuana and hallucinogen use as well as marijuana and nicotine vaping significantly increased in the past five years, with marijuana use and vaping at their highest historic levels for this age group in 2022. The MTF study is funded by the National Institute on Drug Abuse (NIDA), part of the National Institutes of Health, and is conducted by scientists at the University of Michigan's Institute for Social Research, Ann Arbor.

While binge drinking has generally declined for the past 10 years among younger adults, adults aged 35 to 50 in 2022 reported the highest prevalence of binge drinking ever recorded for this age group, which also represents a significant past-year, five-year, and 10-year increase.

"Substance use is not limited to teens and young adults, and these data help us understand how people use drugs across the lifespan," said NIDA director, Nora Volkow, M.D. "Understanding these trends is a first step, and it is crucial that research continues to illuminate how substance use and related health impacts may change over time. We want to ensure that people from the earliest to the latest stages in adulthood are equipped with up-to-date knowledge to help inform decisions related to substance use."

Since 1975, the MTF study has annually surveyed substance use behaviors and attitudes among nationally representative samples of eighth, 10th, and 12th graders. The MTF longitudinal panel study conducts follow-up surveys on a subset of the participants after the 12th grade to track their drug use through adulthood. After high school, the participants are followed every other year through age 30, then every five years afterward, with the oldest participants now in their 60s.

Data for the 2022 survey of adults were collected via online and paper surveys from April 2022 through October 2022. Researchers divided the data into two age groups to conduct trend analyses: 19 to 30 years old and 35 to 50 years old. Key findings include:

Marijuana Use: For adults aged 19 to 30, the percentages of those reporting past-year marijuana use and daily marijuana use reached their highest levels ever reported by the study. Past-year use was reported by approximately 44% of those surveyed in 2022, an increase from five years ago (35% in 2017) and 10 years ago (28% in 2012). Daily marijuana use also reached its highest level reported in 2022 (11%), which was greater than five years (8% in 2017) and 10 years ago (6% in 2012).

Reports of past-year marijuana use among adults aged 35 to 50 also reached an all-time high in 2022 (28%). This had increased from the previous year (25% in 2021) and five years ago (17% in 2017), and more than doubled compared to 10 years ago (13% in 2012).

Vaping: Past-year marijuana vaping was reported by 21% of adults 19 to 30 years old in 2022, the highest levels reported since the measure was first added in 2017 (12%), as well as a notable increase from the past year (19% in 2021) and five years ago (12% in 2017). Past-year nicotine vaping among this younger adult group also reached a historic high in 2022 (24%), nearly double the rate reported five years ago in 2017 (14%), when the measure was first added.

Among adults aged 35 to 50, reports of past-year marijuana vaping remained at similar levels (9% in 2022) since 2019, when these measures were first available in this age group. Prevalence of past-year nicotine vaping has also remained steady in this age group since it has been reported, with 7% reporting in 2022.

Hallucinogen Use: Among adults aged 19 to 30, 8% reported past-year use of hallucinogens, significantly higher than five years ago (5% in 2017) and 10 years ago (3% in 2012). Types of hallucinogens reported by participants included LSD, MDMA, mescaline, peyote, shrooms or psilocybin, and PCP. Most of past-year use in 2022 reported by adults in this age group involved hallucinogens other than LSD (7% in 2022).

Past-year hallucinogen use reached historically high prevalence among adults 35 to 50 years old, reported by 4% in 2022. The prevalence reported in 2022 was also a substantial increase compared to the year before (2% in 2021) and five and 10 years ago (no greater than 1% in both 2017 and 2012).

Alcohol Use: Over the past decade, rates of alcohol use - including past-month use, daily drinking, and binge drinking - have shown an overall downward trend for adults 19 to 30 years old. Past-year drinking slightly increased for this age group in 2022 (84%) compared to five years ago (82% in 2017).

Alcohol use among adults aged 35 to 50 has shown a gradual increase over the past 10 years, with past-year drinking increasing from 83% in 2012 to 85% in 2022. Binge drinking in this older group reached its highest levels (29% in 2022), and increased over the past year, five years, and 10 years (26% in 2021; 25% in 2017; 23% in 2012).

The study also showed that past-year use of cigarettes, sedatives, and non-medical use of opioid medications ("narcotics other than heroin") showed a 10-year decline for both adult age groups. Reports of past-year amphetamine use continued a 10-year decrease among 19- to 30-year-olds and a 10-year increase among 35 to 50 year-olds. Drug use trends among college and non-college young adults, demographic subgroups, and other additional data are also included in the report.

"The value of surveys such as MTF is to show us how drug use trends evolve over decades and across development - from adolescence through adulthood," said Megan Patrick, Ph.D., a research professor at the University of Michigan and principal investigator of the MTF panel study. "Behaviors and public perception of drug use can shift rapidly, based on drug availability and other factors. It's important to track this so that public health professionals and communities can be prepared to respond."

Results from the related 2022 MTF study of substance use behaviors and related attitudes among teens in the United States was released in December 2022, and 2023 results are upcoming in December 2023.

For more information on substance and mental health treatment programs in your area, call the free and confidential National Helpline 1-800-662-HELP (4357) or visit www.FindTreatment.gov.

###

About the National Institute on Drug Abuse (NIDA): NIDA is a component of the National Institutes of Health, U.S. Department of Health and Human Services. NIDA supports most of the world's research on the health aspects of drug use and addiction. The Institute carries out a large variety of programs to inform policy, improve practice, and advance addiction science. For more information about NIDA and its programs, visit www.nida.nih.gov.

About the National Institutes of Health (NIH): NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit www.nih.gov.

About substance use disorders: Substance use disorders are chronic, treatable conditions from which people can recover. In 2021, over 46 million people in the United States had at least one substance use disorder. Substance use disorders are defined in part by continued use of substances despite negative consequences. They are also relapsing conditions, in which periods of abstinence (not using substances) can be followed by a return to use. Stigma can make individuals with substance use disorders less likely to seek treatment. Using preferred language can help accurately report on substance use and addiction. View NIDA's online guide.
NIH...Turning Discovery Into Health®

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Marijuana and hallucinogen use, binge drinking reached historic highs among adults 35 to 50 | National Institute on Drug Abuse

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For younger adults 19 to 30, marijuana, vaping, hallucinogen use are at or near historically high levels

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The impact poverty has on identity and the success of the college system (Rylee Barker, period 5)

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The impact poverty has on identity and the success of the college system (Rylee Barker, period 5)

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(Quantitive data)

This article explains how growing up in poverty leads to a majority group of people accepting their poverty-identity which leads to those who grow up in poverty to be complacent when selecting jobs. This leads to those who grew up in poverty to continue the cycle of working at low paying jobs with little opportunity to move up in the ranks.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4863915/

(Qualitative data)

This study focuses on explaining how in specific examples it is found that being below the poverty line has a negative impact on one’s social relations with peers and family.

How the college system has failed

https://files.eric.ed.gov/fulltext/ED565220.pdf

(Qualitative data)

This study focuses on explaining how the college system is responsible for the class divide we see in todays society using examples on students in mass amounts of debt to explain how the college system has failed to do what it was originally intended to do, which is to allow people to become more educated to get a better job.

https://www.insidehighered.com/news/2021/09/13/survey-shows-americans-are-divided-over-value-degree

(Quantitive data)

This article uses a study of 2200 Americans to explain the split in opinions of the college system, mentioning how those who went to college and are successful economically are much more likely to say that college is beneficial than those who didn’t go to college. It also described how age played a part in determining if college was worth it.

Rylee Barker, P5

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Mental health in adults and substance use.

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Mental health in adults and substance use.

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This article is an example of quantitative data collected about “Mental health and substance use” as it contains graphs, statistics, studies and measurements about the topic.

-Posted by Alondra P.

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Mental Health and Substance Use State Fact Sheets | KFF

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This analysis and series of state fact sheets examine data looking at mental health and substance use disorder across states and capacity to meet residents’ during the COVID-19 pandemic.

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This is an article that uses qualitative data and goes into depth how divorce might affects children.

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Divorce can be a difficult time for a family. Not only are the parents realizing new ways of relating to each other, but they are learning new ways to parent their children. When parents divorce, the effects of divorce on children can vary. Some children react to divorce in a natural and understanding way, while other children may struggle with the transition.

Children are resilient and with assistance the divorce transition can be experienced as an adjustment rather than a crisis. Since the children in a divorce vary (different temperaments, different ages), the effects of divorce on children vary, too. FamilyMeans understands this and approaches a divorce by understanding what the effects are on children of all dispositions.

With this in mind, here are some of the most commonly seen effects divorce has on children FamilyMeans can help parents manage:

Poor Performance in Academics

Divorce is difficult for all members of the family. For children, trying to understand the changing dynamics of the family may leave them distracted and confused. This interruption in their daily focus can mean one of the effects of divorce on children would be seen in their academic performance. The more distracted children are, the more likely they are to not be able to focus on their school work.

Loss of Interest in Social Activity

Research has suggested divorce can affect children socially, as well. Children whose family is going through divorce may have a harder time relating to others, and tend to have less social contacts. Sometimes children feel insecure and wonder if their family is the only family that has gotten divorced.

Difficulty Adapting to Change

Through divorce, children can be affected by having to learn to adapt to change more often and more frequently. New family dynamics, new house or living situation, schools, friends, and more, may all have an effect.

Emotionally Sensitive

Divorce can bring several types of emotions to the forefront for a family, and the children involved are no different. Feelings of loss, anger, confusion, anxiety, and many others, all may come from this transition. Divorce can leave children feeling overwhelmed and emotionally sensitive. Children need an outlet for their emotions - someone to talk to, someone who will listen, etc. - children may feel effects of divorce through how they process their emotions.

Anger/Irritability

In some cases, where children feel overwhelmed and do not know how to respond to the affects they feel during divorce, they may become angry or irritable. Their anger may be directed at a wide range of perceived causes. Children processing divorce may display anger at their parents, themselves, their friends, and others. While for many children this anger dissipates after several weeks, if it persists, it is important to be aware that this may be a lingering effect of the divorce on children.

Feelings of Guilt

Children often wonder why a divorce is happening in their family. They will look for reasons, wondering if their parents no longer love each other, or if they have done something wrong. These feelings of guilt are a very common effect of divorce on children, but also one which can lead to many other issues. Guilt increases pressure, can lead to depression, stress, and other health problems. Providing context and counseling for a child to understand their role in a divorce can help reduce these feelings of guilt.

Introduction of Destructive Behavior

While children go through a divorce, unresolved conflict may lead to future unexpected risks. Research has shown children who have experienced divorce in the previous 20 years were more likely to participate in crimes, rebelling through destructive behavior which harms a child's health, with more children reporting they have acquired smoking habits, or prescription drug use.

Increase in Health Problems

The process of divorce and its effects on children can be a stressful. Dealing with these issues can take its toll, including physical problems. Children who have experienced divorce have a higher perceptibility to sickness, which can stem from many factors, including their difficulty going to sleep. Also, signs of depression can appear, exacerbating these feelings of loss of well-being, and deteriorating health signs.

Loss of Faith in Marriage and Family Unit

Finally, despite hoping to have stable relationships themselves when they grow up, research has also shown children who have experienced divorce are more likely to divorce when in their own relationships. Some research indicates this propensity to divorce may be two to three times as high as children who come from non-divorced families.

Yet, while these are some of the possible effects of divorce on children, they are by no means absolutes, or written in stone. More and more, families understand just how stressful divorce is for their children, as well as their selves. Families have begun to turn to supportive services such as at FamilyMeans, seeking help to find a peaceful way to divorce. Through our Collaborative Divorce program, we are helping families more successfully navigate this transition, both for the sake of the parents, and for the children involved.

To learn how we can help you through your divorce, contact FamilyMeans today for more information.

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What Are the Effects of Divorce on Children?

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FamilyMeans helps families with counseling & therapy, caregiver support, debt & financial management, youth programs & grief support in Minnesota & Wisconsin.

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-Quantitative

This article provides statistics of the amount of people who have taken students loans, how much loan there is, and the impacts of rising student loans.

-Qualitative

https://www.usnews.com/education/best-colleges/paying-for-college/articles/see-how-student-loan-borrowing-has-changed

This article talks about the way that student loan debt has changed over the years and how inflation has made it more of a burden for borrowers and how it affects their quality of life.

-posted by Louisena

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-Quantitative

This website provides statistics about divorce, the main causes, and the prices. It also shows the difference between the divorce rates between different age groups.

-Qualitative

https://www.kleinattorneys.com/exploring-the-latest-trends-in-us-divorce-data-2023-insights/#:~:text=Over%20the%20years%2C%20divorce%20rates,higher%20than%20in%20earlier%20years.

This article discusses the change in divorce rates and how it reflects on the issues of society.

-posted by Louisena

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Topic 1 - Gender Stereotypes (-Daniella M.)

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Topic 1 - Gender Stereotypes (-Daniella M.)

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1st sociology topic: Gender stereotypes

Data examples:

(Qualitative data) - Studies have examined stereotypical views on gender identity, a specific study had examined the correlation of stereotypes and the moderating role of membership in a sports club as an example. The study depicts that sports clubs can lessen the stereotypical views individuals may have on both men and women as both are seen playing sports.

Https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10513099/

(Quantitative data) - This article evaluates how research studies believe exposure to gender stereotypes at a young age can harmfully affect a child's ways of thinking when growing up. The article depicts that 45% of individuals in a poll said when they were a child, they experienced gender stereotyping, 51% said it affected their career choices and 44% said it harmed their personal relationships.

https://www.fawcettsociety.org.uk/news/fawcett-research-exposure-gender-stereotypes-child-causes-harm-later-life

-Daniella Montoya, Period 5

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The Fawcett Society is today publishing new research which highlights the lifelong impact of gender stereotyping in childhood. In new polling, 45% of people said that when they were children, they experienced gender stereotyping as they were expected to behave in a certain way. Stereotyping in childhood has wide-ranging and significant negative consequences for both women and men, with more than half (51%) of people affected saying it constrained their career choices and 44% saying it harmed their personal relationships.

Half of all women affected (53%) said gender stereotyping had a negative impact on who does the caring in their own family. Older women were particularly affected by this. 7 in 10 younger women (18-34s) affected by stereotypes say their career choices were restricted.

Boys and men feel it too. 69% of men aged under 35 said that gender stereotyping of children has a damaging effect on perceptions of what it means to be a man or a woman. Men were as likely as women to say that gender stereotypes they experienced had negatively affected their relationships.
Sam Smethers, Fawcett Society Chief Executive, said:
"Gender stereotypes hold us all back. We have boys who cannot express their emotions, become aggressive, under-achieve at school and go on to be part of a culture of toxic masculinity which normalises violence. We have girls who have low self-esteem and issues with their body image, with one in five 14-year-old girls self-harming. We have a heavily segregated labour market where just 8% of STEM apprentices are women. Gender stereotyping is at the root of all of this. We have to grasp the challenge to change it."

The new data comes as the Fawcett Society publishes a review of evidence showing that harmful stereotypes are not only endemic, but they are unwittingly and repeatedly replicated and taught across society. Parents with new babies and young children inadvertently reinforce gender stereotypes creating a 'gendered world' through toys, play, language and environment. Teachers differently reward boys' and girls' behaviour, and representations in children's stories are often stereotyped. By age two children are aware of gender and, as early as six years old, children associate intelligence with being male, and 'niceness' with being female.

The report points to the damaging impact this has, drawing links between gender stereotypes held by adolescents and violence against women and girls, and the direct impact on the gender pay gap of the low take-up amongst young women of science, technology and maths subjects. Amid a crisis of self-harm among young women in particular, the report cites evidence that children whose friendship groups emphasise traditional gender stereotypes have lower wellbeing.
Sam Smethers added:
"This isn't a trivial issue about who wears pink or blue, gender stereotypes are harmful. But the evidence is clear, the wiring in our brains is soft not hard. We can challenge attitudes and change lives, but we must wake up to the harm that gender stereotypes are doing to all of us and the price that we are paying for it."

The research also identifies key interventions, particularly aimed at younger children, which work to challenge and change gender norms and mitigate against the harms seen in later life.

children's literature that challenges gender norms can undo children's previously held perceptions

whole-school approaches to gender stereotyping have demonstrated positive results

In Sweden challenging gender stereotypes is an explicit requirement of the school curriculum.

Additional key findings:

a majority of under 35s agree that stereotypes have wide-ranging adverse effects on children's subject choices at school, young people's career choices, attitudes to who does the caring and attitudes to what it means to be a man or a woman

54% of women aged over 35 affected by childhood stereotypes say they negatively affected decisions about whose job it is to care for others in your own family, compared with 38% of men aged over 35.

46% of people agree government should take action to challenge gender stereotyping.

In the coming weeks the Fawcett Society will launch a 'Commission on Gender Stereotypes in Early Childhood' to raise awareness, build a new consensus on the issue and examine the evidence of what works to challenge stereotypes, change childhood and change lives.

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Fawcett research shows exposure to gender stereotypes as a child causes harm in later life

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7 MARCH 2019: New polling today shows 'significant and wide-ranging consequences for both women and men'.

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This source portrays quantitative data as it provides statistics and percentages of the Americans that believe that economic equality exists in the US vs. the American who believe that there is an excessive amount of economic inequality.

This source also portrays qualitative data as it specifically states why views on economic inequality may differ due to different household situations or in other cases political standpoints.

-Daniyah Brown pd. 5

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Pew Research Center's Social & Demographic Trends Project

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Most Americans think there is too much economic inequality in the country these days, and about half say addressing inequality requires significant changes to the economic system. Even so, among those who see too much inequality, most (70%) say some amount is acceptable.

Roughly four-in-ten Americans (42%) say reducing inequality should be a top priority for the federal government. Among this group, large majorities say the influence it gives to the wealthy and the limits it places on people's opportunities are major reasons why inequality should be given priority status. Relative to other issues, though, the public does not rank inequality among the country's biggest problems.

Views on economic inequality differ significantly by party and by household income. And they differ by income within party coalitions - particularly among Republicans.

About six-in-ten Americans say there is too much economic inequality in the country

Overall, 61% of Americans say there is too much economic inequality in the country today. Roughly a quarter (23%) say the country has about the right amount of inequality and 13% say there is too little inequality.

Across income groups, the public is about equally likely to say there is too much economic inequality. However, upper- (27%) and middle-income Americans (26%) are more likely than those with lower incomes (17%) to say that there is about the right amount of economic inequality. Lower-income adults are more likely than those with middle and upper incomes to say there's too little inequality.

Views on this differ substantially by party. About four-in-ten Republicans and those who lean toward the Republican Party (41%) say there is too much inequality, compared with roughly eight-in-ten Democrats and Democratic leaners (78%). Instead, Republicans (43%) are much more likely than Democrats (7%) to say there is about the right amount of economic inequality in the country these days.

There are also differences by income tier within each party. Lower-income Republicans are more likely than higher-income Republicans to say there's too much inequality in the country today (48% vs. 34%). In turn, higher-income Republicans are more likely than those with lower incomes to say there is the right amount of inequality (54% vs. 28%).

Among Democrats, majorities in all income groups say there is too much economic inequality. But higher-income Democrats are more likely to express concern over this issue: 93% of upper-income Democrats say there's too much economic inequality in the country today, compared with 84% of middle-income Democrats and 65% of lower-income Democrats.

Most who see inequality as a problem say the economic system needs significant changes

Most Americans who see too much inequality in the country say that major changes are needed in order to address the issue. About two-thirds (67%) say this, while 14% say the system needs to be completely rebuilt. Roughly one-in-five (19%) say that only minor changes are required in order to address inequality.

Among those who say there is too much inequality, lower-income Americans are the most likely to say the system needs to be completely rebuilt - 18% say this compared with 13% of middle-income adults and 8% of those in the upper-income tier. Across income groups, roughly equal shares say the system will require major changes.

Again, there are differences by party. About a third of Republicans who say there is currently too much economic inequality (36%) say that only minor changes are required to fix the problem. Only 11% of Democrats who see too much inequality say the same. Instead, 74% of these Democrats think major changes are needed to fix the issue, compared with half of their Republican counterparts.

Republicans' views about how much work is needed to address economic inequality differ by income. A majority of lower-income Republicans who see too much inequality (63%) say major changes are needed in order to address the issue. By comparison, only 43% of upper-income Republicans who see too much inequality say the same. About one-in-ten lower income Republicans (14%) say the system needs to be completely rebuilt in order to address inequality.

Among Democrats, there is generally more agreement across income groups. Upper- and lower-income Democrats who say there is too much inequality largely agree that the system requires major changes (78% among upper-income and 72% among lower-income). Even so, lower-income Democrats are more likely than middle- and upper-income Democrats to say the system needs to be completely rebuilt.

Most who see too much economic inequality say some amount of inequality is acceptable

While most Americans say there is too much economic inequality in the country these days, many are willing to accept some level of it. Among those who say there is too much inequality, 70% say some amount is acceptable. About three-in-ten (29%) say no amount is acceptable.

Across all income groups, majorities of those who say there's too much economic inequality say that some amount is acceptable. Still, upper-income Americans (85%) are more likely to say this than those with middle (72%) or lower incomes (59%). Among lower-income Americans who say there is too much inequality, 40% say that no amount of economic inequality is acceptable in the country.

Republicans and Democrats who say there is too much economic equality are largely in agreement on this point. Majorities from each group say some inequality is acceptable (77% among Republicans and 68% among Democrats).

Health care and drug addiction seen as more pressing problems than inequality

When asked about 11 major issues facing the country today, concern about economic inequality ranks around the middle of the pack, with 44% saying this is a very big problem. By comparison, about two-thirds say the affordability of health care (66%) and drug addiction (64%) are very big problems.

The affordability of college, the federal budget deficit and climate change are also viewed as big problems by higher shares of adults. Inequality is roughly on par with concerns about illegal immigration and racism. And more view it as a very big problem than say the same about terrorism, sexism and job opportunities for all Americans.

Adults with lower incomes are more likely than those with middle or upper incomes to say that economic inequality is a very big problem in the country today. About half of lower-income adults (53%) say this, compared with 41% of middle-income Americans and 42% of those with higher incomes.

Concern over economic inequality also varies by partisanship. Two-thirds of Democrats - compared with just 19% of Republicans - say inequality is a very big problem in the country today. Again, Republicans' views on this differ significantly by income. Lower-income Republicans (35%) are much more likely than their middle-income (15%) and higher-income (8%) counterparts to say that economic inequality is a very big problem. Among Democrats, majorities of upper-, middle- and lower-income adults say economic inequality is a very big problem. Upper-income Democrats are somewhat more likely than lower-income Democrats to express this view (71% vs. 63%).

Lower-income Americans are more likely than other income groups to say reducing economic inequality should be a top priority for the federal government

Just as economic inequality doesn't rise to the top of the list of "very big problems," according to the American public, it's not viewed as the most pressing policy priority for the federal government to address. About four-in-ten U.S. adults (42%) say that reducing economic inequality should be a top priority for the federal government, placing it lower on the list than making health care more affordable (72%), dealing with terrorism (65%), reducing gun violence (58%) and climate change (49%), and roughly equivalent to reducing illegal immigration (39%).

The degree to which Americans see reducing income inequality as a priority differs by income and by party. Adults with lower incomes are more likely than those with middle and upper incomes to say this should be a top priority. And, by a margin of roughly three-to-one, Democrats are more likely than Republicans to say the same (61% vs. 20%).

Among Republicans, differences by income tier persist. While few Republicans overall say economic inequality should be a top government priority, lower-income Republicans are far more likely than higher-income Republicans to say this (35% vs 9%). Democrats, on the other hand, are united across income tiers. About six-in-ten Democrats across income groups say that reducing economic inequality should be a top priority for the federal government.

For those who say reducing inequality should be a government priority, large majorities point to unfair access it affords the wealthy and limits it places on others

When Americans who say reducing economic inequality should be a top priority for the federal government are asked why they believe that, 87% say inequality limits people's opportunities. A similar share (86%) says a major reason why reducing inequality should be a priority is that inequality gives the wealthy too much political influence and access. About seven-in-ten (71%) point to the harmful effect inequality has on economic growth, while 55% say inequality goes against the country's values.

Views on why reducing inequality should be a top priority for the federal government differ somewhat by party. For example, 89% of Democrats who say reducing inequality should be a top priority say the fact that inequality limits people's opportunities is a major reason why it should be addressed, while 79% of Republicans say the same.

Majorities of Republicans and Democrats who say reducing inequality should be a top priority also point to inequality giving the wealthy too much political influence and access and being harmful to economic growth as major reasons why they think reducing inequality should be a priority.

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Most Americans think there is too much economic inequality in the country these days, and about half say addressing inequality requires significant changes to the economic system. Even so, among those who see too much inequality, most (70%) say some amount is acceptable.

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Topic 2 - Divorces impact on children           (-Daniella M.) 

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Topic 2 - Divorces impact on children           (-Daniella M.) 

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2nd sociology topic: Divorce and its impact on children

Data examples:

(Qualitative data) - Studies as depicted through this website have made research supporting the fact that divorce heavily impacts children as a child's perception of divorce can result in even the most resilient kids to develop mental health problems when understanding that their family has become separated.

Https://www.proquest.com/docview/1636350624?sourcetype=Scholarly%20Journals

(Quantitative data) - This website depicts how divorce effects kids and how family structure undergoes the impact of divorce and changes as a result. The website supports the fact that divorce serves as a heavy impact on families by stating that children of divorce are 50% more likely to develop health problems, children of divorce are 20% less physically healthy, and how teenagers in single-parent or separated families are more likely to need psychological help in terms of their mental health due to the impact divorce leaves on them at a young age.

Https://www.owenbylaw.com/blog/2018/october/statistics-children-divorce/#:~:text=Children%20born%20out%20of%20wedlock,have%20custody%20of%20their%20children.

-Daniella Montoya, Period 5

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Marriages that end in divorce are prevalent in the United States, as 40% of all American marriages will end in a divorce at some point. While divorce significantly impacts the two spouses, it also impacts their children's lives. At Owenby Law Firm, we want our divorce clients to make an informed decision about what's best for them and their families. For this reason, we gathered these insightful statistics concerning children and divorce.

Children & Divorce Statistics

Family & Divorce

50% of all children in the United States will witness the end of a parent's marriage.

An additional 50% of the children who witness a parent's divorce will also see the breakup of a parent's second marriage.

Twins and triplets are 17% more likely to witness a divorce than children born without multiples.

A daughter is nearly 5% more likely than a son to see a parent's divorce.

Spouses with three daughters are 10% more likely to get a divorce than spouses with three sons.

Children born out of wedlock are 24% more likely to see their parents' divorce.

Children of divorce are 50% more likely to marry another child of divorce.

Children of divorce are 35% more likely to have a divorce of their own.

90% of divorced mothers have custody of their children.

79% of custodial mothers receive child support.

Under 30% of custodial fathers receive child support.

Physical Effects

Children of divorce are more likely to experience physical hardship (injury, asthma, headaches, speech impediments, etc.) than children whose parents remain married.

Children of divorce are 50% more likely to develop health problems.

Children of divorce are 20% less physically healthy.

Emotional Effects

Children of multiple divorces are considered "less pleasant" to be around by their peers.

Teens in single-parent and blended families are 300% more likely to need psychological help.

Children of divorce are more likely to develop psychological problems when compared to children who lose a parent to death.

Children from broken homes are almost twice as likely to attempt suicide.

Educational Effects

Children of multiple divorces receive lower grades than their peers.

Children of divorce are twice as likely to drop out of high school.

Need an Understanding & Caring Team?

Clearly, divorce can be difficult for children; however, these are only statistics and don't have to be you and your family's divorce scenario. We truly believe hiring the right representation can have a significant impact on your divorce proceedings. Owenby Law Firm prides itself in not just investing in your case but investing in your family's future. When you're ready, feel free to give us a call at the number below.
Need caring and invested representation? Call (904) 770-3141 now for a free initial consultation.

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Thinking about divorce? Here are some statistics to help you identify trends and scenarios that your children will deal with when going through the divorce process.

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This source includes qualitative data as it thoroughly describes the rapid rise in the participation of women in the workforce which has contributed towards major development in the workforce. It also includes how women were more likely to pursue higher levels of education.

This source also includes quantitative data as it repeatedly includes percentages of how much women’s contributions to the improvement of work places have drastically increased. For example the author includes that women’s participation in work places went up from 57.1 to 57.4 in only a span of months.

Daniyah Brown pd. 5

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In 2019, 57.4 percent of all women participated in the labor force. This was up from 57.1 percent who participated in 2018, but 2.6 percentage points below the peak of 60.0 percent in 1999. By comparison, the labor force participation rate for men was 69.2 percent in 2019, little changed from the previous year and 17.4 percentage points below its peak of 86.6 percent in 1948.

The rapid rise in women's labor force participation was a major development in the labor market during the second half of the 20th century. Overall, women's labor force participation increased dramatically from the 1960s through the 1980s, before slowing in the 1990s. With the dawn of the 21st century, labor force participation among women began a gradual decline, until the participation rate hit a recent low in 2015 of 56.7 percent.

Women's involvement in the labor market has changed in several notable ways over the past several decades. For example, women became much more likely to pursue higher levels of education: from 1970 to 2019, the proportion of women ages 25 to 64 in the labor force who held a college degree quadrupled, whereas the proportion of men with a college degree a little more than doubled over that time. Since 1970, women have become more likely to work full time and year round. Also, women with children have increased their participation in the labor force considerably. In addition, women's earnings as a proportion of men's earnings have grown over time: women working full time earned 62 percent of what men earned in 1979 and 82 percent in 2019. More recently, women in the baby-boom generation (defined as people born between 1946 and 1964) have begun to retire in large numbers, which has put downward pressure on their labor force participation rate over the past decade or so.

This report presents labor force and earnings data for women and men from the Current Population Survey (CPS), a national monthly survey of approximately 60,000 households conducted by the U.S. Census Bureau for the U.S. Bureau of Labor Statistics. Unless otherwise noted, data are annual averages from the CPS. (For a detailed description of the source of the data and an explanation of concepts and definitions used, see the technical notes.)

Selected demographic characteristics

Women's labor force participation was 57.4 percent in 2019, up from 57.1 percent in 2018. Men's labor force participation, which always has been much higher than that for women, was 69.2 percent in 2019, little changed from the previous year (69.1 percent). (See table 2.)

In 2019, the unemployment rate for women was 3.6 percent, down 0.2 percentage point from a year earlier. The rate for men was 3.7 percent in 2019, also down 0.2 percentage point from a year earlier. Women's unemployment rates varied considerably by race and ethnicity. In 2019, Asian women had the lowest rate (2.7 percent), followed by White women (3.2 percent). Unemployment rates for Hispanic or Latino women and Black or African American women were higher, at 4.7 percent and 5.6 percent, respectively. Men's unemployment rates exhibit a similar pattern. The rates for Asian men (2.7 percent) and White men (3.3 percent) were below those for Hispanic men (4.0 percent) and Black men (6.6 percent). (See tables 2 and 3.)

Labor force participation varies by marital status and differs between women and men. Never-married women had the highest participation rate of all women, at 65.0 percent in 2019. Separated and divorced women were more likely to participate in the labor force (63.7 percent and 60.8 percent, respectively) than married women (58.6 percent). By contrast, married men were more likely to participate in the labor force (73.0 percent) than separated men (70.1 percent), never-married men (68.1 percent), and divorced men (64.7 percent). Labor force participation rates for widowed women and men, who tend to be older, were 19.8 percent and 24.2 percent, respectively. (See table 4.)

The labor force participation rate for women with children under 18 years of age was 72.4 percent in March 2019, lower than the rate of 93.5 percent for men with children under 18 years. Among mothers, the labor force participation rate for those with children 6 to 17 years old, at 77.0 percent, was considerably higher than for those with younger children. The rate for women with children under 6 years old was 66.4 percent, and the rate for women with children under 3 years old was 63.8 percent. By contrast, the labor force participation rate for fathers was fairly similar, regardless of the age of their children; the rate was 92.2 percent for fathers with children 6 to 17 years old, slightly lower than the rates for fathers of children under 6 years old (95.0 percent) and fathers of children under 3 years old (95.3 percent). (See tables 5 and 7; data were collected in the 2019 Annual Social and Economic Supplement to the CPS.)

Historically, unmarried mothers are much more likely to participate in the labor force than married mothers. In March 2019, 78.2 percent of unmarried mothers were in the labor force, compared with 70.1 percent of married mothers. (See table 6; data were collected in the 2019 Annual Social and Economic Supplement to the CPS.)

Educational attainment

The educational attainment of women ages 25 to 64 in the labor force has risen substantially over the past half century. In 2019, 45 percent of women ages 25 to 64 held a bachelor's degree and higher, compared with 11 percent in 1970. In 2019, 5.4 percent of women in the labor force had less than a high school diploma-that is, did not graduate from high school or earn a GED-down from 34 percent in 1970. (See tables 9A and 9B.)

Occupation and industry

Women accounted for 51.8 percent of all workers employed in management, professional, and related occupations in 2019, somewhat more than their share of total employment (47.0 percent). The share of women in specific occupations within this large category varied. For example, 18.7 percent of software developers, 27.6 percent of chief executives, and 36.4 percent of lawyers were women, whereas 88.9 percent of registered nurses, 80.5 percent of elementary and middle school teachers, and 61.7 percent of accountants and auditors were women. (See table 11.)

In 2019, Asian and White women were more likely to work in higher paying management, professional, and related occupations (53.3 percent and 46.1 percent, respectively) than were Black (37.2 percent) and Hispanic women (28.5 percent). However, Black (27.6 percent) and Hispanic (31.1 percent) women were more likely than Asian (20.2 percent) and White women (19.5 percent) to work in lower paying service occupations. (See table 12.)

By industry, women accounted for more than half of all workers within several sectors in 2019: education and health services (74.8 percent), other services (53.9 percent), financial activities (52.6 percent), and leisure and hospitality (51.2 percent). (Other services include repair and maintenance industries, personal and laundry services, membership associations and organizations, and private households.) However, women were substantially underrepresented (relative to their share of total employment) in manufacturing (29.4 percent), agriculture (26.2 percent), transportation and utilities (24.1 percent), mining (15.8 percent), and construction (10.3 percent). (See table 14.)

Earnings

In 2019, women who worked full time in wage and salary jobs had median usual weekly earnings of $821, which represented 82 percent of men's median weekly earnings ($1,007). Among women, earnings were higher for Asians ($1,025) than for Whites ($840), Blacks ($704), and Hispanics ($642). Women-to-men earnings ratios were higher for Blacks (92 percent) and Hispanics (86 percent) than for Whites (81 percent) and Asians (77 percent). (See table 16; note that the comparisons of earnings in this report are on a broad level and do not control for many factors, like occupation, that may be important in explaining earnings differences.)

Women's median usual weekly earnings vary by educational attainment. In 2019, female full-time wage and salary workers age 25 and older with less than a high school diploma had earnings of $494. Women who had only a high school diploma had earnings of $633, those with an associate's degree had earnings of $763, and those with a bachelor's degree and higher had earnings of $1,195. (See table 17.)

By occupation, median usual weekly earnings of female full-time wage and salary workers were the highest in 2019 for chief executives ($2,019), veterinarians ($1,985), computer and information systems managers ($1,892), physicians and surgeons ($1,878), lawyers ($1,878), and pharmacists ($1,877). Earnings for men were highest for chief executives ($2,509), physicians and surgeons ($2,500), architectural and engineering managers ($2,457), pharmacists ($2,245), and lawyers ($2,202). (See table 18.)

In 2019, 3 percent of women paid hourly rates had earnings at or below the prevailing federal minimum wage ($7.25 per hour). Among women 25 years and older who were paid an hourly rate, 2 percent had earnings at or below the minimum wage, compared with about 6 percent of women ages 16 to 24. (See table 20.)

Hours of work

In 2019, 23 percent of employed women usually worked part time-that is, less than 35 hours per week. By comparison, 12 percent of employed men usually worked part time in 2019. The percentage of employed women working part time has not changed much over the past five decades. (See table 21.)

Of all women who worked at some point during the calendar year of 2018, 64 percent worked full time and year round (50 to 52 weeks), compared with 41 percent in 1970. The proportion of men who worked full time and year round also rose over the period, from 66 percent in 1970 to 76 percent in 2018. (See table 23; data were collected in the 1971 through 2019 Annual Social and Economic Supplements to the CPS and reflect earnings and work experience in the previous calendar year.)

Married-couple families

Among married-couple families, 53 percent had earnings from both the wife and the husband in 2018. This percentage, which has changed little over the past 10 years, is below the peak of 60 percent in the mid- to late 1990s but above the 44 percent seen in 1967. Couples in which only the husband worked for pay represented 18 percent of married-couple families in 2018, versus 36 percent in 1967. (See table 24B; data were collected in the 1968 through 2019 Annual Social and Economic Supplements to the CPS and reflect earnings and work experience in the previous calendar year.)

The working poor

Among people who were in the labor force for at least 27 weeks in 2018, more women (3.9 million) than men (3.1 million) lived below the official poverty level. The working-poor rate (the ratio of the working poor to all individuals who were in the labor force for at least 27 weeks) was 5.3 percent for women and 3.7 percent for men. Black and Hispanic women were much more likely to be among the working poor than White or Asian women. The working-poor rates for Black and Hispanic women were 9.7 percent and 8.7 percent, respectively, higher than the rates of 4.5 percent for White women and 3.1 percent for Asian women. (See table 26; data are from the 2019 Annual Social and Economic Supplement to the CPS and reflect earnings and work experience in the previous calendar year.)

Worker displacement

From January 2017 through December 2019, 2.7 million workers age 20 and older were displaced from jobs they had held for at least 3 years; women accounted for 45 percent of those displaced. Labor market outcomes were similar for displaced women and men. Displaced women were about as likely as men to have found a new job in January 2020: the reemployment rate was 68 percent for women and 72 percent for men. Displaced women and men were also about equally likely to be unemployed in January 2020, at 13 percent and 12 percent, respectively. Twenty percent of displaced women and 16 percent of displaced men had left the labor force. (See table 27; data are from the January 2020 Displaced Worker, Employee Tenure, and Occupational Mobility Supplement to the CPS.)

Employee tenure

In January 2020, the median number of years that employed women had been with their employers was 3.9 years, about unchanged from January 2018. Median employee tenure (the point at which half of all workers had more tenure and half had less tenure) for men held at 4.3 years. (See table 28; data are from the January 2020 Displaced Worker, Employee Tenure, and Occupational Mobility Supplement to the CPS.)

School enrollment

Of the 3.2 million young people ages 16 to 24 who graduated from high school between January and October 2019, 66 percent (2.1 million) were enrolled in college in October of that year. For the 2019 high school graduates, the college enrollment rate was higher for young women (70 percent) than for young men (62 percent). (See table 29; data are from the October 2019 School Enrollment Supplement to the CPS.)

Among those enrolled in high school, young women were slightly more likely to be in the labor force (23.7 percent) in October 2019 than were young men (21.0 percent). Among college students, women were much more likely to participate in the labor force than men, at 53.6 percent and 46.1 percent, respectively. Among young people ages 16 to 24 who were not enrolled in school in October 2019, the unemployment rate for those without a high school diploma was 12.4 percent for young women and 16.1 percent for young men. In contrast, the unemployment rates for young women and men with at least a bachelor's degree were 4.8 percent and 5.8 percent, respectively. (See table 30; data are from the October 2019 School Enrollment Supplement to the CPS.)

Multiple jobholders and the self-employed

In 2019, 8.1 million workers had more than one job. Just over half (4.1 million) of these workers were women. The multiple jobholding rate for women, at 5.6 percent, was higher than that for men, at 4.7 percent. (See table 31.)

In 2019, 4.8 percent of working women in nonagricultural industries were self-employed, compared with 6.4 percent of men. Among the self-employed, 40.1 percent were women in 2019, compared with 26.8 percent in 1976. (See table 32.)

Foreign born

Foreign-born women were less likely than native-born women to be in the labor force in 2019 (54.8 percent, compared with 57.9 percent). By contrast, foreign-born men were more likely to be in the labor force (78.0 percent) than were native-born men (67.4 percent). The unemployment rate for foreign-born women, at 3.7 percent, was about the same as for native-born women, at 3.6 percent. At 2.7 percent, the unemployment rate for foreign-born men was lower than that of native-born men (4.0 percent). (See table 33.)

Union membership

In 2019, 9.7 percent of female wage and salary workers were members of unions, compared with 10.8 percent of their male counterparts. For both men and women, the union membership rate in 2019 was lower than in 1983 (the first year that union membership data were regularly collected in the CPS), but the rate for men fell by much more than did the rate for women. In 1983, union membership rates were 24.7 percent for men and 14.6 percent for women. (See table 34.)

Veterans

There were 1.1 million female veterans of the U.S. Armed Forces in the labor force in 2019. Women accounted for 12 percent of the 9.3 million veterans in the labor force. The unemployment rate for female veterans was 3.7 percent in 2019, and the rate for male veterans was 3.0 percent. (See table 35.)

People with disabilities

Of the 16.2 million women with disabilities in 2019, 2.9 million, or 17.8 percent, participated in the labor force. A little over half of women with disabilities (52 percent) were age 65 and older; labor force participation among this age group was 5.7 percent, compared with 31.0 percent for those ages 16 to 64. Among the 14.2 million men with disabilities, 24.3 percent participated in the labor force in 2019. Forty-seven percent of men with disabilities were age 65 and older. Among men in this age group, 10.8 percent were labor force participants, compared with 36.3 percent of men ages 16 to 64 with disabilities. Among people with a disability, the unemployment rate for women was 7.3 percent, nearly the same as that for men, at 7.4 percent, but more than twice the rates of women and men without a disability (3.5 percent and 3.6 percent, respectively). (See table 36.)

Race, age, gender, and Hispanic
or Latino ethnicity

Civilian
noninstitutional
population

Civilian labor force

Not in labor
force

Year

Civilian labor force (thousands)

Percent distribution

Total

Less than a high school diploma

High school graduates, no college⁽¹⁾

Some college or associate's degree

Bachelor's degree and higher⁽²⁾

n.e.c. = not elsewhere classified.
Note: Dash indicates data not available.
Source: U.S. Bureau of Labor Statistics, Current Population Survey.

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This report presents historical and recent labor force and earnings data for women and men from the Current Population Survey (CPS), a national monthly survey of approximately 60,000 households.

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Mental health in adults and substance abuse. 

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Mental health in adults and substance abuse. 

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In this interview they talk about mental health and how substance abuse influences.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8950841/

This article contains qualitative data about how substance use affects people with social disadvantages.

-Posted by Alondra P.

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Psychiatric Interviewing: Asking about substance use

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Ipad kid epidemic/how children are being raised now

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Ipad kid epidemic/how children are being raised now

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An example of qualitative data that shows many studies that the support the idea that young kids glued to technology isn't good for them.

Emiliana Soto

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Young children are increasingly becoming addicted to their screens, leading to negative effects on their development.
It seems that everywhere we go - restaurants, streets and playgrounds - there always seems to be a kid entranced by their iPad, hopelessly unaware of what's going on around them.

This is part of a new generation of "iPad kids," a boom in children hooked to their tablets as a result of the increasing integration of technology into our daily lives at ever younger ages, further exacerbated by the device-reliance caused by the pandemic.

According to the U.S. Census Bureau, 80% of households with children owned a tablet in 2021, compared to only 60% of households without children. Even for children at the preschool level, 24% of their parents had bought them tablets.

Beginning with the pandemic, screen time for children under 18 has increased by over 52%, from 2.7 hours to 4.1 hours a day. Given the addictive nature of social media apps - including YouTube, TikTok and Instagram - many children have gone down a spiral of iPad addiction.

People casually throw around the phrase "iPad kid" to refer to their siblings or children, pointing out how they're always on their tablets. Yet, using this phrase as a humorous characterization fails to recognize the real dangers.

With the increase in iPad usage only imposing damage on children, parents must begin to take action and stop letting electronics take care of their child.

The harms of screen time addiction among children can already be seen. A 2023 study found that kids who had more than four hours of screen time compared to those you didn't were five times more likely to have stunted communication skills, twice as likely to have stunted personal and social skills and twice as likely to have stunted fine motor skills.

This lack of communication skills extends even further as children addicted to their screens often become short tempered, growing a self-centered ego as if everything has to go their way every time.

A study by the University of Washington found that 93% of parents reported that their child, ages 1 to 5, "throws a tantrum, whines or resists ending screen time," and 37% said enforcing screen time limit "almost always ends in a fight."

Even worse, the harmful effects of device use from early childhood can extend to children's teenage and adult years. A study by Yale University concluded that youth who spent more time on digital technology were more likely to exhibit higher levels of internalizing problems two years later, including depression, anxiety and social anxiety. The study also showed links between screen time and complaints about physical symptoms.

Currently, 95% of teenagers use smartphones, with over 45% reporting near-constant use. With more kids getting hooked on iPads, the future of teenagers' screen time addiction and mental health looks rather despondent.

This begs the question: If iPads are so harmful, why are so many children getting access to them? The answer stems from parents, who have voiced that iPads are an easy way to keep their kids engaged, since a quick distraction for their children can alleviate stress in potentially difficult situations.

However, parents should recognize that introducing screen time to their children at an early age has many negative effects - a way to calm kids down may turn into a cycle of addiction that impacts their development and later life.

Providing a child with unlimited access to the internet can in no way be an adequate substitute for real parenting, especially with such young children. A child's development needs the care and attention - and face-to-face engagement - that only a parent or guardian can provide.

Parents should introduce screen time controls and educate their kids about the harms of screen time or simply not buy an iPad for their children at all.

Better still, parents should focus on forming bonds with their child at a young age, as parent-child interaction is key for the child to develop into a happy, resilient individual. They can play board games, go to a park or spend other quality time with their kids.

Here is a plea to parents: Think long and hard before bringing a tablet into your home. A simple distraction may seem desirable at first, but there are much better things to do with your kids that don't involve an iPad.

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New 'iPad kid' phenomenon reflects unsettling reality of screen time addiction - and it's time for parents to do something about it

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Young children are increasingly becoming addicted to their screens, leading to negative effects on their development. It seems that everywhere we go - restaurants, streets and playgrounds - there always seems to be a kid entranced by their iPad, hopelessly unaware of what's going on around them.

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Ipad kid epidemic/how children are being raised now

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Ipad kid epidemic/how children are being raised now

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An example of qualitative data that goes into detail about how the pandemic has cased kids to receive more screentime than ever and how it's affecting them.

Emiliana Soto

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Children’s Screen Time Has Soared in the Pandemic, Alarming Parents and Researchers (Published 2021)

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“There will be a period of epic withdrawal,” warned one addiction specialist, once schools, activities and social life return to normal.

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Race Plays a Part in Wrongful Convictions

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Race Plays a Part in Wrongful Convictions

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This article uses quantitative data to go into detail how race is a factor in wrongful convictions.

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According to a recent study of wrongful convictions, the number of people convicted of crimes who have been proved innocent has increased 70% in the last five years. An analysis of those cases revealed that race is a substantial factor in why people are wrongly convicted.

The report, Race and Wrongful Convictions in the United States 2022, reviewed the cases of 3,200 innocent defendants exonerated in the U.S. since 1989 and found that Black Americans are seven times more likely than white Americans to be falsely convicted of serious crimes. This is true across all major crime categories except for white collar crime, the report said.

Black Americans are seven times more likely than white Americans to be falsely convicted of serious crimes.

For homicides, the National Registry of Exonerations found the risk of a wrongful conviction in cases where the victim was white is nearly twice that of cases where the victim was Black. Racial disparities are even worse for sexual assault crimes, where researchers found that Black people are eight times more likely to be wrongly convicted than a white person for a crime involving sexual violence. Again, the study found the risk of a wrongful conviction increases dramatically if the victim is white as opposed to a person who is Black.

The report reveals that racial disparities are most extreme in cases involving drug crimes. Black people are 19 times more likely to be wrongly convicted of a drug crime than white people, according to the report.

Across all crime categories, researchers found that Black people wrongly convicted of a crime are likely to spend much longer periods of time in unjust incarceration than innocent white people.

The report identifies many of the specific reasons for wrongful convictions and concludes that police or prosecutorial misconduct are often the source of these miscarriages of justice.

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Study Shows Race Is Substantial Factor in Wrongful Convictions

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A recent study analyzing the cases of people who were wrongfully convicted revealed that race was a substantial factor.

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An example of qualitative data with statistics and a chart that show how much crime has increased over the past few years in America.

Emiliana Soto

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(Quantitative) This article provides evidence on the work places having favoritism towards one gender

https://people.cs.uchicago.edu/~ravenben/publications/pdf/gender-cscw18.pdf

(Qualitative) In this article it states that some places had biased but it dropped.

-Dana

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AssessFirst, Paris, France

King's College London, Institute of Psychiatry, Psychology and Neuroscience, University of London, London, United Kingdom

Birkbeck Business School, Faculty of Business and Law, Birkbeck, University of London, London, United Kingdom

Introduction: Gender biases in hiring decisions remain an issue in the workplace. Also, current gender balancing techniques are scientifically poorly supported and lead to undesirable results, sometimes even contributing to activating stereotypes. While hiring algorithms could bring a solution, they are still often regarded as tools amplifying human prejudices. In this sense, talent specialists tend to prefer recommendations from experts, while candidates question the fairness of such tools, in particular, due to a lack of information and control over the standardized assessment. However, there is evidence that building algorithms based on data that is gender-blind, like personality - which has been shown to be mostly similar between genders, and is also predictive of performance, could help in reducing gender biases in hiring. The goal of this study was, therefore, to test the adverse impact of a personality-based algorithm across a large array of occupations.

Method: The study analyzed 208 predictive models designed for 18 employers. These models were tested on a global sample of 273,293 potential candidates for each respective role.

Results: Mean weighted impact ratios of 0.91 (Female-Male) and 0.90 (Male-Female) were observed. We found similar results when analyzing impact ratios for 21 different job categories.

Discussion: Our results suggest that personality-based algorithms could help organizations screen candidates in the early stages of the selection process while mitigating the risks of gender discrimination.

1. Introduction

Research dating back as far as the 1970s (see Davison and Burke, 2000 for a review, which covers multiple countries) has shown that gender discrimination in hiring occurs, and continues to be a prevalent issue in today's hiring practices-despite the findings from cross-temporal meta-analysis indicating that belief in competence equality has grown over time ( Eagly et al., 2020). Yet, a recent meta-analysis of hiring discrimination experiments conducted between 2005 and 2020 ( Lippens et al., 2023) reveals that gender discrimination is highly complex and varied, with instances of both males and females facing discrimination in certain cases. The relative advantages of male and female candidates hinge on demand-side factors. These may include the impact of certain job characteristics that are traditionally associated with one gender over the other on selection criteria, as well as how closely a candidate aligns with the typical characteristics of their gender category. Further substantiating these findings, a comprehensive meta-re-analysis of over 70 employment audit experiments conducted across more than 26 countries and five continents concluded that in male-dominated professions, which are typically higher-paying, being female can be a disadvantage. Conversely, in female-dominated professions, which tend to be lower-paying, being female is viewed positively ( Galos and Coppock, 2023), thus confirming gender-role congruity bias. Besides, this bias consistently manifests in hiring decisions. For instance, Koch et al. (2015) meta-analysis concluded that it is more pronounced among male raters, and it does not diminish even when raters are provided with additional information about the candidate. However, despite both males and females facing discrimination based on occupation characteristics, the price paid by females is often higher than that of their male counterparts, as they often have limited access to higher-paying jobs and roles with greater responsibilities. In addition, in line with the backlash effect, which refers to a social and psychological phenomenon where individuals are penalized for violating societal norms or expectations regarding gender ( Williams and Tiedens, 2016), females are in a double-bind. As concluded by Castaño et al. (2019) in a systematic review, "if women adopt masculine roles they are perceived as cold and instrumental, whereas if women adopt feminine roles they are perceived as less competent" (p. 0.14) -an effect that men do not typically experience. As a consequence, in highly prestigious occupations, even if females perform equally, they are rewarded significantly lower ( Joshi et al., 2015). It results that the representation of females progressively declines higher up the hierarchy. Data from LinkedIn's Economic Graph indicates that obstacles for females begin to appear as early as at the managerial level. Globally, only 25% of female ascend to the C-Suite level, even though the ratio of male to female is nearly equal at the individual contributor level ( LinkedIn, 2022).

Addressing gender bias in hiring is not only a matter of ethical responsibility, but it is also crucial due to the harmful consequences such biases can engender. For example, a meta-analysis by Triana et al. (2019) found that perceived gender discrimination is negatively related to job attitudes, physical health outcomes and behaviors, psychological health, and work-related outcomes. Interestingly, even minimal biases can lead to substantial instances of hiring discrimination and losses in productivity, underscoring the significant practical impact of these biases. In a series of simulations, Hardy et al. (2022) established that a slight bias of 2.2% led to disparate treatment rates that were 13.5% higher than those observed in a bias-free model. Furthermore, the chances of a woman receiving a favorable hiring decision were almost halved, being 49% lower than the odds for their male counterparts with similar qualifications. The financial repercussions of this were significant, with bias accounting for 16.1% of new hire failure rates, ultimately leading to a utility loss per hiring due to bias amounting to -$710.54 per hire. The negative impact started to manifest with as little as 1% bias, which resulted in 8.7% disparate treatment and a utility loss of -$355.36. This effect escalated under the simulation of a higher 4% bias, where it led to 20.3% disparate treatment and a staggering utility loss of -$2,125.64. Furthermore, the authors found that contextual factors alter, but cannot obviate the consequences of biased evaluations. Consequently, it's crucial to identify strategies that reduce bias in hiring decisions.

2. Intervention for mitigating gender bias

Efforts have been made to implement interventions for reducing gender discrimination, but yielded mixed outcomes. According to a recent systematic review, half of the intervention measuring social change in gender equality did not achieve beneficial results ( Guthridge et al., 2022), leading the authors to conclude that "in the past 30 years we have not uncovered the keys to social change in order to enhance gender equality and non-discrimination against girls and women" (p. 0.335). In the specific context of recruitment, studies have consistently underlined the pervasive nature of unconscious stereotypes and the ease with which these biases can be triggered. For instance, Isaac et al. (2009), in a comprehensive review spanning over 30 years of research, found that conventional interventions, such as diversity training and employment equity programs, fail to guarantee gender equity in hiring despite their widespread use, and can even prove to be counterproductive. Similarly, counter-stereotype training appears to be effective only under specific conditions. Nevertheless, their review pinpointed several institutional interventions that could be promising to foster gender equity in hiring. They also highlighted actions that female applicants themselves could undertake. While their research suggests viable interventions to promote gender equity in hiring, it also underscores the issue's complexity. Some recommendations appear as desperate "Hail Mary" attempts to combat gender bias. For instance, the advice, "If you are visibly pregnant, it might be wise to obscure it with your clothing" (p. 0.6), while effective, exposes the depth of societal bias we are grappling with. Also, it is important to recognize that such advice could be considered as pernicious, as it perpetuates and reinforces societal bias, rather than addressing the root causes of gender inequity in hiring practices.

Traditional interventions include diversity or counter-stereotype training ( Bezrukova et al., 2012), the introduction of gender quotas ( Krook and Zetterberg, 2014), lean-in approach ( Chrobot-Mason et al., 2019), and equity guidelines. Yet, according to the International Labor Organization, even though 75 percent of companies worldwide have embraced policies of equal opportunity, diversity, and inclusion, gender biases stubbornly linger in selection ( International Labour Organization [ILO], 2019). Indeed, despite good intentions, such interventions can have unintended consequences and potentially generate new issues. Caleo and Heilman (2019) synthesized the potential ways in which these interventions could backfire, including (1) promoting gender stereotyping, (2) reducing personal responsibility for bias, (3) fueling the perception of undeserved preference, (4) prompting negative trickle-down effects, (5) creating tokens, (6) encouraging discriminatory behavior, (7) depleting cognitive resources, and (8) doing harm to those who lead bias-reducing initiatives. Their analysis highlights the complex nature of gender bias in hiring, and the importance of carefully considering the unintended consequences of interventions. To this end, we'll briefly explore the impact of conventional interventions in the next paragraphs.

Diversity training has been shown to be effective at reducing the extent to which assessors assign stereotypic labels to male candidates (e.g., determined and competitive) and female candidates (e.g., submissive and helpful) ( Kawakami et al., 2007). However, this effect did not emerge if assessors engaged in the stereotyping task immediately after their counter-stereotype training. Despite the potential impact of training interventions, their effectiveness tends to be short-lived, with discrimination resurfacing as early as 3 months after the interventions ( Derous et al., 2020). This finding emphasizes the limited long-term sustainability of such interventions in combating bias. Also, other research showed that training claiming to limit unconscious bias is ineffective, and ironically contributes to activating stereotypes ( Madera and Hebl, 2013). For instance, Dobbin et al. (2007) conducted a study revealing that despite the adoption of sensitivity and diversity training by big corporations, there was no significant increase in gender diversity. This finding raises questions about the effectiveness of such training programs in achieving meaningful change. As argued by Noon (2018), unless the everyday discriminatory acts are effectively addressed, the adoption of such unconscious bias training in the workplace and in hiring may have limited utility to mitigate biases.

Gender quotas have been implemented as a means to address gender inequality, but research suggests that their effectiveness is not without drawbacks. While they aim to promote gender diversity, there are concerns that quotas may inadvertently reinforce stereotypes and fuel the perception that women are less competent. This is supported by findings from Leibbrandt et al. (2018), who found evidence of a severe backlash against women under gender quotas, leading to sabotage and undermining their success. Furthermore, the impact of quotas on corporate boards has also been examined. Yu and Madison (2021) conducted research showing that quotas for women on corporate boards have primarily resulted in decreased company performance. This raises questions about the direct correlation between quotas and improved outcomes. In addition, the introduction of gender quotas may intensify the negative effects of second-generation bias and perpetuate gender inequality in the workplace, as suggested by recent work by Loumpourdi (2023). This highlights the complex dynamics at play when implementing quotas and emphasizes the need for comprehensive approaches that address underlying biases and promote gender equality in a more nuanced and systemic manner.

Regarding equity guidelines, Ng and Wiesner (2007) found that implementing basic employment equity messages only had a positive impact when underrepresented group members were equally or more qualified than the majority group. However, when preferential treatment was given to less qualified candidates, men who were underrepresented in the profession tended to be favored over underrepresented women. Similarly, stronger employment directives typically led to detrimental outcomes whereby such perceived coercive employment equity messages resulted in men being favored over women. As a result, Castilla and Benard (2010) draws a paradoxical conclusion that in organizations that strongly advocate for meritocracy, decision-makers tend to exhibit a preference for men over equally qualified female employees. This finding highlights a discrepancy between the professed value of meritocracy and the actual biases that can influence decision-making processes.

Considering the evidence of gender biases in selection and assessment, in conjunction with interventions that are shown to be largely ineffective, there is a need to explore alternative ways of mitigating these issues. This is particularly important since gender diversity is positively related with higher employee wellbeing and positive job appraisal ( Clark et al., 2021), as well as with productivity in contexts where gender diversity is viewed as normatively accepted ( Zhang, 2020). To address these challenges, an important step is to enhance the structure of the evaluation and selection procedure. For example, Wolgast et al. (2017) showed that using tools for systematizing information about the applicants could help in mitigating biases and in selecting more competent applicants.

3. Algorithms as a solution against bias

One solution to alleviate biases could be the use of hiring algorithms, which allow us to go beyond our intuition and cognitive biases, by bringing standardization and structure to hiring decisions. An algorithm could be defined as a set of operations or tasks to be carried out following a certain logic, with the aim of answering a question or solving a problem ( Jean, 2019). In other words, an algorithm acts like a set of instructions, turning the information we feed into it into recommendations. The utilization of algorithms at different steps of the hiring pipeline is becoming increasingly prevalent in today's workplace ( Tambe et al., 2019), and systematic review point out the potential for these algorithms to revolutionize HR management ( França et al., 2023). In the hiring process, algorithms learn from past data of old applicants to predict how suitable future applicants might be for a job. Basically, they figure out what attributes from past successful applicants led to good job performance, and then use this understanding to predict which future applicants might be the best fit for the job. The increasing adoption of algorithms is largely driven by their efficiency. For example, in a meta-analysis comparing mechanical and clinical data combination in selection, Kuncel et al. (2013) showed that, in predicting job performance, the difference in the validity between mechanical and clinical data combination methods resulted in an enhancement of prediction accuracy exceeding 50%. Other studies showed that algorithms make better hiring decisions in terms of the employee's performance outcomes ( Sajjadiani et al., 2019; Li et al., 2020) and in hiring fill rate ( Horton, 2017). Taken together in a recent systematic literature review, these results regarding performance suggest that algorithmic hiring methods are equal or better than human when selecting the best candidates ( Will et al., 2022).

Recently, scholars have also been advocating for the use of such algorithms to reduce implicit biases in hiring processes and have proposed frameworks to evaluate AI-assisted interventions ( Lin et al., 2021). According to Leutner et al. (2022), by using AI for hiring purposes, employers will be able to control for not only gender bias but other discriminatory characteristics as AI technology is able to be trained in a way to filter through the necessary characteristics required for candidates and to ignore other features. This is supported by several studies, showing that machine learning has no adverse impact on gender ( Sajjadiani et al., 2019) or that a fair ranking algorithm could increase the selection of female candidates ( Sühr et al., 2020). In regards to empirical evidence, Li et al. (2020) revealed that some algorithms could increase the share of women selected, up to a balance of 50%, compared to 35% for hiring decisions made by humans. Similarly, Avery et al. (2023) conducted a comparative analysis between human-evaluation and AI-evaluation treatments. The authors found that human evaluators consistently rated males higher than females by a substantial 0.15 standard deviations. This gender discrepancy was most noticeable at the higher end of the distribution, with men being 6.8 percentage points more likely to rank in the top 25%, and 7.73 percentage points more likely to land in the top 10%. In contrast, when AI was employed, the gender difference shrank considerably to just a 0.04 standardized difference. Furthermore, the representation of males and females in the top 50%, 25%, and 10% categories under the AI condition was nearly equal, showcasing the potential for AI to mitigate human biases in evaluation processes. Hiring algorithms could also benefit by increasing the perceived equity of the hiring process. For example, (1) women prefer to be judged by an algorithm because of its perceived objectivity over a human ( Pethig and Kroenung, 2023), (2) algorithms are perceived as less discriminatory than humans, which increases people's comfort toward their usage ( Jago and Laurin, 2021), and (3) applicants with prior discrimination experiences deem algorithm-based decisions more positively than those without such experiences ( Koch-Bayram et al., 2023).

Despite these findings, many researchers have sounded the alarm. For instance, Drage and Mackereth (2022), in their review of assertions made by AI providers, suggested that endeavors to eradicate gender and race from AI frequently misinterpret these concepts as discrete characteristics rather than broader structures of power, or that that using AI as a fix for gender diversity issues, an example of technosolutionism, fails to address the inherent systemic issues within organizations. Others raise concerns that algorithms could unintentionally exacerbate existing biases within recruitment processes ( Kelly-Lyth, 2021). Algorithmic bias takes on a discriminatory aspect when it results in consistent disparities linked to factors legally protected, such as gender. For instance, Dastin (2022) documented a case involving Amazon's hiring algorithm, which persistently gave higher employability scores to men than to women, while Chen et al. (2018), testing the adverse effects of candidates search engines, showed that female candidates were ranked statistically lower than male candidates. This circumstance has prompted scholars to delve into the exploration of algorithmic biases in hiring and strategies to mitigate them ( De Cremer and De Schutter, 2021). From a psychological perspective, research shows that, while individuals view algorithm-driven decisions as less prone to bias, they also generally regard it as less fair ( Feldkamp et al., 2023). Moreover, algorithmic decisions resulting in gender disparities are less likely to be perceived as biased compared to human decisions, because people tend to believe that algorithms make decisions devoid of context, thereby disregarding individual characteristics ( Bonezzi and Ostinelli, 2021). From a technical perspective, Rieskamp et al. (2023) identified four types of strategies aimed at reducing discrimination in these systems, namely pre-process, in-process, post-process, and feature selection. This review implies that interventions can be implemented at various stages of the algorithm development process to effectively mitigate bias. This is supported by van Giffen et al. (2022), who listed different types of biases in algorithm and in machine learning, distinguishing, for example, biases related to the use of historical biased data ( Mehrabi et al., 2019), data which are not representative for the relevant population, or measurement biases. However, intervening to reduce subgroup differences in selection often presents a trade-off regarding accuracy. This situation represents what is known as the validity-diversity dilemma, which involves maintaining a balance between selecting valid performance predictors and minimizing adverse impact. While interventions aimed at reducing subgroup disparities could decrease model accuracy ( Zhang et al., 2023), strategies employing multi-penalty optimization are promising in addressing this issue ( Rottman et al., 2023).

In summary, these findings suggest that training an algorithm to predict the preferences of a recruiter and mimic human intuition will inevitably surface and amplify biases. On the other hand, training an algorithm to predict genuine success, using more gender-blind data that accurately forecast job performance, will likely mitigate biases in hiring decisions. This understanding underpins the guidelines on AI-Based Employee Selection Assessments provided by the Society for Industrial and Organizational Psychology (SIOP). The organization strongly urges providers to generate scores that (1) are considered fair and unbiased, (2) are clearly related to the job, (3) predict future job performance, (4) produce consistent scores that measure job-related characteristics, and (5) documented for verification and auditing ( Society for Industrial and Organizational Psychology [SIOP], 2023). In other words, "from both research and workplace law perspectives, a clear and theoretically founded link should be established between the outcome (e.g., predicted job performance) and the algorithmic features" ( Society for Industrial and Organizational Psychology [SIOP], 2020).

Considering these guidelines, there is great potential for using algorithms to reduce gender discrimination in hiring if it is personality-focused since theory proposes that personality predicts job performance ( Schmitt, 2014), and does not vastly differ between genders. For instance, the gender similarities hypothesis ( Hyde, 2005) suggests that males and females are similar in most psychological variables. With respect to empirical evidence, when personality facets are examined separately, the effect sizes are close to zero in most cases ( Zell et al., 2015). Still, other scholars suggested that some differences between genders exist, with the most impacted facets being those related to agreeableness and neuroticism ( Weisberg et al., 2011; Kajonius and Johnson, 2018). Thus, the extent of gender differences observed in research findings is still a subject of debate among scientists: some argue that these findings are more commonly characterized by similarities, while others assert that substantial differences are frequently observed. Interestingly, new findings show that gender differences or similarities are reflecting differing ways of organizing the same data, leading Eagly and Revelle (2022) to recommend "recognizing the forest and the trees of sex/gender differences and similarities. It is necessary to step away from the individual trees, perhaps to a hilltop, to observe the patterning of trees in a forest" (p. 1355). While minor differences may exist on particular facets, it is, therefore, essential to transcend a one-dimensional understanding and view the broader picture, observing how the aggregation of various personality facets can highlight distinct differences between genders, or potentially offset certain differences observed within a single facet. For example, while larger differences emerge from averaging multiple indicators that differ by gender ( Eagly and Revelle, 2022), one could expect that such differences will be lowered by aggregating a facet that differs by gender with others that do not. Contextualizing the measure of personality ( Judge and Zapata, 2015), in order to benefit from the information brought by facet-level ( Soto and John, 2017), as well as reducing adverse impact, is, therefore, an intriguing path to explore.

More precisely, it is interesting to look at whether or not personality facets aggregates will lead to bias and adverse impact in personality-based hiring algorithms. Recent research has examined the accuracy of personality prediction in AI-based hiring systems and found that certain tools demonstrate significant instability in measuring key facets. Consequently, these tools cannot be considered valid assessment instruments ( Rhea et al., 2022). However, it is still uncertain whether alternative personality-based hiring algorithms, designed to predict job performance based on personality facets, could potentially result in adverse impacts or biases. Indeed, training an algorithm based on personality data, and teaching it to identify relevant and non-gendered cues of performance for a role, could probably help (1) in hiring people who perform better, as personality is predictive of job performance ( Schmitt, 2014) and who turnover less ( Kubiak et al., 2023b), and in (2) achieving natural gender balance for different roles, because even though differences in specific personality facets between genders exist, these differences are smaller compared to other attributes currently used in hiring decisions ( Kuhn and Wolter, 2022). Initial findings provide support for this hypothesis, demonstrating that specific personality-based algorithms exhibit gender fairness ( Kubiak et al., 2023a). However, these studies were limited in their scope and examined a small number of roles.

Therefore, our study introduces a new breed of algorithms for multiple reasons. Firstly, it employs a personality-centric approach, which stands in stark contrast to conventional algorithms that aim to digitize existing hiring procedures by training on data from candidates' resumes. Such data is riddled with bias ( Parasurama et al., 2022), which inevitably trickles down into the algorithmic results ( Houser, 2019). Secondly, our algorithm strives to predict future job performance, a marked departure from other algorithms that merely assess personality without making job performance projections. Thus, our study's algorithms primarily target the identification of personality aspects that drive job performance in a specific occupation, subsequently scoring candidates by juxtaposing their personality, gauged through a personality assessment, against these predictive factors. Finally, to counteract the often-criticized "black box" effect ( Ajunwa, 2020), our algorithms are based on explainable regression methods, in order to ensure efficiency but also transparency of the operations.

Our study expands the current knowledge, with the objective of testing whether we can adopt a personality-based algorithm to make hiring recommendations, whilst eliminating any adverse impact with regards to gender. Therefore, we hypothesize that a personality-based hiring algorithm would recommend hiring female and male candidates in (almost) similar proportions for different roles.

4. Materials and methods

This study involved the use of diverse samples. Firstly, training samples were utilized to construct predictive models for each occupation. Predictive modeling, as defined by Kuhn and Johnson (2013), is "a process of developing a mathematical tool or a model that generates an accurate prediction" (p. 2). In our study, a predictive model is defined as a combination of personality facets that generates an accurate prediction of job performance for a specific occupation. Secondly, a global analysis sample was employed to evaluate any potential adverse impact. For the sake of convenience, these samples will be referred to as training samples and analysis sample in the following sections.

4.1. Participants

Training samples were based on data from 18 employers, all clients of a specialized online assessment platform called "AssessFirst," dedicated to predictive hiring and personality assessments. These employers specialized in different industries, including retail, technology, consulting, finance and banking, engineering or transportation. Furthermore, the size of the companies varied significantly within the selected group. The range included small-sized companies with approximately 100 employees, as well as large international corporations with over 50,000 employees. Most were located in France (39.90%), followed by Russia (22.60%), the USA (13.46%), and the United Kingdom (9.62%). Other countries included Brazil, Austria, Chile, Germany, Hungary, Morocco, Poland, Portugal, Romania, South Africa and Ukraine. These countries provided a broad geographical base that further enhanced the generalization of the results. These employers were using the platform in a high-stake hiring context, in order to enhance their selection and assessment processes with a heightened degree of objectivity. By using the online recruitment platform, these organizations endeavored to refine their hiring practices. They utilized the platform's capabilities to construct predictive models for the occupations they sought to fill. The process for developing predictive models is described in the next section. This approach facilitated the comparison of prospective candidates' personality profiles against the established predictive model, providing a comprehensive analysis of how well a candidate's personality aligns with the specific requirements of the occupation. This thorough evaluation offered them deep insights, enabling them to make well-informed and objective hiring decisions. The selection of employers for this study was based on their active usage of the online platform during the period between 2021 and 2022. The primary criterion for inclusion was their utilization of the algorithmic-driven predictive model generation feature offered by the online platform. We only integrated into the samples employers who have undergone extensive training on platform usage and have demonstrated their proficiency by creating multiple predictive models. This stringent approach guaranteed that employers who were part of the sample were utilizing the platform correctly. The selection process focused solely on these aspects, without any commercial considerations involved. The purpose of this sampling approach was to ensure that the employers chosen had experience with and utilized the specific feature being investigated, allowing for targeted analysis of the predictive models generated through the platform.

4.2. Models generation

Our study hinged on data provided by these 18 employers, involving 208 unique occupations they were recruiting for. A total of 21 job categories were represented, predominantly sales (26.92%), financial services (13.46%), customer service (10.58%) and business development (7.69%). For each occupation, a distinct predictive model was designed, totaling 208 predictive models. In our study, we focused on developing predictive models that specifically considered the personality facets relevant to job performance in a given occupation. For example, Company 1, which was recruiting for a human resource role in Hungary, generated a predictive model that incorporated the personality facets of Extraversion, Agreeableness, and Openness. These facets were selected by the algorithm based on their statistical associations with job performance in that particular role. It is important to highlight that our algorithm exclusively relies on personality-related data (scores ranging from 1 to 10 on 20 personality facets) and performance-related data (scores ranging from 1 to 5). Our approach represents a departure from traditional hiring algorithms, which typically rely solely on data extracted from the CV or resume of candidates. Instead, we introduced a novel methodology that goes beyond CV data and incorporates personality facets relevant to job performance. Predictive models were generated directly by the employers using a dedicated feature on the online platform. The online platform provider describes the feature as an algorithm-based contact analysis tool that empowers employers to autonomously analyze their data and generate data-driven predictive models for the specific occupations they are hiring for. This tool leverages algorithms to extract insights from the data provided by employers, allowing them to uncover valuable patterns and relationships between personality facets and job performance. The process of predictive model creation in our study was, therefore, characterized by two distinct data collection stages. This was subsequently followed by the application of an algorithm, which selected the relevant personality facets to predict performance in the role. This approach ensured a well-rounded, scientific basis for all the predictive models devised in the study. The process of predictive modeling in the online platform works as follows:

- First, employers selected a representative sample of current employees in the occupation they were recruiting for. For instance, Company 1 chose a sample of 20 employees in the Human Resources role. To accomplish this, employers simply sent invitation emails to the selected employees through the online platform. In this study, it is important to note that the authors did not have direct contact with the employees involved. Instead, the employees were invited by their respective employers to participate in the study. The responsibility of explaining the purpose of the invitation to the selected employees rested with the employers. Subsequently, each employee independently created an account on the platform and provided their consent for their data to be utilized by the employer specifically for the purpose of predictive modeling. Once their account on the online platform was created, employees were asked to complete a forced-choice personality questionnaire. On average, it took approximately 12 min to complete the questionnaire, which consisted of 90 items. The personality questionnaire utilized a hierarchical model of personality based on the Five-Factor Model (FFM). It assessed 20 facets, with each personality trait being evaluated through four distinct facets. The scoring of each facet was done using Item Response Theory (IRT) modeling, and calibrated on a scale from 1 to 10, according to a Gaussian distribution. Following the completion of the assessment, each employee was, therefore, positioned and evaluated in terms of the 20 personality facets. This positioning allows us to understand and quantify the individual's characteristics and tendencies across the various personality facets. Extensive research has demonstrated the questionnaire's strong predictive validity ( = 0.63), as well as its reliability, as measured by Cronbach's alpha (α = 0.79) and test-retest reliability ( r = 0.80). Additionally, the questionnaire exhibits high sensitivity (δ = 0.96). The number of employees across the 208 training samples of our study varied from 20 employees to 151 ( M = 41).

- Secondly, the performance of each employee was assessed by their respective direct manager. Managers autonomously accessed the online platform and assigned a rating to each employee within their respective training sample using a standardized scale ranging from 1 (indicating very poor performance) to 5 (reflecting excellent performance). A standardized scale was privileged to ensure objectivity, consistency, comparability and easiness of data collection. During the rating process, managers were prompted to consider the employee's proficiency and objective job performance, such as revenue generation in the case of a sales occupation. To ensure accuracy of the performance ratings, definitions for each score were directly proposed within the online platform as guidance. This allowed for a comprehensive evaluation of each employee's performance based on the manager's insights and observations.

- Thirdly, once all employees in the training sample for one of the 208 occupations had completed the personality assessment and received ratings from their managers, the online platform automatically employed regression-based algorithms to analyze the data. Regression analysis is a statistical technique used to model the relationship between a dependent variable and one or more independent variables. This type of algorithm was chosen by the online platform because it is considered a fundamental algorithm in machine learning and artificial intelligence ( Hope, 2020), in particular due to their: (1) simplicity, as regression is straightforward to understand and interpret, (2) efficiency, as regression is computationally efficient compared to other algorithms, and does not require heavy computational resources, and (3) predictive insights, as regression provides coefficients for each feature, indicating the relationship between the feature and the output variable, thus allowing for a high degree of explainability. In the context of our research, regression-based algorithms were employed to uncover patterns and relationships between the personality facets assessed through the questionnaire and the performance ratings provided by managers. These algorithms use the collected data to determine the extent to which each personality facet influences performance. The process involves fitting a regression model to the data, which estimates the coefficients or weights associated with each personality facet. These coefficients quantify the strength and direction of the relationship between the independent variables (personality facets) and the dependent variable (performance rating). The regression algorithm learns from the data and iteratively adjusts these coefficients to minimize the difference between the predicted performance and the actual performance ratings. By employing regression algorithms, the online platform automatically analyzes the data, identifies the most influential facets, and constructs a predictive model specific to the occupation. This model can then be used to predict candidates' future performance. Therefore, while regression analysis itself is a statistical technique, when utilized within an automated system or platform to analyze data and make predictions, it can be considered part of the broader field of algorithms and machine learning ( Hastie et al., 2009; Goodfellow et al., 2016). It is worth noting that prior to deployment, the validity of each predictive model ( N = 208) was estimated and showed good accuracy, precision, recall and ROC AUC. Results are presented in Table 1.

The predictive models used in this study were autonomously created by individual employers. All relevant data pertaining to each model, including the training sample used, performance score, and results of the regression analysis (i.e., the facets taken into account in the models and score's expectation for each), were securely stored in the database, following GDPR regulations, of the online recruitment platform. This database served as a repository for the information related to the predictive models created by each employer and was re-used for the purpose of this study.

4.3. Procedure

The initial step of the procedure involved collecting data related to the 208 predictive models from the database. During this process, no filters or selection criteria other than previously mentioned were applied, and all the predictive models created by trained clients of the online recruitment platform between 2021 and 2022 were included. This approach ensured that a comprehensive dataset was obtained, encompassing all available models within the specified timeframe, without any exclusion or bias in the selection process. Author 1 and 3, being affiliated with the online recruitment platform, had convenient access to facilitate the data collection process. For each predictive model, a dataframe consisting of various variables was available. These variables encompassed the following information: (1) name of the company, (2) job category associated with the occupation, (3) specific occupation name, (4) country, (5) data regarding the users included in the training sample, including scores for each personality facet and performance score, in a JSON format (6) facets incorporated in the predictive model and the score expected on each facet, either a high score or a low score, and (7) performance metrics of the predictive model, including accuracy, recall, precision, and ROC AUC.

The second step of the procedure was to assess the potential adverse impact of the predictive models created regarding gender. For this, we constituted a global analysis sample of "potential candidates" who had already taken the personality assessment and had profiles on the online recruitment platform was utilized. These participants have registered on the platform at different times, motivated by various reasons such as receiving invitations from companies or simply wanting to explore and learn more about themselves through the assessments. This approach was chosen for several reasons: (1) utilizing the existing pool of individuals who already had profiles and had taken the personality assessment on the online platform allowed for convenient access to a substantial sample size, (2) although these individuals may not have applied to one of the 208 specific occupations studied, they represented a global population of individuals who could potentially apply for those occupations, broadening the scope of the analysis, and (3) by utilizing this approach, we were able to explore a wider range of predictive models compared to the limitations imposed by using real candidates or specific samples for all 208 occupations. By adopting this methodology on a global scale, we were able to successfully conduct this study on a large and diverse participant pool. The testing sample, therefore, consisted of individuals who met the following criteria: (1) created an account on the online assessment platform in 2022, (2) completed the same personality assessment as described earlier, and (3) provided consent for their anonymized data to be used for scientific and publication purposes. In this specific research, individuals were not directly informed or contacted. However, their data was used with their consent once they registered on the online platform. The analysis sample comprised 273,293 individuals, with 51% identifying as females and 49% as males. The majority of the sample was primarily from France ( n = 210,364, 77%) and held either a master's degree ( n = 97,584, 36%) or a bachelor's degree ( n = 96,405, 35%). The study involved access to specific information for each individual in the analysis sample. The available information included the following data points: (1) a score ranging from 1 to 10, representing the measurement of 20 personality facets through the use of a personality assessment employed in this research, and (2) the gender of the individual, categorized as either male or female. By utilizing this global sample, the methodology aimed to assess the potential impact of gender, providing a comprehensive understanding of how males and females scored in relation to each predictive model and the corresponding recommendations made by the scoring algorithm. For each individual within the analysis sample, a fit score was calculated, representing the level of alignment between their personality profile and the predictive model utilized. The fit score were ranging from 0 to 100%. For the purpose of the analysis, this fit score was calculated in a simple way. If the score of the candidate on a facet aligns with the expectation of the predictive model, the candidate was attributed a maximum score for the facet. If the score of the candidate on a facet is opposite to the expectation in the predictive model, the candidate was attributed a minimum score for the facet. If the score of the candidate on a facet taken into account is neutral, the candidate was attributed a medium score for the facet. Then, a simple formula calculates the fit score by summing the individual facet scores and dividing it by the total number of facets in the predictive model. The total result is then multiplied by 100 to express it as a percentage. A higher fit score, closer to 100%, indicated a stronger alignment between the candidate's profile and the facets that explained performance in the occupation, suggesting a higher likelihood of success on the role. Overall, individuals in the analysis sample who scored above 60% or above the 70th percentile on a predictive model were considered as recommended candidates by the online recruitment platform. Others who fell below these thresholds were not considered recommended. The choice of this threshold was based on studies conducted by the online platform, which demonstrated that individuals scoring above the 70th percentile had better performance and retention rates in the months following their hiring ( Kubiak et al., 2023b). Following this procedure, we obtained the fit scores of the 273,293 individuals composing the analysis sample for each of the 208 predictive models. The average fit score for females was 52.97 ( SD = 11.48), and 53.22 for males ( SD = 11.56).

4.4. Analysis

To analyze fairness and adverse impact, we applied the concept of impact ratio. The impact ratio is a statistical measure used to assess adverse impact in employment practices, particularly in the context of equal employment opportunity and fair hiring practices. It generally compares the selection rate of a protected group to the selection rate of a reference group (typically the group with the highest selection rate) within a specific job or employment process. The impact ratio is calculated by dividing the selection rate of the protected group by the selection rate of the reference group. In our first analysis, the impact ratio was calculated by dividing the recommendation rate for females (proportion of females who scored above 70th percentile or fit score above 60%) by the recommendation rate for males. Instead of using the selection rate as the metric, the recommendation rate was chosen for evaluation. This decision was made because the algorithm functions as a tool to provide recommendations to employers, rather than making independent decisions. The clients utilizing the online platform are the ultimate decision-makers. Therefore, in order to assess the fairness of the algorithm's recommendations, rather than the fairness of human decisions, the recommendation rate was deemed more relevant for the research's objective. While the focus of the analysis was on females as the protected class, considering evidence of discrimination against them, a reverse analysis was also conducted with males as the protected class. This allowed for a comprehensive evaluation of fairness across both genders. Guidelines from the Equal Employment Opportunity Commission ( U.S. Equal Employment Opportunity Commission [EEOC], 1979), specifically the four-fifths rule, were followed to assess fairness. According to the rule, a selection tool, or a predictive model in the context of our study, with an impact ratio between 0.8 and 1.0 is generally considered fair. Impact ratios below the threshold of 0.8 indicate a disparate impact, meaning the algorithm or selection method tends to recommend more of one gender over the other. The impact ratios were examined using two approaches: (1) mean weighted impact ratio across all predictive models, and (2) impact ratios broken down by job category, providing a detailed analysis of fairness in each specific job category. By considering these measures, the study aimed to evaluate the fairness of the predictive models and identify any potential disparities in recommendation rates between genders, in accordance with EEOC standards.

5. Results

In the first analysis, which considered females as the protected class when calculating the impact ratio (Female-Male), we identified 124 predictive models with impact ratios ranging from 0.74 to 1 (mean weighted impact ratio = 0.91; SD = 0.06). The remaining 84 models had impact ratios higher than 1, and were, therefore, considered in the second analysis, with males as the protected class. It is worth mentioning that only eight models from the 124 had impact ratios below 0.8, and were really close to the threshold defined by EEOC. Also, Cohen's d showed no significant effect on average (mean | d| = 0.11). Results of analysis 1 are presented in Table 2. In the second analysis (Male-Female), as expected, 84 models were identified, with impact ratios ranging from 0.71 to 0.99 (mean weighted impact ratio = 0.90; SD = 0.06). Only 3 models missed the 0.8 threshold, and Cohen's d showed no significant effect on average (mean | d| = 0.11). Results of analysis 2 are presented in Table 3.

To examine potential impact further, we examined the average impact ratio by job category. Results are presented in Table 4 and show that the average impact ratios are above the 0.8 threshold for every category. The lowest results were for the categories "human resources" and "management board" when males were considered as the minority group, with mean weighted impact ratios of 0.82. Even so, this is in line with EECO standards and supports our study hypothesis.

Also, to simulate and test each predictive model, we chose to test them on a neutral sample composed of so-called "potential candidates" who were people derived from a global population. In practice, however, candidates who will be scored by the algorithm have higher chances of holding a similar and specific position, which is related to the predictive model (e.g., salespeople for a sales representative predictive model). We ran a preliminary analysis to estimate how testing the algorithm on a specific sample would impact the results. This analysis was conducted on three different occupations: project manager, customer service representative and technician. Overall, impact ratios did not differ significantly and were still matching the EEOC requirements. Results are presented in Table 5. While promising, these results were obtained through analyzing three jobs only, and further investigation at a larger scale is required to ensure that results replicate with specific samples.

Table 5. Comparison of impact ratios depending on the type of sample.

6. Discussion

This research focus stemmed from alarmingly high gender discrimination that is ongoing in selection and assessment, despite legislation that should prevent discrimination on the basis of gender. To overcome such biases and improve selection, recent years have seen an increase in the use of algorithms in hiring decisions. Nevertheless, little is known about how these kinds of algorithms are used in practice, and some vendors of algorithmic pre-employment assessments are too opaque about the fairness of their solution ( Raghavan et al., 2020). Also, while these systems are increasingly subject to technical audits regarding their performance, there is still a lack of proof to support the claims being made by such tools ( Sloane et al., 2022). Still, new evidence has shown that using hiring algorithms could help in making better hiring and reducing human bias in selection ( Lakkaraju et al., 2017; Li et al., 2020; Will et al., 2022). These examples should not, however, hide other widely publicized and criticized practices, where the use of algorithms has contributed to exacerbating gender discrimination. Instead, it must open the way to the development and usage of more ethical algorithms, where the beneficial effects prevail. To address this issue, one must rely on data which are mostly gender-blind and are truly predictive of performance. Even if they are widely used in current hiring algorithms, pieces of information from the CV do not meet this double requirement, and force the reproduction of gender bias in selection. There is, indeed, a lot of gendered data in someone's CV ( Parasurama et al., 2022), and simple algorithms can differentiate gender from CV with high accuracy, even after removing the most gendered data like the names, hobbies or gendered words ( Parasurama and Sedoc, 2021). On the contrary, data related to personality facets seems better suited for a hiring algorithm's training, mostly because they are less impacted by gender compared to other data traditionally used in the hiring process and are valid predictors of job performance.

Drawing upon these conclusions, our study examined the gender equity of a novel personality-based hiring algorithm. The overarching aim was to establish whether the algorithm would recommend equal numbers of males and females for several occupations; thus, not being biased toward one gender or another. As hypothesized, results demonstrate that the algorithm does not show gender inequalities when recommending the best-suited candidates for the role, meaning there is no adverse impact. In this sense, impact ratios were in the recommended standard by the EEOC for 95% of the predictive models created. Only 5% of the predictive models fell short below and are considered as having a slight impact. These results illustrate that, when they are trained with the right data, algorithms could help in building more efficient selection processes, which are also fairer for women.

From a theoretical perspective, this work improves our knowledge about how to build gender-blind hiring algorithms by using data related to personality. Also, it complements other studies, by showing that biases and adverse impacts can be reduced even when screening facet-level. Our study demonstrates that while certain distinct differences may exist between males and females concerning specific facets, these disparities become less impactful when viewed within a broader constellation of multiple facets. By aggregating these characteristics with other facets that display similarity across genders, we effectively mitigate the potential for adverse impacts. This approach ensures a more balanced and fair assessment, underscoring the fact that individual variations do not necessarily lead to gender-based discrimination when considered in a comprehensive personality algorithm framework. Ultimately, the crucial question is not about these algorithms achieving perfect fairness in their predictions. Instead, it is about determining whether they enhance existing methods and surpass the current human-driven status quo. While the use of algorithms does raise essential and legitimate concerns, their potential for fostering more efficient and fairer decision-making processes cannot be overlooked, especially when they are trained with appropriate data. In particular, their potential to ensure a more balanced playing field for women is a significant step forward in achieving equity. In addition, our study provides evidence that even simple algorithms can effectively reduce gender discrimination. Many individuals have expressed concerns about using algorithmic hiring processes due to a lack of understanding ( Liem et al., 2018). However, our findings demonstrate that explainable algorithms can have a significant positive impact. By showcasing the potential of such algorithms, we aim to encourage the adoption of fair and unbiased decision-making tools in hiring.

Moreover, our conclusions are opening the way for future research about personality-based hiring algorithms. First, an interesting question arising from this work is about the capacity of such algorithms to be applied in practice, where they will probably be trained on male-dominated samples, as many could be forced to do due to the current disparities in the workplace. However, even if an algorithm is trained on a male-dominated sample, it could still provide fair outcomes when applied to a balanced or neutral sample, if it leverages data equally representative of both genders. This potential fairness arises from the algorithm's reliance on well-distributed data, where the features it uses for prediction are equally prevalent in both males and females. For example, if an algorithm is trained to predict job performance based on facets like imagination, trust or self-efficacy. Although these traits might be learned from a male-dominated sample, they are not exclusive to any gender ( Kajonius and Johnson, 2018). Males and females alike can exhibit high levels of imagination, trust or self-efficacy. Therefore, if the algorithm focuses on these universally applicable facets rather than gender-specific features, it should provide fair and unbiased predictions when applied to a gender-balanced sample ( Kubiak et al., 2023a). Second, it is still unclear whether these kinds of algorithms could display the same results for other kinds of discrimination, for example, disability-based discrimination, which remains intense ( Lippens et al., 2023). Third, even if our study showed that there was no adverse impact for 95% of the predictive models tested, we still need to address the 5% remaining: while their impact ratios are really close to the EECO requirements and do not fall lower than 0.71, some adjustments are required in order to use them in high-stakes hiring practice and be confident that they will not harm any group based on gender. For these models, future research could focus on addressing the diversity-validity dilemma, which concerns the tradeoff between selecting valid predictors of performance while minimizing adverse impact ( Pyburn et al., 2008; Rupp et al., 2020; Rottman et al., 2023). As such, it seems necessary to identify strategies to target facets within the predictive model that lower the impact ratio, and to propose alternatives. It could also foster the algorithm's explainability, by being transparent about the predictive model limitation, and how one could improve it to make it fairer regarding gender while making the smallest compromises possible about validity. For example, studies could use a feature importance framework to iteratively prune biased features with the lowest predictive power from the model.

Our work also has several practical implications. First, given the prevailing talent shortage, employers are increasingly finding it challenging to fill roles effectively. As such, it is imperative they shift focus and explore alternate indicators of potential, beyond traditional markers like academic degrees, to truly uncover and understand the essence of talent and assess the employability of their candidates ( Chamorro-Premuzic, 2017). Employers can consider personality as a compelling alternative to traditional CV-based assessments, as it relates performance while being less susceptible to gender bias ( Schmidt et al., 2016; Sackett et al., 2022). In addition, it is becoming increasingly imperative for employers to demonstrate that their hiring practices and tools are devoid of biases, ensuring that no particular group is unfairly disadvantaged based on their gender ( Hunkenschroer and Kriebitz, 2023). Our study shows great potential in helping employers to accurately identify the underlying mechanisms of performance for a specific occupation and to reduce gender biases. That way, they might be able to hire people who are better suited for the role and perform better, and who are more diverse in terms of gender. Secondly, personality-based algorithms, by increasing the fairness of the hiring process, could probably promote organizational attractiveness. Indeed, considering the existing labor talent shortages and the significant role of an organization's recruitment process perception in determining a candidate's decision to accept a job offer ( Hausknecht et al., 2004), enhancing the perceived fairness of algorithmic recruitment tools carries substantial implications. Recent research showed that algorithm-driven hiring processes are perceived as less fair compared to human-only decisions by candidates ( Lavanchy et al., 2023) and that people feel less capable of influencing the outcome of an algorithm compared to human judgment ( Li et al., 2021; Hilliard et al., 2022). Interestingly, fairness mediates the association between an algorithm-based selection process and organizational attractiveness and the intention to further proceed with the selection process ( Köchling and Wehner, 2022). Consequently, it is in the best interest of employers to utilize personality-based algorithms, due to their increased fairness, to improve their attractiveness among potential candidates. This ensures that candidates are not discouraged or deterred from the process due to the perception of algorithmic unfairness. Thirdly, implementing an algorithm-based evaluation system could potentially boost the number of female applicants for a company and enhance the completion rates for the assessment process. This is due to the observed tendency of women being more inclined to complete an assessment when informed that the evaluation is conducted by an algorithm, rather than a human recruiter ( Avery et al., 2023). Such a shift could play a pivotal role in fostering gender diversity within organizations by expanding the pool of female candidates applying for jobs. Heilman (1980) found that both male and female evaluators made significantly more favorable personnel decisions when females constituted 25% or more of the total candidate pool. Thus, increasing the representation of females in the candidates pool through algorithm-based evaluations could lead to more balanced hiring outcomes. Fourthly, our study serves as a useful guide for employers navigating forthcoming legislation such as New York's AI hiring law. Recently enacted, the NYC Automated Employment Decision Tool law mandates employers using AI in hiring to disclose its use to candidates. Further, it necessitates annual independent audits to demonstrate the absence of discriminatory practices in their systems. Moreover, candidates are granted the right to request information from potential employers about what data the technology collects and analyzes. Non-compliance with these regulations could result in fines of up to $1,500. Our study helps employers align their processes with these requirements, paving the way for transparent, accountable, and unbiased algorithm-driven hiring.

7. Limitations

Several limitations of this research should be taken into consideration. First, while the strength of our study was that it considered 208 occupations across 21 categories, we did not include occupations that are more stereotypically judged as being gender specific. Therefore, future research can aim to retest our algorithm on an even wider array of job categories and focus specifically on occupations which are perceived to be predominately feminine. For example, studies showed that occupations related to caregiving are seen as being more feminine ( Couch and Sigler, 2001), or that it persists presumptions about the gender of people employed in healthcare, notably nurses ( Ekberg and Ekberg, 2017). Our sample unfortunately did not include occupations from these highly stereotypical categories. We could not include these occupations in our study, as none of the participating employers were recruiting for such roles. In fact, the employers utilizing the online platform were primarily focused on filling business-related positions (see Table 4).

Secondly, our study's scope was limited to gender as a characteristic, which leaves room for further exploration. Recent research indicates the existence of intersectional effects between various attributes. For instance, Derous and Pepermans (2019) uncovered a "double jeopardy" situation for Maghreb/Arab female applicants applying for high-cognitive demand roles-an issue not apparent in applications for low-cognitive demand jobs. Such findings emphasize the necessity for more nuanced investigations that consider the interactions between multiple characteristics. Future research could delve into the potential adverse impacts of personality-based algorithms by examining intersectionality, such as the combined effect of gender and ethnicity. This could pave the way for more comprehensive understanding and better refinement of fair algorithmic-based hiring practices.

Third, our study tested the algorithm on males and females, as data collection for these genders was simpler and more easily accessible. However, we acknowledge that there are numerous gender non-conforming categories. Unfortunately, we did not find any satisfactory published research which studied how personality differs between males, females and people identifying as gender diverse. The only evidence we have drawn upon is the analysis proposed by Anzani et al. (2020), which delved into the personality patterns of a transgender cohort compared with normative samples of cisgender females and males. Their findings revealed that transgender women scored lower than cisgender women on two primary domains (Negative Affectivity and Psychoticism) and on seven facets. Transgender men, meanwhile, scored lower than cisgender men on Antagonism and five other facets. However, these results were derived from relatively small sample sizes of transgender individuals, all of whom were pursuing medical treatments. Consequently, these findings may not accurately represent the broader transgender and gender-non-conforming population. This indicates the necessity for future investigation into the algorithm's gender neutrality, especially when considering the inclusion of diverse groups beyond the traditional gender binary.

Finally, we should also mention potential bias in how the rating of each employee (from 1 to 5) was made by their manager. Indeed, even though managers were prompted to reflect on the employee's productivity and objective performance, no other specific guideline was proposed. As a result, there is a chance that different managers could have reflected upon different types of performance when making their ratings. Gender bias has also frequently been identified in performance appraisal. For example, (1) Correll et al. (2020) showed that it exists differences in the language used to describe females and males performance and that the same behaviors could impact performance ratings differently depending on the employee's gender, (2) Benson et al. (unpublished) revealed differences in potential ratings between gender, and, (3) Rivera and Tilcsik (2019) showed that the number of scale points used for the evaluations significantly affect the size of the gender gap in male-dominated fields. Still, there are reasons to believe that the ratings made were accurate estimates of objective performance: (1) as shown by Jackson and Furnham (2001), biases such as halo do not necessarily reduce rating accuracy, and supervisor ratings are useful measures of overall performance, (2) managerial ratings have a good corrected mean correlation with objective performance for salesperson job performance ( Jaramillo et al., 2005), which is a type of role composing one-third of our total sample, (3) ratings have been shown to be more accurate for unskilled, skilled and professional workers compared to managerial occupations ( Miller and Thornton, 2006), and these three levels of occupations are the most represented in our sample, and (4) each of the scale's point were clearly defined in the rating form. Other studies should, however, try to measure performance in a more structured and controlled manner. Furthermore, future research should also incorporate a more comprehensive understanding of job performance, considering a wide range of relevant factors. For instance, Rotundo and Sackett (2002) pinpointed three broad components of job performance: task performance, citizenship behavior, and counterproductive performance. They further demonstrated that two primary elements of performance-tasks performance and counterproductive performance-were the more weighted by raters. Recent research also suggests an increasing interest in other types of performance. Contextual performance, for example, includes behaviors that contribute to the social and psychological environment ( Ramos-Villagrasa et al., 2022). Adaptive performance, on the other hand, pertains to an employee's ability to modify their thoughts, behaviors, and emotions to adapt to their evolving work environment. Such adaptations can encompass adjustments to new technologies, procedures, business processes, or work roles ( Baard et al., 2014). Given that meta-analyses have revealed that traits have differential relationships with contextual ( He et al., 2019) and adaptive performance ( Huang et al., 2014), it would be prudent to incorporate these insights in future research.

8. Conclusion

Gender stereotypes are incredibly stable. For example, Offermann and Coats (2018) showed that ILTs (Implicit Leadership Theories) did not change during the last 20 years, despite organizational and societal changes. Also, large-scale cross-national field experiments highlight occupational gender composition ( Birkelund et al., 2022; Adamovic and Leibbrandt, 2023), showing disparate proportions of individuals of a particular gender working in specific occupations. This is particularly salient in online hiring, which triggers the use of cognitive shortcuts about the role-specific abilities of each gender ( Galperin, 2021). This persistence of gender discrimination in hiring, despite all the efforts made for so many years, calls for the identification of strategies that will lead to an effective and lasting response. The findings from our research suggest that personality-based hiring algorithms serve as an effective solution, demonstrating non-adverse impact in most instances. In other words, they do not unfairly disadvantage certain groups of people based on their gender. Properly trained and used, these algorithms could help organizations to build fairer decision-making processes.

Data availability statement

The datasets presented in this article are not readily available because even if the data used has been anonymized by AssessFirst, the participants may choose to delete their data at any time: while the data were accessible for scientific purposes during the analysis and publication, it cannot be ensured that the same data will remain legally available in the future. For legal reasons supporting data is, therefore, not available. Requests to access the datasets should be directed to EK, ekubiak@assessfirst.com.

Ethics statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required from the participants or the participants' legal guardians/next of kin in accordance with the national legislation and institutional requirements because written informed consent from the participants was not required to participate in this study in accordance with the national legislation and the institutional requirements.

Author contributions

EK and SB: conceptualization, methodology, data collection, and data analysis. EK: supervision. EK and ME: writing-original draft. All authors contributed to the writing-review and editing and read and agreed to the current version of the manuscript.

Conflict of interest

ME, EK, and SB were employed by AssessFirst.

The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

Schmidt, F. L., Oh, I.-S., and Shaffer, J. (2016). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 100 years of research findings. Working paper. ResearchGate: 17 October 2016.
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Gender equity in hiring: examining the effectiveness of a personality-based algorithm

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IntroductionGender biases in hiring decisions remain an issue in the workplace. Also, current gender balancing techniques are scientifically poorly supported and lead to undesirable results, sometimes even contributing to activating stereotypes. While hiring algorithms could bring a solution, they are still often regarded as tools amplifying human prejudices. In this sense, talent specialists tend to prefer recommendations from experts, while candidates question the fairness of such tools, in particular, due to a lack of information and control over the standardized assessment. However, there is evidence that building algorithms based on data that is gender-blind, like personality - which has been shown to be mostly similar between genders, and is also predictive of performance, could help in reducing gender biases in hiring. The goal of this study was, therefore, to test the adverse impact of a personality-based algorithm across a large array of occupations.MethodThe study analyzed 208 predictive models designed for 18 employers. These models were tested on a global sample of 273,293 potential candidates for each respective role.ResultsMean weighted impact ratios of 0.91 (Female-Male) and 0.90 (Male-Female) were observed. We found similar results when analyzing impact ratios for 21 different job categories.DiscussionOur results suggest that personality-based algorithms could help organizations screen candidates in the early stages of the selection process while mitigating…

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An example of qualitative data that talks about crime patterns around the world with the inclusion of surveys.

Emiliana Soto.

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Global Crime Patterns: An Analysis of Survey Data from 166 Countries Around the World, 2006-2019

A Correction to this article was published on 27 July 2022

Abstract

Objectives

This article explores the merits of commercially-based survey data on crime through cross-validation with established crime metrics.

Methods

Using unpublished data from 166 countries covering the period between 2006 and 2019, the article describes the geographical distribution across global regions and trends over time of three types of common crime, homicide, and organised crime. The article then explores possible determinants of the geographical distributions through regressing prevalence rates against indices of poverty, inequality, proportion of youth, presence of criminal opportunities (wealth and urbanisation), and governance/rule of law.

Results

The results show that African and Latin American countries suffer from the highest levels of various types of crime across the board, followed by countries in Asia. European, North American and Australian countries experience intermediate or relatively low levels of most types of crime. Levels of common crime have dropped or stabilized globally except in Africa where they went up. Homicides have fallen almost universally. Trends in organised crime are diverging.

Conclusions

Dimensions of governance emerged as powerful determinants of levels of all types of crime. Important determinants of common crime besides governance were poverty, inequality, and proportion of youth. To some extent changes in these same characteristics of countries were found to be correlated with changes in levels of crime over the past fifteen years. The article concludes with a discussion of the study's limitations and suggestions for further research.

Introduction

In this article we explore the merits of the newly available, commercially produced crime data from the Gallup World Poll (GWP), a household survey carried out annually in over 160 countries since 2006, containing questions on experiences with theft as well as with violence (assaults and muggings) (Gallup World Poll 2020). Given that the GWP surveys are behind a pay-wall and thus not publicly available, GWP data on common crime have been analysed sparsely in the criminological literature. To our knowledge, so far only Corcoran and her colleagues have used GWP data to study the cross-national variation in experiences with violence (assaults and muggings) during the period 2006-2013 (Corcoran and Stark 2018, 2020; Corcoran et al. 2018). In this article we will expand their analyses by also examining GWP data on experiences with another type of common crime, i.e. theft. Furthermore, we expand our analyses by analysing data over a longer period, i.e. the full period since the start of the GWP-survey (2006) and 2019.

We first describe the geographical distribution across global regions, sub-regions and countries in people's experiences with theft and violence in 160 countries for the five-year periods 2006-2009, 2010-2014, 2015-2019 and for the entire 14-year period 2006-2019. Second, we describe the trends over time in countries' levels of experienced thefts and violence, and examine whether these levels have increased, decreased or stayed stable over the 14-year period. Next, we will look at intercorrelations between prevalence rates of common crime (i.e. both theft and violence) and non-common crimes (homicide, and organised crime/corruption). Finally, we will use our dataset on the prevalence of these types of crime to examine whether and to what extent often used indicators of possible determinants of crime are correlated with levels and trends of both common and non-common crime across the world.

A Short History of Cross-National Studies on Crime

Studying cross-national variation in common crime has a long history. Throughout the nineteenth century criminologists have studied geographical variations in rates of recorded crime. A dominant theme in this early literature was the association of crime with poverty, urbanization and social disorganization. The traditional source of information on levels and trends of common crime were court statistics on convictions for criminal offences. In the twentieth century these court statistics were supplemented by statistics of crimes recorded by the police. Such statistics were later internationally collected by organisations like the United Nations and Interpol. However, comparing common crime recorded by police forces or courts cross-nationally is problematic, since countries, police forces and courts apply different legal definitions, work procedures and counting rules. Due also to varying readiness of citizens to report incidents of crime to the police and rates of detection, the proportions of crimes that remain hidden from the official records (the so-called dark numbers of crime) vary greatly across countries. Consequently, available information on crime recorded by the police or other criminal justice actors is known to be non-comparable across countries as a measure of crime.

To overcome the problems of internationally non-comparable court and police data on common crime, criminologists since the 1980s moved their international comparative research into two new directions: (a) analysing data on non-common crime, e.g. homicide, corruption and organised crime and/or (b) analysing data from national and international crime victimization surveys.

Cross-National Studies on Non-Common Crime

Using a purpose-built database focussing on homicide rates, Archer and Gartner ( 1984) gave new impetus to the field of cross-national criminological research. The general idea was that homicide is the type of crime that has the least cross-national differences in legal definitions and procedures, and that almost all incidents come to the attention of criminal justice systems and/or forensic doctors, in all countries. In the 1990s international homicide data became systematically available from the UNODC's Global Study on Homicide and from the World Health Organization (WHO). These data today cover almost all countries in the world (UNODC 2019). When international homicide data became more readily available, a new wave of epidemiological studies using national data followed (Koeppel et al. 2015).

In addition, political scientists, economists and criminologists started to analyse other types of non-common crime. In particular, more recently, cross-national analyses have sought to understand determinants of global variation in measures of corruption and organised crime (see for review on corruption: Wysmulek 2019). This became possible, since several organisations (e.g. the World Economic Forum (WEF) and Transparency International (TI)) started to carry out surveys among business executives and/or households from many nations on experiences with corruption and organized crime (WEF 2019; TI 2019). So, for non-common crimes (homicide, corruption and organised crime) a growing variety of up-to-date, cross-nationally comparative data are available for a large number of countries around the world.

Crime Victimization Surveys

In order to circumvent the many uncertainties concerning crimes recorded by criminal justice actors as measures of crime, the USA and some European nations launched, in the 1970s, crime victimization surveys among households focussing on rates of victimization by offences as defined in the domestic criminal codes (Biderman and Reiss 1967). The results of these surveys provide an alternative, and in many respects more comprehensive, source of information about crime to those recorded by the police. However, national crime victimization surveys have different designs, data collection procedures and questionnaires in the different countries, thereby limiting the comparability of their results.

To overcome these problems, the International Crime Victim Survey (ICVS) was launched by criminologists with expertise in national crime surveys (Van Dijk et al. 1990; Lynch 2006). Since its initiation, surveys have been carried out once or more in altogether 85 countries (Van Kesteren et al. 2013). Over 350,000 citizens across the world have to date been interviewed with the same questionnaire, translated in at least thirty languages. For almost three decades these data have been the only source available on self-reported data on common crime covering multiple countries in several world regions. However, it must be recognized that the ICVS covers only about a third of all countries/territories in the world (and especially lacks data from Africa), most countries were only surveyed once or twice, and new surveys since 2010 have been few and far between.

Fortunately, the Gallup World Poll (GWP) with its much wider coverage and greater periodicity, contains questions on experiences with common crimes which can be harnessed for comparative international analysis.

Theoretical Perspectives on Cross-Country and Over-Time Variations in Crime

Throughout the nineteenth century statisticians and social scientists have studied geographical variations in rates of recorded crime. Pioneers such as Guerry (1802-1866), Quetelet (1796-1874), and Von Mayr (1841-1925) started comparative studies investigating and explaining differences in crime across European geographical areas. Later in the nineteenth century, Durkheim ( 1897) examined how socio-economic circumstances and changes impacted on European countries' suicide and homicide levels. A dominant theme in this early 'cartographic' literature was the association of crime with, inter alia, poverty, urbanization and social disorganization (for an overview see Bonger 1916). Ecological research resurfaced in the beginning of the twentieth century, when scholars described the distribution of crime and delinquency, including homicide, across neighbourhoods and identified structural factors determining levels of crime (see e.g. Park and Burgess 1925; Shaw and McKay 1942).

Current empirical criminological studies explaining cross-national and over-time within country variation in crime rates show a broad range of different theoretical approaches. Three sets of factors emerge as the common ground of contemporary epidemiological studies seeking to explain variation in crime. The first set consists of motivational determinants, like poverty, unemployment, inequality and proportions of young people. A second set comprises opportunity-related factors like urbanization, community cohesion and wealth. And an emerging third set of determinants centres around the functioning of state and democratic institutions (governance).

Motivational Factors

Many scholars have theorized that countries' crime levels are related to factors motivating persons to commit crime. Durkheim (2005 < 1897 >) already hypothesized that rapid social change creates normlessness or 'anomie' leading people to engage in deviant behaviour. In the same vein Merton's strain/anomie theory argued that individuals facing economic hardship and blocked opportunities may experience feelings of injustice and resentment pressuring them to commit crime (Merton 1938).

Reviews of more recent empirical studies aiming to explain cross-national differences in crime confirm the importance of factors related to motivations to offend. In cross-national studies, poverty, economic inequality and, to a lesser extent, unemployment were found to be strongly correlated with homicide rates (LaFree 1999; Nivette 2011; Pare and Felson 2014; Lappi-Seppälä and Lehti 2014; Koeppel et al. 2015; UNODC 2019). Furthermore, analyses of ICVS data confirm moderately strong correlations between inequality and levels of victimization by various types of common crime (Nieuwbeerta 2002; Van Wilsem 2004; Van Dijk 2008). Structural correlations were also found between the percentage of young people in populations and levels of both common crime and homicides (Van Dijk 2008; LaFree and Tseloni 2006; McCall et al. 2013). In line with this finding, the existence of a 'youth bulge' has been linked to various forms of civil unrest, especially in the Global South (Urdal 2006).

Opportunity-Related Factors

A second set of determinants of crime prominent in current epidemiological studies are opportunity-related factors like urbanization, community cohesion and wealth. Several criminological theorists emphasised the role of criminal opportunities. For example, according to 'routine activity theory', crimes are more likely to occur at places where there are (1) more motivated offenders, (2) more suitable targets, and (3) fewer capable guardians (Cohen and Felson 1979). In this perspective, higher wealth increases the availability of easily 'stealabe' consumer goods and-especially in large urban settings-breeds social anonymity and weak social guardianship. This theoretical perspective also emphasised the role of the availability of alcohol, drugs and firearms to foster and facilitate crime. Criminal opportunity theory has also been used to explain the prevalence of various types of organised crime (Bullock et al. 2010).

Over the past decades, a large number of empirical studies have confirmed the epidemiological importance of factors related to criminal opportunities. Victimization surveys have shown that levels of common crime across the Western world went up in tandem with the availability of suitable targets, such as (poorly secured) motor vehicles (Van Dijk 2008; Farrell et al. 2014), and that a higher degree of urbanization and lower social cohesion are related to higher levels of common crime (Lee 2000; Van Wilsem 2004; Van Dijk 2008; Corcoran and Stark 2020).

Governance

A distinct third set of factors emerging in the literature explaining variation in countries' levels of crime centres around the functioning of state and democratic institutions. Historically, the role of a (good functioning) state to prevent criminal and violent behavior was argued by the seventeenth century philosopher Thomas Hobbes. Furthermore, the importance of the role of the (emergence of) a nation-state for reducing crime is theorised in historical studies on homicide (Eisner 2014). In addition, political scientists and economists-especially from the New Institutionalist School-have increasingly pointed to the nefarious linkages between bad governance, corruption, violence and underdevelopment (Acemoglu and Robinson 2012; Wenmann and Muggah 2010; World Bank 2011; UNDP 2013; Acemoglu et al. 2017). From this perspective, poorer nations are caught in traps of weak state institutions, underdevelopment and high levels of crime and corruption (Kaufmann and Kraay 2002; Kaufmann et al. 2009).

The importance of the role of countries' levels of 'governance' for their levels of violence and crime is also shown in several empirical studies of current crime levels. Van Dijk demonstrated how dysfunctional governance, organised crime and underdevelopment are intercorrelated at the country level (Van Dijk 2007, 2008). In cross-national studies on homicide, various indicators of 'poor governance', rule of law or legitimacy emerged as key independent determinants of homicide rates (LaFree and Tseloni 2006; Nivette and Eisner 2013; Chu and Tusalem 2013; Lappi-Seppälä and Lehti 2014; Karstedt 2015; Stamatel 2016; Huebert and Brown 2019). Furthermore, bad governance was found to be one of the main dimensions of the Vulnerability Index for human trafficking/modern slavery grounded in GWP data (Joudo Larsen and Durgana 2017).

Data, Measures, and Indices

Gallup World Poll Data

Two out of the broad range of Gallup World Poll's many items relate to experiences with theft and violent crime respectively. We use these data from all Gallup World Poll surveys held in the 14-year period 2006-2019. The surveys are conducted in over 160 countries worldwide, making up more than 98% of the world's adult population. The target population is the entire civilian, non-institutionalized adult (aged 15 + or 18 + years) population. The coverage area is the entire country including rural areas, and the sampling frame represents the entire country. The survey is translated into the primary languages of the countries and is then given to approximately 1000 individuals. The survey is conducted annually in most countries, but in some it is conducted once every two or three years-and in a few countries only every five or six years. The survey is conducted over the telephone in countries where at least 80% of the population has telephones by means of either random-digit dialling or a nationally representative list of phone numbers. Face-to-face interviewing is used in the other countries. More detailed information regarding the GWP's methodology can be found at the website of the Gallup organisation ( www.gallup.com).

To make the data optimally nationally representative and cross-nationally comparable, we apply the data weights as provided by the GWP. These weights account for oversamples, household size, national demographics (i.e. gender, age, and-where available-education or socioeconomic status), nonresponse, unequal selection probability, and design effects. In addition, we exclude all respondents under 18 years of age to ensure consistent age thresholds across countries.1

Gallup Sample of Countries

Our sample of countries comprises all countries for which data on victimization of theft and assault are available in the Gallup World Poll over the years 2006-2019. This set of countries includes a total of 166 countries out of the 190 countries recognised by the United Nations during that period. Missing countries are all relatively small with the exception of North Korea. According to the geographical classification of the United Nations, the sample encompasses 40 countries from Europe, 2 from North-America, 26 from Latin America and the Caribbean, 49 from Africa, 47 from Asia and 2 from Oceania. Especially notable is the inclusion of 49 countries from Africa, a region conspicuously underrepresented in other datasets on crime, comprising of 17 countries from Eastern Africa, 7 from Middle Africa, 6 from Northern Africa, 5 from Southern Africa, and 14 from Western Africa (see Table 1).

Since in many years over the 14-year-period 2006-2019 questions on common crime are included in the GWP-questionnaire and Gallup interviews approximately 1000 residents per country annually, we have data on crime from 1780 so-called 'country/years'. Since most countries are, as said, surveyed in multiple years, our measures for common crime are based on almost 1.8 million interviews, i.e. on average 10.6 thousand interviews per country (see Table 1).

Measures

Common Crime Measures

In our study we focus on two questions in the GWP-questionnaire pertaining to the actual experience of victimization by common crimes, i.e., whether a victim of theft ("Within the past 12 months, have you had money or property stolen from you or another household member?") and whether a victim of violence, i.e., assault or mugging ("Within the past 12 months have you been assaulted or mugged?"). We constructed three measures on victimization of common crime based on these two questions. First, we used the yearly prevalence rate of persons who indicated they were a victim of theft-and calculated the average theft rate (in %) in each year in the 166 countries from which these data were available (N = 1780 country/years). Second, we did a similar exercise using the data on victimization of violent crime to calculate the violence ( assault/mugging) rate (in %) in the 165 countries and all years/years for which these data are available (N = 1315). Third, we used both GWP-questions together and calculated the rate of persons who were victim of theft and/or violence in all years and all 165 countries from which both questions are available (N = 1302).2

Next, we cross-validated the resulting national prevalence rates from Gallup World Poll with estimates of similar types of crime from the last rounds of the International Crime Victim Survey (ICVS) (Van Dijk 2008). These last rounds of the ICVS, conducted between 1996 and 2010, cover many Western countries, i.e. Europe, North America, Australia, and New Zealand, several countries in Asia and Latin America and-in a more limited number-Africa. The comparison could be made for the 69 countries participating in both types of survey. Considering the many differences between the ICVS and GWP methodologies, including in formulation of questions on crime experiences, and in periods of data gathering (1996-2010 and 2006-2019 respectively) near perfect correlations between the ICVS and GWP victimization prevalence rates were not to be expected. Correlations were found to be moderately strong. For example, the Pearson correlations between the GWP and ICVS-based rates for various types of theft are 0.63 (N = 69) and for assault/muggings 0.67 (N = 68) respectively. Furthermore, the Pearson correlations between our combined GWP-based measure for theft and/or violence and the ICVS's overall crime rate, covering all ten different types of crime used, is 0.62 (N = 69). The latter correlation suggests that the Gallup World Poll's two broadly defined and partly overlapping items on theft and assault/muggings capture the volume of common crime in a country surprisingly well.

Homicide

To monitor progress towards achieving crime-related Sustainable Development Goals the United Nations recommends the use of homicide statistics besides survey-based data on violence (UNODC 2019). The WHO collects data on homicide from public health sources through a dataset on the causes of mortality. The UNODC collects data primarily from criminal justice sources, although for some countries the UNODC relies on public health data. Where both criminal justice and public health sources exist, the two sources often provide similar results (Andersson and Kazemian 2018). In our sample the Pearson correlation between the average UNODC and WHO measures for the period 2006-2017 was 0.81 (N = 97 countries). We choose to use the more comprehensive UNODC dataset (UNODC 2019), available for 135 of the GWP-countries over the period 2006-2017 (see also Table 2).

Organised Crime

Organised crime is defined in the UN Convention on Transnational Organised Crime as the commission of 'serious crimes by a structured group of three or more persons for material gain'. This definition has been specified by listing secondary characteristics such as high-level corruption, money-laundering, infiltration in the legal economy, and instrumental violence (Fijnaut and Paoli 2004). An item in the survey of the World Economic Forum (WEF) asks business executives, "In your country, to what extent does organized crime (mafia-oriented racketeering, extortion) impose costs on businesses?' (Schwab 2015). This item captures infiltration into the legal economy through the perspectives of business executives. Answers to this question are strongly correlated to measures of corruption and of money-laundering and moderately to a proxy measure of mob-related violence consisting of country rates of unsolved homicides (Van Dijk 2007). For Africa, a new comprehensive index of organised crime harnessing experts' assessments of the presence of various sorts of criminal markets and criminal actors in their country has been designed. This index was found to be strongly correlated to the WEF item on 'costs on businesses' (ENACT 2019).

To measure the extent of organised crime and related corruption, we combined measures from three widely available sources. The first measure is the item in the WEF survey just mentioned. The second measure is the Corruption Perceptions Index (CPI) of Transparency International (Transparency International 2015) which aggregates information from business people and country experts on the level of corruption. The third measure is an item in the GWP, which asks private respondents "Is corruption in government widespread?" The three measures are highly intercorrelated.3 To construct an Organised Crime Index, the three measures were averaged, then standardised (with a mean of 0 and standard deviation of 1), and normalised4-so that they each range from 00 to 100 (with higher scores meaning more organised crime and corruption). We constructed this index by averaging the three normalised scores. Scores on this index could be calculated for 163 countries.

Determinants of Crime

In our review of studies on the possible determinants of crime (see above) we distinguish three main theoretical perspectives, respectively those focussing on motivations to offend, on opportunities of crime, and on the efficacy of state institutions (governance). To construct measures of the key determinants falling under these three headings, we selected indicators for which reliable data wasavailable for more than 150 of the 166 GWP countries and-to be able to study correlates of trends-for each of these countries for (almost) every year in the period 2006-2019.5 The indicators encompassed three separate indicators of offender-related determinants (Poverty, Inequality, and % Youth), two indicators of opportunity-related determinants (Wealth and Urbanization) and one for Governance, which includes, inter alia, indicators of governance and the rule of law (See Table 2 for details).

Analytic Strategy

The first aim of our analyses is to describe the geographical distribution across global regions, sub-regions and countries in people's experiences with crime in countries for the period 2006-2019. To do this, we use data for the entire 14-year period, but in order to take possible changes over time into account, also for the periods 2006-2009, 2010-2014, and 2015-2019 separately (see Table 3). Note that when calculating crime figures for (sub-) regions we first average on the data in each country, and then calculate the average over the countries in a (sub-)region.6

The second aim is to describe developments in common crime between 2006 and 2019 in each of the 139 countries in the world for which we have sufficient Gallup World Poll (GWP) data available to adequately examine trends.7 Since not for all countries survey data for all years are available, and we are interested in overall long terms trends, and not in yearly or short term fluctuations, we decided to use predicted values from OLS-linear regression models that were estimated for each country individually based on real values from available years. In these models, the dependent variable is the prevalence of crime (in %) in that country, and the independent variable is the calendar year. These models thus generate predicted levels of crime assuming a linear trend in each country.8 We calculated the differences between the predicted levels of crime in the last year (i.e. 2019) and the first year (i.e. 2006) in each country as measure for the size of 'linear change'. In other words: the trends are presented as "percentage point" i.e. the simple numerical difference between the predicted percentage in 2019 minus the predicted percentage in 2006 (see Tables 4 and 5). When presenting 'linear change' per (sub-)region (see also Tables 4 and 5), the measures of the countries in these (sub-)regions are averaged.9

The third aim of the analyses in this paper is to explore whether and to what extent the patterns of cross-national and over-time variation in relevant country characteristics are related to levels and trends in countries' levels of common and non-common crime. In these analyses we take three steps. As a first step we examine bi-variate correlations between (changes in) country characteristics and levels of and trends in common and non-common crime (see Table 7). Second, since many of the chosen possible determinants are highly correlated to each other, we have next run multi-variate ordinary least square (OLS) regression models in which the independent effects of (trends in) country characteristics are examined while controlling for the effects of (trends in) the other characteristics. OLS-regression models are run to explore effects of country characteristics on countries levels of crime (see Table 8), and separate models are run to explore effects of trends in country characteristics on trends in countries' levels of crime (see Table 9).

As a third step of our analyses of the relationships between determinants of crime and (trends in) levels of crime, multi-level models were conducted wherein cross-sectional and trend analyses are done simultaneously. This strategy has the advantage that the full multi-country and multi-year dataset can be used in one model (for Theft there are a total of 1780 country/year observations, for Violence 1315 and for Theft and/or Violence 1302). These models have the additional advantage that when estimating the coefficients, separate residual components can be specified at the country- and year-level, and adjustments can be made for the correlation of the error components of the two levels. Since the results of the multi-level models fully correspond with the results of the separate cross-sectional and over-time OLS-regression analyses-and the latter analyses are more easily understandable-we focus on the OLS-regression results in the main text of the paper and present results of the multi-level models in " Appendix B ".

Describing Worldwide Patterns and Trends of Crime

Regional and Sub-Regional Variation in Common Crime

In this section we look at the distribution of victimisation rates for two separate types of common crime (theft and violence (assault/muggings)) and for the combined victimisation rate of theft and/or violence over six world regions and twenty-one sub-regions, including four individual nations (Canada, USA, Australia, and New Zealand). Table 3 summarizes the results for the world regions and sub-regions. It does this for the entire 14-year period 2006-2019, and, to check for consistency, for the periods 2006-2009, 2010-2014, and 2015-2019 separately.

Levels of common crime, expressed in one-year victimization percentages for theft and assault/muggings-and their combination-appear to vary substantially and consistently across regions and sub-regions around the world. Furthermore, the geographical distribution of levels of crime is largely uniform across theft and assault/muggings.10 Generally, African and Latin American, including Caribbean countries appear to suffer most from these types of common crime across our measures. Africa ranks first for theft and violence. Especially Sub-Saharan Africa shows very high levels of both types of crime. Levels in North Africa are close to the global mean. Latin America ranks second for both theft and violence. Sub-regional variation is limited here. Asia, Europe, North America and Oceania (Australia and New Zealand) experience medium to high levels of both types of common crime with New Zealand experiencing the highest level of theft.

Two results stand out in the light of prior comparative research. First, the very high level of common crime across Sub-Saharan Africa. Prior research using ICVS data already indicated that populations in Sub- Saharan Africa experienced relatively high common crime rates-but that finding related to a much more limited number of countries and to an older period (mainly 1996-2000). Moreover, prior studies of GWP data (Corcoran and Stark 2018, 2020) showed that levels of violent crime (i.e. of assault/muggings) were the highest in Sub-Saharan countries, but did not present data on levels of property crime. On average around a quarter of the population in Sub-Saharan Africa reported having their money or property stolen from them or another household member in the course of last year, and more than ten percent reported that they had been assaulted and/or mugged.

Second, the very high victimisation rates of property crimes in Latin America and the Caribbean stand out too. Prior research typically highlighted the high violence rates in Latin America (Corcoran and Stark 2018, 2020). The current result shows that Latin American countries in an international perspective also experience very high victimisation rates for theft. A fifth of the populations in these countries reported having their money or property stolen from them or another household member in the past year. This too had already emerged from analyses of the ICVS datasets, but only for a smaller number of countries and for a less recent period (Van Dijk 2008).

Global Trends in Common Crime

Next, we look at the trends in victimisation rates of theft and violence (assault/muggings), and of the combined victimisation rate of theft and/or violence over six world regions and twenty-one sub-regions. Table 4 summarizes the results of the trend analyses, and presents average linear trend estimates (in percentage points) for all countries per world-region and sub-region.11 As explained in the analytical strategy section above, these trend estimates represent the numerical difference between the predicted percentage in 2019 minus the predicted percentage in 2006. For example, the value of -4.1 of the trend estimate for Oceania for common crime (theft and/or violence) represents a decrease in estimated victimisation rates from 19.6 percent in the year 2006 to 15.5 percent in the year 2019-and thus a change of 19.6-15.5% = − 4.1 percent points (%p.).12

The trend analysis of common crime around the world over the past fourteen years-as summarized in Table 4-confirms prior studies showing that levels of common crime have, possibly due to improved security, been declining in Europe, Australia and New Zealand since the turn of the century (Van Dijk et al. 2012; Farrell et al. 2014). Our data show that since 2006 common crime has declined across Asia, except in Southern Asia, and across Latin America as well. Somewhat surprisingly, the GWP-data did not show a continuation of the much discussed 'crime decline' in the USA since 1995 (Zimring 2006). Estimated levels of theft and violence in the USA are roughly the same in 2019 as they were in 2006. The crime drop in the USA has set in some years earlier than elsewhere (Van Dijk 2008), and seems to have bottomed out sooner too.13

Africa emerges as the only world region where crime has gone up since 2006 (with on average 11.6 percentage points). In 27 of the 35 African countries included in the trend analysis, levels of crime increased substantially over the period 2006-2019, i.e. more than five percentage points. Rises are most pronounced in Sub-Saharan countries.

To further examine the geographical distribution of trends in common crime we looked at the correlations between countries' trends for theft, violent crime (assault/muggings) and common crime. The correlation between countries trends in national theft rates and rates of violence appeared to be moderate (r. = 47; n = 136).14 When a country experiences an increase in levels of property crime it is somewhat more likely to experience an increase in levels of violent crime as well, and vice versa, but this is far from assured.

By way of summing up, Fig. 1 presents an overview of our findings on the distribution of both levels and trends in common crime across world regions, sub-regions and countries. It reveals at a glance the uniquely diverging position of Africa as the world region wherein most countries have experienced both the highest average prevalence during 2006-2019 and the most pronounced increases during this period. Latin America stands out as the world region with the second highest average prevalence but with a declining trend in most countries. In Asia prevalence is highest in South Asia. This is also the only Asian sub-region where the rate has in most countries gone up. Elsewhere in the world prevalence was relatively low during 2006-2019 and has declined or remained stable.

Prevalence and trends in common crime, 2006-2019 (Per country and region)

Regional and National Variation and Trends in Non-Common Crime

As discussed, criminologists in the 1980s switched their attention to the collection and analysis of international data on non-common crime, e.g. homicide, and corruption/organised crime. Now that data on common crime have also become more widely available, it is interesting to see to what extent levels and trends in common crimes are correlated to levels and trends in these non-common crimes. First, we will present the results on variations in homicides and organised crime.

Table 5 shows homicide rates calculated per 100,000 inhabitants based on the UNODC World Reports on Homicide from 2006 to 2017 for 142 countries. The world average rate per 100,000 is 8. Latin America is in a league of its own with an elevated rate of 23, with Central America leading with an average rate of 32. Africa comes in second place with a much lower regional rate of 8. This average is lifted upward by the exceptionally high rate of Southern Africa (24). In most other African regions rates of homicide lie far below the global mean. Rates of other world regions vary within a narrow range of 1 to 3. In Asia Central Asia stands out with a relatively high rate of 5. The lowest rates are found in Western Europe and in Oceania (Australia/New Zealand). Within the Western world, the USA shows a conspicuously high rate of 5.

Trend analysis of homicides (see also Table 5) could be adequately done for 121 countries worldwide. It shows a uniform modest decline across all world regions.15 The only noticeable exception is Central America where the homicide rates went up by 1,5 points (i.e. per 100.000 inhabitants) (see also Alvazzi del Frate and Mugellini 2012).

Table 5 also shows the regional average scores on our composite Organised Crime/Corruption Index, which, as explained, includes business executives' perceptions of mafia-type practices and two items on corruption in government, between 2007 and 2017. The findings display that the highest rates for exposure to organised crime/corruption are, once again, found in Africa and Latin America (both 68 on the 0-100 scale used), followed by Asia. Lowest rates are found in Western and Northern Europe and in Oceania. Within Europe, the levels are comparatively high in Eastern and Southern Europe (scores of 64 and 60 respectively). The level is relatively high in the USA too (49), especially when compared to that of Canada (27).

The trend data on organised crime show a small global increase with considerable regional variation. According to the index organised crime has gone up in North America (plus 6 percentage points), Australia (plus 9) and Latin America (plus 3). In Europe organised crime went down somewhat in Eastern Europe but up everywhere else. Trends were also divergent in Asia. Finally, organised crime went on average down in Africa with Northern Africa, where the level went up with 11 percentage points, being a clear-cut exception.

Intercorrelations of Common and Non-Common Crime

We have earlier reported on the strong cross-sectional associations between national rates for three types of common crime (r = 0.85 or more). Our analyses showed that rates of homicide and organised crime are moderately correlated with each other (r = 0.41; N = 136). Some degree of correlation was to be expected since, as discussed, instrumental violence is seen as one of the defining characteristics of organised crime.

To examine the geographical association of common and non-common crime, we calculated the Pearson correlations between the country rates for theft, violence (assault/muggings), and their combination (theft and/or violence), and our measures for homicide and organised crime (See Table 6).

As can be seen in Table 6 rates of common crime show weak to moderate correlations with rates of non-common crime. Correlation coefficients between our measure for common crime (theft and/or violence) and homicide and organised crime are 0.34 and 0.45 respectively. So, if certain countries experience high levels of theft and/or violence, they are only somewhat more likely to be exposed to high levels of homicide and/or organised crime too. Although the correlations are only moderately strong, it seems worth noting that countries in Africa and Latin-America rank highest for all types of common and non-common crime alike.

Next, we looked at the correlations between trends in common and non-common crime. Different from the correlations between levels of common crime, those between estimated linear change measures of common crime and non-common crime are non-existent or very weak. There is, for example, only a very low correlation between trends in common crime and those in homicide rates (r. = 0.18). Our trend data on common and non-common crime thus suggest that common and non-common types of crime show considerable divergence in their movements over time.

By and large, our epidemiological crime data show that countries' levels of different types of common crime show roughly similar geographical distributions and trajectories over time but that this does not, or to a much lesser degree, hold for types of non-common crime. Homicides and organised crime show geographical patterns and trajectories distinctly different from those of common crime. This finding suggests that determinants of crime at the macro level may be different for common than for non-common types of crime. Whether this supposition is valid, we will explore in the next section.

Testing Explanations for Worldwide Patterns and Trends of Crime

Determinants of Cross-National Variation in Crime

As a first step in our explorative analysis of possible determinants of various types of crime, we examine bi-variate correlations between country characteristics (averaged over the period 2006-2019) and levels of common and non-common crime (also averaged over 2006-2019) (see Table 7). As can be seen in this table, all six determinants are significantly correlated with most or all five measures of crime with homicide as exception (with rates being uncorrelated to poverty and urbanization).

Two sets of indicators are correlated with crime in the expected direction. First, the motivational determinants, Poverty, Inequality, and Youth present an unambiguous picture. In line with offender-related hypotheses, poorer, more unequal, and younger populations experience higher levels of all five types of crime, except homicide. Second, our composite index of governance appears to be inversely related to all five types of crime, most strongly so with organised crime (r = − 0.73). However, contrary to expectation, the correlations between the two opportunity-related determinants and all five types of crime are reversed, suggesting that levels of crime are significantly lower in more urbanized, affluent societies.

Since many of the chosen independents including poverty and wealth are highly correlated to each other, a multi-variate analysis is obviously called for to examine the independent relationships with crime.

As a next step in our explorative analysis of possible determinants of various types of crime, we have run multi-variate OLS-regression models in which the independent effects of country characteristics are examined while controlling for the effects of the others. Such analyses are not unproblematic, since several of our country characteristics are so strongly inter-correlated that problems of multi-collinearity arise when running ordinary regression models. In particular, our index of governance is very strongly inter-correlated with our set of independents representing offender-related factors (Poverty, Inequality and Proportion), and, though to a lesser degree, with opportunity-related factors (Wealth and Urbanisation) as well. As a remedy, we have introduced dummy variables in our regression models representing three groups of countries: failed states (with governance scores < 1.5, N = 26), frail states (governance 1.5-8.5, N = 96), and effective states (governance > 8.5, N = 36) (as reference group) respectively-and centred the values of the other independent variables around their means of each of these groups separately. In this way we have analysed the correlations of crime with the variance in the other independents among countries with similar degrees of governance (a fixed effects model).16

Doing this not only overcomes the 'technical' multi-collinearity problem. It also follows the theoretical ideas emerging from the New Institutionalist School in economics about the close linkage between bad governance and underdevelopment (Acemoglu and Robinson 2012). Good governance of states is regarded as the principal driver of sustainable development-e.g. less poverty and inequality. As can be seen in " Appendix A", our dataset supports this theoretical notion. The results of the regression analyses are presented in Table 8.

The results, first of all, show clear and consistent inverse relationships between the countries' level of (good) governance, and the measures of all five types of crime. The estimated parameters for each of the two country groups represent the average crime rates of the 'failed states' and 'frail states' compared to the 'effective states'. The results show that failed and frail states suffer from significantly more crime problems overall than more effective states. The importance of good governance is most pronounced for organised crime. These results fully confirm the institutionalist perspective: bad governance is linked not only to underdevelopment but to various forms of insecurity as well.

The second main finding is that the motivational, offender-focussed factors of poverty, inequality, and proportion of youth are important predictors of common crime, even after controlling for the effects of different levels of governance. Apparently, classical criminological notions about poverty-related, motivational causes of common crime have at the global scale lost none of their pertinence.

Third, in the multi-variate analysis the urbanization indicator is positively related to common crime, as predicted by criminal opportunity theory: anonymous urban environments breed more crimes by 'opportunistic' offenders (Felson and Cohen 1980). However, contrary to expectations, wealth is not positively related to theft or violent crime. The absence of a significant relationship between wealth and crime is probably due to the dual and opposing impact of wealth on common crime. While affluence brings a larger supply of suitable targets, its criminogenic impact, predicted by opportunity theory, may be offset by lower numbers of motivated offenders. In addition, above average investments in security measures in more affluent societies may have reduced their vulnerability for opportunistic property crimes (Van Dijk 2008; Farrell et al. 2014).

Finally, for non-common crime the results are less clear in several respects. A country's percentage of youth in the population is a predictor of homicide, as suggested by the literature. And a nation's level of inequality is associated with organised crime. However, poverty, wealth and urbanization are not associated with either homicide or organized crime. The latter findings hint at the complex, still poorly understood interrelationships between governance, organised crime and wealth (ENACT 2019).

Determinants of National Trends in Crime

The availability of trend data on the five types of crime for the period 2006-2019 allows an explorative test of the relevance of the determinants of crime for explaining changes over time in levels of common and non-common crime. Possibilities for such test are of course conditional on the availability of trend data of the independents as well. For this paper we use the time series data available on all six indicators included in the cross-national analyses (see Table 2).

Using these data, we generated predicted values for each indicator from OLS-linear regression models that were estimated for each country individually based on real values from available years (similar to what we did to obtain trend estimates for crime). Next, we calculated the differences between the predicted scores in the last year (i.e. 2019) and the first year (i.e. 2006) in each country as measure for the size of 'linear change'. Subsequently, we examine the extent to which these linear trends in country characteristics are related to linear trends in crime. Again, as in the cross-sectional analyses, bivariate analyses (not shown here) were followed by OLS-regression analyses (see Table 9).17

The results show that global variation in trends in crime cannot be explained as adequately by the determinants included in the analyses as cross-national variation. The explained variance of trends in crime is much smaller (i.e. less than 31% for violence and homicide, and around 50% for the other types of crime) than of cross-sectional variation (47% for homicide and 72% or more for the other crime types). Furthermore, several of the estimated multivariate correlates are statistically insignificant.

In line with the findings of the cross-sectional analyses presented above, positive correlations were found between changes in percentage youth and trends in theft, violence and in these crimes combined. In countries with increasing proportions of (marginalised) young various types of crime have gone up.

Contrary to our cross-sectional finding that poverty is associated with more common crime, negative correlations were found between changes in poverty and changes in common crimes, especially thefts. This could either mean that countries with increasing poverty are experiencing less common crime, or that countries with decreasing poverty experience more crime. Since changes in our measure of wealth are not significantly correlated with changes in levels of common crime, the finding that less poverty goes together with more thefts calls for further scrutiny.

Finally, trends in governance-related factors appear to be associated with our measure of organised crime/corruption but not with other types of crime. Trends in our index of organised crime were found to be inversely correlated with changes in the quality of Governance/Rule of Law and Wealth (GDP). In line with the institutionalist perspective, the increases in organised crime/corruption in some parts of the world seem to have gone together with deteriorations in the functioning of state institutions, less economic growth, and more poverty.

Discussion and Limitations

In recent years polling companies have started to supply survey-based datasets on levels of various types of common and non-common crime across the world. Cross-validation with results from in-depth criminological studies such as the ICVS has shown encouraging results in this study. Country prevalence of common criminality can apparently be reasonably well estimated with just two catch-all items on theft and assault/muggings in national sample surveys. Credible data on (recorded) homicides and perceptions of organised crime and corruption have also become available.

The datasets used on prevalence of thefts, assaults/muggings, common crime overall, (recorded) homicides, and organised crime/corruption, covering 166 countries worldwide, shows huge variation across regions and sub-regions. By far the highest levels of common crime are experienced by populations in the Global South, most notably in Africa-especially sub-Saharan Africa- and Latin America. Levels of homicide are highest in Latin America, particularly in Central America and the Caribbean, followed by Southern Africa. Organised crime shows, once again, the highest concentrations across Africa and Latin America, and in Asia. Within the Western world, Eastern and Southern Europe and the USA stand out with comparatively high scores on organised crime/corruption.

By and large, the geographical distribution reveals the existence of a deep North-South Security Divide in the beginning of the twenty-first century. Over the past fifteen years this gap has widened by the continued rise in levels of common crime in Africa and South Asia and of homicides in Central America while almost everywhere else these forms of crime have dropped. Trends in organised crime, including grand corruption, show a somewhat different picture with decreases in sub-Saharan Africa, and increases in Latin and North America, Australia and parts of Europe.

Differences in the geographical distribution of different types of crime and divergent trends in these types of crime between 2006 and 2019 shed doubt on general theories about the macro-causes of crime. This is confirmed by our explorative analyses of relationships between determinants of crime and levels of various types of crime. Traditional ideas about 'root causes of crime' such as poverty and inequality emerged strongly in regression analyses of levels of common crime but less so in those of homicides and organised crime. Apart from these common causes of crime, levels of common crime seem to be co-determined by the availability of easy targets of theft and reduced social control in urban environments. Urbanization, however, is totally unrelated to levels of homicides or organised crime.

Our explorative analyses furthermore point at the pervasive impact of governance-related factors on crime levels: prevalence of all types of crime is significantly higher to the extent that state and democratic institutions are weaker. This appears to be true not only, as was to be expected from previous studies, for homicide (La Free and Tseloni 2006; Chu and Tusalem 2013; Karstedt 2015) and organised crime (Van Dijk 2007; ENACT 2019), but, to some extent, for common crime as well.

A subsequent analysis of the correlates of trends over time of common crime confirmed the role of governance-related factors in explaining variation across countries in the movement of various types of crime. Besides, changes in common crime over the past fifteen years were strongly related to ongoing urbanization, increased proportions of young and growing inequalities. The exceptional, and pronounced increases in common crime in Sub-Saharan countries, discussed above, are likely to have been driven by expanding 'youth bulges' across the region.

The findings concerning governance conform to, and elaborate on the New Institutionalist School in comparative economics. The institutional capacity of countries seems to be the principal driver not just of sustainable development but of internal security as well. Between economic stagnation and organised crime appear to exist nefarious, mutually reinforcing relationships (Acemoglu et al. 2017). Linkages between governance, development and common crime, partly mediated by governance-related factors as (extreme) poverty, inequality, and high proportions of (marginalised) youth, are close as well. Many poorer nations seem in the grip of vicious circles of poorly functioning state institutions, underdevelopment, expanding youth bulges and accompanying high levels of all sorts of crime (Van Dijk 2008; Wenmann and Muggah 2010; World Bank 2011; UNDP 2013). Our results underline the importance of reducing levels of crime and violence as integral part of the United Nation's 2030 Agenda for Sustainable Development.

Limitations

For our analyses we have used readily and widely available international measures of crime and of the main possible determinants of crime mentioned in criminological literature. This reliance on available data has introduced important limitations to our analysis. The results show that the chosen core determinants explain a considerable part of cross-sectional variance in prevalence of common crime and organised crime but less so in that of homicides. Their explanatory power for medium term trends over time proved to be limited for all types of crime. Unexplained cross-sectional and over time variance may be related to important criminogenic factors omitted in our analysis, both general and crime-specific ones. Examples of the latter are gender inequality, alcohol abuse and firearm possession as drivers of violent crime and homicides. Special cultural factors have remained altogether unexplored in our analyses. Subsequent studies should widen the choice of correlates and seek to specify relevant aspects of broadly operationalised variables as inequality, youth or 'bad governance'.

Future international surveys or other studies will hopefully provide more refined measures of common crime, homicides, organised crime and other types of crime. These should then, ideally, be regressed against tailor-made operationalisations of possible determinants informed by current criminological theory. Such focussed cross-sectional and longitudinal analysis would bring research into the macro causes of crime to the next level. Even such improved correlational analysis would not, however, allow drawing conclusions on causality. Other types of research are required for causal inference. Correlational analysis should be complemented by studies focussing on crime trends in countries affected by major and sudden upheavals due to external forces like war, natural disasters or pandemics. A pertinent example would be an analysis of crime trends in countries where conflicts have disrupted the normal functioning of state institutions and/or the economy.

Change history

27 July 2022

A Correction to this paper has been published: https://doi.org/10.1007/s10940-022-09553-w

Notes

1. We also did sensitivity analyses by excluding countries in which the GWP-documentation indicated that less than 85% of the population was represented (e.g. due areas where the safety of interviewing staff is threatened, scarcely populated islands in some countries, and areas that interviewers can reach only by foot, animal, or small boat). The results of these sensitivity analyses are very similar to the analyses using all countries. We therefore do not show the results of the sensitivity analyses in this paper. Furthermore, we also test for the robustness of the results by excluding countries with fewer than 3 years of GWP data. Again, these results were very similar to the analyses on all countries (not shown in this paper).

2. We recognise that the measure for common crime combines a household rate for theft and a personal rate for assault/mugging. In reports on the ICVS rates for personal and household crimes are similarly combined into an overall prevalence rate for victimization experiences as individual persons and/or household member (burglaries and car thefts). In this respect the GWP-based common crime rate and the ICVS over all prevalence rate are fairly similar.

3. The correlations between the measures are: WEF-TI .70 (n = 139), WEF-Gallup .51 (N = 139), TI-Gallup: .54 (N = 138). The reliability index of the scale is: .81 (N = 1.496).

4. Standardised: with mean of 0 and standard deviation of 1, and Normalised: Normalised Value = 1 + (Value - minimum value)*(100-1)/(maximum value - minimum value).

5. In early stages of our explorative, cross-sectional analyses we looked at a larger selection of possible determinants including unemployment, social disorganisation (operationalized as rapid changes in wealth), alcohol consumption and possession of firearms. Unemployment and social disorganisation appeared to be unrelated to our main measures of crime. Alcohol consumption was found to be significantly related to levels of violence and homicides in multivariate analyses and so was firearm possession to homicides. Our initial operationalisation of Governance was a scale of nine indicators taken from the World Bank Governance Index, the Fragile State Index and the WEF surveys (police performance). In our final analyses we have included only one of these indicators, the FSI P1 indicator of State Legitimacy. Results concerning the role of governance of earlier multi-variate analyses using the composite scale were identical to the ones presented here.

6. When doing this, we gave each country the same weight-regardless of number of inhabitants of a country or the number of respondents in Gallup World Poll in each country.

7. We included 139 countries for which data is available from at least one year in the period 2006-2010 and one year in the period 2015-2019.

8. The models are as follows: Crime ij = γ iD i + β iYear ij + µ ij, with Crime ij-i.e. the level of crime in each country i and year j-being the dependent variable, D i dummies for all the countries, and Year ij the Years (from 2006 thru 2019, and β i the countries' trend parameters. We centred the Year ij-variable around the value in the first year of the observation period, i.e. 2006.

9. When doing this, we gave each country the same weight-regardless of number of inhabitants of a country or the number of respondents in Gallup World Poll in each country.

10. The Pearson correlations between the countries' average prevalence rates for Theft and Violence in the period 2006-2019 is 0.85, for Theft and 'Theft and/or Violence' 0.97 and for Violence and 'Theft and/or Violence' 0.95.

11. Note that the trends reported in Table 4 do not necessarily match with the figures reported in Table 3. For example, Table 3 seems to suggest a stable overall crime rate in Asia between 2006/10 and 2015/19, while table 4 reports a decline by 1% point (across the 14-year period). These differences result from the different ways in which the analyses were done: Table 3 presents average levels of crime victimization rates in the counties per (sub-region) for the periods, 2006/10, 2011-2014, and 2015/19, whereas Table 4 present average linear trend estimates (in percentage points) for all countries per world-region and sub-region (see Sect. 4.4. Analytical strategy). Moreover, the trend analyses presented in Table 4 are based on a more restricted number of countries, i.e., only countries for which data is available for at least one year in the period 2006/10 and one in the period 2015/19. Nevertheless, the overall pictures of Tables 3 and 4 are very similar.

12. Readers might wonder why no statistical significance levels are presented for the trend parameters. This is since the presented average linear change estimates per (sub-) region result from averaging estimates of country level OLS-regression analyses-and not from regression analyses per (sub-)region (see Sect. 4.4. Analytical Strategy). Moreover, we preferred to focus on whether the trends in crimes are substantive (in percentage points) rather than on statistical significance (see also Fig. 1).

13. Rates of violent crime in the USA have been more or less stable since 2003 according to the NCVS (Morgan and Truman/BJS, 2020). Rates for property crimes are not comparable with those of GWP.

14. Correlations between trends in theft and violence and trends in the composite rate for common crime were - logically - very high (r. = 90 and .80 respectively).

15. Similar to the trend analyses for common crimes, we used predicted values for homicide and organised crime from OLS-linear regression models that were estimated for each country individually based on real values from available years. In these models, the dependent variable is the prevalence of homicide or organised crime in that country, and the independent variable is the calendar year. These models thus generate predicted levels of these type of crimes assuming a linear trend in each country. We calculated the differences between the predicted levels of crime in the last year (i.e. 2017) and the first year (i.e. 2006 for homicide and 2007 for organised crime) in each country as measure for the size of 'linear change'.

16. For all regression models, both for cross-national variation and variation in trends, the variance inflation factors (VIFs) are under 3, suggesting that multicollinearity is not a problem. We have also examined the data for potential outliers (e.g. using residuals) and rerun all models excluding the possibly influential outliers from the analyses (the pertaining (number of) countries excluded differ across types of crime - but are not more than 9). These extra analyses (results not shown) yielded very similar or identical results.

17. Since the correlations between the linear trends in the determinants are low or at most moderate, and there is no problem of multi-collinearity, we did not include dummies for failed and fragile states in the regression models.

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Acknowledgements

The authors express their gratitude to the Minderoo Foundation and Gallup Inc. for allowing access to data from Gallup World Poll.

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Authors and Affiliations

1. Netherlands Study Center for Crime and Law Enforcement, Amsterdam, The Netherlands

Jan van Dijk

2. Department of Criminology, Leiden University, Leiden, The Netherlands

Paul Nieuwbeerta

3. Walk Free, An Initiative of the Minderoo Foundation, Perth, Australia

Jacqueline Joudo Larsen

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Correspondence to Jan van Dijk.

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The original online version of this article was revised: The incorrect data from the Tables 1, 3, 4, 7, 8, 9 and Appendix B has been corrected.

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Appendices

Appendix A

See Table 10.

Table 10 Average scores on correlates-by region and level of governance (N = 166 countries)

Appendix B

See Table 11.

Table 11 Relationships between countries' country characteristics and levels of crime: results of multi-level regression models

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van Dijk, J., Nieuwbeerta, P. & Joudo Larsen, J. Global Crime Patterns: An Analysis of Survey Data from 166 Countries Around the World, 2006-2019. J Quant Criminol 38, 793-827 (2022). https://doi.org/10.1007/s10940-021-09501-0
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# data[].attributes.attachment_link.title
Global Crime Patterns: An Analysis of Survey Data from 166 Countries Around the World, 2006-2019 - Journal of Quantitative Criminology

# data[].attributes.attachment_link.description
Objectives This article explores the merits of commercially-based survey data on crime through cross-validation with established crime metrics. Methods Using unpublished data from 166 countries covering the period between 2006 and 2019, the article describes the geographical distribution across global regions and trends over time of three types of common crime, homicide, and organised crime.

# data[].attributes.attachment_caption
About Human Trafficking - United States Department of State

# data[].attributes.body
This article talks about human trafficking and how big of a deal it is. It provides statistics and plans to try and lower the rates in which it
happens.

(Quantitative): The article states that there are 27.6 million victims at any given moment

(Qualitative): The article talks about the most common things a trafficked person is forced to do. Some of these things are sexual acts, agricultural work (farming), drug smuggling, peddling and begging, etc. these things are all done for the benefit of the traffickers and usually are agains the trafficked persons will.

# data[].attributes.attachment_link.readable_text
Human trafficking, also called trafficking in persons, has no place in our world. As both a grave crime and a human rights abuse, it compromises national and economic security, undermines the rule of law, and harms the well-being of individuals and communities everywhere. It is a crime of exploitation. Traffickers profit at the expense of their victims by compelling them to perform labor or to engage in commercial sex in every region of the United States and around the world. With an estimated 27.6 million victims worldwide at any given time, human traffickers prey on people of all ages, backgrounds, and nationalities, exploiting them for their own profit.

LEARN MORE

Human Trafficking in the United States

In the United States, traffickers compel victims to engage in commercial sex and to work in both legal and illicit industries and sectors, including in hospitality, traveling sales crews, agriculture, janitorial services, construction, landscaping, restaurants, factories, care for persons with disabilities, salon services, massage parlors, retail services, fairs and carnivals, peddling and begging, drug smuggling and distribution, religious institutions, child care, and domestic work.

"Trafficking in persons," "human trafficking," and "modern slavery" are umbrella terms - often used interchangeably - to refer to a crime whereby traffickers exploit and profit at the expense of adults or children by compelling them to perform labor or engage in commercial sex.  When a person younger than 18 is used to perform a commercial sex act, it is a crime regardless of whether there is any force, fraud, or coercion involved.

The United States recognizes two primary forms of trafficking in persons:  forced labor and sex trafficking.  The basic meaning of these forms of human trafficking and some unique characteristics of each are set forth below, followed by several key principles and concepts that relate to all forms of human trafficking.

More than 175 nations have ratified or acceded to the UN Protocol to Prevent, Suppress and Punish Trafficking in Persons (the UN TIP Protocol), which defines trafficking in persons and contains obligations to prevent and combat the crime.

The United States' Trafficking Victims Protection Act of 2000, as amended (TVPA), and the UN TIP Protocol contain similar definitions of human trafficking.  The elements of both definitions can be described using a three-element framework focused on the trafficker's 1) acts; 2) means; and 3) purpose.  All three elements are essential to form a human trafficking violation.
Forced Labor
Forced Labor, sometimes also referred to as labor trafficking, encompasses the range of activities involved when a person uses force, fraud, or coercion to exploit the labor or services of another person.

The  "acts"  element of forced labor is met when the trafficker recruits, harbors, transports, provides, or obtains a person for labor or services.

The  "means"  element of forced labor includes a trafficker's use of force, fraud, or coercion.  The coercive scheme can include threats of force, debt manipulation, withholding of pay, confiscation of identity documents, psychological coercion, reputational harm, manipulation of the use of addictive substances, threats to other people, or other forms of coercion.

The  "purpose"  element focuses on the perpetrator's goal to exploit a person's labor or services.  There is no limit on the location or type of industry.  Traffickers can commit this crime in any sector or setting, whether legal or illicit, including but not limited to agricultural fields, factories, restaurants, hotels, massage parlors, retail stores, fishing vessels, mines, private homes, or drug trafficking operations.

All three elements are essential to constitute the crime of forced labor.

There are certain types of forced labor that are frequently distinguished for emphasis or because they are widespread:
Domestic Servitude
"Domestic servitude" is a form of forced labor in which the trafficker requires a victim to perform work in a private residence.  Such circumstances create unique vulnerabilities. Domestic workers are often isolated and may work alone in a house.  Their employer often controls their access to food, transportation, and housing.  What happens in a private residence is hidden from the world - including from law enforcement and labor inspectors - resulting in barriers to victim identification.  Foreign domestic workers are particularly vulnerable to abuse due to language and cultural barriers, as well as a lack of community ties.  Some perpetrators use these types of conditions as part of their coercive schemes to compel the labor of domestic workers with little risk of detection.
Forced Child Labor
The term "forced child labor" describes forced labor schemes in which traffickers compel children to work.  Traffickers often target children because they are more vulnerable.  Although some children may legally engage in certain forms of work, forcing or coercing children to work remains illegal.  Forms of slavery or slavery-like practices - including the sale of children, forced or compulsory child labor, and debt bondage and serfdom of children - continue to exist, despite legal prohibitions and widespread condemnation.  Some indicators of forced labor of a child include situations in which the child appears to be in the custody of a non-family member and the child's work financially benefits someone outside the child's family; or the denial of food, rest, or schooling to a child who is working.
Sex Trafficking
Sex trafficking encompasses the range of activities involved when a trafficker uses force, fraud, or coercion to compel another person to engage in a commercial sex act or causes a child to engage in a commercial sex act.

The crime of sex trafficking is also understood through the "acts," "means," and "purpose" framework.  All three elements are required to establish a sex trafficking crime (except in the case of child sex trafficking where the means are irrelevant).

The  "acts"  element of sex trafficking is met when a trafficker recruits, harbors, transports, provides, obtains, patronizes, or solicits another person to engage in commercial sex.

The  "means"  element of sex trafficking occurs when a trafficker uses force, fraud, or coercion.  Coercion in the case of sex trafficking includes the broad array of means included in the forced labor definition.  These can include threats of serious harm, psychological harm, reputational harm, threats to others, and debt manipulation.

The  "purpose"  element is a commercial sex act.  Sex trafficking can take place in private homes, massage parlors, hotels, or brothels, among other locations, as well as on the internet.
Child Sex Trafficking
In cases where an individual engages in any of the specified "acts" with a child (under the age of 18), the means element is irrelevant regardless of whether evidence of force, fraud, or coercion exists.  The use of children in commercial sex is prohibited by law in the United States and most countries around the world.
Key Principles and Concepts
These key principles and concepts relate to all forms of trafficking in persons, including forced labor and sex trafficking.
Consent
Human trafficking can take place even if the victim initially consented to providing labor, services, or commercial sex acts.  The analysis is primarily focused on the trafficker's conduct and not that of the victim.  A trafficker can target a victim after a victim applies for a job or migrates to earn a living.  The trafficker's exploitative scheme is what matters, not a victim's prior consent or ability to meaningfully consent thereafter.  Likewise, in a sex trafficking case, an adult victim's initial willingness to engage in commercial sex acts is not relevant where a perpetrator subsequently uses force, fraud, or coercion to exploit the victim and cause them to continue engaging in the same acts.  In the case of child sex trafficking, the consent of the victim is never relevant as a child cannot legally consent to commercial sex.
Movement
Neither U.S. law nor international law requires that a trafficker or victim move across a border for a human trafficking offense to take place.  Trafficking in persons is a crime of exploitation and coercion, and not movement.  Traffickers can use schemes that take victims hundreds of miles away from their homes or exploit them in the same neighborhoods where they were born.
Debt Bondage
"Debt bondage" is focused on human trafficking crimes in which the trafficker's primary means of coercion is debt manipulation.  U.S. law prohibits perpetrators from using debts as part of their scheme, plan, or pattern to compel a person to work or engage in commercial sex.  Traffickers target some individuals with an initial debt assumed willingly as a condition of future employment, while in certain countries traffickers tell individuals they "inherited" the debt from relatives.  Traffickers can also manipulate debts after the economic relationship begins by withholding earnings or forcing the victim to assume debts for expenses like food, housing, or transportation.  They can also manipulate debts a victim owes to other people.  When traffickers use debts as a means to compel labor or commercial sex, they have committed a crime.
Non-Penalization
Governments should not penalize or prosecute victims of trafficking in persons for the unlawful acts traffickers compelled them to commit.  This principle aims to protect victims from being held legally responsible for conduct that was not their choice, but rather was driven by traffickers.  If a government has penalized or punished a victim in such a way, the government should vacate the conviction and/or expunge the victim's record.
State-Sponsored Human Trafficking
While the TVPA and UN TIP Protocol call on governments to proactively address trafficking crimes, some governments are part of the problem, directly compelling their citizens into sexual slavery or forced labor schemes.  From forced labor in local or national public work projects, military operations, and economically important sectors, or as part of government-funded projects or missions abroad, officials use their power to exploit their nationals.  To extract this work, governments coerce by threatening the withdrawal of public benefits, withholding salaries, failing to adhere to limits on national service, manipulating the lack of legal status of stateless individuals and members of minority groups, threatening to punish family members, or conditioning services or freedom of movement on labor or sex.  In 2019, Congress amended the TVPA to acknowledge that governments can also act as traffickers, referring specifically to a "government policy or pattern" of human trafficking, trafficking in government-funded programs, forced labor in government-affiliated medical services or other sectors, sexual slavery in government camps, or the employment or recruitment of child soldiers.
Unlawful Recruitment or Use of Child Soldiers
Another manifestation of human trafficking occurs when government forces or any non-state armed group unlawfully recruits or uses children - through force, fraud, or coercion - as soldiers or for labor or services in conflict situations.  Children are also used as sex slaves.  Sexual slavery, as referred to here, occurs when armed groups force or coerce children to "marry" or be raped by commanders or combatants.  Both male and female children are often sexually abused or exploited by members of armed groups and suffer the same types of devastating physical and psychological consequences associated with sex trafficking.
Accountability in Supply Chains
Forced labor is well documented in the private economy, particularly in agriculture, fishing, manufacturing, construction, and domestic work; but no sector is immune.  Sex trafficking occurs in several industries as well.  Most well-known is the hospitality industry, but the crime also occurs in connection with extractive industries where activities are often remote and lack meaningful government presence.  Governments should hold all entities, including businesses, accountable for human trafficking.  In some countries, the law provides for corporate accountability in both the civil and criminal justice systems.  U.S. law provides such liability for any legal person, including a business that benefits financially from its involvement in a human trafficking scheme, provided that the business knew or should have known of the scheme.

Prosecution, Protection, Prevention, and Partnership

The "3P" paradigm-prosecution, protection, and prevention-continues to serve as the fundamental framework used around the world to combat human trafficking. The United States also follows this approach, reflected in the United States' Trafficking Victims Protection Act of 2000 , as amended (TVPA), and in the Protocol to Prevent, Suppress and Punish Trafficking in Persons, Especially Women and Children supplementing the United Nations Convention against Transnational Organized Crime (Palermo Protocol) . In addition, a fourth "P"-for partnership-serves as a complementary means to achieve progress across the 3Ps and enlist all segments of society in the fight against human trafficking.

Victims of Human Trafficking

Human trafficking victims can be of any age, race, ethnicity, sex, gender identity, sexual orientation, nationality, immigration status, cultural background, religion, socio-economic class, and education attainment level. In the United States, individuals vulnerable to human trafficking include children in the child welfare and juvenile justice systems, including foster care; runaway and homeless youth; unaccompanied foreign national children without lawful immigration status; individuals seeking asylum; American Indians and Alaska Natives, particularly women and girls; individuals with substance use issues; racial or ethnic minorities; migrant laborers, including undocumented workers and participants in visa programs for temporary workers; foreign national domestic workers in diplomatic households; persons with limited English proficiency; persons with disabilities; LGBTQI+ individuals; and victims of intimate partner violence or other forms of domestic violence.

Who are the Traffickers?

At the heart of this phenomenon is the traffickers' aim to profit from the exploitation of their victims and the myriad coercive and deceptive practices they use to do so. Traffickers can be strangers, acquaintances, or even family members, and they prey on the vulnerable and on those seeking opportunities to build for themselves a brighter future.

Human Trafficking vs. Migrant Smuggling

Human trafficking can include, but does not require, movement. Human trafficking is distinct from the separate crime of migrant smuggling. Human trafficking occurs when a trafficker uses force, fraud, or coercion to compel another person to work or engage in a commercial sex act. It sometimes involves crossing a border but does not require it. By contrast, migrant smugglers engage in the crime of bringing people across international borders through deliberate evasion of immigration laws. While these are distinct crimes, individuals who are smuggled may become vulnerable to and victims of human trafficking.

How Many Victims of Human Trafficking Are There?

It is hard to find reliable statistics related to human trafficking. The quality and quantity of data available are often hampered by the hidden nature of the crime, challenges in identifying individual victims, gaps in data accuracy and completeness, and significant barriers regarding the sharing of victim information among various stakeholders. For these reasons, data and statistics may not reflect the full nature or scope of the problem.
International Labour Organization
The International Labour Organization (ILO) and the Walk Free Foundation, in partnership with the International Organization for Migration (IOM), released Global Estimates of Modern Slavery in September 2022. This report estimates that, at any given time in 2021, approximately 27.6 million people were in forced labor. Of these, "17.3 million are exploited in the private sector, 6.3 million in forced commercial sexual exploitation, and 3.9 million in forced labour imposed by state." The definition of forced labor used in this report is based on ILO Forced Labour Convention, 1930 (No. 29), which states in Article 2.1 that forced labor is "all work or service which is exacted from any person under the menace of any penalty and for which the said person has not offered himself voluntarily."

This report also estimates that 49.6 million people were in "modern slavery" at any given time in 2021, but this figure includes both the estimate for forced labor and an estimate for forced marriage. Consistent with current implementation of U.S. law, it is recommended to use only the 27.6 million estimate when referring to human trafficking. While some instances of forced marriage may meet the international or U.S. legal definition of human trafficking, not all cases do. Note further that the term "modern slavery" is not defined in international or U.S. law.

In addition, the National Human Trafficking Hotline provides on its website data sets on the issue of human trafficking in the United States. These data sets are based on aggregated information learned through phone calls, emails, online tips, and texts the hotline receives and should not be confused with prevalence studies or closed-out confirmed cases. Note that the hotline receives several types of calls in addition to those about human trafficking cases. The hotline does not verify the accuracy of information reported, but it determines on a case-by-case basis whether the information should be passed on to an appropriate local, state, or federal investigative and/or service agency equipped to investigate the tip and/or respond to the needs of the potential victim.

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About Human Trafficking - United States Department of State

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Human trafficking, also called trafficking in persons, has no place in our world. As both a grave crime and a human rights abuse, it compromises national and economic security, undermines the rule of law, and harms the well-being of individuals and communities everywhere. It is a crime of exploitation.

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Does social media have an effect on mental health 

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Does social media have an effect on mental health 

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(Qualitative) Supports the idea that social media has a negative effect on how mental health is

https://etactics.com/blog/social-media-and-mental-health-statistics

(Quantitative) The article provides statistics about the percentages of mental health being damaged by social media in different age groups

-Dana

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Cyberpsychology, Behavior and Social Networking

Abstract

During the past decade, online social networking has caused profound changes in the way people communicate and interact. It is unclear, however, whether some of these changes may affect certain normal aspects of human behavior and cause psychiatric disorders. Several studies have indicated that the prolonged use of social networking sites (SNS), such as Facebook, may be related to signs and symptoms of depression. In addition, some authors have indicated that certain SNS activities might be associated with low self-esteem, especially in children and adolescents. Other studies have presented opposite results in terms of positive impact of social networking on self-esteem. The relationship between SNS use and mental problems to this day remains controversial, and research on this issue is faced with numerous challenges. This concise review focuses on the recent findings regarding the suggested connection between SNS and mental health issues such as depressive symptoms, changes in self-esteem, and Internet addiction.

Introduction

During the past 10 years, the rapid development of social networking sites (SNSs) such as Facebook, Twitter, MySpace, and so on has caused several profound changes in the way people communicate and interact. Facebook, as the biggest social networking Web site, today has more than one billion active users, and it is estimated that in the future, this number will significantly increase, especially in developing countries. Facebook is used for both business and personal communication, and its application has brought numerous advantages in terms of increasing connectivity, sharing ideas, and online learning.

Recently, however, some researchers have associated online social networking with several psychiatric disorders, including depressive symptoms, anxiety, and low self-esteem. Since social networks are a relatively new phenomenon, many questions regarding their potential impact on mental health remain unanswered. On the other hand, due to the popularity of these online services in the general population, any future confirmed connection between them and psychiatric diseases would pose a serious public health concern.

This concise review focuses on the recent research regarding the suggested connection between social networking and depressive symptoms, changes in self-esteem, and other potential psychiatric problems and issues. The articles cited in this text were selected from the Web of Science citation indexing database (Thomson Reuters) using KoBSON search tool (Konzorcijum biblioteka Srbije za objedinjenu nabavku; Serbian Library Consortium for Coordinated Acquisition). The search was conducted using a total of 50 different keywords related to social networking and mental health, such as "Facebook," "Twitter," "Depression," "Addiction," "self-esteem," and so on. The priority was given to the articles published during the past 10 years in the journals with high 2 year and 5 year impact factors (the upper 50% rank in the journal category), as well as to the articles with higher number of citations. The number of citations for selected article was determined using the Elsevier Scopus database.

Facebook and Symptoms of Depression

Although several studies have made the connection between computer-mediated communication and signs and symptoms of depression, this issue remains controversial in current psychiatry research. There are many potential reasons why a Facebook user may have a tendency to become depressed, as there are numerous factors that may lead an already depressed individual to start to use or increase their use of SNS.

In 1998, Kraut et al. published one of the first studies to indicate that Internet use in general significantly affects social relationships and participation in community life.1 In this research, the authors found that increased time spent online is related to a decline in communication with family members, as well as the reduction of the Internet user's social circle, which may further lead to increased feelings of depression and loneliness. This work was later followed by several other publications where it was suggested that computer use may have negative effects on children's social development.2

At the time when these studies were conducted, most of today's social networks did not exist. For example, Facebook was founded in 2004, and became popular among children and adolescents a few years later. Instead, most works were focused on the investigation of possible effects of Internet browsing, e-mail checking, and other online and offline behaviors (i.e., violent video games) on mental health.

With the development of social networks, the time children and adolescents spend in front of the computer screens has significantly increased. This has led to the further reduction of intensity of interpersonal communication both in the family and in the wider social environment. Although social networks enable an individual to interact with a large number of people, these interactions are shallow and cannot adequately replace everyday face-to-face communication.

Since social networks are a relatively recent phenomenon, this potential relationship between their use and feelings of loneliness and depression has not yet been properly investigated. Most of the research on this issue has been published during the past few years, and so far, the scientific community has not been able to interpret and discuss the results fully.

In our recent study in a high school student population, we found a statistically significant positive correlation between depressive symptoms and time spent on SNS.3 Depression symptoms were quantified using the Beck Depression Inventory (BDI-II). On the other hand, no such correlation was detected between BDI score and time spent watching television. Other authors have reported that there is no relationship between SNS and depressive symptoms in a sample of older adolescents-university students using the Patient Health Questionnaire-9 depression screen.4 Apart from differences in applied methodology, there is a possibility that different age groups (i.e., high school children vs. older adolescents) may react differently to SNS content and challenges.5

In 2013, Kross et al. published a study on the relationship between Facebook use and subjective well-being in young adults.6 The design of this research was based on text messaging the participants five times per day for 2 weeks in order to evaluate their mood, feeling of loneliness, social interactions, and social Facebook use. This approach was combined with the application of a conventional set of questionnaires, such as the Beck Depression Inventory, Rosenberg Self-Esteem Scale, Social Provision Scale, and Revised UCLA Loneliness Scale.6 The results indicated that users' subjective perception of well-being and life satisfaction may be undermined. It goes without saying that any decline of this sort may increase depressive signs and symptoms.

One of the reasons why time spent on SNS may be associated with depressive symptoms is the fact that computer-mediated communication may lead to the altered (and often wrong) impression of the physical and personality traits of other users. This may lead to incorrect conclusions regarding physical appearance, educational level, intelligence, moral integrity, as well as many other characteristics of online friends. Recently, Chou and Edge published an article about the potential impact of using Facebook on students' perceptions of others' lives. The study carried out on 425 undergraduate students of at a state university in Utah reported that Facebook use is linked to participants' impression that other users are happier, as well as the feeling that the "life is not fair."7 Perceiving others as happier and more successful does not necessarily result in depression. However, in individuals who already have certain depressive predispositions as well as other psychiatric comorbidities, this may further negatively impact mental health.

As it is thought that Facebook may be one of the factors influencing the development of depressive symptoms, it is also assumed that certain characteristics of online behavioral may be predictive factors in depression identification and assessment. Today, it is clear that SNS such as Facebook can be useful in the early detection of depression symptoms among users. Recently, Park et al. published a study in which they suggested that the more depressive the user is, the more he/she would use Facebook features that focus on depression tips and facts. The authors designed a unique application -EmotionDiary-that was proven to be capable of evaluating symptoms of depression in individuals.8 In other words, certain depressive behavioral characteristics of a social network user can be quantified, and that quantification has a potentially high predictive value for a future diagnosis of depression. Apart from these results, this work also presented some evidence that a depressed Facebook user has other characteristics, such as a fewer friends and location tagging. Since these traits can be quantifiable, they could also be valuable predictors for possible future depression screening.

However, it should be stressed that there is still no conclusive evidence that use of Facebook and other SNS causes depression or even a single symptom of depression. Kraut et al., the authors of the above-mentioned study on Internet and depression, recently published results indicating that online communication with friends and family (today mostly done on SNS) is actually associated with a decline in depression.9 It seems that when social networks and the Internet in general are used to strengthen and maintain social ties, particularly within family members and close friends, the resulting social support has beneficial effects on mental health. On the other hand, extensive use of SNS outside these circles might weaken existing close family and friend interactions and increase feelings of loneliness and depression.

Social Networking and Self-Esteem

Many authors define the term "self-esteem" as "the evaluative component of the self-the degree to which one prizes, values, approves or likes oneself."10,11 It is an important factor in developing and maintaining mental health and overall quality of life.12-14 Low self-esteem is associated with the pathogenesis of numerous mental illnesses, including depression, eating disorders, and addiction.15-22 Recent studies have presented conflicting results regarding the potential influence of Facebook and other SNS on self-esteem.

One of the possible explanations regarding the negative relationship between Facebook and self-esteem is that all social networking platforms where self-presentation is the principal user activity cause or at least promote narcissistic behavior.23-27 A report by Mehdizadeh described the findings of a study in which 100 Facebook users at York University provided self-esteem and narcissistic personality self-reports. The results indicated that individuals with lower self-esteem are more active online in terms of having more self-promotional content on their SNS profiles. In other words, certain Facebook activities (such as "The Main Photo" feature) were negatively correlated with self-esteem measured with the Rosenberg Self-Esteem Scale.23

On the other hand, some authors have presented results indicating that Facebook use may actually enhance self-esteem. A study by Gonzales and Hancock included groups of student participants exposed to three different settings: exposure to a mirror, exposure to one's own Facebook profile, and a control setting. The level of self-esteem in all participants was estimated using the Rosenberg Self-Esteem Scale. The results showed the positive effects of Facebook on self-esteem supporting the so-called Hyperpersonal Model in which selective self-presentation positively impacts impressions of the self.28

According to data from recent literature, as well as the above-mentioned research, there are indeed several models/theories on the possible effect of computer-mediated communication on self-esteem in the general population. Objective self-awareness theory29 suggests that any stimulus causing the self to become the object (instead the subject) of the consciousness will lead to a diminished impression of the self. These stimuli include looking at oneself in a mirror, hearing one's own voice, writing one's own curriculum vitae, or any other situation during which the subject's attention focuses on the self.28 It is probable that a typical Facebook user will every day have multiple visits to his/her own profile page during which he will view his already posted photographs, biographical data, relationship status, and so on. All of these events, especially in light of similar data obtained from other users' profiles, may lead to either a short-term or a long-term reduction in self-esteem.

The "hyperpersonal model" of behavior during computer-mediated communication, mentioned in the study by Gonzales and Hancock, is also one of the possible factors that can modulate the self-esteem of a Facebook user. This model stresses the advantages of computer-mediated communication over conventional face-to-face communication in terms of users being able to optimize self-presentation to others more effectively.28 In fact, it is suggested that when using an online platform, the subject has more time to select, emphasize, and present those aspects of his/her personality, character, and temperament that would be viewed more favorably by the receivers or, in this case, other Facebook users. This is in contrast to conventional face-to-face interaction where the subject does not have enough time and opportunity to present the positive features of himself selectively. Based on this model, we could assume that this selective self-presentation on a SNS and increased relationship formation would impact positively on self-evaluation and therefore self-esteem.

It is probable, however, that the overall impact of SNS on self-esteem is much more complex. Constant self-evaluation on an everyday basis, competition and comparing one's own achievements with those of other users, incorrectly perceiving physical/emotional/social characteristics of others, feeling of jealousy, and narcissistic behavior-these are all factors that may positively or negatively influence self-esteem. Unfortunately, despite several research efforts during the past decade, this issue still remains unresolved, and probably many years will pass before we comprehend the true nature of this relationship.

Online Social Network Addiction

Addiction to online social networking, as well as Internet addiction in general, are recent and insufficiently investigated phenomena, frequently discussed and sometimes disputed in the psychiatric literature.30-35 The addictive nature of SNS is supported primarily by the mental preoccupation of many chronic SNS users who as a result tend to neglect other aspects of their social functioning such as family and offline friends. In addition, according to our own observations, sudden cessation of online social networking (i.e., lack of Internet connection) may in some chronic users cause signs and symptoms that at least partially resemble the ones seen during drug/alcohol/nicotine abstinence syndrome.

Online social networking as a potential addiction disorder has so far been discussed in many publications.30,31,33,35-37 SNS addiction represents a relatively new issue in psychiatry research, and as with other potentially SNS-related disorders, many questions remain unanswered.

In 2012, Andreassen et al. developed the Facebook Addiction Scale, a scoring system initially based on a total of 18 items, testing features of addiction such as salience, mood modification, tolerance, withdrawal, conflict, and relapse.37 The authors applied the scale along with other questionnaires (such as Addictive Tendencies Scale, Online Sociability Scale, etc.) on a sample of 423 students. The test showed a relatively high reliability and proved to be applicable to the student population. The same year, regarding this study, Griffiths35 expressed concern that the term "Facebook addiction" may be obsolete due to a large variety of activities that can be done on Facebook besides conventional social networking (i.e., playing games). Nevertheless, any attempt to design a scoring system that would be able to quantify at least a certain aspect of social networking addiction is, in our opinion, an important addition to the present knowledge in this field.

Wolniczak et al.38 recently adapted The Internet Addiction Questionnaire in order to test Facebook dependence in the student population. The authors also tested the sleep quality of Facebook users using the Pittsburgh Sleep Quality Index. The results showed that Facebook dependence may be related to poor quality of sleep. To our knowledge, this is the first study to modify existing questionnaires for Internet addiction in order to test Facebook use.

Probably, the most important question is whether SNS addiction is actually a mental disorder, and whether it should be diagnosed and treated as such. The Tenth Revision of the International Classification of Diseases and Health Problems (ICD-10) defined several specific criteria for dependence syndrome such as a strong desire or sense of compulsion, difficulties in controlling consumption behavior, physiological withdrawal state after reduction or cessation, evidence of tolerance, and so on.39 A diagnosis should be made if three or more of the above-mentioned criteria are present (at a certain time point) during the previous year.

It is clear that many of these diagnostic criteria could be applied to a minor percentage of chronic Facebook users who, as a result of this prolonged computer use, have problems in normal everyday functioning. However, one must be very careful with this approach, since in the future it could be quite difficult to distinguish SNS addiction from Internet addiction, which is a much more general disorder (Internet addiction disorder, problematic Internet use, or compulsive Internet use). Furthermore, it should be noted that neither Internet nor SNS addiction have been included in the latest disease classification manuals such as Diagnostic and Statistical Manual of Mental Disorders (DSM-5). In addition, SNS and Internet-related mental problems are frequently seen together with other diagnosable mental illnesses, or, in other words, these problems are complicated by comorbidity.34 Therefore, it remains unclear whether potential SNS addiction is an independent illness, or merely a manifestation of other mental issues such as, for example, personality disorders.

All in all, it remains to be seen whether SNS addiction will ever be recognized as a separate mental disorder. It can be expected that in the future, this issue will be a focal point of many research studies, and that, in the years to come, it will become the subject of a wide debate among psychiatrists, psychologists, and other specialists. The final results and conclusions will have a substantial impact on the future organization of the mental health system, particularly considering that online social networking affects such a large proportion of the world population.

Future Prospects

It can be expected that future research regarding the potential effects of online social networking on mental health is going to be faced with numerous difficulties. First, so far, many authors investigating this issue have used a cross-sectional study approach in their methodology, followed by correlation analysis. The existence of a correlation does not necessarily equal causality. For example, Facebook and self-esteem may be related in terms of Facebook usage, causing lower self-esteem, but this may also mean that people with low self-esteem use Facebook more often. In other words, it is very difficult, and sometimes impossible, to conclude which variable is the cause and which is the effect. In the future, longitudinal designs would be much more helpful in determining the effects of SNS use on mental health. Ultimately, the data obtained from experimental studies would enable us to draw definite conclusions on this relationship.

It should be noted that most of the research done so far on social networking and mental health was done on a healthy population (i.e., high school students, university students, adolescents in general). When it is stated that, for example, "time spent on social networking is related to depression," the authors usually mean that this time correlates with physiological mood oscillations (measured with various psychological scales), rather than depression as a clinical entity. In fact, to our knowledge, no research of this sort has so far been conducted on psychiatric patients. Therefore, a possible connection between social networking and mental health issues can only be discussed in terms of normal physiological (psychophysiological) variations of psychic functions.

We should always have in mind that not all of the social networks are the same. The largest and most popular SNS, Facebook, is based on creating and updating personal profiles, where users can upload photos, videos, comments, statuses, and notes. Another popular SNS, Twitter, is based on a different concept: users post and read short text messages ("tweets") in which they express their thoughts and opinions. Most of the studies mentioned in this text have been focused on Facebook as the predominant SNS, and even in the studies where authors in the title state the term "social networking," in most cases, Facebook is the primary target of investigation. In fact, after searching the available scientific databases, we were unable to find a single study that was primarily focused on Twitter and its potential impact on mental health. In the future, it can be expected that Twitter will also become the subject of many research efforts.

Many studies simply do not test various potential confounding factors that may influence conventional correlation in terms of enhancing or reducing it. For example, it may well be possible that people with some personality disorders (which are quite frequent and often undiagnosed) spend much more time on online social networks compared to the general population because computer-mediated communication enables them to be socially more successful. These individuals, if included in a research study, will probably influence the results of self-esteem, depression, addiction, and other questionnaires. In other words, any future study on this topic, in order to meet quality standards, will need to have established precise inclusion and exclusion criteria in order to make the study sample as homogenous as possible. These criteria are often difficult to define and even more difficult to implement, so the other possible approach would be to use a large study sample. This would also have to be combined with additional statistical tests such as multivariate regression analysis.

Most of the research on social networking and mental health has so far been performed using conventional psychiatric questionnaires, such as the above-mentioned Rosenberg Self-Esteem Scale, the Beck Depression Inventory, and others. Today, it is not uncommon that for assessment of the same psychiatric sign/symptom, several different scales exist. For example, for quantification of depressive symptoms, the researcher may choose between scales such as the Beck Depression Inventory, the Centre for Epidemiological Studies-Depression Scale (CES-D), the Hamilton Rating Scale for Depression (HAM-D), the Zung Self-Rating Depression Scale, the Montgomery-Åsberg Depression Rating Scale (MADRS), and so on. Although these scales are established tools in psychology and psychiatry research, sometimes when designing a study, it is difficult to determine which scale has the best sensitivity for the given population/study sample. This may be especially the case when being used in the general population or in different age groups such as high school students, university students, and so on. In the future, there may be a need to design and implement novel, advanced scales that would be adjusted to evaluate potential mental problems in light of the rapid development of information technology, or at least to compare the existing ones in terms of establishing a set of recommendations for their application in these new conditions.

In conclusion, it is clear that during the past 10 years, online social networking has caused significant changes in the way people communicate and interact. It is unclear, however, whether some of these changes affect normal aspects of human behavior and cause psychiatric disorders. In the future, additional research will be needed to identify and describe the potential relationship between the use of SNS and various mental health issues.

Acknowledgments

The author is grateful to the Republic of Serbia, Ministry of Science and Education (Grants 175059 and 41027), as well as the Project 62013 of the DEGU Society, Belgrade, Serbia. The author also apologizes to all researchers in the fields of psychology, psychiatry, and social networking whose articles were not cited (unintentionally or due to the page limitations) in this work.

Author Disclosure Statement

No competing financial interests exist.

References

10. Blascovich J, Tomaka J. (1991) Measures of self-esteem. In: Robinson JP, Shaver PR, eds. Measures of personality and social psychological attitudes. San Diego, CA: Academic Press, pp. 115-155 [ Google Scholar]

11. Gerber GL. (2001) Women and men police officers: status, gender, and personality. Westport, CT: Greenwood Publishing Group [ Google Scholar]

29. Duval S, Wicklund RA. (1972) A theory of objective self-awareness. New York: Academic Press [ Google Scholar]

Articles from Cyberpsychology, Behavior and Social Networking are provided here courtesy of Mary Ann Liebert, Inc.

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Online Social Networking and Mental Health

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During the past decade, online social networking has caused profound changes in the way people communicate and interact. It is unclear, however, whether some of these changes may affect certain normal aspects of human behavior and cause psychiatric disorders. ...

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https://www.google.com/imgres?imgurl=https%3A%2F%2Fmedia.nature.com%2Flw767%2Fmagazine-assets%2Fd41586-020-01846-z%2Fd41586-020-01846-z_18100818.png&tbnid=VH_RpD2gaAzRdM&vet=1&imgrefurl=https%3A%2F%2Fwww.nature.com%2Farticles%2Fd41586-020-01846-z&docid=iPh0PqEIf44jQM&w=600&h=508&hl=en-us&source=sh%2Fx%2Fim%2Fm4%2F3

This is an example of quantitive data by providing the rate of fatal police shootings per 100 criminal homicides.

-Ayannah

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https://researchguides.uic.edu/c.php?g=1048457&p=7608559

This is an example of qualitative data because it gives descriptive data about police brutality in America and why it’s an issue.

-Ayannah

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This article goes into detail about the effects of parental divorce and what it does to a child both behaviorally and psychologically.

Qualitative data: Young children may react to divorce by becoming more aggressive and uncooperative or by withdrawing. Older children may feel deep sadness and loss.

Quantitative data: One out of every two marriages today ends in divorce and many divorcing families include children. This shows that this is not an uncommon occurrence.

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Children and Divorce

No. 1; Updated January 2017

One out of every two marriages today ends in divorce and many divorcing families include children. Parents who are getting a divorce are frequently worried about the effect the divorce will have on their children. During this difficult period, parents may be preoccupied with their own problems, but continue to be the most important people in their children's lives.

While parents may be devastated or relieved by the divorce, children are invariably frightened and confused by the threat to their security. Some parents feel so hurt or overwhelmed by the divorce that they may turn to the child for comfort or direction. This can add to the pressure and stress a child is experiencing. Divorce can be misinterpreted by children unless parents tell them what is happening, how they are involved and not involved, and what will happen to them.

Children often believe they have caused the conflict between their parents. Many children assume the responsibility for bringing their parents back together, causing them additional stress.

Vulnerability to both physical and mental illnesses can originate in the traumatic loss of one or both parents through divorce. With care and attention, however, a family's strengths can be mobilized during a divorce, and children can be helped to deal constructively with the resolution of parental conflict.

Talking to children about a divorce is difficult. The following tips can help both the child and parents with the challenge and stress of these conversations:

Do not keep it a secret or wait until the last minute.

Tell your child together with your spouse if possible.

Keep things simple and straight-forward and don't share more information than your child is asking for.

Tell them the divorce is not their fault.

Admit that this will be sad and upsetting for everyone.

Reassure your child that you both still love them and will always be their parents.

Do not discuss each other's faults or problems with the child.

Parents should be alert to signs of distress in their child or children. Young children may react to divorce by becoming more aggressive and uncooperative or by withdrawing. Older children may feel deep sadness and loss. Their schoolwork may suffer and behavior problems are common. As teenagers and adults, children of divorce can have trouble with their own relationships and experience problems with self-esteem.

Children will do best if they know that their mother and father will still be their parents and remain involved with them even though the marriage is ending and the parents won't live together. Long custody disputes or pressure on a child to "choose" sides can be particularly harmful for the youngster and can add to the damage of the divorce. Research shows that children do better when parents can minimize conflict and cooperate on behalf of the child.

In rare situations, a child may reject contact with one parent. This may happen for no apparent reason or with the encouragement of the other parent. This can be harmful and painful for the child and the rejected parent.

Parents' ongoing commitment to the child's well-being is vital. If a child shows signs of distress, the family doctor or pediatrician can refer the parents to a child and adolescent psychiatrist for evaluation and treatment. In addition, the child and adolescent psychiatrist can meet with the parents to help them learn how to make the strain of the divorce easier on the entire family. Psychotherapy for the children of a divorce, and the divorcing parents, can be helpful.

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One out of every two marriages today ends in divorce and many divorcing families include children.

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Twelve children aged 10-13 from two homes were interviewed using 4 lifeworld extensional dimensions: “lived body”, “live time”, and “lived human relations” for data analysis. - Layla Johnson

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Quantitative

A study in Galicia, Spain, found that parental separation significantly impacts, children’s socioeconomic status, psychological adjustment, social relations, self-concept, and academic achievement. Children from separated families are more likely to fall below the poverty, line, experience, anxiety, depression, hostility, and interpersonal alienation, and have lower self-concept and academic achievement. Additionally, they are more likely to be exposed to gender violence. The study highlights the importance of understanding the relationships among these variables, and their implications for interventions. - Layla Johnson

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Estimating the Epidemiology and Quantifying the Damages of Parental Separation in Children and Adolescents

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Parental separation is linked to multiple negative outcomes for children in all spheres of life. A field study was designed to estimate the epidemiology and to quantify the outcomes on the wellbeing of children from separated parents. Thus, data on socio-economic…

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https://neurosciencenews.com/ai-chatbot-creative-thinking-23920/ (Qualitative Data)

The article discuss how A.I. and humans think and process simple task and assignments differently, but also how A.I. can excel at doing task better than most humans.

https://www.zippia.com/advice/machine-learning-statistics/ (Quantitative Data)

While there are some risk with integrating the use of A.I. in our everyday lives, the article above provides satisfactory data that debunks the risk and show that A.I. can improve businesses efficiency and effectively carry important task.

-Matthew PT

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https://www.ipr.northwestern.edu/news/2023/how-has-covid-19-affected-children-and-adolescents.html#:~:text=He%20cited%20research%20by%20Stanford's,year%20of%20learning%20in%20reading. (Qualitative Data)

Presents the notion that the pandemic had lasting long-term effects on children’s social skills, personalities, and mental health due to not being in physical school for more than a year.

https://ourworldindata.org/children-not-in-school (Quantitative Data)

The article explains that children that go to school in their early development can set than many years behind in cognitive and social development all because of the impoverished nations that most of these children live in.

-Matthew PT

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Social inequality

-Quantitative data includes statistics on income distribution or education levels across different social groups.

Qualitative data is the interviews with individuals sharing their experiences with discrimination or poverty.

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Power and politics are at the heart of health. The way the world is shaped by those in power results in the distribution of money, power and resources at global, national and local levels. This distribution impacts the conditions, or social determinants of health, such as the cleanliness of our water and air, and whether we can afford to provide nutritious food for our families.
Unequal power structures have resulted in a system in which some people have the conditions to realise their right to health, whilst others do not.
In recent years, international institutions and many governments have pursued an approach that has directly undermined health and well-being. Instead of recognising how society impacts the health of people, this approach -commonly known as neoliberalism - focuses on individual responsibility. They have pushed forward policies such as privatising services and cutting government spending on things like health and education, whilst giving more power to private business by slashing regulation and enabling tax dodging. This has driven us headlong into vast inequality, causing poor health, poverty and insecurity in society today.

Tax dodging by big corporations means they get rich whilst taking money from public services. Bad trade agreements prioritise big businesses over people and the environment. And the so-called 'war on drugs' targets the very poorest, with devastating effects - black people living in poverty are far more likely to face prosecution for using drugs than their wealthier, white peers. All of these things hurt the poorest the most, regardless of where they live.

Social injustice is killing people on a grand scale

- WHO Commission on the Social Determinants of Health.

Global inequality

But these unfair structures are seen both between individuals and communities in all countries. They also benefit rich powerful countries at the expense of poor ones. For example countries in sub-Saharan Africa receive over $160 billion in resources such as loans, remittances and aid each year. Yet over $200 billion is extracted from the continent through actions like tax avoidance, debt payments and resource extraction, meaning countries sub-Saharan Africa are net creditors to the rest of the world of over $40 billion each year. This seriously limits the ability of the world's poorest countries to provide services such as healthcare to their citizens.

It is common for debates about health to overlook these power imbalances, as they are a threat to the global status quo of power and resources. Instead, people often focus on technical solutions or aid to address the symptoms of the problem, ignoring the root causes.

At Health Poverty Action we believe that improving health means directly addressing the root causes of the problem. This requires ensuring people have the right environments to be healthy, which therefore requires a fundamental change in the global distribution of power and resources.

Find out more in our policy reports on the root causes of poor health.

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Power & politics | Health Poverty Action

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Power and politics have a crucial impact on health around the world

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Cultural norms

Quantitative examples are survey results showing the percentage of people who adhere to certain traditions.

Qualitative data comes from ethnographic studies with detailed descriptions of cultural practices in a community.

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by Winston Sieck updated

In some countries, women are expected to cover themselves from head to toe. In others, bikini bottoms are plenty sufficient. In some places, baskets are carried in the arms. In others, they are placed on the head.

Cultural norms are the standards we live by. They are the shared expectations and rules that guide behavior of people within social groups. Cultural norms are learned and reinforced from parents, friends, teachers and others while growing up in a society.

Norms often differ across cultures, contributing to cross-cultural misunderstandings.

Many studies have documented these differences. Far more casual observers have commented on them. Recently, Michele Gelfand and a large team of cross-cultural psychologists stepped back from the cataloging process and asked a bigger question.

They wanted to know how much cultural norms really matter. Do norms matter more in some places than others?

Some societies may care quite a bit about their cultural norms, insisting on strong conformity to them across the board. They reflect "cultural tightness." Others tolerate a lot of deviance from the norms. These are "culturally loose" societies.

Gelfand and colleagues theorized that tightness and looseness are reflected at different levels within a culture that mutually support one another. They published their research in a Science article, " Differences between tight and loose cultures." In it, Gelfand's team describes evidence for each of the following four levels:

1. Ecological & Historical Threats. Hostile neighbors, disease, and dense populations increase the need for coordinated and disciplined action from the population. More factors like these tighten the cultural norms. As the threats diminish, cultures loosen up.

2. Socio-Political Institutions. Culturally tight nations tend to have more autocratic governments, restricted media, stronger suppression of dissent, and more severe punishments for crime.

3. Everyday Social Situations. All kinds of interactions with fellow members of the culture are more formal in nations with tight cultural norms. These include situations at home, the workplace, school, places of worship, parks, and others. Loose cultures provide more room for individual discretion in such situations. A wider range of behavior is counted "appropriate."

4. Psychological Adaptations. People's minds become attuned to the different requirements of living in places with tight or loose cultural norms. Individual psychology then further supports the level of cultural tightness or looseness. People living in tight cultures become more focused on avoiding mistakes. They are more cautious in their own behavior, and more closely monitor themselves and others for norm violations.

Culturally tight or loose societies appear completely dysfunctional when viewed from the other perspective. The cultural tightness-looseness framework can help you to take a step back, and see things a bit differently. It can help you take a cross-cultural perspective. When you see or read about events around the world, think about whether the players involved are from tight or loose cultures. Consider how they got that way, and all the factors involved in maintaining the system as it is.

Without understanding, the differences between countries with tight and loose cultural norms provide much fodder for conflict. Going back to that first level, falling into conflict can increase tightness in cultural norms across the board.

Image Credit: Gigi Ibrahim

References

Filed Under: Tagged With: Culture & Communication, general, values Popular

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Cultural Norms: Do they Matter? - Global Cognition

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by Winston Sieck updated In some countries, women are expected to cover themselves from head to toe. In others, bikini bottoms are plenty sufficient. In some places, baskets are carried in the arms. In others, they are placed on the head. Cultural norms are the standards we live by.

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This article is an example of both Qualitative and Quantitative data. It speaks on how feminism has changed over the years and how it affects the different races and groups of women.

-Posted by Sanique

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The feminist movement has changed drastically. Here’s what the movement looks like today

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For Women’s History Month, ABC News spoke to feminists across the generations to discuss what defines modern feminism.

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This is an article which uses quantitative data to go into detail about the link between race and wrongful convictions.

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Race and Wrongful Conviction

Nearly 60% of the people that the Innocence Project has helped to free or exonerate since 1992 are Black.

This demographic rate is consistent with research by the National Registry of Exonerations showing that more than half of the 3,300 people who were exonerated between 1989 and 2022 are Black, despite the fact that Black people account for just 13.6% of the U.S. population. Indeed, a 2022 report from the registry found that innocent Black people were seven times more likely to be wrongly convicted of murder than innocent white people. The racial disproportionality in wrongful conviction cases reflects persistent biases in the criminal legal system.

Police investigatory practices such as deception in interrogations, threats to witnesses and the accused, and tainted witness identification are drivers of racial disparities in wrongful convictions. The cases of Black people exonerated from murder convictions are 50% more likely to involve police misconduct than those of white people exonerated from murder convictions. Intentionally suggestive witness identifications occur twice as frequently in the cases of Black and Latinx exonerees as they do in the cases of white exonerees.

Even without intentional misconduct tainting an identification, a cross-racial eyewitness identification is particularly unreliable. People are more likely to misidentify a person of a different race, and white people are particularly bad at recognizing people who are not white. Mistaken cross-racial identifications play a large role in sexual assault cases where Black men convicted of raping white women are six times more likely to be innocent than white men convicted of raping white women.

Pretrial decisions by courts and prosecutors also greatly impact the likelihood of wrongful convictions for Black and brown people. Black and Latinx people accused of crimes are more likely to be detained pretrial, putting their jobs, housing, and families at risk. When prosecutors offer a plea bargain that would allow a person immediate release from pretrial detention, there is a strong incentive for an innocent person to agree to plead guilty and accept responsibility for a crime they didn't commit. Nearly 25% of those exonerated since 1989 pled guilty, and nearly 75% of this number are Black and brown people.

As a case comes to trial, race-based exclusion can shape the composition of the jury, which affects the likelihood that an innocent person will be convicted. All-white or nearly all-white juries are common in criminal cases around the country. The lack of jury diversity results from courts using unrepresentative lists to summon potential jurors, barriers to juror service that fall disproportionately on people of color, legal standards that allow for the exclusion of jurors based on viewpoints correlated to race, and prosecutors intentionally striking people of color from juries. All-white or nearly all white juries make wrongful convictions more likely because, compared to diverse juries, they spend less time deliberating, are less skilled at accurately assessing the reliability of evidence, and are more likely to apply racial stereotypes in decision-making.

After a conviction, wrongfully convicted Black people can fight for years or decades before being exonerated. The National Registry of Exonerations has that it takes Black people an average of three years longer than white people to be exonerated in murder cases. Black sexual assault exonerees spent an average of four years longer before being exonerated. Some of this delay is a result of official misconduct that is prevalent in the cases of Black exonerees. In many cases, evidence that should have been provided to the defense before trial remains hidden for decades.

To address the disproportionate and unjust treatment that leads to the wrongful conviction of Black and brown people, the Innocence Project is committed to strengthening police and prosecutorial accountability; ensuring that interrogations are recorded and improving lineup protocols; requiring prosecutors to timely provide crucial evidence to defense counsel and regulate jailhouse informants; sharpening forensic science practices; and more.

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Innocence Project: Race and Wrongful Conviction

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The racial disproportionality in wrongful conviction cases reflects persistent biases in the criminal legal system.

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This article provides quantitative data on how feminism affects the different races of women and groups (how it might exclude).

-Sanique

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This article traces the history of U.S. mainstream feminist thought from an essentialist notion of womanhood based on the normative model of middle-class white women's experiences, to a recognition that women are, in fact, quite diverse and see themselves differently. It begins with the question of the social construction of gender and the mainstream feminist assumption that 'woman' means middle class white woman. The challenge to this assumption is then posed by women of color, poor women, immigrants, lesbians and women in the 'third world." Section Three presents the various forms of inclusion of black women within mainstream feminist frameworks. Following that is a discussion on the construction of whiteness, the privileges that race afford white women, and feminist strategies to overcome racism within mainstream feminism. Section Five reviews the struggles of Latina and Asian American women, the specific questions of identity they confront, and how these relate to mainstream feminism. Section Six discusses the challenges posed to U.S. mainstream feminism by third world feminists.

Feminists in the U.S. have worked arduously to address the question of difference among women, together with what unites women in common contexts of struggle. The focus on difference, as well as identity, however, often overlooks the actual lives of many women of color who struggle not so much with how to disabuse themselves of a certain identity, but with how to establish one in the first place. Concentrating on identity and difference, either by working to obliterate or represent it, also tends to the neglect of power relations that establish, hold apart, and bring together such differences in the first place.

This article further explores how sexism and racism are structural problems endemic to American culture. As such, they need to be addressed systematically, along with class and all other systems of domination. The structural aspect is evident in the ease by which biological racism morphs into cultural racism, spawning condescending and racist attitudes toward third world women, and a blindness of "first world" complicity in third world oppressions. As Audre Lorde has made clear, "the master's tools will never dismantle the master's house." The conclusion explores how feminists unite to struggle against systems of domination and exploitation, and work to give up privileges bequeathed by these systems, admittedly an uncomfortable proposition for those benefiting from power, to dismantle the "master's house" and the multitude of oppressions that it sustains.

Table of Contents

1. Introduction

2. Are All Women the Same?

3. Mainstream Feminism and African American Women in the United States

4. White Privilege and the Question of Racism in U.S. Mainstream Feminism

5. Chicana/Latina and Asian American Women and U.S. Mainstream Feminism

6. Third World Feminisms and Mainstream Feminism in the U.S.

7. Conclusion: "There is No Hierarchy of Oppressions"

8. References and Further Reading

1. Introduction

The question of difference has been central to U.S. feminism since the inception of a women's movement in the United States. When Sojourner Truth, a black woman, walked into the predominately white Women's Convention in Akron, Ohio in 1851, three years after the first Women's Rights Convention in Seneca Falls, New York, jaws dropped. Not a sound could be heard. Truth was an imposing woman. She stood almost 6 feet tall and bore the scars of brutal beatings, the sale of her children, and the loss of her own parents while she was sold off into slavery. Surrounded by affluent, educated white women and their gentlemen supporters, her presence at first stirred fear, but eventually gave rise to awe. The white women at the conference didn't want to muddy their struggle and demands for women's rights with the uncomfortable subject of race and the rights of colored folk, despite their debt to Fredrick Douglass' efforts to keep the controversial issue of women's suffrage central at the first Convention in Seneca Falls. Yet, when Truth rose to enter into the conversation, her words, collected under the title "Ain't I a Woman," not only drew strong admiration, but presaged what would come to be the fundamental question of Western feminism: What exactly is a woman?

In the speech titled "Ain't I a Woman," Truth reveals the contradictions inherent to the use and meaning of the term woman, and exposes the political, economic, and cultural assumptions underlying its use. Taking the platform at the Convention in Ohio, she spoke out against the declarations of several men. They believed that women were to refrain from strenuous work, both physical and mental, so to better fulfill their "womanly nature." But Truth knew nothing of this so-called nature that they espoused and engendered. What she knew was toil and work as arduous as any man could endure.

That man over there says that women need to be helped into carriages, and lifted over ditches, and to have the best place everywhere. Nobody ever helps me into carriages, or over mud-puddles, or gives me any best place! And ain't I a woman? Look at me! Look at my arm! I have plowed, and planted, and have gathered into barns, and no man could head me! And ain't I a woman? I could work as much, and eat as much as man - when I could get it - and bear the lash as well! And ain't I a woman? I have borne thirteen children and seen most all sold off to slavery, and when I cried out with a mother's grief, none but Jesus heard me! And ain't I a woman? (Truth, 2009).

Almost one hundred years later, Truth's questioning can be heard in Simone de Beauvoir's challenge to claims that the meaning of womanhood is self-evident. In her groundbreaking and canonical work The Second Sex (1949, 1st English trans., 1953), Beauvoir set the course for the subsequent study of the "woman question" in the West by putting the issue of gender into focus. Responding to male discontentment that French women were losing their femininity and were not as "womanly" as they believed Russian women to be, Beauvoir wondered if one is born a woman or whether, in fact, one must become a woman through various socialization and indoctrination processes. This critical perspective led her to challenge the usefulness of the category of woman altogether and to ask whether it was, in fact, helpful as a term representing all the experiences of the so-called members of the "second sex." Perhaps nothing better illustrates Beauvoir's concerns regarding the legitimacy and effectiveness of the category of "woman" than the development of white, U.S. mainstream feminist thought in relation to challenges posed by women of color, the poor, lesbians, immigrants, and women from "third world" nations. In making their voices heard, these marginalized women expanded feminist thinking by showing that ideologies of womanhood had just as much to do with race, class, and sexuality, as they had to do with sex.

2. Are All Women the Same?

Feminists in the U.S. have set out to identify, expose, and subvert the longstanding gender stereotypes that have been used to dominate and subordinate women. Central to any theory of feminism, then, is how terms like "woman," "female," and "feminine" are construed or misconstrued. The pioneer women in the U.S. suffragist movement spoke of and fought for women's rights, using the term woman to signify all women. What they failed to recognize was that their notion of womanhood was modeled on the experiences and problems of a small percentage of females who, like them, were almost exclusively white, middle-class, and relatively well-educated. However, the assumption that middle-class white women's experiences represented all women's experiences was not only made by the early Suffragists, but continued to shape the ideal of womanhood well into the second wave of the American feminist movement and beyond.

In The Problem That Has No Name, a book that helped usher in the second wave of feminism in the U.S., Betty Friedan exposed the hidden frustrations of women who had bought into the "mystique of feminine fulfillment" (2001:24). Trading in their career ambitions for the promised bliss of marriage, motherhood, and domesticity, many women instead found themselves trapped and isolated behind white picket fences in what Friedan described as the "housewife's syndrome." But, what Friedan also failed to recognize was that this syndrome affected only a certain minority of women- namely, those who were white, middle-class, and often highly educated, like herself. She did not realize that the binary and complimentary gender divisions she assumed, woman as breadmaker and man as breadwinner, were built upon a racialized patriarchy that excluded women of color, the poor, and immigrants from this "mystique of femininity." It was these women who would be called upon to leave their children and homes to care for the children and homes of the white women who had successfully "liberated" themselves from domesticity to voluntarily enter into the work force.

Discounting the lives of women of color by assuming that the experiences of white women were representative of the lives of all women, Friedan imagines a unity among women's experiences that simply does not exist. According to bell hooks, this ideal of gender solidarity is built upon an assumption of sameness that is supported by the idea that there exists a common oppression of patriarchy around which women must rally. "The idea of 'common oppression' was a false and corrupt platform disguising and mystifying the true nature of women's varied and complex social reality" (1984:44). This complexity is especially disclosed in the lives of women of color who must contend with multiple and overlapping forms of oppressions-including oppression by white women, who fail to acknowledge the different struggles confronting women who are not like them.

Mainstream feminist thought continues to grapple with the interrelations between gender and race, as well as class, colonialism, imperialism, and issues of sexual orientation in what might arguably be called a third wave of feminism in the U.S.. More importantly, the critiques of women who have suffered the most from sexist societies - women of color, the poor, third world women - are now at the forefront of a contemporary, progressive feminist politics. Thus, to understand the current contours of mainstream feminist thought in the U.S. and the question of race, one must look at how feminist theory and practice have addressed differences among women, and the specific ways that differences within women's lives have shaped their relationships to mainstream U.S. feminism.

3. Mainstream Feminism and African American Women in the United States

Feminist theorists have addressed the relationship of race and feminism in at least two different ways. One approach is to view race as integral to gender and explore the ways in which gender identity is constructed in relation to race, and how racial identity is equally constructed in relation to gender. The other follows a method whereby the voices of women of color are added to the conventional curriculum in a sort of separate but equal manner. This latter approach has been called the "additive" approach. Because it simply adds the voices of those historically excluded from the mainstream feminist canon, but does not examine the constitution of these voices within the contexts of power that have given rise to them, it carries the risk of essentializing gender and race, or assuming these categories to be fixed and timeless.

With respect to the former, Jacquelyn Dowd Hal highlights the interconnections of race and gender in her discussion of lynching. Hal shows that lynching was not only used to enforce labor contracts, maintain racial etiquette and the socio-economic status quo, but was also effective in re-inscribing gender roles among whites. White men cast themselves as protectors of white women, sheltering them from the presumed threat of black male sexual prowess, while simultaneously securing white women's adherence to ideals of chastity and femininity (Brooks-Higginbootham, 1989: 132). These ideals were further re-inscribed by white women in their perceptions and accusations regarding black male sexuality. Ida B. Wells had made the same observation, arguing that white men maintained their ownership over white women's bodies by using them as the terrain for lynching black males (Carby, 1986: 309). It comes as little surprise, then, that by joining anti-lynching campaigns white women were not only defending black males, but simultaneously reacting against Southern chivalry and their roles as fragile sex objects (Brooks-Higginbootham, 1989: 133).

The more popular approach to the question of race and feminism, however, seems to have been the "additive" approach. In "Toward a Black Feminist Criticism" (1977), Barbara Smith embarks on a journey that she states no man or woman has gone on before: documenting black women's experience and culture while providing black women with a resource for reading about their lives. "It is galling that ostensible feminists and acknowledged lesbians have been so blinded to the implications of any womanhood that is not white womanhood and that they have yet to struggle with the deep racism in themselves that is at the source of this blindness" (Carby, 1992: 158). Smith believes that it is necessary both to retrieve the writings of black women and to place them before black feminist literary critics who are able to interpret these writers experiences. She argues that black women writers share a singular tradition of styles, themes and aesthetics that are rooted in a shared culture of oppression. Furthermore, she believes that these themes are expressed in a uniquely black woman's language that is accessible only to black feminist literary critics who simply need turn inwards, or towards their own lived experiences, in order to decipher the messages told by black women writers (Carby, 1992:164). With her novel idea of an "identity politics," Smith went on to form the black lesbian feminist Combahee River Collective in Boston.

"The Combahee River Collective Statement" (1986), along with This Bridge Called My Back, Writings by Radical Women of Color,published two years earlier, gave voice to women of color and served as the primary texts from which white women and women of color would draw in discussions of race and gender. In the Combahee Statement, the Collective explained their need to organize and come together as black women into a movement for black women. "We realize that the only people who care enough about us to work consistently for our liberation is us. Our politics evolve from a healthy love for ourselves, our sisters, and our community, which allows us to continue our struggle and our work" (1995: 21-22). Black-only movements worked to raise the self-esteem of black women and address specific problems confronting all black people. Angela Davis also describes how, despite the sexist and heterosexist elements of the Black Nationalist Movement, it gave her a framework within which to understand herself as beautiful and valuable. In addition, Black Nationalism also served to counter racist images of African-Americans by providing positive images of Africa. "I was able to construct a psychological space within which I could 'feel good about myself.' I could celebrate my body (especially my nappy hair, which I always attacked with a hot comb in ritualistic seclusion), my musical proclivities and my suppressed speech patterns, among other things...This distanced me from the white people around me while simultaneously rendering controllable the distance I had always felt from them" (1992:319).

Patricia Hill Collins invokes the notion of a shared black women's language and highlights a common tradition that reaches back to the idea of an "African consciousness." However, she cautions against carving out a uniquely black female voice, or category of experience, for fear of sliding into an essentialist perspective which may, ultimately, be counterproductive. She recognizes that identifying a black feminist thought problematically assumes that "being Black and/or female generates certain experiences that automatically determine the variants of a Black and/or feminist consciousness" (1991:21). Still, Collins maintains that black women have certain perspectives that arise out of a shared experience, along with a different relation to knowledge production that give rise to a uniquely "black feminist standpoint" (1991:21-22).

Collins draws on the mainstream feminist strategy of "standpoint theory" that Nancy Hartsock helped develop out of Karl Marx's insight that the material conditions of existence structure one's lived experiences,. A standpoint theory argues that the place from which one stands influences the perspective or view that one has of the world; and, further, that those who are most oppressed are able to provide a broader and clearer perspective on the whole of society and societal relations (Hartsock, 1999). Collins believes that any black feminist standpoint must take into account white domination, the concomitant struggle for self-definition, and the Afrocentric worldview that helps blacks cope with racial domination. This Afrocentricism, Collins claims, existed prior to,and is independent of, racial oppression. Moreover, it has given rise to traditions of storytelling and narrative that value concrete, lived experience, as well as black women's community and sisterhood (1991:206, 212). Collins' version of standpoint feminism, therefore, focuses on concrete lived experiences that have their roots in African oral traditions, black families, churches, and other black organizations.

But even the idea of this mitigated account of an essential black female identity does not sit well with many black women. For example, Hazel Carby sees the idea of black feminist criticism, as well as any notion of a specifically black feminist consciousness, as a problem and not a solution. She traces this problem to the processes whereby one finds academic legitimation by aiming to fit into certain allotted slots that are open for discussions of racial and gender identity within mainstream curricula. Carby advocates the need to examine racism and sexism not as trans-historical and essentialist categories, but as historical practices which are enmeshed with evolving sets of social, political, and economic practices that function to maintain power in a given context and society (1989:18). Any emphasis on the elaboration of standpoint theory, Carby claims, sanctions the segregation and ghettoization of race and gender, while simultaneously positing white women as a normative standard (1992:193 ).

Moreover, Carby believes that this supplemental approach, which consists simply in adding the experiences and writings of women of color to the established mainstream feminist canon, will not solve the problems of "exclusion" from mainstream feminism, but will instead further reify differences. Joan Scott echoes these remarks and cautions women against relying on an uncritical deployment of experience to tell their stories. By assuming experience to be self-evident and transparent, one naturalizes difference and leaves unexamined the constitutive mechanisms according to which people's experiences have been historically constructed by relational webs of power and multiple oppressions (1991: 25-26). These mechanisms are structural and institutional. They are therefore more difficult to identify and eradicate. To adequately address the root causes of racism in the feminist movement, women must therefore acknowledge that any attempt to universalize their experiences colludes, not only with ideologies of white womanhood, but also with the dominant and privileged white male norms. The prominence given to white women's experience, Carby points out, is no accident. "White women are made visible because they are the women that white men see" (1986: 302). Taking into account the historical and political contexts that define gender reveals the racial constructions that structure both the lives of whites and people of color.

Many black women, especially those excluded from the earlier Suffragist movement, went even further and drew an explicit link between imperialism, racism, and patriarchy. This link was cemented at the 1893 World's Columbian Exposition in Chicago, where a group of black women who had thought they were there to represent the lives of American women, were instead made part of exhibits featuring "exotic" peoples, which further fed into racist stereotypes and fears (Carby, 1986). Subsequently, these women came to recognize the need to form their own national organizations. In 1896, a number of black women's groups merged into the National Association of Colored Women (NACW), headed by Josephine Ruffin and Mary Church Terrell. Its members included Harriet Tubman, Frances E.W. Harper, and Ida Bell Wells-Barnett. Harper and Anna J Cooper, the fourth African American woman to earn a Doctorate in the U.S., saw an inseparable link between imperialism, domestic racial oppression, and unrestrained patriarchal power. Cooper writes in A Voice from the South: By A Woman from the South (1892):

"Whence came this apotheosis of greed and cruelty? Whence this sneaking admiration we all have for bullies and prizefighters? Whence the self-congratulation of 'dominant' races, as if 'dominant' meant 'righteous' and carried with it a title to inherit the earth? Whence the scorn of so-called weak or unwarlike races and individuals, and the very comfortable assurance that it is their manifest destiny to be wiped out as vermin before the advancing civilization?" (Carby, 1986:305).

Cooper's observations came 40 years after Arthur de Gobineau declared in The Inequality of Races, that, indeed, Africans were "incapable of civilization" because they did not have the drive or ambition to conquer their neighbors, but rather lived "side by side in complete independence of each other" (Bernasconi, 2000:47). It was this conquering drive that Gobineau argued marked European civilization as advanced in contrast to the backwardness of Africans, who practiced living in harmonious co-existence with their neighbors.

In recognition of the advantages that race has conferred upon white women, many feminists have embarked upon analyses of race and gender that moves towards an acknowledgment of white privilege and racial injustice. Feminists have also worked to develop strategies for addressing white racism and identifying power differentials between women, between men, and among white women and men of color.

4. White Privilege and the Question of Racism in U.S. Mainstream Feminism

In 1988, inspired by the model of how men gain advantage from women's disadvantage, Peggy McIntosh began to document some of the ways in which white women have benefited from racism. Having observed how men were taught not to recognize their male privilege, McIntosh explored some of the unconscious avenues that allow white women not to recognize their "unearned skin privilege" (2008:63). "[W]hites are taught to think of their lives as morally neutral, normative, and average, and also ideal, so that when we work to benefit others, this work is seen as work that will allow 'them' to be more like 'us'" (2008:63). Positioning whites as the norm is seen by Anna Stubblefield as pivotal to securing the superiority of whites. "The ideology of white supremacy is that whiteness sets the standard-whiteness is normative-such that anything that is symbolic of or associated with blackness is therefore deviant" (2005:74).

McIntosh describes how she was taught to view racism as prejudice or bigotry, and to subscribe discriminatory acts of cruelty to isolated individuals, rather than to acknowledge "invisible systems conferring racial domination on my group from birth" (2008:68). She lists the unearned advantages that come from being a member of the dominant group, such as the comfort that comes from being in situations that reflect the worldview, values, and ideals of whites. White privilege ranges from the confidence white parents have that their children will receive educational materials highlighting the accomplishments and contributions of their race, to not attributing acts of injustice to racial prejudices, and not having to stand as a representative for one's particular racial group. Marilyn Frye further discusses the privilege that whites have to define or determine how others will see them. More specifically, she contrasts the images and ideals that whites have of themselves with the ways in which they are viewed by men and women of color to underscore the disparity in perceptions (2001:85). Because whites are taught that they are moral, honest, and fair, they believe that they alone are capable of and responsible for teaching others about what is right and wrong. This confidence is built upon a body of established Western principles, codes, and rules that presume to guarantee the correctness of their moral judgments. However, these self-descriptions of the dominant racial group are not shared by the majority of people of color who view many whites as behaving arbitrarily, or in a self-serving, violent, and often oppressive ways.

In "The Whiteness Question" (2005), Linda Alcoff argues that the key to overcoming racism lies in a confrontation with the "psychic processes of identity formation[.]" Tracing the origins of whiteness to domination and exploitation, Alcoff asserts that "whiteness" is inseparable from the subjection, denigration, objectification, and repudiation of those who are perceived as non-white. "The very genealogy of whiteness was entwined from the beginning with a racial hierarchy, which can be found in every major cultural narrative from Christopher Columbus to Manifest Destiny to the Space Race and the Computer Revolution" (2005). Before the concept of race originated in the 16 th century, various populations of people identified and structured their communities in varieties of ways that did not include reference to skin color. The origins of the category of race are, indeed, the origins of European expansion and oppression against Africans, Asians, indigenous peoples in the Americas and Australia, and even Muslims. According to G.W.F. Hegel, it is only Europeans, or, more precisely, Christians who are able to attain the highest level of reason and spirituality by distancing themselves from the "absolute" through rationality. Africans are not able to actualize these higher mental and spiritual faculties because they fetishize the absolute by objectifying it in relics that they then toss away when their fetish fails to come to their aid. Muslims too, while successful at raising God above the level of the sensuous, are nevertheless unable to bring God back down to earth and unite the universal with the concrete, and therefore are unable to attain self-conscious reason (Bernasconi, 2000).

Alcoff, therefore, concludes that white collective self-esteem and identity are rooted in forms of white supremacy. Thus, to break free from racist ideology may not be such an easy task for whites, as it threatens the very foundations of their pride and self-love. This threat arises from the acknowledgement that historical achievements, and the legacy of cultural resources from which a white identity is drawn, are steeped in practices of racial oppression and domination. Consequently, relinquishing racism means not only giving up the actual privileges and benefits that are associated with being white, but may involve shunning one's ties to a cultural history upon which white personal esteem and sense of self are grounded. Feelings of hysteria, shame, and anxiety often accompany this break. Yet, belonging to a history is crucial to one's esteem and identity. Alcoff, therefore, suggests a form of "white double consciousness" that moves from a recognition of practices of domination, exploitation, and discrimination to "a newly awakened memory of the many white traitors to white privilege who have struggled to contribute to the building of an inclusive human community. The Michelangelos stand beside the Christopher Columbuses, and Michael Moores next to the Pat Buchanans" (2005).

The interrelationship between white identity and white supremacy has lead some anti-racist whites, most notably Noel Ignatiev, to go further and to call for the overall abolition of the white race: "Treason to whiteness is loyalty to humanity" (1997). Marilyn Frye similarly advocates a disassociation from "whiteness" by calling for whites to opt out of the club she calls "whiteliness" (2001: 85). The very conditions for disclaiming whiteness, a disclaiming of identity that some women of color point out is possible only for whites, rests in the understanding that race is something socially constructed. Frye explains that being white "is like being a member of a political party, or a club, or a fraternity-or being a Methodist or a Mormon" (2001:85).

The possibility of relinquishing "whiteliness," therefore, involves a recognition of its contingency, and depends upon the repudiation of practices that arise from enacting, embodying and animating whiteness. Transforming consciousness is one step toward eliminating whiteliness. However, Frye and McIntosh are clearly aware that reflection and reorientation address only a fraction of the problems associated with race, since most of these are stubbornly structural and institutional. Still, Linda Gordon fears that a failure to begin addressing these difficult problems merely contributes towards legitimating more of the same-whites talking only about themselves (1991).

Sarita Srivastava is similarly unhappy with the direction that discussions of race have taken insofar as they tend toward white self-examination and constructions of whiteness. When analysis of race and racism occurs in feminist organizations, the emphasis, she finds, often falls on white guilt rather than organizational change. This results in self-centered strategies by whites to correct their moral self-image, an image that sustains inequalities, and, Srivastava argues, is rooted in the very foundations of feminism, imperialism, and nationalism that are the target of change.(2005: 36). Rather than work directly to alter the order of racial oppression, white women instead strive to empathize with the victims. Empathy serves to underscore white women's "goodness," and transforms the essentially socio-political nature of the problem to a more personal one. This practice further reinforces decades of racist and colonialist practices by validating white women's moral authority and their belief that they have somehow been entrusted with the responsibility to educate and liberate those less civilized (2005: 44). Thus, Srivastava argues that white women fail to genuinely confront their own racism by focusing on their guilt and, in doing so, maintain power inequities. She quotes a woman of color's frustration over white women's refusal to look at their racism during political discussions on the topic of race. "The indignant response, anger, the rage that turns to tears, the foot stomping, temper tantrum, which are very typical responses [to being called racist]. Every single organization that I have been in, every single one. So I realized that it wasn't about me...after awhile [laughter]" (2005: 42-43).

Alcoff further shows how white feminists distance themselves from a serious critique of racism by focusing on behavior modification, rather than challenging oppressive institutional structures and calling for wealth redistribution. In her analysis of Judith Katz's White Awareness: Handbook for Anti-Racism Training (Katz 1978), Alcoff describes Katz's depiction of how she came to terms with the depth of her own racism as a painful, demoralizing process that threatened her self-trust. While Katz warns against wallowing in white guilt, she nonetheless links anti-racism to psychological liberation while, at the same time, distancing herself from the workings and mechanisms of racist practices that are endemic to the culture. The focus on difference and overcoming of difference, either by obliterating or representing it, tends to neglect the power relations that establish, hold apart, and bring together such differences in the first place. Concentrating on identity and difference also overlooks the actual lives of many women of color who struggle, not so much with how to disabuse themselves of a certain identity, but, to the contrary, with how to establish an identity in the first place.

5. Chicana/Latina and Asian American Women and U.S. Mainstream Feminism

Struggling to negotiate and come to terms with an identity, many women of color are not as eager as white women to give up their racial or ethnic distinctiveness. "To be oppressed," Norma Alarcon explains, "means to be disenabled not only from grasping an 'identity', but also from reclaiming it" (1995:364). Moreover, specific histories of oppressions have positioned women differently with regard to gender roles and the family. Cherrie Moraga describes how Latina women's relationships to ideals of gender and motherhood have been uniquely shaped by colonization. Accompanying European expansion and colonization, was the concomitant threat of genocide. The fear of extinction strengthened the commitment to traditional family ideals and roles, such as encouraging women to be pregnant and assuming males at the head of the household. "At all costs, la familia must be preserved...We believe the more severely we protect the sex roles with the family, the stronger we will be as a unity in opposition to the anglo threat" (1995:181). Consequently, Moraga explains, Latina feminists' relation to gender roles and the structure of the family confront a very particular kind of resistance. While mainstream feminists are challenging traditional sex roles of men and women, some Latina feminists, due to their certain histories of colonization, seek to preserve these roles. Thus, Latina women's concerns are often foreign to, and often in direct opposition to, mainstream white feminists who seek to abolish or overcome conventional forms of gender identity, especially within the family.

U.S. immigration policies and discriminatory practices against Asian Americans have also sometimes lead to the embracing of gender ideals among Asian American women that are in opposition to the ideals of many white feminists in the U.S.. Ester Ngan-Ling Chow shows how racism, colonialism, and imperialism have worked to position Asian American women differently toward Asian American men, feminism, and Westernization. Addressing the apparent lack of feminist consciousness and activism in Asian American women, she attributes this deficit to ethnic pride and solidarity with Asian American men to end racial discrimination against Asians in the U.S.. Asian American men, for example, often view Asian American women's engagement with mainstream U.S. feminism as a threat to the Asian American community. Chow also points to specific Asiatic values of obedience, filial duty, loyalty, fatalism, and self-control that encourage forms of submissiveness among Asian American women that are incompatible with American values of individualism and self-assertiveness. The force of traditional Asian values contributes to the particularity of Asian American women's struggles, and work to distance their struggle from the concerns of the mainstream, white feminist movement. These differences, among others, are why Chow states: "The development of feminist consciousness for Asian American women cannot be judged or understood through the experience of White women" (1991:266).

Yen Le Espiritu further discusses the complexities surrounding the intersections of race, class, and gender confronting Asian American women. Regrettably, some Asian American women find themselves victims of the discrimination faced by Asian American men. Among other things, Espiritu writes, racial ideology defines Asian American men as feminine and weak-a rendering that incidentally works to confirm the notion that manhood is white. Frustrated also by the higher value placed on Asian American women's employability, some Asian American men try to assert their power by physically abusing the women and children in their lives. Breathing humor into these problems of physical abuse, Espiritu draws upon a joke that gets a laugh from both men and women. "When we get on the plane to go back to Laos, the first thing we will do is beat up the women!'" (Espiritu, 1997: 136). Despite the discriminations Asian American women endure within their community, they too often find it difficult to juggle between the desire to expose male privilege, and the desire to unite with men in their shared struggle against prejudice and discrimination.

Gloria Anzaldua describes the particular ways that a feminist consciousness is developed by Latina women who many times find themselves struggling to arrive at a positive image of themselves. She explains how an internalization of racism and colonialist mentality has given rise to shame, self-hatred, and abuse of other Latina women in various communities. Self-hatred and the hatred one has towards others like oneself are further ignited by jostling for the limited positions of superiority that are open to women of color. Here is where ethnic and cultural identity begin to be conflated with race and purported biological distinctions. In the early phases of colonialism, European colonizers flexed their powers overtly in order to destroy the fabric, legal codes, cultural systems, mannerisms, language and habits of the colonized under the guise of civilizing the "savage natives." Slowly, local inhabitants internalized Western values, attitudes, and ways of life, including racialized thinking that resulted in a desire for some Latin Americans to become more white and reject their indigenous cultures. "Like them we try to impose our version of 'the ways things should be', we try to impose one's self on the Other by making her the recipient of one's negative elements, usually the same elements that the Anglo projected on us" (1995: 143).

More graphically, Anzaldua alludes to how the "forced cultural penetration" of rape has, so to speak, inseminated white values into the bodies of women of color (1995:143). A Latina woman with lighter skin who does not speak the language of her ancestors is often held suspect by other Latina women and cast out of the community. Anzaldua attributes this exclusionary practice to an "internalized whiteness that desperately wants boundary lines (this part of me is Mexican, this Indian)[.]" (1995: 143). In opposition to the Enlightenment fantasy of a uniform and self-contained subject, Anzaldua introduces the concept of "mestiza consciousness," a consciousness of the Borderlands that captures the multiplicity and plurality of Latina consciousness. "From this racial, ideological, cultural and biological cross-pollinization, an 'alien' consciousness is presently in the making-a new mestiza consciousness, una conciencia de mujer " (2008: 870). Writing primarily in English but peppering her discussion of mestiza consciousness with phrases in Spanish, Anzaldua puts the non-Spanish reader in an uncomfortable position, paralleling the discomfort felt by many immigrants who are confronted with a language they don't understand. In this way, Anzaldua describes and invokes an appreciation of the inner conflict that those straddling two or more cultures, languages, and value systems experience. She provides a provocative illustration of warring cultures that produce in their subjects a "psychic restlessness" (2008).

The notion of a splintered personality brought on by a collision of cultures is also addressed by Alcoff, who proposes a positive reconstruction of mixed race identities whereby one finds comfort in ambiguity and a contentment with living the "gap" (2000:160). "I never reach shore: I never wholly occupy either the Angla or the Latina identity. Paradoxically, in white society I feel my Latinness, in Latin society I feel my whiteness, as that which is left out, an invisible present, sometimes as intrusive as an elephant in the room and sometimes more as a pulled thread that alters the design of my fabricated self" (2000:160).

Maria Lugones gives a phenomenological description of what it is like to shift between identities as a person of mixed race or a hyphenated identity. When voluntarily embraced, she calls this practice of shifting identities "world traveling." "Those of us who are 'world'- travelers have the distinct experience of being different in different 'worlds' and ourselves in them" (1995: 396). Lugones' concept of world traveling arose out of her awareness of the different levels of comfort she experiences in embodying different identities in distinct worlds. In some worlds, Lugones observes she is more playful and not overly concerned with how others view her. However, while inhabiting a world in which her identity is constructed negatively, or strictly on the basis of her ethnicity, she finds she is less playful and may even begin to animate self-defeating stereotypes.

Shifting in and out of various worlds, Lugones advocates a strategy whereby women attempt to empathize with each other by trying to stand in one another's shoes. Laurence Thomas, to the contrary, warns against such a strategy that asks people who are so differently positioned within society to try to identify with each other's experiences. Instead, he introduces the model of "moral deference": "the act of listening that is preliminary to bearing witness to another's moral pain, but without bearing witness to it" (1986: 377). In this stance, the one suffering has the platform and the one listening, who does not inhabit the same socially constituted identity, cedes the platform by recognizing the incommensurability of his or her experience of the other's pains and struggles. It is this respect - rooted in an acknowledgment of the irreducibility of lived experience-that is at the heart of Third World Women's appeal to Western Feminists.

6. Third World Feminisms and Mainstream Feminism in the U.S.

Significantly, the concerns raised by women of color in the U.S. are almost identically replayed by third world women, in what might be called a shift from biological to cultural racism. However, instead of fighting against a cultural norm of white womanhood, third world feminists are fighting to assert their difference in opposition to a monolithic and dominant notion of Western feminism that is increasingly gaining legitimacy by controlling how women in the third world are represented.

Chandra Talpade Mohanty raises awareness of the impact of Western Scholarship on third world women "in a context of a world system dominated by the West[.]" (1991:53). She encourages Western feminist scholarship to situate itself within the current Western hegemony over the production, publication, distribution, and consumption of information, and to examine its role within this context (1991:55). In her analysis of the representations of third world women in nine texts in the Zed Press "Women in the Third World" series, Mohanty finds that in almost all these texts women are monolithically represented as victims of an unchanging patriarchy. These representations uproot women from their lived situations and the practices that shape, and are shaped by them. "The crucial point that is forgotten is that women are produced through these very relations as well as being implicated in forming these relations" (1991:59).

When women's lives and struggles are not historically and locally situated, they are robbed of their political agency. Those, then, writing about third world women "become the true 'subjects' of this counterhistory" (1991:71). Western scholarship must, therefore, recognize the ethnocentric universalism it assumes in encoding and representing all third world women as victims of an ahistorical and decontextualized notion of patriarchy that results in a homogenous notion of the oppressed third world women. Only when feminist thinkers examine their role within Western dominations can genuine progress be made.

Uma Narayan highlights the facticity of women's historical situations in her exposition of the particularities that women in the third world confront in participating in a feminist movement. Because of the histories of colonialism and imperialism, suspicions against feminist movements as possible instruments of colonial domination surround attempts made by women to organize for change. Specifically, Narayan explores how the term Westernization is used to silence critiques by third world feminists regarding the status and treatment of women in their communities. Ironically, it is Western educated and assimilated men in the third world that are spearheading these attacks against third world feminists by accusing them of disrespecting their culture and embracing Western values and customs. Narayan rejects the implication that feminism is foreign to the third world, noting that historical and political circumstances that raise awareness of women's oppression give rise to a feminist consciousness that is organic to third world women's lives.

Minoo Moallem locates a "feminist imperialism" in Western women's desire to enlighten third world women to the civilizing project of the West, wherein first world women become the norm and third world women get constructed as a singular, non-Western other (2006). Elora Shehabuddin identifies a feminist imperialism in Western women's attempt to position themselves as the saviors of Muslim women, thereby ignoring women's voices fighting to make change within the Muslim world "In presenting change in the Muslim world as possible only with the intervention from the United States-either by force through the violent eradication of oppressive Muslim men or the less dramatic support of 'moderate' Muslim groups and individuals-these writers foreclose the possibility of change from within Muslim societies" (2011: 121).

Ignoring the racism inherent in colonialist narratives documenting the oppression of Muslim women by Muslim men, Shehabuddin points out, Western feminists are content to draw on stories of abuse by a few vocal "Muslim escapees" as representative of the victimization of all Muslim women. What seems to be the primary concern of these Western feminists is not the actual lives of women in the Muslim world, but the assertion of their own moral authority, exercised in presumably righting the sexism in the Islamic world. In this way, Western feminists repeat and redirect their racism and condescension toward Muslim women and third world women in general, while conveniently avoiding the sexism and oppression in their own backyards. The remedy to cultural racism is an acknowledgement of it and a commitment to displace Eurocentricism by actually listening to women's experiences, and engaging women in the hopes of opening up a dialogue. Shehabuddin writes: "In the end, the only way to find out 'what Muslim women want' is to listen to them, not by assuming their needs and concerns are self-evident because they identify as Muslims and not by taking a small group of vocal, articulate individuals-whose opinions on issues like Israel and the war on terror are more acceptable-as the representative and authentic voices" (2011: 132).

7. Conclusion: "There is No Hierarchy of Oppressions"

The history of U.S. feminist thought has evolved from an essentialist notion of womanhood based on the normative model of middle-class white women's experiences to a recognition that women are, in fact, quite diverse and see themselves differently. "The real problem of feminism," states Elizabeth Spellman, "is how it has confused the condition of one group of women with the condition of all women" (1988:15 ). In assuming that the experiences of middle-class white women represented the lives of all women, a false unity and solidarity among women was presupposed. Taking account of the multiple and overlapping forms of oppression that many women, especially women of color and third world women must negotiate, reveals the complexity and diversity of women's lives. Women of color in the U.S., for example, not only define themselves in a struggle against white men and men of color, but also in resistance to white women. The same holds for third world women who find themselves fighting against the omission of their experiences and the overarching assumptions made by "first world" feminists regarding their needs and the forms of subordination they confront. Moving away from a monolithic notion of woman, U.S. feminist theory and practice engages difference by focusing on context-specific positionings of women in relation to other constantly changing categories. But some women worry that without a commonality uniting women the power to make changes will be lost.

To address the complexity of the multitude of oppressions confronting women, Mohanty suggests a model based on "imagined communities of women" organized by "the way we think about race, class, and gender-the political links we choose to make among and between struggles" (1991:4). In these communities, political alliances are formed not by a person's race or sex, but on the basis of "common contexts of struggle against specific exploitative structures[.]" (1991:7) Today, U.S. mainstream feminism is engaged with recognizing diversity and forming cross-cultural coalitions against injustices. The recognition of difference, however, is not complete without a further commitment to making institutional change.

Like sexism, racism is a problem that is structural and endemic to American culture and needs to be addressed systematically, along with class and all other systems of domination. As Robert Bernasconi notes, "Personal attitudes are not the main source of the problem and they cannot provide the solution" (2005: 20). The structural aspect is evident in the ease by which biological racism morphs into cultural racism, spawning condescending and racist attitudes toward third world women and a blindness of first world complicity in various forms of third world oppressions. Indeed, as Audre Lorde has made clear, "the master's tools will never dismantle the master's house." However, by waging struggles against systems of domination and exploitation and assuming responsibility to actively give up the privileges bequeathed by these systems, admittedly an uncomfortable proposition, U.S. feminists embark upon dismantling the master's house and the multitude of oppressions that it sustains.

Still, a change in personal attitudes does go a long way. When mainstream feminists recognize the interconnections between gender, race, nationalism and class, Espiritu writes, "then they can better work with, and not for, women (and men) of color" (Espiritu, 1997: 140). In sum, feminists in the U.S. have worked arduously to address the question of difference among women, as well as what unites women in common contexts of struggle. In the early twentieth century, Emma Goldman wrote of the significance of recognizing and respecting differences, while at the same time working together in spite of these differences to challenge institutional inequalities that prevent individuals from living together in a free society. Goldman laid out a vision for a way forward that goes beyond the mere tolerance of difference when she said: "The problem that confronts us today and which the nearest future is to solve, is how to be one's self and yet in oneness with the others, to feel deeply with all human beings and still retain one's own characteristic qualities" (1973: 509).

8. References and Further Reading

Alarcon, N., "The Theoretical Subject(s) of This Bridge Called My Back and Anglo-American Feminism" in Making Face, Making Soul/Haciendo Caras: Creative and Critical Perspectives by Feminists of Color, (ed.) Anzaldua, G., Aunt Lute Books, 1995.

Alcoff, L., "Chapter 9: The Whiteness Question" Linda Martin-Alcoff, 2005.

Alcoff, L., The Idea of Race, (eds.) Bernasconi, R. and Lott,T., Indianapolis: Hackett Publishing, 2000.

Anzaldua, G., "La Conciencia de la Mestiza/Towards a New Consciousness," in The Feminist Philosophy Reader, (eds.) Bailey, A. and Cuomo, C., New York: McGraw Hill, 2008.

Anzaldua, G., "En Rapport, In Opposition: Cobrando cuentas a las neustras," in Making Face, Making Soul/Haciendo Caras: Creative and Critical Perspectives by Feminists of Color, (ed.) Anzaldua, G., Aunt Lute Books, 1995.

Bernasconi, R. "Waking up White and in Memphis" in White on White/Black on Black (ed.) Yancy, G., Rowman & Littlefield Publishers, Inc., 2005.

Brooks-Higginbotham, E., "The Problem of Race in Women's History," in Coming to Terms: Feminism, Theory, Politics, (ed.) Weed, E., New York: Routledge, 1989.

Carby, H., "On the Threshold of Woman's Era: Lynching, Empire, and Sexuality in Black Feminist Theory," in Race, Writing and Difference, (ed) Gates, H.L, University of Chicago Press: Chicago, 1986.

Carby, H., "The Multicultural Wars," in Black Popular Culture, (ed.) Dent, G., Bay Press: Washington, 1992.

Carby, H. Reconstructing Womanhood: The Emergence of the Afro-American Woman Novelist,U.S.A: Oxford University Press, 1989

Collins, P.H., Black Feminist Thought, New York: Routledge, 1991.

Combahee River Collective, "A Black Feminist Statement The Combahee River Collective" in Words of Fire: An Anthology of African-American Feminist Thought, (ed) Guy-Sheftall, B., New Press, 1995.

Davis, A., "Black Nationalism: The Sixties and the Nineties," in Black Popular Culture, (ed.) Dent, G., Bay Press: Washington, 1992.

Espiritu, Yen Le, "Race, Class and Gender in Asian America" in Making More Waves: New Writings by Asian American Women, eds. Elaine H. Kim, Lilia V. Villanueva, and Asian Women United of California, Beacon Press Books: Boston, 1997.

Friedan, B. The Feminine Mystique, New York: Dell Publishing Inc., 1974.

Frye, M., "White Woman Feminist 1983-1992," in Race and Racism, (ed.), B. Boxill, U.S.A: Oxford University Press, 2001.

de Gobineau, A., "The Inequality of Human Races," in The Idea of Race (eds.) Bernasconi, R. and Lott, Indianapolis: Hackett Publishing, 2000.

Goldman, E. "The Tragedy of Woman's Emancipation," in The Feminist Papers: From Adams to de Beauvoir, (ed.) Ross, A. S., Boston: Northeastern University Press, 1973.

Gordon, L., "On Difference," Genders 10, Spring 1991.

Grande, S., "Whitestream Feminism and the Colonialist Project: A Review of Contemporary Feminist Pedagogy and Praxis," Educational Theory, Summer 2003,Volume 53, Number 3.

Hartsock, Nancy, The Feminist Standpoint Revisited, And Other Essays (Basic Books, 1999), pp. 105-133.

Hooks, b., Feminist Theory: From Margin to Center, Boston: South End Press, 1984.

Ignatiev, N., "The Point Is Not To Interpret Whiteness But To Abolish It" in Race Traitor, ed. Noel Ignatiev, 1997.

Lorde, A. "The Master's Tools Will Never Dismantle the Master's House," in This Bridge Called My Back: Writings by Radical Women of Color, (eds.) Moraga, C. and Anzaldua, Kitchen Table- Women of Color Press, 1984.

Lorde, A. "There is No Hierarchy of Oppressions," Illvox, May 12, 2008.

Lugones, M. "Playfulness, 'World'-Travelling, and Loving Perception" in Making Face, Making Soul/Haciendo Caras: Creative and Critical Perspectives by Feminists of Color, (ed.) Anzaldua, G., Aunt Lute Books, 1995.

McIntosh, P., "White Privilege and Male Privlege," in The Feminist Philosophy Reader, (eds.) Bailey, A. and Cuomo, C., New York: McGraw Hill, 2008.

Moallem, M., "Feminist Scholarship and the Internationalization of Women's Studies," Feminist Studies 32, no. 2 (Summer 2006) 334

Mohanty, C. "Introduction: Cartographies of Struggle: Third World Feminism and the Politics of Feminism" in Third World Women and the Politics of Feminism, (eds.) Mohanty, C., Russo, A., Torres, L., Indiana University Press, 1991.

Mohanty, C., "Under Western Eyes: Feminist Scholarship and Colonial Discourses" in Third World Women and the Politics of Feminism, (eds.) Mohanty, C., Russo, A., Torres, L. (eds.) Indiana University Press, 1991.

Moraga, C., "From a Long Line of Vendidas: Chicanas and Feminism" in Making Face, Making Soul/Haciendo Caras: Creative and Critical Perspectives by Feminists of Color, (ed.) Anzaldua, G., Aunt Lute Books, 1995.

Narayan, U., "Contesting Cultures: 'Westernization,' Respect for Cultures and Third-World Feminists," in The Second Wave: A Reader in Feminist Theory, (ed.) Nicholson, L., New York:Routledge,1997.

Ngan Ling Chow, E., "The Development of Feminist Consciousness Among Asian American Women," in The Social Construction of Gender, (eds.) Lorber, J. and Farrel, S. Sage Publications, 1991.

Scott, J., "The Evidence of Experience," Critical Inquiry 17, 4 (Summer 1991)

Shehabuddin, E., "Gender and the Figure of the 'Moderate Muslim': Feminism in the Twenty-first Century,' in Judith Butler and Elizabeth Weed, eds. The Question of Gender: Joan W. Scott's Critical Feminism (Indiana University Press, 2011).

Spelman, E., Inessential Woman: Problems of Exclusion in Feminist Thought, Beacon Press: Boston, 1988.

Srivastava, S., "You're calling me a racist? The Moral and Emotional Regulation of Antiracism and Feminism," Signs the Journal of Women in Culture and Society, 2005, vol 31, no. 1 (30, 44, 42-43)

Stubblefield, A., "Meditations on Postsupremacist Philosophy" in White on White/Black on Black, G. Yancy (ed.), New York: Rowman &Littlefield, 2005.

Thomas, L., Moral Deference, 1998.

Truth, S., "Ain't I A Woman? December 1851," Internet Modern History Sourcebook, (ed.) Paul Halsal (March 2009).

Author Information

Sharin N. Elkholy
Email: elkholys@uhd.edu
University of Houston - Downtown
U. S. A.

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This article traces the history of U.S. mainstream feminist thought from an essentialist notion of womanhood based on the normative model of middle-class white women's experiences, to a recognition that women are, in fact, quite diverse and see themselves differently.

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How does pressure affect student athletes

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How does pressure affect student athletes

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(Qualitative) This article talks about student-athletes mental health due to performing well in their sport to get a scholarship, as well as performing well in school.

-Camden Franklin

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The student-athletes on many of our favorite sports teams may face unique challenges and setbacks during their college sports career.

Student-athlete mental health may be affected by the constant stress of maintaining elite athletic performance while balancing class and a healthy social life.

Student-athletes may also struggle with body dysmorphia, heckling from spectators, low self-esteem, and sleep deprivation.

Student-athletes should reach out for help from a university counselor, or seek professional services if they feel as though their mental health has started to suffer.

When many of us tune in to watch our favorite basketball, football, or volleyball team, student-athlete mental health is often the last thing on our minds-and tend to only feel if our beloved team loses. From our perspective in the bleachers (or from the couch), it might seem like student-athletes are able to function perfectly, without anything holding them back-or afflicting them mentally.

Unfortunately, this isn't usually the case. Student-athlete mental health concerns are a real issue, and due to stigma and the possibility of unsupportive peers, these athletes may not know where to turn when faced with depression, body image issues, chronic stress, and more.

Student-Athlete Mental Health: What Are the Ups and Downs?

Being a student-athlete can affect your mental health in some positive ways-exercise can often reduce mental stress, promote mental clarity, and increase positive relationships with peers. However, student-athletes are also at a greater risk of requiring treatment for substance use , eating disorders , and anxiety disorders compared with other students.

The pressures to fit into an athletic team's social group may bring on some social anxiety. Additionally, the pressures and demands of being a student-athlete and balancing academic priorities are tremendous.

How Many Student-Athletes Have Mental Health Issues?

There's no real way to gauge student-athlete mental health on a large scale, especially when reporting such concerns is often heavily stigmatized. What is certain is that the pressure to maintain a high level of academic performance, become accepted into a team's social network, and also maintain a high level of athletic performance brings on an elevated amount of mental health challenges .

Many student-athletes may be high achievers due to the drive expected of them both on and off the field and often struggle with perfectionism: the need to maintain excellence.

What Is the Most Common Mental Illness in Athletes?

Student-athlete mental health is often affected by the following conditions:

An additional example of pressure related to body dysmorphia may involve weight and body image-related concerns. For example, student-athlete mental health might be affected by a coach asking them to gain weight in order to reach a certain weight class for a wrestling match or basketball or football position. They may also be asked to lose weight in order to be able to run faster or farther for a track meet.

Outside of their athletic team, a student-athlete may struggle to fit in with other students. This might involve feeling the pressure to be thinner or appear smaller like their peers, which may bring on patterns of disordered eating.

Student-Athlete Mental Health: What Can Cause Depression?

The pressure to perform at a top-tier level may often bring on added anxiety-and those thoughts may become mixed with depressive thinking patterns and emotions, such as hopelessness or the fear of making mistakes.

Student-athletes might experience depression for a number of other reasons, including:

Difficulty maintaining a high level of athletic performance

Trouble maintaining their academic performance

Negative self-talk

Lack of peer support

Verbal or physical abuse from coaches

Heckling from spectators

Sleep deprivation and disorders

Overtraining

What Do Athletes Struggle with Mentally? How Can They Get Help?

Between training, performing, and academics, there is often little time for sleep, maintaining social relationships, and hobbies. This can cause a significant amount of strain, especially if the student-athlete is on scholarship.

Instead of struggling with their mental health concerns in silence, student-athletes should reach out to talk with a mental health professional. Many therapists and counselors have experience treating student-athlete mental health concerns and can help to address many of the specific stressors and issues experienced by these young individuals.

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Student-athlete mental health: A closer look at the unique stressors collegiate athletes may face | Thriveworks

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Learn more about Student-athlete mental health: A closer look at the unique stressors collegiate athletes may face

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How does pressure affect student athletes

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How does pressure affect student athletes

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(Quantitative) This article talks about how scarce it is for schools to give out scholarships. It uses percentages and statistics to show this and it explains how athletes have to put most of their time into the sport.

-Camden Franklin

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Nearly 57% of high school students participate in sports and only 2% of those athletes will go on to receive an athletic scholarship, creating a competitive environment where only the most dedicated will succeed. Because the window of opportunity is small, athletes are pressured to commit most of their time to their sport for a…

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Social media affecting child development.

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Social media affecting child development.

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This article goes into depth on how social media can affect a child's growth; whether it be their communication, socialization, or their actions and mindset.

Qualitative data on this topic is the adults viewpoint on watching the children grow up along with social media and how its impacting their social life. Teenagers and young adults are stating how they see a huge decrease on their wellbeing. Catherine Steiner mentions how kids are missing out on many things that the media can not provide for them in a positive way.

The Quantitative data is that in a research that consisted of 296 healthy 2-5 year old's (52% boys 48% girls), (and 224 mothers from the LIFE Child cohort study were analyzed. Screen times and parent–child interactions were assessed using standardized parental questionnaires. Developmental skills were investigated using the standardized development test ET 6-6-R. High screen times in children (>1 h/day) were significantly associated with lower percentile ranks but the kids who had less screen time had a higher percentile rank with education.

https://www.nature.com/articles/s41390-021-01433-6

Rebekah B.

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Many parents worry about how exposure to technology might affect toddlers developmentally. We know our preschoolers are picking up new social and cognitive skills at a stunning pace, and we don't want hours spent glued to an iPad to impede that. But adolescence is an equally important period of rapid development, and too few of us are paying attention to how our teenagers' use of technology - much more intense and intimate than a 3-year-old playing with dad's iPhone - is affecting them. In fact, experts worry that the social media and text messages that have become so integral to teenage life are promoting anxiety and lowering self-esteem.

Young people report that there might be good reason to worry. A survey conducted by the Royal Society for Public Health asked 14-24-year-olds in the UK how social media platforms impacted their health and well-being. The survey results found that Snapchat, Facebook, Twitter, and Instagram all led to increased feelings of depression, anxiety, poor body image, and loneliness.

Indirect communication

Teens are masters at keeping themselves occupied in the hours after school until way past bedtime. When they're not doing their homework (and when they are) they're online and on their phones, texting, sharing, trolling, scrolling, you name it. Of course before everyone had an Instagram account teens kept themselves busy, too, but they were more likely to do their chatting on the phone, or in person when hanging out at the mall. It may have looked like a lot of aimless hanging around, but what they were doing was experimenting, trying out skills, and succeeding and failing in tons of tiny real-time interactions that kids today are missing out on. For one thing, modern teens are learning to do most of their communication while looking at a screen, not another person.

"As a species we are very highly attuned to reading social cues," says Catherine Steiner-Adair, EdD, a clinical psychologist and author of The Big Disconnect. "There's no question kids are missing out on very critical social skills. In a way, texting and online communicating puts everybody in a context where body language, facial expression, and even the smallest kinds of vocal reactions are rendered invisible."

Lowering the risks

Certainly speaking indirectly creates a barrier to clear communication, but that's not all. Learning how to make friends is a major part of growing up, and friendship requires a certain amount of risk-taking. This is true for making a new friend, but it's also true for maintaining friendships. When there are problems that need to be faced - big ones or small ones - it takes courage to be honest about your feelings and then hear what the other person has to say. Learning to effectively cross these bridges is part of what makes friendship fun and exciting, and also scary. "Part of healthy self-esteem is knowing how to say what you think and feel even when you're in disagreement with other people or it feels emotionally risky," notes Dr. Steiner-Adair.

But when friendship is conducted online and through texts, kids are doing this in a context stripped of many of the most personal - and sometimes intimidating - aspects of communication. It's easier to keep your guard up when you're texting, so less is at stake. You aren't hearing or seeing the effect that your words are having on the other person. Because the conversation isn't happening in real time, each party can take more time to consider a response. No wonder kids say calling someone on the phone is "too intense"- it requires more direct communication, and if you aren't used to that it may well feel scary.

If kids aren't getting enough practice relating to people and getting their needs met in person and in real time, many of them will grow up to be adults who are anxious about our species' primary means of communication - talking. And of course social negotiations only get riskier as people get older and begin navigating romantic relationships and employment.

Cyberbullying and the imposter syndrome

The other big danger that comes from kids communicating more indirectly is that it has gotten easier to be cruel. "Kids text all sorts of things that you would never in a million years contemplate saying to anyone's face," says Donna Wick, EdD, a clinical and developmental psychologist. She notes that this seems to be especially true of girls, who typically don't like to disagree with each other in "real life."

"You hope to teach them that they can disagree without jeopardizing the relationship, but what social media is teaching them to do is disagree in ways that are more extreme and do jeopardize the relationship. It's exactly what you don't want to have happen," she says.

Dr. Steiner-Adair agrees that girls are particularly at risk. "Girls are socialized more to compare themselves to other people, girls in particular, to develop their identities, so it makes them more vulnerable to the downside of all this." She warns that a lack of solid self-esteem is often to blame. "We forget that relational aggression comes from insecurity and feeling awful about yourself, and wanting to put other people down so you feel better."

Peer acceptance is a big thing for adolescents, and many of them care about their image as much as a politician running for office, and to them it can feel as serious. Add to that the fact that kids today are getting actual polling data on how much people like them or their appearance via things like "likes." It's enough to turn anyone's head. Who wouldn't want to make themselves look cooler if they could? So kids can spend hours pruning their online identities, trying to project an idealized image. Teenage girls sort through hundreds of photos, agonizing over which ones to post online. Boys compete for attention by trying to out-gross one other, pushing the envelope as much as they can in the already disinhibited atmosphere online. Kids gang up on each other.

Adolescents have always been doing this, but with the advent of social media they are faced with more opportunities - and more traps - than ever before. When kids scroll through their feeds and see how great everyone seems, it only adds to the pressure. We're used to worrying about the impractical ideals that photoshopped magazine models give to our kids, but what happens with the kid next door is photoshopped, too? Even more confusing, what about when your own profile doesn't really represent the person that you feel like you are on the inside?

"Adolescence and the early twenties in particular are the years in which you are acutely aware of the contrasts between who you appear to be and who you think you are," says Dr. Wick. "It's similar to the 'imposter syndrome' in psychology. As you get older and acquire more mastery, you begin to realize that you actually are good at some things, and then you feel that gap hopefully narrow. But imagine having your deepest darkest fear be that you aren't as good as you look, and then imagine needing to look that good all the time! It's exhausting."

As Dr. Steiner-Adair explains, "Self-esteem comes from consolidating who you are." The more identities you have, and the more time you spend pretending to be someone you aren't, the harder it's going to be to feel good about yourself.

Stalking (and being ignored)

Another big change that has come with new technology and especially smart phones is that we are never really alone. Kids update their status, share what they're watching, listening to, and reading, and have apps that let their friends know their specific location on a map at all times. Even if a person isn't trying to keep his friends updated, he's still never out of reach of a text message. The result is that kids feel hyperconnected with each other. The conversation never needs to stop, and it feels like there's always something new happening.

"Whatever we think of the 'relationships' maintained and in some cases initiated on social media, kids never get a break from them," notes Dr. Wick. "And that, in and of itself, can produce anxiety. Everyone needs a respite from the demands of intimacy and connection; time alone to regroup, replenish and just chill out. When you don't have that, it's easy to become emotionally depleted, fertile ground for anxiety to breed."

It's also surprisingly easy to feel lonely in the middle of all that hyperconnection. For one thing, kids now know with depressing certainty when they're being ignored. We all have phones and we all respond to things pretty quickly, so when you're waiting for a response that doesn't come, the silence can be deafening. The silent treatment might be a strategic insult or just the unfortunate side effect of an online adolescent relationship that starts out intensely but then fades away.

"In the old days when a boy was going to break up with you, he had to have a conversation with you. Or at least he had to call," says Dr. Wick. "These days he might just disappear from your screen, and you never get to have the 'What did I do?' conversation." Kids are often left imagining the worst about themselves.

But even when the conversation doesn't end, being in a constant state of waiting can still provoke anxiety. We can feel ourselves being put on the back burner, we put others back there, and our very human need to communicate is effectively delegated there, too.

What should parents do?

Both experts interviewed for this article agreed that the best thing parents can do to minimize the risks associated with technology is to curtail their own consumption first. It's up to parents to set a good example of what healthy device usage looks like. Most of us check our phones or our email too much, out of either real interest or nervous habit. Kids should be used to seeing our faces, not our heads bent over a screen. Establish technology-free zones in the house and technology-free hours when no one uses the phone, including mom and dad. "Don't walk in the door after work in the middle of a conversation," Dr. Steiner-Adair advises. "Don't walk in the door after work, say 'hi' quickly, and then 'just check your email.' In the morning, get up a half hour earlier than your kids and check your email then. Give them your full attention until they're out the door. And neither of you should be using phones in the car to or from school because that's an important time to talk."

Not only does limiting the amount of time you spend plugged in to computers provide a healthy counterpoint to the tech-obsessed world, it also strengthens the parent-child bond and makes kids feel more secure. Kids need to know that you are available to help them with their problems, talk about their day, or give them a reality check.

"It is the mini-moments of disconnection, when parents are too focused on their own devices and screens, that dilute the parent-child relationship," Dr. Steiner-Adair warns. And when kids start turning to the internet for help or to process whatever happened during the day, you might not like what happens. "Tech can give your children more information that you can, and it doesn't have your values," notes Dr. Steiner-Adair. "It won't be sensitive to your child's personality, and it won't answer his question in a developmentally appropriate way."

In addition Dr. Wick advises delaying the age of first use as much as possible. "I use the same advice here that I use when talking about kids and alcohol - try to get as far as you can without anything at all." If your child is on a social media platform, Dr. Wick says that you should friend them and monitor their page. But she advises against going through text messages unless there is cause for concern. "If you have a reason to be worried then okay, but it better be a good reason. I see parents who are just plain old spying on their kids. Parents should begin by trusting their children. To not even give your kid the benefit of the doubt is incredibly damaging to the relationship. You have to feel like your parents think you're a good kid."

Offline, the gold standard advice for helping kids build healthy self-esteem is to get them involved in something that they're interested in. It could be sports or music or taking apart computers or volunteering - anything that sparks an interest and gives them confidence. When kids learn to feel good about what they can do instead of how they look and what they own, they're happier and better prepared for success in real life. That most of these activities also involve spending time interacting with peers face-to-face is just the icing on the cake.

Frequently Asked Questions

How does social media affect behavior negatively?

How does social media affect social skills?

How does social media affect teenagers' mental health?

Is social media harmful?

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How Using Social Media Affects Teenagers - Child Mind Institute

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How does social media affect teens? Experts say kids are growing up with more anxiety and less self-esteem due to social media. Read advice for parents from specialists in our article.

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This article provides statistics on how eating disorders are such a common occurrence. every hour someone dies due to an eating disorder.

https:/injepijorunal.biomedcentral.com/articles/10.1186/s40621-021-00299-w

this article contains information regarding the characteristics and patterns of older adult homicides in the United States along with more information about murders that occurred in the United States.

~ posted by Rejinai Petit-Raymond

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STRIPED, in collaboration with the Academy for Eating Disorders (AED) and Deloitte Access Economics has conducted the most comprehensive examination to date of the social and economic burden of eating disorders in the United States. The product of a yearlong collaboration, the report provides a critical new body of evidence on the devastating impact of eating disorders on individuals, families, and society. In addition to estimating the direct cost of treatment for eating disorders, the report documents a range of additional economic costs, including informal care giving, productivity, and broader costs to society and estimates substantial losses in wellbeing.

Click here to download the above infographic.
Infographics with key findings tailored for each state!Click here for your state's data.

Expert Advisory Panel for This Report: We offer a debt of gratitude to the members of the Expert Advisory Panel for their extensive guidance on the preparation of this report: S. Bryn Austin, Rebecca Hutcheson, Johanna S. Kandel, Jillian Lampert, Elissa Myers, Tracy K. Richmond, Mihail Samnaliev, Katrina Velasquez, Zachary J. Ward, Ruth S. Weissman, and Davene R. Wright.

Funding: This report was supported by a Boston Children's Hospital Pediatric Associates Research Program grant and by the Ellen Feldberg Gordon Fund for Eating Disorders Prevention Research.

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Report: Economic Costs of Eating Disorders

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STRIPED, in collaboration with the Academy for Eating Disorders (AED) and Deloitte Access Economics has conducted the most comprehensive examination to date of the social and economic burden of eating disorders in the United States. The product of a yearlong collaboration, the report provides a critical new body of evidence on the devastating impact of eating disorders on individuals, families, and society.

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(Quantitative) This article shows statistics and graphs about how teens use and feel about social media. Most say that social media has a positive effect on them.

-Camden Franklin

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Pew Research Center: Internet, Science & Tech

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Majorities of teens credit social media with strengthening their friendships and providing support while also noting the emotionally charged side of these platforms

Society has long fretted about technology's impact on youth. But unlike radio and television, the hyperconnected nature of social media has led to new anxieties, including worries that these platforms may be negatively impacting teenagers' mental health. Just this year, the White House announced plans to combat potential harms teens may face when using social media.

Despite these concerns, teens themselves paint a more nuanced picture of adolescent life on social media. It is one in which majorities credit these platforms with deepening connections and providing a support network when they need it, while smaller - though notable - shares acknowledge the drama and pressures that can come along with using social media, according to a Pew Research Center survey of U.S. teens ages 13 to 17 conducted April 14 to May 4, 2022.

Eight-in-ten teens say that what they see on social media makes them feel more connected to what's going on in their friends' lives, while 71% say it makes them feel like they have a place where they can show their creative side. And 67% say these platforms make them feel as if they have people who can support them through tough times. A smaller share - though still a majority - say the same for feeling more accepted. These positive sentiments are expressed by teens across demographic groups.

When asked about the overall impact of social media on them personally, more teens say its effect has been mostly positive (32%) than say it has been mostly negative (9%). The largest share describes its impact in neutral terms: 59% believe social media has had neither a positive nor a negative effect on them. For teens who view social media's effect on them as mostly positive, many describe maintaining friendships, building connections, or accessing information as main reasons they feel this way, with one teen saying:

"It connects me with the world, provides an outlet to learn things I otherwise wouldn't have access to, and allows me to discover and explore interests." - Teen girl

While these youth describe the benefits they get from social media, this positivity is not unanimous. Indeed, 38% of teens say they feel overwhelmed by all the drama they see on social media, while about three-in-ten say these platforms have made them feel like their friends are leaving them out of things (31%) or have felt pressure to post content that will get lots of likes or comments (29%). Another 23% say these platforms make them feel worse about their own life.

Teen girls report encountering some of these pressures at higher rates. Some 45% of girls say they feel overwhelmed because of all the drama on social media, compared with 32% of boys. Girls are also more likely than boys to say social media has made them feel like their friends are leaving them out of things (37% vs. 24%) or worse about their own lives (28% vs. 18%).

When asked how often they decide not to post on social media out of fear of it being using against them, older teen girls stand out. For example, half of 15- to 17-year-old girls say they often or sometimes decide not to post something on social media because they worry others might use it to embarrass them, compared with smaller shares of younger girls or boys.

These are some of the key findings from a Pew Research Center online survey of 1,316 U.S. teens conducted from April 14 to May 4, 2022.

The strong presence of social media in many teenagers' lives begs the question: What impact, if any, are these sites having on today's youth?

Even as teens tend to view the impact of social media on their own lives in more positive than negative terms, they are more critical of its influence on their peers. While 9% of teens think social media has had a mostly negative effect on them personally, that share rises to 32% when the same question is framed about people their age.

There are also gaps when looking at the positive side of these platforms. Some 32% of teens say social media has had a positive effect on them personally, compared with a smaller share (24%) who say the same about these platforms' impact on teens more broadly.

Still, regardless of whether teens are assessing social media's impact on themselves or others, the most common way they describe its effect is as neither positive nor negative.

Parents are often on the front lines in navigating challenges their children may face when using social media. While previous Center surveys reflect parents' anxieties about social media, only a minority of teens in this survey describe their parents as being highly concerned about their use of these sites.

Some 22% believe their parents are extremely or very worried about them using social media, while another 27% say their parents are somewhat worried. However, many teens - 41% - say their parents are worried only a little or not at all. And 9% say they aren't sure about the level of concern their parents have over their social media use. These youth also weighed in on whether parents overall - not just their own - have an accurate picture of what it's like to be a teenager on social media. Some 39% say teens' experiences are better than parents think, while 27% say things on social media are worse for teens than parents think. Still, one-third believe parents' assessments are about right.

Teens who see social media as having a mostly positive effect on people their age are more likely than teens who see mostly negative effects to say teens' experiences on social media are better than parents think. They are also more likely to say they have had positive experiences while personally using these platforms.

Whether teens see social media's effects as positive or negative relates to their perspective on whether parents' views stack up to reality. About six-in-ten teens who say that social media has had a mostly positive effect on people their age say teens' experiences on social media are better than parents think, while a plurality of teens who say social media has been mostly negative for people their age say teens' experiences on social media are worse than parents think.

Teens who have a more positive view of social media's effect on their peers report more positive personal experiences with these platforms. More than half (54%) of teens who see social media as having a mostly positive effect on people their age say that what they see on social media makes them feel a lot more connected to what's going on in their friends' lives. About four-in-ten say they feel a lot like they have a place where they can show their creative side. Some 35% of teens who see the effect as mostly positive say social media makes them feel a lot like they have people who can support them through tough times, and 28% say it makes them feel a lot more accepted. By comparison, much smaller shares - about or quarter or fewer - of teens who see social media as having a negative effect say what they see on social media makes them feel each of these positive experiences a lot.

While teens who have a positive outlook on the impact of social media are more likely to report personally benefiting from these sites, they tend to say they've experienced the more negative side in similar proportions as those who rate these sites' effect on teens negatively. There is one exception: 12% of teens who believe social media has a mostly negative effect on teens say they feel overwhelmed by all of the drama on these platforms a lot, compared with 6% of those who see its impact as mostly positive.

Beyond broad measurement of social media, this survey also tackled two popular topics in the debates around social media: online activism and digital privacy.

Only small shares of teens are engaging in online activism on social media, but experiences and views vary by political affiliation

On topics from MAGA to Black Lives Matter, social media platforms have become an important way for people of all ages to share information, mobilize and discuss issues that are important to them.

But this survey reveals that only a minority of teens say they have been civically active on social media in the past year via one of the three means asked about at the time of the survey. One-in-ten teens say they have encouraged others to take action on political or social issues that are important to them or have posted a picture to show their support for a political or social issue in the past 12 months. Some 7% say the same about using hashtags related to a political or social cause on social media during this period. Taken together, 15% of teens have engaged in at least one of these activities on social media in the past 12 months.

While majorities of both Democrats and Republicans have not used social media in this way, there are some notable partisan differences among those who engage in activism. For example, 14% of teens who identify as Democrats or who lean toward the Democratic Party say they have used social media to encourage others to take action on political or social issues that are important to them in the past 12 months, compared with 6% of teens who are Republicans or GOP leaners. And larger shares of Democrats than Republicans say they have posted pictures or used hashtags to show support for a political or social issue in the past year. In total, Democratic teens are twice as likely as Republican teens to have engaged in any of these activities during this time (20% vs. 10%).

Not only do small shares of teens participate in these types of activities on social media, relatively few say these platforms play a critical role in how they interact with political and social issues.

About one-in-ten or fewer teens say social media is extremely or very important to them personally when it comes to exposing them to new viewpoints, getting involved with issues that are important to them, finding other people who share their views, helping them figure out their own views on an issue or giving them a venue to express their political opinions.

Just as Democratic teens are more likely than Republican teens to engage in these forms of online activism, they also see social media as a more integral tool for civic engagement. For example, 18% of Democratic teens say social media is extremely or very important to them when it comes to exposing them to new points of view, compared with 8% of Republican teens. Democrats are also more likely than Republicans to say these platforms are at least very important to them for getting involved with issues that are important to them, finding others who share their views or helping them figure out their own way of thinking.

And when asked about what people should do more broadly, Democratic teens (22%) are more likely than Republican teens (12%) to say that regardless of whether they engage in online activism themselves, it is very or extremely important for people to speak out about political or social issues on social media.

Teens feel a lack of control over their personal data but aren't too concerned about social media companies having this information

Amid the continued privacy discussions in the media and among policymakers, teens have nuanced views on the topic. Just 14% of teens report feeling a lot of control over the personal information that social media companies collect about them. Meanwhile, 60% of teens feel like they have little to no control. A further 26% say they are not sure how much control they have over companies' collection of this information.

Despite feeling a lack of control over their data being collected by social media companies, teens are largely unconcerned. A fifth of teens (20%) say they feel very or extremely concerned about the amount of their personal information social media companies might have. Still, a notable segment of teens - 44% - say they have little or no concern about how much these companies might know about them.
"TikTok is more of a place to watch videos ... then Instagram [is] more to see what my friends are up to and then Snapchat [is] a way of more direct communication." - Teen girl
To inform and supplement this survey, the Center conducted a series of teen focus groups to better understand how teens were using social media and thinking about topics related to it. These focus groups highlight how nuanced teens' views on social media truly are.

Teens share how different platforms serve different purposes as they navigate online life and that using these platforms can lead to a variety of emotions and experiences, from anxiety to excitement and from improved social connections to bullying:

"I've liked, especially during the pandemic, being able to communicate with my friends more, since I couldn't see them in person. And then also, having something to watch to entertain me, which was good, because we were just stuck at home." - Teen girl
"Okay, for me, it is like bullies or like negative comments or stuff like that, you just see a lot of people hating under the comments, under your posts and stuff like that." - Teen boy "During the pandemic, I feel like less people were using social media in certain ways, because there wasn't much to post, like going out. You're just staying at home. But TikTok, everyone was on it, because it was their source of entertainment." - Teen girl
As teens walk us through their perspectives, they also share how the pandemic changed (and didn't change) their social media habits and what they think their lives would be like if social media disappeared overnight:
"I think it would be a little bit [messed up if social media disappeared]. I spend 99% of my time indoors in front of my computer, if I'm not playing games, I'm watching pirated videos. If I'm not watching videos, maybe I'm reading an article. I'm always online. And I hardly step out of my room. I have had issues with my dad. He said my room is too creepy. I should come outside and play with people but I'm not really good at making friends. So, it's a bit hard on me." - Teen boy "[When] we were younger, [social media] didn't have an effect on us and social media wasn't as big as it is now. I feel like we were more free and more happy, and no stress or overthinking or insecure." - Teen girl
For more quotes and themes from the focus groups, see Chapter 3.

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Monica Anderson, Emily A. Vogels, Andrew Perrin and Lee Rainie

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Connection, Creativity and Drama: Teen Life on Social Media in 2022

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Majorities of teens credit social media with strengthening their friendships and providing support while also noting the emotionally charged side of these platforms.