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Found looking for more resources for mental health. This website touches base on all ages of mental health disorders, and also brings up homelessness and the effect that can have on mental health. The data is evidence based and comes from SAMHSA. Provides great visuals and different graphics for different situations. Even shows how living in rural areas can effect resources to mental health treatment. I think that this website is very inclusive, it uses all ages, several different circumstances such as living in rural areas, cities, or even homelessness.

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You Are Not Alone
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Millions of people are affected by mental illness each year. Across the country, many people just like you work, perform, create, compete, laugh, love and inspire every day.

22.8% of U.S. adults experienced mental illness in 2021 (57.8 million people). This represents 1 in 5 adults.

5.5% of U.S. adults experienced serious mental illness in 2021 (14.1 million people). This represents 1 in 20 adults.

16.5% of U.S. youth aged 6-17 experienced a mental health disorder in 2016 (7.7 million people)

7.6% of U.S. adults experienced a co-occurring substance use disorder and mental illness in 2021 (19.4 million people)

Annual prevalence of mental illness among U.S. adults, by demographic group:

Non-Hispanic Asian: 16.4%

Non-Hispanic Native Hawaiian or Other Pacific Islander: 18.1%

Non-Hispanic Black or African American: 21.4%

Hispanic or Latino: 20.7%

Non-Hispanic White: 23.9%

Non-Hispanic American Indian or Alaska Native: 26.6%

Non-Hispanic mixed/multiracial: 34.9%

Lesbian, Gay or Bisexual: 50.2%

Annual prevalence among U.S. adults, by condition:

Schizophrenia: <1%

Obsessive Compulsive Disorder: 1.2%

Borderline Personality Disorder: 1.4%

Bipolar Disorder: 2.8%

Posttraumatic Stress Disorder: 3.6%

Major Depressive Episode: 8.3%

Anxiety Disorders: 19.1%

Mental Health Care Matters
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47.2% of U.S. adults with mental illness received treatment in 2021

65.4% of U.S. adults with serious mental illness received treatment in 2021

50.6% of U.S. youth aged 6-17 with a mental health disorder received treatment in 2016

The average delay between onset of mental illness symptoms and treatment is 11 years

Annual treatment rates among U.S. adults with any mental illness, by demographic group:

Non-Hispanic Asian: 25.4%

Hispanic or Latino: 36.1%

Non-Hispanic Black or African American: 39.4%

Non-Hispanic White: 52.4%

Non-Hispanic mixed/multiracial: 52.2%

Male: 40%

Female: 51.7%

Lesbian, Gay or Bisexual: 55.6%

10.6% of U.S. adults with mental illness had no insurance coverage in 2021

11.9% of U.S. adults with serious mental illness had no insurance coverage in 2021

160 million people live in a designated Mental Health Professional Shortage Area

The Ripple Effect Of Mental Illness
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Having a mental illness can make it challenging to live everyday life and maintain recovery. Beyond the individual, these challenges ripple out through our families, our communities, and our world.

PERSON

People with depression have a 40% higher risk of developing cardiovascular and metabolic diseases than the general population. People with serious mental illness are nearly twice as likely to develop these conditions.

33.5% of U.S. adults with mental illness also experienced a substance use disorder in 2021 (19.4 million individuals)

The rate of unemployment is higher among U.S. adults who have mental illness (7.4%) compared to those who do not (4.6%)

High school students with significant symptoms of depression are more than twice as likely to drop out compared to their peers

Students aged 6-17 with mental, emotional or behavioral concerns are 3x more likely to repeat a grade.

FAMILY

At least 8.4 million people in the U.S. provide care to an adult with a mental or emotional health issue

Caregivers of adults with mental or emotional health issues spend an average of 32 hours per week providing unpaid care

COMMUNITY

21.1% of people experiencing homelessness in the U.S. have a serious mental health condition

Among people in the U.S. under age 18, depressive disorders are the most common cause of hospitalization (after excluding hospitalization relating to pregnancy and birth)

Among people in the U.S. aged 18-44, psychosis spectrum and mood disorders account for nearly 600,000 hospitalizations each year

19.7% of U.S. Veterans experienced a mental illness in 2020 (3.9 million people)

9.6% of Active Component service members in the U.S. military experienced a mental health or substance use condition in 2021

Across the U.S. economy, serious mental illness causes $193.2 billion in lost earnings each year

WORLD

Depression and anxiety disorders cost the global economy $1 trillion in lost productivity each year

Depression is a leading cause of disability worldwide

Common Warning Signs Of Mental Illness
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Diagnosing mental illness isn't a straightforward science. We can't test for it the same way we can test blood sugar levels for diabetes. Each condition has its own set of unique symptoms, though symptoms often overlap.

It's Okay To Talk About Suicide
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Thoughts of suicide can be frightening. But by reaching out for help or checking in with family and friends, we can avoid devastating outcomes.

Suicide is the 2nd leading cause of death among people aged 10-14 and the 3rd leading cause of death among those aged 15-24 in the U.S.

​Suicide is the 12th leading cause of death overall in the U.S.

46% of people who die by suicide had a diagnosed mental health condition

90% of people who die by suicide may have experienced symptoms of a mental health condition, according to interviews with family, friends and medical professionals (also known as psychological autopsy)

Annual prevalence of serious thoughts of suicide, high risk populations:

U.S. Adults: annual average 4.8%

Native Hawaiian/Other Pacific Islander: 7.4%

Mixed/Multiracial: 8.2%

American Indian/Alaska Native: 8.5%

Youth Populations

Young adults aged 18-25: 13%

High school students: 22%

LGBTQ youth: 45%

Lesbian, gay and bisexual youth are nearly 4x more likely to attempt suicide than straight youth

79% of people who die by suicide are male

Transgender adults are nearly 9x more likely to attempt suicide at some point in their lifetime compared to the general population

2020: Recognizing The Impact
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2020 was a year of challenges, marked by loss and the uncertainty of the COVID-19 pandemic.

We must recognize the significant impact of the pandemic on our mental health-and the importance of increasing access to timely and effective care for those who need it.

1 in 15 U.S adults experienced both a substance use disorder and mental illness

12+ million U.S adults had serious thoughts of suicide

1 in 5 U.S adults report that the pandemic had a significant negative impact on their mental health

Among people aged 12 and older who drink alcohol, 15% report increased drinking

Among people aged 12 and older who use drugs, 10% report increased use

Among U.S. adults who received mental health services:

26.3 million U.S adults received virtual mental health services in the past year

2020: Youth & Young Adults
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Youth and young adults experienced a unique set of challenges during the COVID-19 pandemic-isolation from peers, adapting to virtual learning, and changes to sleep habits and other routines.

We must recognize the significant impact of these experiences on young people's mental health-and the importance of providing the education, care and support they need.

Among U.S. adolescents (aged 12-17):

Among U.S. young adults (aged 18-25):

1 in 5 young people report that the pandemic had a significant negative impact on their mental health

1 in 10 people under age 18 experience a mental health condition following a COVID-19 diagnosis

Mental Illness And The Criminal Justice System
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People with mental illness deserve help, not handcuffs. Yet people with mental illness are overrepresented in our nation's jails and prisons. We need to reduce criminal justice system involvement and increase investments in mental health care.

CRIMINAL JUSTICE SYSTEM

About 2 million times each year, people with serious mental illness are booked into jails.

About 2 in 5 people who are incarcerated have a history of mental illness (37% in state and federal prisons and 44% held in local jails).

66% of women in prison reported having a history of mental illness, almost twice the percentage of men in prison.

Nearly one in four people shot and killed by police officers between 2015 and 2020 had a mental health condition.

Suicide is the leading cause of death for people held in local jails.

An estimated 4,000 people with serious mental illness are held in solitary confinement inside U.S. prisons.

COMMUNITIES

70% of youth in the juvenile justice system have a diagnosable mental health condition.

Youth in detention are 10 times more likely to suffer from psychosis than youth in the community.

About 50,000 veterans are held in local jails - 55% report experiencing a mental illness.

Among incarcerated people with a mental health condition, non-white individuals are more likely to go to solitary confinement, be injured, and stay longer in jail.

ACCESS TO CARE

About 3 in 5 people (63%) with a history of mental illness do not receive mental health treatment while incarcerated in state and federal prisons.

Less than half of people (45%) with a history of mental illness receive mental health treatment while held in local jails.

People who have healthcare coverage upon release from incarceration are more likely to engage in services that reduce recidivism.

Mental Health & Access To Care In Rural America
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People from all communities are affected by mental illness, but rural Americans often experience unique barriers to managing their mental health.

Among U.S. adults in nonmetropolitan areas, 2020:

21% experienced mental illness

6% experienced serious mental illness

13% experienced a substance use disorder

5% had serious thoughts of suicide

Access to Treatment is Severely Limited

25+ Million rural Americans live in a Mental Health Professional Shortage Area, where there are too few providers to meet demand

Some Populations Face Additional Challenges

53% of rural adults say the COVID-19 pandemic has affected their mental health

66% of farmers and farmworkers

71% of younger adults aged 18-34

Many rural states have a postpartum depression rate higher than the national average of 13%:

21% in Alabama

22% in Mississippi

23% in Arkansas

Rural youth are at an increased risk of suicide, but highly rural areas have fewer youth suicide prevention services

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Millions of people in the U.S. are affected by mental illness each year. It's important to measure how common mental illness is, so we can understand its physical, social and financial impact - and so we can show that no one is alone. These numbers are also powerful tools for raising public awareness, stigma-busting and [...]

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I stumbled across this website while looking up resources for mental health. Healthy People is targeted towards helping everyone live healthy lives have a good sense of well being. This website is wanting to make an improvement in those with mental and substance disorders who get treatment. The data they have from 2018 says that 3.4% of those who had mental health/substance use disorder actually got treatment for both. It gives you another good perspective of the need for more resources for those with mental health and substance use disorders. I think that this site is fairly inclusive.

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Increase the proportion of people with substance use and mental health disorders who get treatment for both — MHMD‑07 - Healthy People 2030 | health.gov

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Adults with both a mental health and substance use disorder often get treated for one or the other but not both. An approach that treats both disorders together is critical for getting people the care they need.

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Found searching NIH website for Mental Health Statistics. I think it is targeting more specifically for people that are using the statistics in research. I believe that it is evidence based because it includes data points from several different resources as well as data tables. This helps show the proportions of mental illness in relation to resources avaliable and that we should be doing better to provide more resources. I feel that it was fairly inclusive it used ages 18+ for the survey.

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National Institute of Mental Health (NIMH)

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Mental illnesses are common in the United States. It is estimated that more than one in five U.S. adults live with a mental illness (57.8 million in 2021). Mental illnesses include many different conditions that vary in degree of severity, ranging from mild to moderate to severe. Two broad categories can be used to describe these conditions: Any Mental Illness (AMI) and Serious Mental Illness (SMI). AMI encompasses all recognized mental illnesses. SMI is a smaller and more severe subset of AMI. Additional information on mental illnesses can be found on the NIMH Health Topics Pages.

Definitions

The data presented here are from the 2021 National Survey on Drug Use and Health (NSDUH) by the Substance Abuse and Mental Health Services Administration (SAMHSA). For inclusion in NSDUH prevalence estimates, mental illnesses include those that are diagnosable currently or within the past year; of sufficient duration to meet diagnostic criteria specified within the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV); and, exclude developmental and substance use disorders.

Any Mental Illness

Any mental illness (AMI) is defined as a mental, behavioral, or emotional disorder. AMI can vary in impact, ranging from no impairment to mild, moderate, and even severe impairment (e.g., individuals with serious mental illness as defined below).

Serious Mental Illness

Serious mental illness (SMI) is defined as a mental, behavioral, or emotional disorder resulting in serious functional impairment, which substantially interferes with or limits one or more major life activities. The burden of mental illnesses is particularly concentrated among those who experience disability due to SMI.

Prevalence of Any Mental Illness (AMI)

Figure 1 shows the past year prevalence of AMI among U.S. adults.

In 2021, there were an estimated 57.8 million adults aged 18 or older in the United States with AMI. This number represented 22.8% of all U.S. adults.

The prevalence of AMI was higher among females (27.2%) than males (18.1%).

Young adults aged 18-25 years had the highest prevalence of AMI (33.7%) compared to adults aged 26-49 years (28.1%) and aged 50 and older (15.0%).

The prevalence of AMI was highest among the adults reporting two or more races (34.9%), followed by American Indian / Alaskan Native (AI/AN) adults (26.6%). The prevalence of AMI was lowest among Asian adults (16.4%).

Figure 1

*Persons of Hispanic origin may be of any race; all other racial/ethnic groups are non-Hispanic. NH/OPI = Native Hawaiian / Other Pacific Islander | AI/AN = American Indian / Alaskan Native

Mental Health Services - AMI

Figure 2 presents data on mental health services (including virtual services) received within the past year by U.S. adults aged 18 or older with any mental illness (AMI). NSDUH defines mental health services as having received inpatient treatment/counseling or outpatient treatment/counseling, or having used prescription medication for problems with emotions, nerves, or mental health.

In 2021, among the 57.8 million adults with AMI, 26.5 million (47.2%) received mental health services in the past year.

More females with AMI (51.7%) received mental health services than males with AMI (40.0%).

The percentage of young adults aged 18-25 years with AMI who received mental health services (44.6%) was lower than adults with AMI aged 26-49 years (48.1%) and aged 50 and older (47.4%).

Figure 2

*Persons of Hispanic origin may be of any race; all other racial/ethnic groups are non-Hispanic. Note: Estimates for Native Hawaiian / Other Pacific Islander and, American Indian / Alaskan Native groups are not reported in the above figure due to low precision of data collection in 2021.

Prevalence of Serious Mental Illness (SMI)

Figure 3 shows the past year prevalence of SMI among U.S. adults.

In 2021, there were an estimated 14.1 million adults aged 18 or older in the United States with SMI. This number represented 5.5% of all U.S. adults.

The prevalence of SMI was higher among females (7.0%) than males (4.0%).

Young adults aged 18-25 years had the highest prevalence of SMI (11.4%) compared to adults aged 26-49 years (7.1%) and aged 50 and older (2.5%).

The prevalence of SMI was highest among AI/AN adults (9.3%), followed by adults reporting two or more races (8.2%). The prevalence of SMI was lowest among Asian adults (2.8%).

Figure 3

* Persons of Hispanic origin may be of any race; all other racial/ethnic groups are non-Hispanic. NH/OPI = Native Hawaiian / Other Pacific Islander | AI/AN = American Indian / Alaskan Native.

Mental Health Services - SMI

Figure 4 presents data on mental health services received within the past year by U.S. adults 18 or older with serious mental illness (SMI). The NSDUH defines mental health services as having received inpatient treatment/counseling or outpatient treatment/counseling or having used prescription medication for problems with emotions, nerves, or mental health.

In 2021, among the 14.1 million adults with SMI, 9.1 million (65.4%) received mental health treatment in the past year.

More females with SMI (67.6%) received mental health treatment than males with SMI (61.3%).

The percentage of young adults aged 18-25 years with SMI who received mental health treatment (57.9%) was lower than adults with SMI aged 26-49 years (67.0%) and aged 50 and older (71.0%).

Figure 4

*Persons of Hispanic origin may be of any race; all other racial/ethnic groups are non-Hispanic. Note: Estimates for Asian, Native Hawaiian / Other Pacific Islander, and American Indian / Alaskan Native groups are not reported in the above figure due to low precision.

Prevalence of Any Mental Disorder Among Adolescents

Based on diagnostic interview data from National Comorbidity Survey Adolescent Supplement (NCS-A), Figure 5 shows lifetime prevalence of any mental disorder among U.S. adolescents aged 13-18.¹

An estimated 49.5% of adolescents had any mental disorder.

Of adolescents with any mental disorder, an estimated 22.2% had severe impairment and/or distress. DSM-IV based criteria were used to determine severity level.

Figure 5

Data Sources

1. Merikangas KR, He JP, Burstein M, Swanson SA, Avenevoli S, Cui L, Benjet C, Georgiades K, Swendsen J. Lifetime prevalence of mental disorders in U.S. adolescents: results from the National Comorbidity Survey Replication--Adolescent Supplement (NCS-A). J Am Acad Child Adolesc Psychiatry. 2010 Oct;49(10):980-9. PMID: 20855043

2. Substance Abuse and Mental Health Services Administration. (2022). Key substance use and mental health indicators in the United States: Results from the 2021 National Survey on Drug Use and Health (HHS Publication No. PEP22-07-01-005, NSDUH Series H-57). Rockville, MD: Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. Retrieved from https://www.samhsa.gov/data/report/2021-nsduh-annual-national-report .

Statistical Methods and Measurement Caveats

National Survey on Drug Use and Health (NSDUH)

Diagnostic Assessment:

The NSDUH AMI and SMI estimates were generated from a prediction model created from clinical interview data collected on a subset of adult NSDUH respondents who completed an adapted (past 12 month) version of the Structured Clinical Interview for DSM-IV-TR Axis I Disorders (Research Version, Non-patient Edition) (SCID-I/NP; First, Spitzer, Gibbon, & Williams, 2002), and was differentiated by level of functional impairment based on the Global Assessment of Functioning Scale (GAF; Endicott, Spitzer, Fleiss, & Cohen, 1976).

The assessment included diagnostic modules assessing the following: mood, anxiety, eating, impulse control, substance use, adjustment disorders, and a psychotic symptoms screen.

The assessment did not contain diagnostic modules assessing the following: adult attention deficit hyperactivity disorder (ADHD), autism spectrum disorders, schizophrenia or other psychotic disorders (although the assessment included a psychotic symptom screen).

People who only have disorders that are not included in these diagnostic modules may not be adequately detected. However, there are known patterns of high comorbidities among mental disorders; these patterns increase the likelihood that people who meet AMI and/or SMI criteria were detected by the study, as they may also have one or more of the disorders assessed in the SCID-I/NP.

Population:

The entirety of NSDUH respondents for the AMI and SMI estimates were the civilian, non-institutionalized population aged 18 years old or older residing within the United States.

The survey covered residents of households (persons living in houses/townhouses, apartments, condominiums; civilians living in housing on military bases, etc.) and persons in non-institutional group quarters (e.g., shelters, rooming/boarding houses, college dormitories, migratory workers' camps, and halfway houses).

The survey did not cover persons who, for the entire year, had no fixed address (e.g., homeless and/or transient persons not in shelters); were on active military duty; or who resided in institutional group quarters (e.g., correctional facilities, nursing homes, mental institutions, long-term hospitals).

Some people in these excluded categories had AMI and/or SMI, but were not accounted for in the NSDUH AMI and/or SMI estimates.

Data regarding sex of the respondent was assessed using male and female categories only. Gender identity information was not collected in the survey.

Survey Non-response:

In 2021, 53.0% of the selected NSDUH sample of people 18 or older did not complete the interview. This rate of non-response is higher than in previous years. Please see the Background on the 2021 NSDUH and the COVID-19 Pandemic section below for more information.

Reasons for non-response to interviewing include the following: refusal to participate (30.1%); respondent unavailable or never at home (18.8%); and other reasons such as physical/mental incompetence or language barriers (4.2%).

People with mental illness may disproportionately fall into these non-response categories. While NSDUH weighting includes non-response adjustments to reduce bias, these adjustments may not fully account for differential non-response by mental illness status.

Data Suppression:

For some groups, data are not reported due to low precision. Data may be suppressed in the above charts if the data do not meet acceptable ranges for prevalence estimates, standard error estimates, and sample size.

Background on the 2021 NSDUH and the COVID-19 Pandemic:

Data collection methods for the 2021 NSDUH changed in several ways because of the COVID-19 pandemic: the 2021 NSDUH continued the use of multimode data collection procedures (both in-person and virtual data collection) that were first implemented in the fourth quarter of the 2020 NSDUH. Overall, 54.6% of interviews were completed via the web, and 45.4% were completed in person. In 2021, the weighted response rates for household screening and for interviewing were 22.2% and 46.2%, respectively, for an overall response rate of 10.3% for people aged 12 or older.

Given the use of multimode data collection procedures throughout the entirety of the collection year and the rate of non-response, comparison of estimates from the 2021 NSDUH with those from prior years must be made with caution.

Please see the 2021 National Survey on Drug Use and Health Methodological Summary and Definitions report for further information on how these data were collected and calculated.

National Comorbidity Survey Adolescent Supplement (NCS-A)

Diagnostic Assessment and Population:

The NCS-A was carried out under a cooperative agreement sponsored by NIMH to meet a request from Congress to provide national data on the prevalence and correlates of mental disorders among U.S. youth. The NCS-A was a nationally representative, face-to-face survey of 10,123 adolescents aged 13 to 18 years in the continental United States. The survey was based on a dual-frame design that included 904 adolescent residents of the households that participated in the adult U.S. National Comorbidity Survey Replication and 9,244 adolescent students selected from a nationally representative sample of 320 schools. The survey was fielded between February 2001 and January 2004. DSM-IV mental disorders were assessed using a modified version of the fully structured World Health Organization Composite International Diagnostic Interview.

Survey Non-response:

The overall adolescent non-response rate was 24.4%. This is made up of non-response rates of 14.1% in the household sample, 18.2% in the un-blinded school sample, and 77.7% in the blinded school sample. Non-response was largely due to refusal (21.3%), which in the household and un-blinded school samples came largely from parents rather than adolescents (72.3% and 81.0%, respectively). The refusals in the blinded school sample, in comparison, came almost entirely (98.1%) from parents failing to return the signed consent postcard.

For more information, see PMID: 19507169 and the NIMH NCS-A study page.

Last Updated: March 2023

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An overview of statistics for mental illnesses. Mental illnesses are common in the United States. One in six U.S. adults lives with a mental illness (43.4 million in 2015). Mental illnesses include many different conditions that vary in degree of severity, ranging from mild to moderate to severe.

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Effects of COVID/ Mental Health of healthcare workers

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Effects of COVID/ Mental Health of healthcare workers

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Found using Google Scholar looking for more research for mental health. This is targeted for those studying the correlation between mental health and covid. I think it is evidence based because the researchers did a cross-sectional web survey to get their data and frame the rest of their research. It helps to show just how many people were effected from metal health during COVID especially in the hospitals. I think the survey could have been a little more inclusive with other countries , it was originally done in Nepal.

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Mental health impacts among health workers during COVID-19 in a low resource setting: a cross-sectional survey from Nepal

Abstract

Background

Health care workers exposed to COVID-19 might be at increased risk of developing mental health problems. The study aimed to identify factors associated with anxiety, depression and insomnia among health workers involved in COVID-19 response in Nepal.

Methods

This was a cross-sectional web-based survey conducted between April 26 and May 12, 2020. A total of 475 health workers participated in the study. Anxiety and depression were measured using a 14-item Hospital Anxiety and Depression Scale (HADS: 0-21) and insomnia was measured by using a 7-item Insomnia Severity Index (ISI: 0-28). Multivariable logistic regression analysis was done to determine the risk factors of mental health outcomes.

Results

Overall, 41.9% of health workers had symptoms of anxiety, 37.5% had depression symptoms and 33.9% had symptoms of insomnia. Stigma faced by health workers was significantly associated with higher odds of experiencing symptoms of anxiety (AOR: 2.47; 95% CI: 1.62-3.76), depression (AOR: 2.05; 95% CI: 1.34-3.11) and insomnia (AOR: 2.37; 95% CI: 1.46-3.84). History of medication for mental health problems was significantly associated with a higher likelihood of experiencing symptoms of anxiety (AOR: 3.40; 95% CI:1.31-8.81), depression (AOR: 3.83; 95% CI: 1.45-10.14) and insomnia (AOR: 3.82; 95% CI: 1.52-9.62) while inadequate precautionary measures in the workplace was significantly associated with higher odds of exhibiting symptoms of anxiety (AOR: 1.89; 95% CI: 1.12-3.19) and depression (AOR: 1.97; 95% CI: 1.16-3.37). Nurses (AOR: 2.33; 95% CI: 1.21-4.47) were significantly more likely to experience anxiety symptoms than other health workers.

Conclusion

The study findings revealed a considerate proportion of anxiety, depression and insomnia symptoms among health workers during the early phase of the pandemic in Nepal. Health workers facing stigma, those with history of medication for mental health problems, and those reporting inadequate precautionary measures in their workplace were more at risk of developing mental health outcomes. A focus on improving mental wellbeing of health workers should be immediately initiated with attention to reduction of stigma, ensuring an adequate support system such as personal protective equipments, and family support for those with history of mental health problems.

Background

The new coronavirus disease 2019 (COVID-19) is currently a threat to the global health in an unprecedented manner. Nepal, a South Asian country, is no exception and is affected by the outbreak with overwhelming effects on its economy and health system. The Government of Nepal initiated its response against COVID-19 immediately after its first reported case in the last week of January in a Nepalese traveller from China [ 1, 2]. As of June 29, 13,248 cases and 29 deaths had been reported in the country despite nationwide lockdown imposed from March 24, which continued for nearly 10 weeks [ 3].

The mental health impact of a disease outbreak is usually neglected during pandemic management although the consequences are costly [ 4]. Early evidence has shown that health workers directly involved in the diagnosis, treatment, and care of patients with COVID-19 are at risk of developing mental health symptoms [ 5, 6, 7, 8]. Similar adverse psychological reactions were reported among health care workers in previous studies during the 2003 Severe Acute Respiratory Syndrome (SARS) outbreak [ 9, 10]. The increasing number of confirmed cases and deaths, work burden, inadequate personal protective equipment (PPE), media coverage, lack of specific treatment, vulnerability to infection and having to stay in quarantine, as well as feelings of being inadequately supported in the workplace, can contribute to the mental burden of health workers [ 11].

Psychological wellbeing has an important impact on individuals' performance. The impact of COVID-19 on mental health is well documented in various countries among different populations including health professionals [ 4]. However, evidence regarding the impact of the COVID-19 pandemic on health professionals is not available in Nepal. During the initial response to COVID-19, there were media reports regarding inadequate testing kits, and lack of PPEs [ 12, 13]. At the work place, health workers require a support system to promote their mental wellbeing and their activity need to be continually monitored - this is crucial during health emergencies [ 14]. A timely assessment of mental health status and mental health needs of health workers during emergencies will help the management to respond and reduce psychological distress, and also align health workers to the patient needs. In this context, this study aimed to evaluate mental health outcomes among health care workers involved in the COVID-19 response by quantifying the magnitude of symptoms of depression, anxiety and insomnia and by analysing potential risk factors associated with these symptoms.

Methods

Study design and study participants

A cross-sectional study was conducted via web online survey among health workers working in health facilities in Nepal. Data were collected from April 26 to May 122,020. During the data collection period, Nepal experienced an increase in COVID-19 reported cases from 52 to 217. As of May 12, cases were reported from 19 out of 77 districts of Nepal.

Health professionals working in the management of COVID-19 response, in both public and private health facilities were recruited as study participants through online survey. A network of 25 hub hospitals are designated for COVID-19 management while other hospitals, primary health centres and health posts coordinate with these hub hospitals and run fever clinics for screening of COVID-19 cases. Health professionals included doctors, nurses, pharmacists, diagnostic personnel, paramedics and public health practitioners. A total of 501 responses were received out of which 26 were redundant and hence removed from the analysis. The final sample size of the study was 475.

Data collection methods

The data collection involved two steps: i) identification of survey anchors for participant recruitment online, and ii) survey administration. In the first step, we identified social media platforms and health facility focal persons to recruit the participants followed by non-random sampling of participants interested to participate in the online survey. Online questionnaires on online Google forms were used to collect data from the participants. Study participants were encouraged to fill the online survey form in their leisure. To limit non-health worker's responses to the online survey, forms were only sent upon invitation to potential participants. The inclusion criteria were health workers aged 18 years and above and living in Nepal, and currently working in COVID-19 management. Participants were excluded if they were below 18 years of age, on leave or unable to participate due to physical or emotional distress.

Study variables

The dependent variables in the study included the status of anxiety, depression and insomnia. The independent variables included information about socio-demographic characteristics and work-related variables. The dependent variables and independent variables are presented in Table 1.

Data collection measures

Anxiety, depression and insomnia of the participants were assessed using the 14-item Hospital Anxiety and Depression Scale (HADS), and the 7-item Insomnia Severity Index (ISI). Internal consistency of the tool was ascertained by calculating Cronbach's alpha, which was 0.81, 0.72 and 0.90 for anxiety, depression and insomnia respectively and considered sufficient [ 15, 16].

The HADS is a commonly used tool for measuring anxiety and depression in different settings in many countries including Nepal [ 17, 18, 19, 20, 21, 22]. It has seven items each for measurement of anxiety and depression which are scored from 0 to 21. The total scores of these tools were interpreted as normal (0-7), borderline abnormal (8-10) and abnormal (11-21). For analysis, score more than 7 was considered as the presence of anxiety and depression. Similarly, the score of ISI which records sleep outcome in the past 2 weeks was categorised as no clinically significant insomnia (0-7), subthreshold insomnia (8-14), moderate clinical insomnia (15-21) and severe clinical insomnia (22-28) as in studies done elsewhere [ 8, 23, 24, 25, 26]. For further analysis, a cut-off score of 10 was used to categorise the presence or absence of insomnia as suggested by Morin CM et al. [ 27].

Data analysis

Descriptive analysis was done by calculating frequency and percentages for categorical variables and mean and standard deviation for continuous variables. Chi-square test was used to determine the association between categorical independent variables and categorical dependent variables (Additional file 1). To determine potential factors associated with the outcome variable, multivariable logistic regression analysis was performed, adjusted odds ratio (AOR) and 95% confidence interval (CI) were calculated. For adjusted regression analysis, those variables which were significant at a 10% significance level in bivariate analysis were included in the multivariable logistic regression analysis [ 28]. Similarly, the history of medication for a mental health problem was also fitted into the model regardless of the significance based on the prior knowledge [ 29]. The Variance Inflation Factor (VIF) was calculated before fitting into the model for each of the psychometric scales which showed no evidence of multicollinearity (less than 1.3).

In the multivariable logistic regression models, the effect of gender, ethnicity, profession, education, living with elderly, family member with chronic disease, precautionary measures in the workplace, faced stigma, worked overtime, awareness about government incentive and history of medication for mental health problem was adjusted to identify the factors associated with anxiety symptoms. Similarly for depression, the effect of age, ethnicity, profession, education, living with children, precautionary measures in the workplace, faced stigma, awareness about government incentive and history of medication for mental health problem was adjusted. Likewise for insomnia, the effect of age, ethnicity, profession, education, work experience, living in affected district, faced stigma, working overtime, awareness about government incentive and history of medication for mental health problem was adjusted.

Ethics

Ethical approval for the study was given by the Nepal Health Research Council (Reference number: 2192, 315/2020). Written digital consent was taken from study participants prior to completing the survey form. Participants gave their consent by ticking the designated box. Personal identifiers such as name were not collected during the study. The email address collected from the study participants was only used for quality control and not for analysis purposes.

Results

Socio-demographic characteristic of study participants

Of the study participants, 52.6% were female, 68.4% were in the age group of 20-29 years and 65.9% belonged to the Brahmin/Chhetri ethnic group. The mean (±SD) age of the participants was 28.20 (±5.80) years. More than two-thirds of health workers were either nurses (35.2%) or doctors (33.9%). The majority of the participants were single (62.9%) and had a nuclear family structure (64.8%). More than half of the participants (54.5%) had a family member with a chronic disease condition, 25.1% were living with younger children and 34.3% had elderly people in the family. The percentage of health workers who had a history of medication for any kind of mental health conditions was 4.6% (Table 2).

Work-related characteristics

Regarding the type of health facility, 39% worked in a central or provincial hospital, and 28.2% worked in a private hospital. Nearly half of the participants (45.3%) mentioned working as frontline workers for COVID management while 70.7% had started their job within the last 5 years. The majority of the participants reported changes in their regular job duties (70.3%) and insufficient precautionary measure in their workplace (78.9%) during the outbreak. Around half of the participants (49.1%) were working overtime. The proportion of health workers aware of government incentive scheme for health workers during COVID-19 was 56.8%, of which 69.6% were dissatisfied with this scheme. More than half of the participants (53.7%) faced stigma from the community members. Among those who faced stigma, they were stigmatised because of profession (49.8%), accused of being a carrier of the disease (40.0%), threatened (5.9%) or asked to leave their rented place (4.3%) (Table 3).

Prevalence of anxiety, depression and insomnia

More than one-third of the participants had some symptoms of anxiety (borderline: 23.6% and abnormal: 18.3%). Similarly, 37.5% of the participants experienced symptoms of depression (borderline: 24% and abnormal: 13.5%). Likewise, symptoms of insomnia were prevalent in 33.9% of the participants (sub-threshold insomnia: 26.7%, moderate insomnia: 5.7% and severe clinical insomnia: 1.5%).There was a significant difference in anxiety ( p < 0.001) and depression ( p = 0.001) across different types of profession. However, type of profession was not statistically significant with insomnia ( p = 0.142). Nurses had a higher proportion of symptoms related to abnormal anxiety, abnormal depression and severe clinical insomnia than other professions (Table 4).

Factors associated with anxiety, depression and insomnia among health workers

Stigma experience among health workers was significantly associated with higher odds of experiencing symptoms of anxiety (AOR: 2.47; 95% CI: 1.62-3.76), depression (AOR: 2.05; 95% CI: 1.34-3.11) and insomnia (AOR: 2.37; 95% CI: 1.46-3.84). History of medication for mental health problems was significantly associated with higher likelihood of experiencing symptoms of anxiety (AOR: 3.40; 95% CI: 1.31-8.81), depression (AOR: 3.83; 95% CI: 1.45-10.14) and insomnia (AOR: 3.82; 95% CI: 1.52-9.62). Inadequate precautionary measures in the workplace was significantly associated with higher odds of exhibiting symptoms of anxiety (AOR: 1.89; 95% CI: 1.12-3.19) and depression (AOR: 1.97; 95% CI: 1.16-3.37). As compared to Brahmin/Chhetri ethnic group, Janajati had significantly higher odds of having symptoms of anxiety (AOR = 2.34; 95% CI: 1.44-3.81) and insomnia (AOR = 1.74; 95% CI: 1.04-2.91). Profession wise, nurses (AOR = 2.33; 1.21-4.47) had significantly higher odds of having anxiety symptoms than other health workers while doctors (AOR = 0.57; 95% CI: 0.33-0.99) had significantly lower odds of experiencing symptoms of depression than other health workers. Younger health workers (AOR = 0.33; 95% CI: 0.12-0.91) and those aware of the government incentive for health workers during COVID-19 (AOR = 0.51; 95% CI: 0.34-0.78) were significantly less likely to exhibit symptoms of depression compared with older health workers and those not aware of such incentives. Regarding work experience, those who had less than 5 years' work experience (AOR = 0.50; 95% CI: 0.29-0.85) had lower odds of having symptoms of insomnia compared with those with experience of more than 5 years. Gender, education, living with elderly people, a family member with chronic disease, working overtime and awareness about government incentive was however not statistically significant with the presence of anxiety symptoms. Similarly, ethnicity, education and living with children were not statistically significant with the presence of depression symptoms. Likewise, age, profession, education, working in affected district, working overtime and awareness about government incentive was not statistically significant with the symptoms of insomnia (Tables 5, 6 and 7).

Discussion

This study examined the status of anxiety, depression and insomnia symptoms among health workers in Nepal during the early phase of the COVID19 pandemic. The prevalence of anxiety (41.9%) and depression (37.5%) symptoms among health workers in this study was higher than those found in a recent study conducted among the general population during COVID-19 pandemic in Nepal, which showed that 31% of respondents reported anxiety and 34% of respondents reported depression [ 30]. This might be because health workers have a higher risk of acquiring COVID-19 infection in comparison to the general population, and also due to the stressful and demanding nature of the job. However, the prevalence of anxiety, depression and insomnia in this study was lower than that in health workers from China [ 5] where 44.6, 50.4 and 34.0% of health workers were reported to have anxiety, depression and insomnia respectively. China faced a major impact of COVID-19 and health facilities were overwhelmed with COVID-19 patients requiring hospitalisation and intensive care. The increased risk of infection and stressful environment might have contributed to higher mental health impacts among health workers in China than in Nepal [ 5, 8, 31]. Mental health outcomes among health workers affect their work performance and to address this, specialised mental health services are required [ 8, 32, 33]. The higher perceived risk and having to stay in quarantine during the epidemic might not just result in short term impacts but also lead to long term mental health consequences among health workers [ 34, 35, 36]. There is thus a need to focus on mental wellbeing of health workers involved in the COVID-19 response.

Our findings unveiled that a considerable proportion of health workers in Nepal faced stigma related to COVID-19. Stigma significantly affected all the psychological outcomes among health workers. Stigma among health workers, who are already vulnerable to infection due to increased exposure, might affect their concentration on work. A similar finding was observed in Italy [ 37] where health workers facing stigma during COVID-19 were found to have more burnout, fatigue and psychological distress. It is thus necessary to increase the morale of health workers who are stigmatised, in fear of getting infected or spreading infection to others. Importantly, the drivers and facilitators of stigma in health workers need to be understood for developing an effective response that might require extensive interventions [ 38, 39]. Information directed at the public should thus integrate stigma reduction among health workers as an important strategy towards COVID-19 response.

In this study, inadequate precautionary measures were significantly associated with higher odds of anxiety and depression symptoms among health workers. Lack of precautionary measures including PPE can lead to compromised working conditions, a sense of insecurity and increased exposure to infections. As a large proportion of COVID-19 cases are asymptomatic [ 40], lack of a proper sense of protection among health workers might increase their psychological distress and affect their mental well-being. Three out of four health workers reporting inadequate precautionary measures in the workplace in this study reflects the vulnerability of health workers in Nepal to COVID-19 infections. Studies done globally [ 33, 41, 42, 43] have pointed out the need to equip health workers with PPE as well as provide psychological support to increase resilience to adverse mental health outcomes. This finding should persuade the government of the urgency of arranging adequate precautionary measures for reducing mental health burden among health workers in Nepal.

Our study findings showed that nurses had higher odds of exhibiting anxiety than other health professions. This might be attributed to the higher amount of time spent by them in patient care than other health workers. A study from China also showed that nurses, compared with other health professionals, experienced more unfavourable mental health outcomes [ 5]. Similar findings were found during the SARS epidemic in Canada [ 44] where nurses experienced more psychological distress due to fear, social isolation and work stress. The mental health status of health professionals should thus be closely monitored by the employing health institutions including managing their workload, providing emotional support and responding to their personal needs.

In our study, health workers who had a history of medication for mental health problems had higher odds of exhibiting anxiety, depression and insomnia symptoms compared with those without such history. A similar finding was observed in a study conducted in China where health workers with a history of mental health problems were more likely to have anxiety, depression and stress [ 29]. Family and organisational support will be required for those health workers as the current pandemic might make them more vulnerable to a deterioration in their mental health conditions [ 45, 46].

In this study, gender, work role, marital status, and type of family, living with children, living with elderly people, having a family member with chronic disease, type of health facility, change in duties and working overtime had no significant effect on any mental health outcomes. As our study was conducted in the early phase of the pandemic when no mortality was documented and most of the cases had mild symptoms, working role might not have contributed to a significant difference in mental health outcomes. The other reason could be that health workers working in both frontline and second line might feel equally vulnerable to COVID-19 associated mental health outcomes during the early phase of pandemic. Further studies might be required to confirm these findings as the association might vary over the course of the epidemic in the country.

Recommendations

The unprecedented challenge brought by COVID-19 pandemic is unique in Nepal and a major pressure to its health system after the 2015 Gorkha Earthquake. Health workers in Nepal are currently working under extreme pressure amidst limited health resources such as inadequate staffing, just over 3000 isolation beds and 840 ventilators (increased from 300 ventilators at the beginning of the epidemic) for the population of 29 million [ 3, 47, 48]. It is noteworthy that mental health has not received adequate attention from the government despite its high burden [ 49]. Based on the study findings, we put forward the following recommendations for improving the mental well-being of health workers in Nepal. Firstly, the reduction of stigma among health workers working in COVID-19 response should be prioritised through the mobilization of mass media and community engagement strategy. Provision should be made for living arrangements in the vicinity of health facilities if possible, which may help reduce the stigma faced by the health workers at their residence and neighborhood. This may also reduce the guilt and stress of being a potential carrier and exposing the family members to infection among health workers.. In conditions, where this is not possible,, strict measures against stigmatisation and activities such as forcing health workers to leave their rented home should be taken .. Secondly, there should be an enabling work environment with a good support system, adequate availability of PPE, proper training of health workers on management of COVID-19 and focus on incentives which boost their work morale. It is necessary to provide educational interventions for clearing of doubts of healthcare workers about COVID-19 and provide adequate logistical support to increase protection. Thirdly, personal and family support might be required especially in those who have a history of medication for mental health problems. Finally, psychological intervention with a focus on health workers should be a part of preparedness to reduce its impact not only on their well-being but also on the health system at large.

Study limitations

The study has some limitations which need to be acknowledged. Firstly, the study was conducted during the early phase of pandemic and thus the mental health outcomes might still reflect conditions existing before the pandemic. The relative contribution of the pandemic to the increase in mental health disorders needs to be evaluated using a longitudinal study design. Secondly, there might have been the introduction of selection bias as those health workers without internet access, older health workers, and those who might have been busy in their work duties might not have participated in the study. Thirdly, there might be respondent bias as the findings were self-reported by health workers and based on a subjective scale. Importantly, the tool used in the study should be taken into consideration while reporting mental health outcomes. Although the history of mental illness and medications taken for any kind of mental illness was included in the questionnaire, specific type of mental illness was not identified, which may or may not have affected the current symptoms of anxiety, depression and insomnia. Despite limitations, this study provides early evidence on the mental health status among health workers during the COVID-19 pandemic in Nepal, which should be of interest to policymakers, health facility managers and those involved in the response to COVID-19 or anyfuture epidemic.

Conclusions

This study reported a high prevalence of symptoms of anxiety, depression and insomnia among health workers in Nepal during the initial phase of the pandemic. More than half of the health workers faced stigma and only one out of five health workers reported precautionary measures in their workplace as sufficient. Stigma and history of medication for mental health problems was significantly associated with all the mental health outcomes while inadequate precautionary measures was associated with higher odds of having anxiety and depression symptoms. Nurses had higher odds of developing anxiety than other health workers. Improving mental wellbeing of health workers is recommended by focusing on stigma reduction, equipping health workers with protective measures, as well as ensuring personal and family support for those with a history of mental health issues.

Availability of data and materials

All data generated during this study are included in the manuscript and the supplementary file.

Abbreviations

AOR:

Adjusted Odds Ratio

CI:

Confidence interval

COVID-19:

Corona virus disease 2019

HADS:

Hospital Anxiety Depression Scale

ISI:

Insomnia Severity Index

MERS:

Middle East Respiratory Syndrome

PPE:

Personal protective equipment

SARS:

Severe Acute Respiratory Syndrome

SD:

Standard deviation

VIF:

Variance Inflation Factor

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Acknowledgements

The authors would like to acknowledge all the health workers involved in the study and the Policy, Planning and Monitoring Division of Ministry of Health and Population for providing us a letter of support for the study. We are also grateful to Shiva Raj Mishra and Ms. Anna Durrance-Bagale for reviewing the manuscript.

Funding

None.

Author information

Authors and Affiliations

1. Institute of Medicine, Tribhuvan University, Kathmandu, Nepal

Pratik Khanal & Kiran Paudel

2. National Academy for Medical Sciences, Kathmandu, Nepal

Navin Devkota & Devavrat Joshi

3. Center for Research on Environment, Health and Population Activities (CREHPA), Kathmandu, Nepal

Minakshi Dahal

Contributions

PK, ND and KP conceived the concept and design of the study. ND and KP conducted the survey while PK and MD conducted data analysis. PK wrote the first draft, which underwent substantial revision based on the inputs from all other authors. DJ supervised the whole study process. All the authors have read, reviewed and endorsed the final version of the manuscript.

Corresponding author

Correspondence to Pratik Khanal.

Ethics declarations

Ethics approval and consent to participate

Ethical approval for this study was provided by the Nepal Health Research Council, Kathmandu, Nepal (Registration number: 2192; 315/2020) while a letter of support was obtained from Ministry of Health and Population. An informed e-consent was obtained from individual participants. Study participants were informed clearly about their freedom to opt out of the study at any point of time without providing justification for doing so.

Consent for publication

Not applicable.

Competing interests

Authors have no competing interest associated with this paper. The author's affiliation does not necessarily reflect the view of their employing organisations. The authors prepared a policy brief of 2 pages based on preliminary findings and have shared it with the Ministry of Health and Population.

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Supplementary information

. Anxiety and its associated factors. Additional Table 2. Depression and its associated factors. Additional Table 3. Insomnia and its associated factors

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Khanal, P., Devkota, N., Dahal, M. et al. Mental health impacts among health workers during COVID-19 in a low resource setting: a cross-sectional survey from Nepal. Global Health 16, 89 (2020). https://doi.org/10.1186/s12992-020-00621-z
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Keywords

Anxiety

COVID-19

Depression

Health workers

Insomnia

Mental health

Nepal

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Mental health impacts among health workers during COVID-19 in a low resource setting: a cross-sectional survey from Nepal - Globalization and Health

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Background Health care workers exposed to COVID-19 might be at increased risk of developing mental health problems. The study aimed to identify factors associated with anxiety, depression and insomnia among health workers involved in COVID-19 response in Nepal. Methods This was a cross-sectional web-based survey conducted between April 26 and May 12, 2020.

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Found by searching for research about mental health. Target audience is those caring for people with eating disorders/ providers. I think the data is evidence based because from what I found they were using early screening to detect the eating disorders. I think that this a good resource for those who need to learn more about eating disorders. I feel that it is also very inclusive because it included all of the eating disorders, not just picking and choosing which one.

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Eating Disorders | MQ Mental Health Research

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Transforming mental health through research

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Found searching for data points for mental health. The targeted audience for this page is those caring for people with mental health disorders as well as treatment centers. The data is evidence based, it is from a report that came out in 2022. It can be used to help improve access to treatment for those who need it as well as other resources for them. This piece only includes Americans, to be more inclusive it could potentially become a report that is global.

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What the numbers tell us about the need for care in Pennsylvania

Pennsylvania-and the nation-are in the midst of a mental health crisis.

According to a report released recently by Mental Health America, 19.86 percent of adults are experiencing a mental illness. That's equivalent to nearly 50 million Americans. Among that group, 4.91 percent are experiencing a severe mental illness.

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HAP's behavioral health agenda includes policies to expand access to care so that Pennsylvanians can obtain the services that best fit their needs.

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Understanding the Behavioral Health Crisis through Data

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Pennsylvania-and the nation-are in the midst of a mental health crisis. According to a report released recently by Mental Health America, 19.86 percent of adults are experiencing a mental illness. That's equivalent to nearly 50 million Americans. Among that group, 4.91 percent are experiencing a severe mental illness.

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Found through Johns Hopkins website, the general research of mental illness is targeted towards any illness such as bipolar, schizophrenia, etc. Going further into the website I found research from 2016 regarding workplace mental health. We just completed a project about self care with nurses, this research about workplace mental health can help to find other ways to manage stress.
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Johns Hopkins Bloomberg School of Public Health

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The Department of Mental Health covers a wide array of topics related to mental health, mental illness, and substance abuse. We emphasize ongoing research that enriches and stimulates the teaching programs. All students and fellows are encouraged to participate in at least one research group. Faculty and students from multiple disciplines work together within and across several major research areas:

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Research and Practice | Johns Hopkins Bloomberg School of Public Health

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The Department of Mental Health covers a wide array of topics related to mental health, mental illness, and substance abuse. We emphasize ongoing research that enriches and stimulates the teaching programs. All students and fellows are encouraged to participate in at least one research group.

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National Helpline for mental health and substance use disorders

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National Helpline for mental health and substance use disorders

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Found by searching for mental health awareness, target audience is people suffering from mental health and substance use disorders. I think that it does use evidence based for the resource because it collects data from people using the resource and then uses it to help evaluate how the resource is doing.
Here is a link for the evaluation https://www.samhsa.gov/sites/default/files/samhsa-strategic-plan.pdf
It can be used as a resource for those that come in to our ER's especially and need someone to talk to anonymously. I think that this resource is very inclusive because it includes all of mental health disorders as well as substance use disorders.

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Substance Abuse and Mental Health Services Administration

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Frequently Asked Questions - What is SAMHSA’s National Helpline?