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Algorithms are destroying curiosity, ruining childhood development

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Algorithms are destroying curiosity, ruining childhood development

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A US Senator's opinion on how algorithms serve up content on a platter, denying kids the chance to be curious or think critically

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Opinion | Algorithms Are Making Kids Desperately Unhappy

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Algorithmic recommendations aren’t just bad for kids’ mental health; they’re taking away the journey of discovery that comes with being human.

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Impact of social media on mental health. 

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Impact of social media on mental health. 

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This article talks about statistics rising in mental heath disorders in relation to social media and some legal actions that have been taken.

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Civic Online Reasoning Students are confused about how to evaluate online information. We all are. The COR curriculum provides free lessons and assessments that help you teach students to evaluate online information that affects them, their communities, and the world.

This is what this resource provides ↑

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Free lessons and assessments that help you teach students to evaluate online information that affects them, their communities, and the world.

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Effects Of Video Games On Teen Mental Health

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Effects Of Video Games On Teen Mental Health

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This article is about how video games impact teenagers by showing the negative and positive effects.

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Effects Of Video Games On Teen Mental Health - Bright Path Adolescent Mental Health

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In the dynamic landscape of today’s entertainment, video games have etched an irrefutable mark on the hearts and minds of teenagers. With a profound influence

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The teen years are often marked by heightened stress and increasing pressures. From personal relationships to future plans, teens must juggle expectations from family, teachers, friends, social media, and even themselves. These expectations build up and at times can become overwhelming. And young people are particularly vulnerable because many are still developing coping skills to handle these pressures, potentially leading to feelings of anxiety and burnout.

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Unpacking Grind Culture in American Teens: Pressure, Burnout, and the Role of Social Media

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Teens face feelings of stress and burnout as they balance pressures and expectations from family, school, friends, and more. Keeping an open mind about the role of social media and stressing self-care can reduce pressures and support teens’ well-being.

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Impact of social media on attention span and productivity 

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Impact of social media on attention span and productivity 

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This article focuses on how social media captivates people and uses certain strategies to control their attention spans. It also talks about the other aspects of mental health that social media damages.

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Attention & Mental Health - Center for Humane Technology

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While we often use technology because it informs and entertains us, there’s clear evidence that it also has serious, negative side effects on our mental health, including: increased anxiety, higher rates of depression, more loneliness, lower self-esteem, decreased attention spans, and less quality sleep.

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This article shows the difference between screen times. Difference between different age groups, countries, and years.

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December 20, 2024Exploring Global Trends in Screen Time Usage

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Exploring Global Trends in Screen Time Usage

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The impact of technology and social media

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The impact of technology and social media

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This article shows how individuals from ages 18-24 are impacted in many ways by technology and social media. Not just by having access 24/7 but the unknown addiction it holds over many young adults.

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Much like many relationships a person might have between ages 18 and 24, the relationship a young person has with social media can be complicated. No matter where they live, respondents in a new global survey said social media usage can lead to a fear of missing out (FOMO) or poor body image, but it also can help with social connections and self-expression.

McKinsey Health Institute's (MHI's) 2022 Global Gen Z Survey asked more than 42,000 respondents in 26 countries across continents questions based on the four dimensions of health: mental, physical, social, and spiritual. MHI then analyzed differences and similarities across generations and countries, with a hope of informing the broader dialogue around Gen Z mental health.

Gen Zers, on average, are more likely than other generations to cite negative feelings about social media. They are also more likely to report having poor mental health. But correlation is not causation, and our data indicates that the relationship between social media use and mental health is complex. One surprise: Older generations' engagement with these platforms is on par with Gen Zers. For example, baby boomers in eight of the 26 countries surveyed report spending as much time on social media as Gen Zers, with millennials being the most likely to post. And while negative impacts of social media were reported across cohorts, positive effects were even more common-more than 50 percent of all groups cited self-expression and social connectivity as positives from social media.

More than 50 percent of all groups cited self-expression and social connectivity as positives from social media.

There are also signs that technology provides access to supportive mental health resources for younger people. Gen Z respondents are more likely than other generations to use digital wellness apps and digital mental health programs. Additionally, respondents indicate that certain aspects of social media use can benefit their mental health, such as using social media for self-expression. Young refugees and asylum seekers are among those most likely to cite social media as a tool to stay connected and decrease loneliness.

In the six insights below, MHI delves deeper into the ways in which mental health, technology, and social media intersect for our respondents (see sidebar "Methodology" for further detail). This survey covered additional topics such as climate change and spiritual health (for selected insights, see sidebars "Climate change is a concern for many respondents" and "Gen Z and spiritual health: Insights").

Technology and social media can be a part of the solution

Social media and technology, while part of the broader dialogue around youth mental health, can be powerful tools in promoting well-being and offering scaled mental health support. For example, developers might consider embedding algorithms that make it easier for youth expressing psychological distress to find support groups, crisis hotlines, or emergency mental health services. Additionally, digital mental health companies could consider partnering with virtual and community-based providers to connect people with high-acuity needs to timely and culturally-appropriate crisis services.

Around the world, communities are struggling to provide young people with someone to call, someone to respond, or a safe place to get help during mental health, substance use, and/or suicidal crises. The availability of crisis supports globally is varied, with the majority of countries having no national suicide or mental health crisis line. In addition, communities in every geography lack adequate community mental health services infrastructure to respond to the volume of crises young people experience each year, instead relying on schools, emergency rooms, hospitals, law enforcement, or families to bridge a gap that could save lives and livelihoods. Dispatching specially trained mobile teams or providing a safe place to go in crisis is even more rare-a gap that technology could bridge.

Collaboration between technology companies, mental health professionals, educators, employers, policy makers, and the wider community is necessary. By prioritizing mental health and utilizing technology in a positive way, young people are more likely to achieve and sustain better health. Other strategies that could be considered include using social media to build supportive online communities for affinity groups and promoting youth leaders to create and disseminate content that promotes mental health. Researchers and companies can explore evidence-based strategies such as mental health promotion and mindfulness programs to mitigate the negative effects of social media and to help young people use social media as a platform for authentic self-expression.

A "precision prevention" approach to talking with young people about the role of technology in their lives may help create a more informed, supportive, and healthful environment. By providing parents, educators, and healthcare professionals with these tools, they can become actively engaged in promoting the health of Gen Z and beyond. While addressing these issues may seem overwhelming, it is essential that stakeholders work together to help improve the mental health of young people.

MHI is an enduring, non-profit-generating global entity within McKinsey. MHI strives to catalyze actions across continents, sectors, and communities to achieve material improvements in health, empowering people to lead their best possible lives. MHI sees supporting youth mental health as essential to adding years to life and life to years.

If you would like to learn more about the McKinsey Health Institute (MHI) 2022 Global Gen Z survey and the additional data and insights the McKinsey Health Institute has from the survey, please submit an inquiry via the MHI "contact us" form. The McKinsey Health Institute, as a non-profit-generating entity of McKinsey, is creating avenues for further research that can catalyze action.

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Gen Z mental health: The impact of tech and social media

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A new McKinsey Health Institute survey of more than 42,000 respondents in 26 countries explores the impact of tech and social media on Gen Z's mental health.

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Brain health consequences of digital technology use

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Brain health consequences of digital technology use

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The article explores both the negative and positive impacts of frequent digital technology usage on brain function and behavior. Potential harmful effects include increased attention-deficit symptoms, impaired emotional and social intelligence, technology addiction, social isolation, disrupted sleep, and impaired brain development. Conversely, certain digital tools, such as specific apps and video games, may enhance memory, multitasking abilities, fluid intelligence, and other cognitive functions. The article emphasizes the need for further research on underlying positive and negative effects of digital technology on brain health.

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*Dr Small, Semel Institute, 760
Westwood Plaza, Los Angeles, California 90024, USgsmallmednet.ucla.edu

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Brain health consequences of digital technology use

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Emerging scientific evidence indicates that frequent digital technology use has a significant impact—both negative and positive—on brain function and behavior. Potential harmful effects of extensive screen time and technology use include heightened…

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This article talks about the impact of social media on the adolescent and teenage brain, and how it affects growth among Gen Z.

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What Social Media Does to the Teen Brain

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Despite the headlines, the impact of social apps on adolescent mental health isn’t so clear.

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This article explores the positive and negative effects of social media on relationships. It discusses how social media can enhance connectivity and communication but also lead to issues like jealousy, decreased quality time, and unrealistic relationship expectations.

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Social media can be helpful for connecting when we can't meet - but it can also rob us of quality time when we can.

Social media can affect all areas of your life, including your relationships with partners, friends, and family members.

These effects can be both harmful and helpful. Although social media can worsen certain relationship problems in some cases, it can also be beneficial when used wisely.

Using social media in a positive way can benefit your relationships with others. Setting healthy boundaries around social media and relationships is a crucial step.

Social media can have a negative effect on your relationships in some cases.

Social media can perpetuate jealousy

Jealousy is a natural, common emotion but when left unchecked, jealousy can damage relationships.

Jealousy is often a reflection of our own insecurities. It often has us making up improbable scenarios in our heads - scenarios that might fuel our anger and insecurity.

When you're feeling insecure, you might see a photograph of your partner with a friend and find yourself wondering if they're having an affair. Or, you might feel like you're not attractive or wealthy enough, so you scroll through your partner's Instagram likes to "investigate" whether they're more attracted to other people.

It's easy to project those difficult emotions onto whatever we see on social media. Your actions might find "evidence" to justify your jealousy, even if your partner is totally faithful.

If you're not managing jealousy in a healthy way, social media can perpetuate it.

Social media can decrease the quality time you spend with your loved ones

Has your partner ever whipped out their phone and started scrolling when you're meant to be on a date? Have you?

A 2018 research paper found that increased social media use can have a negative effect on the amount of quality time people spend with their loved ones. The study was self-reporting and more research is needed.

Because social media is designed to be intriguing and easy to scroll, it can be hard to put down your phone and focus on your partner (or friend), aka "partner phubbing." As a result, it can take up a lot of time and attention.

Without even realizing it, you might focus more on your phone instead of connecting with your loved ones.

According to research from 2021, partner phubbing, or pphubbing, is negatively associated with relationship satisfaction. It can lead to feelings of isolation, jealousy, and less intimacy.

Social media can set unrealistic relationship expectations

It's said that comparison is the thief of joy.

Yet we all tend to compare ourselves to others, especially through social media. You might look at the #RelationshipGoals posts on Instagram and feel like your relationship is lacking, even if you usually feel happy with it.

A 2018 study looked at social media and relationship satisfaction. Those who felt social media played a big role in their lives tended to find their romantic relationships less satisfying.

Increased Instagram usage can lead to a decrease in relationship satisfaction and an increase in conflict and negative outcomes, according to a 2021 study. This dissatisfaction and conflict can then fuel an excessive use of Instagram.

We tend to post the highlights of our relationships on social media (gifts from our partners, couples' getaways, and grand romantic gestures). Compared to this, your day-to-day life with your partner might seem dull.

Even if you don't tend to value expensive gifts or fancy vacations, you might worry that your relationship is inadequate or that your partner feels unloved because your relationship isn't like the ones you see online.

Although we tend to focus on the negative aspects of social media, it can also have positive effects on our relationships.

Social media can help you meet new people

Social media can help you connect with new people who you might have not otherwise met. Forums, dating apps, and Facebook groups all enable you to meet people who share your interests. These might materialize as romantic or platonic relationships.

These relationships could be especially important for marginalized people.

Research from 2021 found that social media can help LGBTQIA+ youths find emotional and social support, largely because social media can help them connect with other members of their community.

Social media can help you stay connected

In addition to helping you form new relationships, social media can help you maintain existing relationships. It's a convenient way to stay updated with your friends' and family members' lives.

A 2020 study hypothesized that social media may help long-distance family members stay connected despite the distance. But more research is needed.

But remember that seeing someone's updates isn't the same as communicating with them. If you find yourself needing company or missing a friend, don't just lurk on their page. Try reaching out directly.

Social media can help you spend quality time with your loved ones

Social media can negatively affect the quality time you spend with loved ones. But when used wisely, social media might offer another way to connect with the people you love.

For example, an old-school friend might post about the latest episode of your favorite show, or your cousin might mention starting a hobby you enjoy. This is a great jumping-off point for a discussion or reconnection.

Social media can also give you ideas on creative ways to spend time with your loved ones. You might see a TikTok about a local exercise class for couples and decide to try it with your partner, or Instagram might provide some exciting date ideas.

The following signs suggest that social media could be harming your relationship:

You feel disconnected from your partner.

You find yourself resenting social media, phones, or technology in general.

You check your partner's social media obsessively for signs of cheating or dissatisfaction with your relationship.

You find yourself wanting to replicate couples you see online.

You compare yourself and your loved ones to those you see online.

You feel inadequate or insecure when you look at other relationships.

You find yourself scrolling social media when you're meant to be spending quality time with your loved one.

Consider trying these tips to minimize or avoid the negative effects of social media on your relationships.

Use social media in moderation

Social media can take up a lot of your time, attention, and energy. This can be dangerous not only for your relationships but for your own mental health.

Try to avoid excessive social media use and use it in moderation. This might take time to get used to, but committing to some phone-free time can be very rewarding.

For example, you might try to:

have phone-free lunches or dinners with your loved ones

make your bedroom a laptop- and phone-free zone

create a family morning routine that doesn't involve social media

take a social media break

Set healthy boundaries

What is your partner OK with you posting on social media? What about your friends?

Consider these tips:

checking in with your loved ones about their social media boundaries

asking before you post a photo of your friends on Instagram

talking with your partner before you update your relationship status on Facebook

Likewise, you deserve to have your own social media boundaries respected. Consider telling your friends upfront if you don't want them to tag you, share pictures of you online, or use social media while you're spending time together.

Be realistic

If you often compare yourself to people you see on social media, you might find it helpful to remember that nobody's social media is a perfect representation of their life.

All of us tend to share important updates and positive news on social media, while seldom sharing mundane happenings or events we don't feel ready to talk about.

Try to avoid comparing your day-to-day life to someone else's highlight reel. If you find yourself feeling inadequate or dissatisfied after scrolling Instagram, consider taking a pause and checking in with yourself.

Social media can have both positive and negative effects on your relationships.

When you manage your social media usage in a healthy way, your relationships are likely to reap the benefits.

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Is Social Media Toxic or Healthy for Relationships?

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Social media can be helpful for staying connected with friends and loved ones. But too much social media use can be harmful to our relationships.

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How addiction to technology affects gen z's mental health and how they function when they don't have access to it.

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How Technology Addiction Is Impacting Generation Z | News | Hofstra University, New York

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While three of 10 adults say they use the internet almost constantly*, it is Generation Z—those born between 1997 and 2012—who face the most severe

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Gen Z is a huge marketing demographic on the internet. 28% of 13-17 year olds say social media influenced there purchasing habits. Although people are likely unaware of the true influence with all the targeted ads forced on them. Only 28% of Gen Z think their economic situation will improve over the next year. Gen Z also tends to follow individual content creators more than millennials who may watch more mainstream media.

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Gen Z have been exposed to technology their whole lives. It's no surprise they navigate online platforms like it's second nature. This generation's age bracket includes anyone born between 1997-2012; the oldest among them are now entering adulthood. They are the first true generation of digital natives, growing up in the age of smartphones and constant connectivity.

What Content is Gen Z Consuming?

Nearly all (95%) American teenagers aged 13 to 17 report using TikTok, with 16% saying they use it almost constantly. - Pew Research Center

Shopping and Purchasing Habits

In Gen Z, aged 15 to 22, 63% of respondents rank high-quality products among the most important factors that encourage them to spend more on a brand, while 45% said they spend more on a brand when a friend or someone they know shops there. - Bluestone PIM

You'll stand the best chance of capturing as many customers as possible if you follow an omnichannel strategy. Although this is true of all generations, it's especially so when it comes to Gen Z. They use many different channels to shop (including social media), and they respond well to personalized experiences/messaging. - Talon.One

Topics of Concern for Gen Z

Social change is a priority for Gen Z, who are often stereotyped as social justice warriors. - Nonprofit Pro

I think there's a real authenticity to the Gen Z generation in saying they want to breathe new life into what corporate responsibility looks like. And one of the biggest elements that's come out of the research in the last few years has been the focus on values. They're looking beyond tangible products and actually trying to understand what is it that makes the company tick. What's its mission? What's its purpose? And what is it actually trying to build for us as a society? - McKinsey

Gen Z most closely mirrors millennials on key social and political issues, but without much of the optimism; More US Gen Zers than any other generation (68%) feel the US is headed in the wrong direction. - Insider Intelligence

Additional Factors Influencing Gen Z

Gen Z tend to be comfortable with collating and cross-referencing various sources of information. According to Google, 74% of Gen Z search for information online and 47% of those are looking to verify specific information.

Conclusion

Gen Z is focused on individual expression and identity in their content consumption . They are more likely to advocate for specific causes that they have researched through online media platforms. And they are more open to discussion with others of differing values and belief systems.

Gen Z places great emphasis on company ethics. They are more likely to purchase from a brand with trusted ethics and more likely to boycott brands they deem problematic. Gen Z also shows a strong aversion to causewashing, opting for brands they think are more genuine.

Their habits will evolve as the generation ages, but for now, it's safe to say that social media, music, and video games remain key ways to reach Gen Z. The rise of Gen Z as a marketing demographic and a participant in the workforce have already had significant effects on content trends.

Events, Resources, + More

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Gen Z Content Consumption Fact Sheet - Content Science Review

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Get key facts about Gen Z audience segments and online content consumption habits for Generation Z.

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How has the internet both positively and negatively affected mental health within our generation?  

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How has the internet both positively and negatively affected mental health within our generation?  

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This article talks about how social media can create or worsen depression and anxiety due to FOMO, unhealthy comparisons, distorted perceptions of reality, and more opportunities to exclude people and cyberbully

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Here's How Social Media Affects Your Mental Health | McLean Hospital

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Using social media can directly impact emotional wellness, physical, and mental health. Here are the signs that you are affected.

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How social media impacts Teens Mental Health

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How social media impacts Teens Mental Health

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This article is about the benefits of using social media and how it can harm teens as well. Yale medicine shares how excessive use of social media is not healthy for teens and gives advice for parents on how to prevent having an unhealthy relationship with social media for kids.

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Mental health issues among teens have been rising for more than a decade, and some experts wonder how much social media use is to blame. If you're a parent questioning if-and how-you should monitor the way your teenager uses social media, you're not alone.

In the spring of 2023, United States Surgeon General Vivek Murthy, MD, MBA, released an advisory called Social Media and Youth Mental Health, in which he says there is growing evidence that social media is causing harm to young people's mental health. Soon after, the American Psychological Association (APA) issued its own health advisory. A year later, in June 2024, Dr. Murthy called for a surgeon general's warning label on social media platforms, which would require an act of Congress to implement.

The issue is complicated, however. While there are indicators that it can have a profound risk of harm to teens (more on that below), social media use aimed at making healthy connections with others may actually be beneficial to some people. Dr. Murthy's report indicates that more research is needed to fully understand the impact of social media. For parents, this means there are no easy answers.

"The issues we face now with social media are similar to those we faced when television came out," says Linda Mayes, MD, chair of the Yale Child Study Center (YCSC). She explains that, as with TV watching, there are pros and cons to social media for young people. "So, how do we help parents filter out the parts that may be detrimental?"

Below, Dr. Mayes and YCSC's Yann Poncin, MD, a child psychiatrist, offer advice for parents trying to help their teenagers use social media in a positive way.

But first, some background.

Social media use and teens: Background, benefits, and harms

As a parent, you might ask yourself, "What, specifically, about social media use can have a negative impact on my teen?"

Dr. Murthy's advisory was based on what it describes as a "substantial review of the available evidence." It raises a variety of concerns, including the amount of time adolescents spend on platforms, the type of content they consume (or are exposed to), and the degree to which their online interactions disrupt activities essential for health, such as sleep and exercise. It points out that social media can also affect young users in different ways, depending on their strengths and vulnerabilities as individuals, as well as their cultural, historical, and socio-economic backgrounds.

The report stresses that the brain is going through a highly sensitive period between the ages of 10 and 19, when identities and feelings of self-worth are forming. Frequent social media use may be associated with distinct changes in the developing brain, potentially affecting such functions as emotional learning and behavior, impulse control, and emotional regulation.

What are the potential benefits of social media use by teens?

Some teenagers experience a benefit when they use social media to foster positive connections with others who share common interests or identities (if they are seeking a connection with others who are, say, members of a particular racial identity), creating a space for self-expression. Relationships formed in communities like these can create opportunities for positive interactions with more diverse peer groups than are available to them offline, according to Dr. Murthy's report.

The advisory points to a 2022 survey of American teenagers and their parents by the Pew Research Center, which showed that a majority of respondents felt that social media helps teenagers feel more accepted (58%), like they have people who can support them through tough times (67%), that they have a place to show their creative side (71%), and that they are more connected to what's going on in their friends' lives (80%).

"Posting to let your friends know how you've been spending your time can be a positive or healthy way to connect and hear about each other's day," says Dr. Poncin. "It's no different than 30 years ago when adolescents would be on the phone for three hours connecting with their friends-only now you're online with your friends, saying, 'Meet you after school,' or 'Did you hear about this?'"

What are the potential harms of social media use by teens?

Over the last decade, increasing evidence has identified the potential negative impact of social media on adolescents. According to a research study of American teens ages 12-15, those who used social media over three hours each day faced twice the risk of having negative mental health outcomes, including depression and anxiety symptoms.

The advisory states that other studies "point to a higher relative concern of harm in adolescent girls and those already experiencing poor mental health, as well as for particular health outcomes, such as cyberbullying-related depression, body image and disordered eating behaviors, and poor sleep quality linked to social media use."

"What's more, the social media algorithms are built to promote whatever you seem interested in," says Dr. Mayes. "If a teen searches for any kind of mental health condition, such as depression or suicide, it's going to feed them information about those things, so soon they may begin to think that everyone around them is depressed or thinking about suicide, which is not necessarily good for mental health."

When does the kind of content teens see become an issue?

Teens can easily access extreme, inappropriate, and harmful content. In certain cases, deaths have been linked to suicide- and self-harm-related content, such as "cutting," partial asphyxiation, and risk-taking challenges on social media platforms, according to Dr. Murthy's report. Studies also found that discussing or showing this content can normalize these behaviors.

Eating disorders are yet another concern. A review of 50 studies across 17 countries between 2016 and 2021 published in PLOS Global Public Health suggested that relentless online exposure to largely unattainable physical ideals may trigger a distorted sense of self and eating disorders. This is considered to be a particular problem among girls.

In addition, people who target adolescents-for instance, adults seeking to sexually exploit teens or financially extort them through the threat or actual distribution of intimate images-may use social media platforms for these types of predatory behaviors, according to the Surgeon General's advisory.

Why is excessive use of social media a problem?

The excessive use of social media can harm teens by disrupting important healthy behaviors. Some researchers think that exposure to social media can overstimulate the brain's reward center and, when the stimulation becomes excessive, can trigger pathways comparable to addiction.

Excessive use has also been linked to sleep problems, attention problems, and feelings of exclusion in adolescents. And sleep is essential for the healthy development of teens, according to Dr. Murthy's advisory.

Social media use in teens: A guide for parents

After reading the background, as a parent, you might ask yourself, "Sure, but do kids really use social media that much?"

Social media use among young people is nearly universal now, based on surveys from the Pew Research Center. In 2022, up to 95% of teenagers surveyed (ages 13 to 17) reported using social media, and more than a third of them use it "almost constantly."

Pew has also tracked which social media platforms (or "apps") teenagers are using. In 2023, it found the majority of teens-9 out of 10 for those ages 13 to 17-use YouTube, followed by TikTok, Snapchat, and Instagram. (Their use of Facebook dropped dramatically; there was also a decrease in the use of Twitter, now called X, although that was not as steep.)

With that in mind, YCSC experts provide a guide for parents concerned about their teens' social media use.

1. Determine the age your child will have access to social media.

Experts are still exploring whether there is a "right age" for a child to access social media. The APA explains that adolescents mature at different rates, which makes establishing a universal age recommendation difficult.

Although the minimum age most commonly required by social media platforms in the U.S. is 13, nearly 40% of children ages 8-12 use social media, according to Dr. Murthy's report. That signals how difficult it can be to enforce these rules without parental supervision.

One strategy is to make a social media plan for your family long before the teenage years, Dr. Poncin says. "In my opinion, elementary school-age children should not have full-on internet access using a device with all the social media apps."

In terms of phones, they can start with a "dumbphone," a cell phone that doesn't have email, an internet browser, and other features found on smartphones, he adds.

For middle-schoolers who show maturity and responsibility-who can get themselves to sleep and do their homework, for example-additional access may be fine, notes Dr. Poncin. But he suggests delaying full access to smartphones for as long as possible, opting for a device allowing you to add more apps as your child matures.

Establishing a family social media plan might also be useful-the American Academy of Pediatrics offers a tool that can help. In addition to setting the age at which you plan to start giving your kids phones or internet access, this plan can be used to establish rules and educate children and teens about being careful about privacy settings, avoiding strangers online, not giving out personal information, and knowing how to report cyberbullying, Dr. Mayes says.

2. Keep devices out of the bedroom.

Research shows a relationship between social media use and poor sleep quality, reduced sleep duration, and sleep difficulties in young people, according to Dr. Murthy's advisory. For teens, poor sleep is linked to emotional health issues and a higher risk for suicide.

According to Dr. Murthy's report, on a typical weekday, nearly one-third of adolescents report using screen media until midnight or later. (While screen media use includes various digital activities, social media apps are the most commonly used applications by teens.)

"Knowing that, try to create a culture at home where all phones are turned off by a certain time, and make sure it's at least one hour before going to bed," Dr. Poncin says.

However, you may find that bedtime rules don't work as well as your kids get older. It may be necessary to ask your teen to put their phone outside the bedroom before going to bed. "But, if the response is, 'I do my homework late and have a group chat about math, so I'm going to need the phone to group chat,' and you suspect your teen isn't being honest, that will be a different conversation," Dr. Poncin says. "But having these open conversations is critical."

3. Keep the lines of communication open, and let your teen make mistakes.

It will be easier to talk to your teens about social media if you have comfortable conversations with them about other issues, the doctors say.

"I don't believe you should monitor the content of your teen's phone, because a teenager should have privacy," Dr. Poncin says. "An important part of the teenage years is figuring out who you are in the world. So, it's important for them to explore and even make mistakes without you hovering around them." The goal is to keep lines of communication open and establish some trust with your child, so they'll come to you if there are issues, he adds.

This, too, is similar to the advice given when parents were concerned about the impact of television on children, adds Dr. Mayes. "Research showed that watching TV in and of itself wasn't bad, but it began to have potentially negative effects on kids' behavior when it was used as a babysitter," she says. "The message to parents was to sit beside their kids and watch TV with them, and then talk about what they're watching."

Neither you nor your teen will be happy if you sit beside them and scroll down your social media feeds together, but you can take the time to ask how social media is working for them, Dr. Mayes suggests. "So, you're not saying, 'Oh no! You're on social media!' Rather, you're normalizing it and making it clear that you're willing to talk about what they're experiencing or learning. This sets it up for them to talk to you if they run into a problem, instead of going to their peers or looking for solutions online," she says.

4. Be mindful of your approach when talking to your teen.

Although keeping the line of communication open matters, how you have those conversations is equally important. If you are concerned about your teen's social media use and feel the need to intervene, you might say something like, "It seems like you're on the phone so much that I don't see you just doing homework like you used to do, so I'm just worried how healthy this is for you in terms of getting your stuff done. What do you think about that?" Dr. Poncin says.

You might even need to be more assertive, for instance, saying, "I've noticed that you're on your phone until 1 a.m. When I go to the bathroom, your light is on, and you're on your phone. That's not healthy. So, can we come up with a plan that you're most comfortable with?"

5. Follow the rules yourself.

As a parent, you are a role model and that means following all the same rules you are setting for your children-if you ask your teenager to limit their screen time, you should do so as well, says Dr. Mayes, noting that it's not uncommon to see parents looking at their phones when they are out with their kids.

You might have a hard time resisting your social media feeds, texts, and emails. Sometimes, it helps to admit to your teenagers that you find it difficult to put down your devices, too. "This a global issue, where parents want their kids to do things differently and better than they do," Dr. Poncin says. "So, once again, having an honest conversation is important."
Note: Cyberbullying and online abuse or exploitation can be reported to the school or the police, or on websites such as Take It Down and CyberTipline, according to the Surgeon General report.

# data[].attributes.attachment_link.title
How Social Media Affects Your Teen's Mental Health: A Parent's Guide

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A 2023 U.S. Surgeon General advisory cited growing concerns that social media use impacts young people's mental health. Yale experts offer advice to parents.

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Gen Z mental health: The impact of tech and social media

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Gen Z mental health: The impact of tech and social media

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This article discusses how Gen Z's internet usage has affected the generation's mental health. The article takes a very careful and balanced approach to the issue, considering negative and positive affects on mental health with great detail and focus.

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Gen Z, Social Media, and Mental Health | Rollins School of Public Health | Emory University | Atlanta GA

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Generation Z has almost always been exposed to mobile devices, high speed Wi-Fi, social media, and an internet landscape that allows for constant connectedness—for better or for worse. Rollins experts weigh in on social media’s impacts on the youth mental health crisis.

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This article is a study made on the effects short videos such as instagram reels, Tiktok, etc have on attention span and procrastination

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Abstract

The pervasive nature of short-form video platforms has seamlessly integrated into daily routines, yet it is important to recognize their potential adverse effects on both physical and mental health. Prior research has identified a detrimental impact of excessive short-form video consumption on attentional behavior, but the underlying neural mechanisms remain unexplored. In the current study, we aimed to investigate the effect of short-form video use on attentional functions, measured through the attention network test (ANT). A total of 48 participants, consisting of 35 females and 13 males, with a mean age of 21.8 years, were recruited. The mobile phone short video addiction tendency questionnaire (MPSVATQ) and self-control scale (SCS) were conducted to assess the short video usage behavior and self-control ability. Electroencephalogram (EEG) data were recorded during the completion of the ANT task. The correlation analysis showed a significant negative relationship between MPSVATQ and theta power index reflecting the executive control in the prefrontal region ( r = −0.395, p = 0.007), this result was not observed by using theta power index of the resting-state EEG data. Furthermore, a significant negative correlation was identified between MPSVATQ and SCS outcomes ( r = −0.320, p = 0.026). These results suggest that an increased tendency toward mobile phone short video addiction could negatively impact self-control and diminish executive control within the realm of attentional functions. This study sheds light on the adverse consequences stemming from short video consumption and underscores the importance of developing interventions to mitigate short video addiction.

Keywords: mobile phone short-form video, attention network, executive control, EEG, addiction tendency

1 Introduction

In today's rapidly evolving landscape of smartphone technology and widespread mobile internet access, short-form video platforms have become an integral part of people's daily routines. These platforms, known for their quick and engaging way of sharing information, have amassed a large user base that dedicates significant time to consuming various short video content ( Ye et al., 2022). Despite their popularity, there is a noticeable gap in our understanding of the potential addictive tendencies associated with excessive consumption of these mobile short-form videos and their potential impact on cognitive functions. Previous studies on substance abuse have revealed impaired inhibitory control and a pronounced attentional bias toward cues related to the addictive substance ( Murphy and Garavan, 2011; Wilcockson and Pothos, 2015; Yang et al., 2019; Bowling et al., 2020; Wilcockson et al., 2021). Investigations into behavioral addictions have also revealed disruptions in the control system that governing attentional processes, and the addicts showed deficits in both attention function and control system ( Dong et al., 2017; Wang et al., 2017; Bediou et al., 2018; Kraplin et al., 2020). Similarly, studies in adolescents have shown that excessive use of mobile phones, including short-form video, can lead to social withdrawal and affect normal interpersonal skills ( Tateno et al., 2019). Relatedly, excessive use of mobile phone video may have a negative impact on attention and cause certain health risks ( Liu et al., 2021; Chen et al., 2022). For example, studies suggest that addicted mobile phone short video users have more attention deficits while watching short-form videos, and have impaired attentional concentration during processing interference ( Qi et al., 2022; Zhou et al., 2022). However, the neural mechanism underlying the impact of mobile phone short-form video addiction tendency on the attention is still largely unknown. In fact, investigating how video use impacts neural activity would advance our understanding of how addiction to these stimuli affects attentional processes and ultimately guide more targeted interventions and treatments for individuals struggling with this issue.

Attention plays a pivotal role in cognitive processing with substantial implications for learning and adaptive behavior ( Fan et al., 2002; Raz and Buhle, 2006; Petersen and Posner, 2012; Markett et al., 2022). Among many theories on attention, the tripartite-attentional-network theory posited by Petersen and Posner (2012) is well-recognized. The attention network test (ANT) serves as a commonly used paradigm for assessing the individual variability and neural correlates of attentive characteristics based on this tripartite attentional model ( Fan et al., 2002, 2005; Neuhaus et al., 2010; Petersen and Posner, 2012; Kustubayeva et al., 2022; Markett et al., 2022). In this model, attention system is divided into three sub-networks, namely, alerting, orienting, and executive control. The alerting network is responsible for sustaining vigilant cognitive states, primarily associated with the left frontoparietal network, including frontal and parietal lobes in conjunction with the thalamus ( Posner, 2012). The orienting network is crucial for modulating sensory input and priming actions, prominently engaging the parietal and frontal regions ( Proskovec et al., 2018). The executive control network, often referred to as the conflict network, governs self-regulation and conflict resolution arising from cognitive, emotional, and behavioral processes. The prefrontal cortex (PFC), anterior cingulate cortex (ACC), salience network (SN), were assumed playing significant roles in executive control ( Fan et al., 2002; Posner, 2012; Bowling et al., 2020; Markett et al., 2022).

In the present study, the ANT task was used to characterize individual's attentional capability and electroencephalography (EEG) was used to measure corresponding neural activities. In previous studies, theta brainwaves are considered as a key neural oscillation underlying attention function ( Hermens et al., 2005; Fan et al., 2007; Xu et al., 2013; Fellrath et al., 2016; Magosso et al., 2021; Asanowicz et al., 2023). Particularly, the association between theta oscillations and cognitive conflict resolution has been a focus of previous research, which suggest an increased frontal theta activity during incongruent trials, compared to congruent ones ( Wei and Zhou, 2020). Additionally, studies, including those on meditation, have linked theta and alpha oscillations to internally directed attentional states and positive emotional experiences ( Aftanas and Golocheikine, 2001). The primary source of the theta wave activity is suggested to be the prefrontal cortex, including dorsal anterior cingulate cortex, with indications of its potential generation within the upper cortical layers ( Botvinick et al., 2004), and the midfrontal cortex's theta band activities appear to represent a common computational mechanism associated with the need for cognitive control ( Cavanagh and Frank, 2014).

Based on previous findings that individuals who are prone to short video addiction show impaired behavioral performance on attention tasks ( Chen et al., 2022; Qin, 2022; Ye et al., 2022), we hypothesized that addiction tendencies to short-form videos might have negative impacts on neural activity underlying attentional functioning. Given that previous studies examining the EEG signatures of ANT have highlighted the significance of theta brainwaves for studying attention function ( Neuhaus et al., 2010; Fellrath et al., 2016; Magosso et al., 2021; Kustubayeva et al., 2022; Duan et al., 2023), the present study used a time-frequency signal analysis approach to investigate how the neural activity underlying attentional functioning related to addiction tendencies to short-form videos, with a focus on theta band. While addictive tendencies were measured through a short-form video addiction questionnaire ( Liu, 2022), participants' brain activity was recorded using EEG along with the implementation of the ANT ( Neuhaus et al., 2010).

2 Methodology

2.1 Study participants

2.1.1 Recruitment methods

Healthy adult participants were recruited through social media (WeChat) advertisements. Participants who confirmed their use of a mobile phone short-form video app were allowed to sign up for the experiment.

2.1.2 Participant inclusion criteria

Participants needed to meet the following criteria to be eligible for this study:

1.
Aged between 18 and 65 years;

2.
No diagnosis of neurological disorders or mental illnesses;

3.
No substance use (psychotropic drugs or alcohol) in the past month;

4.
No severe adverse reactions to stimuli such as flickering lights, auditory stimuli, or electromagnetic radiation;

5.
No prior participation in similar EEG studies.

2.1.3 Participant information

A total of 48 healthy participants were recruited for this study, including 13 males and 35 females, with ages ranging from 18 to 33 years (M = 21.80 years, SD = 3.62 years). Participants' educational backgrounds varied from undergraduate to doctoral degrees.

2.1.4 Ethical approval

This study has obtained approval from the Ethics Committee of Zhejiang University and strictly adheres to ethical principles and regulations for protecting participant privacy. Before the experiment, participants were informed that they would be involved in a study related to short video use, and the general procedure of the experiment was explained to them. Participants were also explicitly informed that they have the right to withdraw immediately from the experiment if they experience any physical or psychological discomfort. All participants provided informed consent prior to participation and received compensation for their time.

2.2 Experimental protocol

2.2.1 Overall procedure

This research is a part of an umbrella project aiming to address how short-form video watching modulates brain function and structure. Subsequent to the questionnaire completion, two three-minute sessions of eyes-open resting-state EEG recording were obtained before and after the ANT task. Figure 1 schematically represents the experimental protocol, and detailed information about the entire project is available in the supplementary materials ( Supplementary Figure 1).

FIGURE 1.

Schematic representation of the experimental protocol.

2.2.2 The administration of questionnaires

Participants completed an online questionnaire prior to the EEG experiment. This questionnaire battery encompassed several assessments, shown in the table below ( Table 1).

TABLE 1.

No.

Questionnaires

1

Attention Control Scale (ACS, Qin et al., 2022)

2

Barratt Impulsiveness Scale (BIS-II, Patton et al., 1995; Li et al., 2011)

3

Cohen Perceived Stress Scale (CPSS, Yang and Huang, 2003)

4

Depression and Anxiety Brief Symptom Survey ( Liu et al., 2013)

5

Five Facet Mindfulness Questionnaire (FFMQ, Baer et al., 2008; Deng et al., 2011)

6

Internet Addiction Test (IAT, Young, 1998)

7

Mind Wandering Questionnaire (MWQ, Mrazek et al., 2013; Ju et al., 2016)

8

Mobile Phone Short-Form Video Addiction Tendency Questionnaire (MPSVATQ, Liu, 2022)

9

Self Control Scale (SCS, Tangney et al., 2004; Tan and Guo, 2008)

To comprehensively delineate addictive behaviors and personality traits, we administered a battery of questionnaires commonly employed in addiction researches. Specifically, the Chinese version of the mobile phone short-form video addiction tendency questionnaire (MPSVATQ) was utilized to assess the tendency toward mobile phone short-form video addiction. This unidimensional instrument, derived from the Internet Addiction Test (IAT), yields higher scores indicative of greater addiction tendency and lower scores indicative of less tendency toward addiction. Its reliability and validity have been rigorously evaluated, yielding satisfactory outcomes ( Liu, 2022).

Additionally, the Attention Control Scale (ACS) was employed to appraise attentional capacities, while the Barratt Impulsiveness Scale (BIS-II) was utilized to assess impulsivity. The Cohen Perceived Stress Scale (CPSS) served to gauge subjective stress perceptions, and the Depression and Anxiety Brief Symptom Survey was utilized to evaluate symptoms of depression and anxiety. Furthermore, the Five Facet Mindfulness Questionnaire (FFMQ) was administered to assess mindfulness levels, and the Mind Wandering Questionnaire (MWQ) was used to evaluate levels of mind wandering during daily activities. Lastly, the self-control scale (SCS) was employed to assess individuals' capacity for behavioral regulation. These measures were undertaken to explore potential associations with short-form video addiction.

2.2.3 The administration of ANT task

When performing the ANT task ( Fan et al., 2002; Figure 2A), participants were seated with their chin secured using a chinrest apparatus ( Figure 2B).

FIGURE 2.

(A) the ANT schematic diagram, and (B) the experimental setting.

Stimuli were presented using a custom program developed with Psychtoolbox1 and participants' behavioral responses were recorded via a standard keyboard placed on a computer desk. A total of 192 trials were administered, with 48 trials for each of the four cue types: no cue, center cue, spatial cue, and double cue. Under each cue condition there was 16 trials of neutral, congruent, and incongruent target stimuli, respectively. Throughout the experimental session, a fixation was consistently displayed at the center of the screen. During each trial, a fixation was first displayed with a duration randomly selected from 400 to 1,600 ms. And then, a cue stimulus with a duration of 100 milliseconds was displayed. This cue appeared either above or below the central crosshair (spatial cue), above and below the screen center (double cue), at the central position (central cue), or was absent (no cue). The central cue and double cue provide information about the timing of the impending target presentation (alerting effect), while the spatial cue also conveyed information about the location of the forthcoming target (orienting effect). The target stimulus consisted of five arrows or lines arranged horizontally, presented either above or below the central crosshair. It would disappear once the participants made a judgment, with a maximum presentation duration of 1,700 milliseconds. Participants were instructed to identify the direction of the central arrow when the target stimulus displayed, irrespective of whether the surrounding flanking arrows were straight (neutral), in a consistent orientation, or in an inconsistent orientation (response suppression). Specifically, participants were required to press the "F" key if the middle arrow in the target stimulus pointed left and the "J" key if it pointed right. A post-response interval with variable duration was implemented to ensure a consistent total trial duration of 4,000 milliseconds for each trial. Participants were first required to complete a series of practice trials of the ANT task.

Only individuals who attained an accuracy rate of 85% or higher in the practice trials were deemed eligible to proceed to the formal ANT task. Each practice session contains 12 trials. It should be noted that no participant failed. There are 3 participants could practice up to three times, others needed only one session to achieve an accuracy rate exceeding 85%. Participants were instructed to respond with both speed and accuracy, and no feedback was provided. The ANT experiment lasted approximately 10 min.

2.3 EEG signal acquisition and preprocessing

2.3.1 Acquisition of EEG signal

The entire experimental procedure was conducted at a shielded EEG Laboratory room. A 64 channel electrode caps (Neuroscan Quick-cap, Neuroscan Inc., Sterling, VA, USA) was used and the international 10-20 system for electrode placement was employed. The EEG signal was sampled using a Neuroscan Synamps2 amplifier at 1,000 Hz. Concurrently, vertical and horizontal ophthalmic signals were collected. Generally, these signals are collected to potentially integrate them into subsequent offline EEG analysis. Although these signals can be omitted during the data processing phase if deemed unnecessary, we collect them to ensure the comprehensiveness of our signal acquisition. Impedances were ensured to remain below 10 kΩ before recording.

2.3.2 Preprocessing of EEG data

Offline preprocessing was performed on the EEG data obtained during the ANT task and the resting-state, utilizing EEGlab2. For the EEG data of the ANT task, preprocessing steps involved: (1) elimination of redundant electrodes (CB1, CB2) and the vertical and horizontal electrooculograms (VEO and HEO); (2) down-sampling the signal to 250 Hz; (3) selection of bilateral mastoid electrodes (M1, M2) as references; (4) bandpass filtering with the band range of 0.1-35 Hz; (5) notch filtering at 49-51 Hz to remove powerline interference; (6) segments of signal were acquired by cutting continuous signal from −200 to 1,300 ms with respect to cue onsets; (7) employing Independent Component Analysis (ICA) to mitigate ocular and cardiac artifacts. For resting-state EEG data, preprocessing didn't encompass signal segmentation, other preprocessing steps were the same.

2.3.3 Time-frequency transformation and the spectral analysis of EEG data

For the EEG data of ANT task, the preprocessed data were subjected to Short-Time Fourier Transform (STFT) analysis to delineate their temporal and spectral characteristics (using the EEGLAB toolbox). That is, the EEG signals related to three sub-networks of the attention network: alerting, orienting, and executive control, are transferred to the time-frequency domain, which facilitate us to analyze the time-frequency characteristics of the neural activity. Specifically, a window size of 0.5 s was chosen to capture salient temporal features. In STFT processing, the choice of time window duration impacts the preservation of frequency content within the signal. Opting for a longer time window facilitates the retention of low-frequency components, whereas selecting a narrower time window enhances the preservation of high-frequency components. Given the focus of this study on the theta (4-8 Hz) frequency band, the selection of a 0.5-s time window is deemed advantageous for preserving the characteristic features of signals within this frequency range. Regarding the time window of interest (TWI), it was determined based on ANT task design and previous findings ( Neuhaus et al., 2010; Chang et al., 2015; Kustubayeva et al., 2022). The selection of regions of interest (ROIs) is based on brain regions commonly examined in studies using ANT tasks ( Fan et al., 2002; Posner, 2012; Proskovec et al., 2018; Bowling et al., 2020; Markett et al., 2022).

For the alerting function, the TWI encompassed 650-800 ms following the onset of cue stimuli. In the spectral domain, the theta frequency range (4-8 Hz) was designated as the frequency window of interest (FWI). Mean amplitude calculations were performed on electrodes located at the parietal region (P5, P3, P1, Pz, P2, P4, P6), the parieto-occipital region (PO5, PO3, POz, PO4, PO6), and the occipital region (O1, Oz, O2). Specifically, the mean amplitude was calculated by adding the mean amplitudes from selected electrode points of interest, after obtaining the mean amplitudes from all trials. The log mode is used to perform the baseline correction. Analogous methodologies were applied to the orienting function, with the TWI set at 600-800 ms following the cue stimulus onset, and the same theta frequency range (4-8 Hz) was selected. Electrode clusters comprising the parietal, parieto-occipital, and occipital regions were analyzed accordingly. For the executive control function, the TWI extended from 600 to 900 ms following the appearance of cue stimuli, and the same theta frequency range was selected. The ROIs for amplitude analysis encompassed frontal electrodes (F5, F3, F1, Fz, F2, F4, F6), central frontal electrodes (FC3, FC1, FCz, FC2, FC4), central electrodes (C5, C3, Cz, C2, C4), parietal electrodes (P5, P3, P1, Pz, P2, P4, P6), and parieto-occipital electrodes (PO5, PO3, POz, PO4, PO6). Regarding the analysis of the resting state EEG data, we utilized the Fast Fourier Transform (FFT) analysis. The absolute power values in decibels (dB) obtained through FFT were used as the index of neural oscillation. Specifically, we focused on the theta band (4-8 Hz), and the chosen brain region was same as that for the task data analysis.

2.4 Statistical analysis

2.4.1 Behavioral data analysis

First, we analyzed the pairwise correlation between all the measured questionnaires. Next, for the analysis of behavioral data, a 4 × 3 repeated-measures analysis of variance (RMANOVA) was conducted separately for mean reaction time (RT) and accuracy (ACC), with cue conditions (no cue, center cue, double cue, or spatial cue) and target conditions (congruent, neutral, or incongruent) treated as within-subject factors.

To investigate the association between the efficiency of the three attention sub-networks and the propensity for short video addiction, correlation analyses were performed at both the behavioral and neurophysiological levels. Specifically, regarding the behavioral data analysis, the scores of 3 sub-networks of ANT were correlated with MPSVATQ, respectively. In the ANT task, the scores of three sub-networks of attention were quantized as below:

Alerting Effect = RT of "no cue" condition − RT of "double cue" condition;

Orienting Effect = RT of "center cue" condition − RT of "spatial cue" condition;

Inhibitory Effect = RT of "incongruent" condition − RT of "congruent" condition.

2.4.2 The relationships between short-video addiction tendency and EEG metrics during the ANT task

Regarding the neuroelectric data analysis, we conducted a thorough examination of the correlation between the neural oscillation index reflecting the three sub-networks and the MPSVATQ cross diverse brain regions. The calculation of neural oscillation indexes reflecting the three sub-networks were similar to that in the behavior analysis. Specifically, the indexes of neural oscillation were calculated by replacing RT with mean theta power in the formula above. In addition, gender, age, anxiety and depression scores were used as covariates. Since pervious research revealed that the persons with Facebook addiction have weaker self-control ( Blachnio and Przepiorka, 2016), and a significant negative correlation between MPSVATQ and SCS (see below) was also found in the current study, we further conducted correlation analyses to study the relationship between SCS and the neural oscillation indexes reflecting three attentional sub-networks across different brain regions. Finally, we meticulously analyzed the resting-state EEG data to demonstrate whether the correlation between MPSVATQ and neural oscillation index is task-dependent.

In all analytical procedures, a p-value smaller than 0.05 was considered as significant. To address the issue of Type I errors arising from multiple comparisons, Bonferroni correction at appropriate junctures was applied. The statistical analysis was executed using SPSS 22.0 and MATLAB 2013b.

3 Results

3.1 Demographic information and questionnaire results

Demographic information was displayed in Table 2. A significant positive correlation was found between MPSVATQ and IAT scores, and there was a significant negative correlation between the scores of MPSVATQ and both ACS and SCS scores ( Table 3). While we administered additional questionnaires for measurement purposes, we solely present herein the results that demonstrate significant associations with MPSVATQ, detailed information is in the supplementary materials ( Supplementary Table 1).

TABLE 2.

Age

MPSVATQ

IAT

Anxiety

Depression

SCS

ACS

BIS-II

MWQ

CPSS

FFMQ

M

21.48

50.77

54.83

12.35

10.71

14.88

3.10

36.53

18.56

40.67

122.71

SD

3.16

11.87

11.17

3.06

3.40

2.19

0.60

7.00

4.11

6.14

9.32

TABLE 3.

MPSVATQ

IAT

SCS

ACS

MPSVATQ

-

IAT

0.390**

-

SCS

−0.320*

−0.726**

-

ACS

−0.310*

−0.443**

0.268

-

3.2 Behavioral results

3.2.1 Efficiency of the three attentional networks

First of all, the extreme values exceeding 3 standard deviations from the mean were replaced by the corresponding average value ( Fan et al., 2002; Neuhaus et al., 2010), and the descriptive statistics were displayed in Table 4 and Figure 3.

TABLE 4.

Target

Neutral target

Congruent target

Incongruent target

Cue

RT
(M ± SD) ms

ACC
(M ± SD) %

RT
(M ± SD) ms

ACC
(M ± SD) %

RT
(M ± SD) ms

ACC
(M ± SD) %

FIGURE 3.

Behavioral results. Mean reaction time from correct trials (A) and accuracy (B) as a function of cue and target condition. Error bar represents the standard error of mean.

Then, we carried out a 4 (cue condition: no cue, center cue, double cue, spatial cue) × 3 (target type: neutral, congruent, incongruent) ANOVA on the RT and ACC. Regarding RT, both main effect of cue type and target type were significant ( Table 5). Additionally, the interaction effect between cue and target type was also found to be significant ( Table 5). Follow-up analysis indicated that the RT for the "no cue" condition exhibited the longest duration, which was longer than RTs for the "center cue" (adjusted p(Bonferroni correction) < 0.001), "double cue" (adjusted p < 0.001), and "spatial cue" (adjusted p < 0.001) conditions, with the "spatial cue" condition displaying the shortest RT ( Table 4). RT for the incongruent condition was significantly longer than that for the congruent condition (adjusted p < 0.001).

TABLE 5.

Measure

Factor

F-value

p-value

Partial η ²

RT

Cue

F(3, 141) = 70.20

<0.001

0.60

ACC

Cue

F(3, 141) = 10.27

<0.001

0.18

The ANOVA on ACC displayed similar results, with significant main effect of cue type and target type ( Table 5). The interaction effect between cue and target type was also found to be significant ( Table 5). Follow-up analysis indicated that the ACC for the "center cue" condition was lower than ACC for the "no cue" (adjusted p = 0.046), "double cue" (adjusted p = 0.001), and "spatial cue" (adjusted p < 0.001) conditions, with the "spatial cue" condition displaying the highest accuracy ( Table 4). ACC for the incongruent condition was significantly lower than that for the congruent condition (adjusted p < 0.001).

3.2.2 Correlation analyses: MPSVTQ and RT of ANT

As for the relationship between the efficiency of three attention sub-networks and short-form video addiction tendency, no statistically significant correlation was observed (all p > 0.05). Detailed results can be found in the supplementary materials (see Supplementary Table 2).

3.3 EEG results

The EEG data of the ANT task of 3 participants were excluded because the participants did not strictly comply with the instructions. Specifically, during the EEG experiment, these participants did not maintain stable head positions, resulting in excessive head movement artifacts in the EEG signals. Therefore, 45 participants were included in the analysis.

3.3.1 Non-significant correlation between addiction tendency and EEG metrics associated with ANT subcomponents

We found no significant correlation between MPSVATQ scores and neural oscillation indexes reflecting the alerting network, orienting network, or executive control network (all p > 0.05). The indexes of neural oscillation were calculated by replacing RT with mean theta power in the formula as follows: Alerting Effect = power of the "no cue" condition-power of the "double cue" condition; Orienting Effect = power of the "center cue" condition-power of the "spatial cue" condition; Inhibitory Effect = power of the "incongruent" condition-power of the "congruent" condition. Specific details of these results can be found in the supplementary materials, Supplementary Table 3.

3.3.2 Negative correlation between addiction tendency and the theta power when cognitive control is demanded

A noteworthy negative correlation was only found between the activity of the frontal region and MPSVATQ scores when assessing the theta power under incongruent target condition, with neutral target conditions serving as a control baseline condition ( r = −0.395, p = 0.007, Table 6 and Figure 4). These EEG findings were further elaborated in Figure 5. Despite controlling for gender, age, anxiety, and depression, this negative associations remained significant (for more details please refer to the supplementary materials, Supplementary Table 4). Although no significant negative correlation was found between the activity of the central frontal region, central region, parietal region, and parietal occipital region with MPSVATQ scores when assessing theta power under the incongruent target condition, with neutral target conditions serving as a control baseline, the correlation trend is negative.

TABLE 6.

Brain regions

R

p

Frontal region (F5, F3, F1, Fz, F2, F4, F6)

−0.395

0.007

Middle frontal region (FC3, FC1, FCz, FC2, FC4)

−0.280

0.063

Central region (C5, C3, Cz, C2, C4)

−0.229

0.130

Parietal region (P5, P3, P1, Pz, P2, P4, P6)

−0.014

0.926

Parietal occipital region (PO5, PO3, POz, PO4, PO6)

−0.118

0.439

FIGURE 4.

Scatter plot for correlation between addiction tendency (MPSVATQ score) and frontal theta power difference between incongruent target and neutral target of the ANT task.

FIGURE 5.

(A) The spectrogram of the difference between incongruent target and neutral target at frontal region (illustrated by electrode Fz here). The bands of interest, theta (4-8 Hz), are circled in red. (B) Topography of theta power difference between incongruent and neutral targets of the ANT task, during a time window of 600-900 ms post the cue onset.

The correlation analysis aimed to examine the relationship between SCS and prefrontal region activity revealed no significant results between SCS scores and the theta power under incongruent target condition, with neutral target conditions serving as a control baseline condition ( p > 0.05, please refer to supplementary materials, Supplementary Table 5).

To demonstrate whether the correlation between MPSVATQ and neural oscillation is task-dependent, we conducted an analysis of resting state EEG data. The results showed that no significant correlation was found between theta power of two resting-state EEG sessions and MPSVATQ within the prefrontal region ( p > 0.05, please refer to supplementary materials, Supplementary Table 6). The theta power within the prefrontal region between the two resting-state EEG sessions was not significantly different [ t (43) = 1.42, p = 0.888].

4 Discussion

The principal aim of this study was to explore the complex relationship between mobile phone short video addiction tendency and attention, with focus on alerting, orienting, executive control sub-networks assessed by the attention network test (ANT). Correlation analyses revealed a significant negative relationship between MPSVATQ and self-control, in addition, a significant negative correlation was also found between MPSVATQ and the theta power difference under incongruent minus neutral target condition of the ANT, suggesting that individuals with a proclivity for mobile phone short video addiction may encounter challenges related to executive control and self-control abilities.

In this study, the ANT task evaluates three sub-networks: alerting, orienting, and executive control. Executive control assessed by ANT is quantified by the Inhibitory Effect, which was calculated as the difference in response times (RT) between "incongruent" and "congruent" conditions. This method aligns with measurements used in established executive control tasks like the Stroop, Flanker, Go-Nogo, and Stop-signal tasks. Importantly, while ANT parallels the Flanker task in measuring executive control, it also assesses alerting and orienting functions, providing a comprehensive assessment of attentional networks. Contrary to expectations, we did not find a significant correlation between MPSVATQ and ANT's behavioral performance. It is possible that the simplicity of the task may result in insufficient variation in performance, thereby obscuring the detection of any potential correlations.

However, a significant correlation was observed between MPSVATQ and theta power difference under incongruent minus neutral target condition in the frontal area. This finding aligns with previous studies showing significant differences between addicts and non-addicts in EEG measures but no significant difference in behavioral performance ( Zhou et al., 2022). Importantly, after controlling for variables such as anxiety, depression, age, and gender, the association between MPSVATQ and theta power in the frontal area was still significant. These findings highlight the importance of the prefrontal area in executive control, which is consistent with previous studies on addiction. For example, a recent research revealed lower perceptual sensitivity and hypoactivations during inhibitory control in cognitive control regions (e.g., anterior prefrontal cortex, dorsolateral prefrontal cortex, supplementary motor area), which was associated with task performance and heroin use severity measures in individuals with heroin addiction ( Ceceli et al., 2023). Previous investigations into behavioral addiction also highlighted the significant involvement of the prefrontal lobe in executive control. Specifically, research on Internet addiction shows that the slow-wave activities in the frontal areas were correlated with the commission error rate in the Go/NoGo task in the internet disorder group ( Qi et al., 2022). An earlier study has shown prefrontal cortex may be involved in the circuit modulating impulsivity, and its impaired function may relate to high impulsivity in adolescents with Internet Game Addiction (IGA), which may contribute directly to the Internet addiction process ( Ding et al., 2014). Studies have concluded that compared to healthy controls, gaming addicts have poorer response-inhibition and emotion regulation, impaired prefrontal cortex functioning and cognitive control ( Kuss et al., 2018). The significant negative correlation between MPSVATQ and theta power difference under incongruent minus neutral target condition in the frontal area suggests the use of short video has negative impact on the neural processing underling executive control, even in the absence of observable differences in specific behavioral tasks. Moreover, the theta power of resting state EEG data, measured before and after the ANT task, did not show significant correlation with MPSVTQ, indicating the independence of the task-related findings in this study. Despite the lack of direct associations in certain behavioral manifestations, the identification of relationship between MPSVTQ and theta power reflecting the executive control network in the frontal area highlights the essential role of frontal brain regions in short-form video addiction, providing valuable insights for prospective intervention and prevention strategies. Prior research has prominently underscored the relevance of theta oscillations to cognitive conflict resolution, particularly evident in augmented frontal theta activity during incongruent trials relative to congruent trials ( Wei and Zhou, 2020). This observation implies a pivotal role of theta band oscillations in processes associated with conflict detection, monitoring, and resolution, where heightened theta event-related synchronization (ERS) magnitude correlates with escalated engagement of cognitive control ( Nigbur et al., 2011; Cavanagh and Frank, 2014). The findings of this study revealed a notable negative correlation between MPSVATQ and theta power difference under incongruent minus neutral target condition. Consequently, it is postulated that heightened propensity toward mobile phone short-form video addiction may correspond to diminished executive control capacities. Specifically, individuals with greater addiction tendencies may exhibit reduced cognitive resources for managing conflict during incongruent trials, thereby manifesting a diminished theta power difference in EEG measurements. Should future endeavors explore neuroregulatory interventions for mobile phone short video addiction, theta difference power may hold promise as a crucial neural reference index.

Notably, the most important result was found between MPSVATQ and neural oscillation index calculated by subtracting the theta power of neutral condition from that of incongruent target, which was used to characterize individuals' ability of executive control. However, in previous studies, executive control in ANT was usually defined by the difference between the incongruent and congruent conditions, even in the calculation of EEG indicators ( Neuhaus et al., 2010; Racer et al., 2011; Chang et al., 2015). In the current study, the reaction time of the congruent condition was slightly longer than that of the neutral condition, but did not show statistically significant difference. It is plausible to postulate that the neutral condition functions as a baseline, involving solely the processing of the central arrow's direction, without the need to suppress any conflicting stimuli. In the congruent condition, even though the direction of the central arrow aligns with that of the surrounding arrows, there remains a requirement to divert attention to minimize the impact of the adjacent arrows. This indicates that, similar to what has been observed in the incongruent condition in prior research, attentional processing demands are still present in the congruent condition ( Appelbaum et al., 2011). The significant correlation between MPSVATQ and neural oscillation index calculated by subtracting the theta power of neutral condition from that of incongruent target, but not with that calculated by subtracting the theta power of congruent condition from that of incongruent target further confirmed this argument. However, the specific neurophysiological implication warrants further study.

Finally, this study found a significant negative correlation between short video addiction tendency and self-control questionnaire scores, aligning with prior research emphasizing the relationship between addictive behavior and self-control difficulties ( Racer et al., 2011; Blachnio and Przepiorka, 2016). This underscores the importance of addressing self-control enhancement in interventions targeting short video addiction. Numerous studies have shown that mindfulness meditation is associated with reduced addictive behaviors ( Bowen and Vieten, 2012; Davis et al., 2014a, b; Sriburapar, 2021; Parisi et al., 2023). It effectively reduces the risk of Internet addiction by enhancing an individual's level of self-control. This increase in self-control further leads to a decrease in the individual's stress level, which reduces the likelihood of developing Internet addiction ( Song and Park, 2019). It can be inferred that mindfulness training may also have a positive effect on reducing addiction to mobile phone short-form videos. No significant result was observed when assessing the relationship between self-control and theta activity in the frontal area reflecting three sub-networks assessed during ANT paradigm. Since self-report measures of trait self-control capture central tendencies of aggregates of many different instances of behavior, whereas behavioral inhibition tasks are momentary one-time state measures ( Wennerhold and Friese, 2020). These results indicate that the theta power difference between incongruent and neural target conditions primarily captures a momentary state rather than a comprehensive measure of self-control.

5 Conclusion

The present study was undertaken to delve into the association between mobile phone short video addiction tendency and attentional functions, as well as potential changes in brain activity. We found a significant negative correlation between short video addiction tendency and neural oscillation index reflecting the executive control network in the frontal area. This finding suggests that a higher propensity for short video addiction may impair executive control. Furthermore, we identified a strong negative correlation between short video addiction and self-control abilities, indicating that higher addiction levels are associated with diminished self-control. Short-form videos, being self-stimulating and content-rich, capture attention with minimal psychological effort. Prolonged consumption of such content may primarily engage the lower-order cortical brain regions, such as those associated with emotional processing, and suppress activity in higher-order areas responsible for self-control and attention. This pattern may enhance the susceptibility to short video addiction, with a simultaneous decline in self-control. Given the current findings, we can develop mental training interventions to enhance self-control, for example, incorporating mindfulness meditation practices to address self-control deficits associated with short video addiction.

6 Limitations and recommendations for future research

Although this study has yielded findings, it is not without its limitations. To further delve into the cognitive mechanisms of smartphone short video addiction, several suggestions for future research are proposed. Firstly, longitudinal research designs can be employed to track the dynamics of individual addiction tendencies and cognitive functions, unraveling causal relationships. Secondly, future studies could benefit from a larger and more diverse sample size, including a wider range of participants such as children and the elderly. Additionally, employing a more gender-balanced sample and extending the research to encompass a greater variety of short video categories, like those found on YouTube, would enhance the generalizability of the current findings. Thirdly, the incorporation of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), could enable more precise delineation of brain activity alterations. Fourthly, exploring additional factors influencing smartphone short video addiction, such as daily mobile short video usage time, social and psychological variables, would contribute to a more comprehensive understanding of psychological mechanisms of short video addiction. Lastly, future research could also look into developing and testing interventions based on the findings of this and similar studies, aiming to mitigate the effects of short video addiction on attentional functions.

Data availability statement

The original contributions presented in this study are included in this article/ Supplementary material, further inquiries can be directed to the corresponding authors.

Ethics statement

The studies involving humans were approved by the Ethics Committee, Department of Psychology and Behavioral Sciences, Zhejiang University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

TY: Conceptualization, Data curation, Investigation, Methodology, Writing - original draft, Writing - review & editing. CS: Conceptualization, Formal analysis, Writing - review & editing. WX: Conceptualization, Formal analysis, Software, Writing - review & editing. YH: Funding acquisition, Methodology, Supervision, Writing - original draft, Writing - review & editing. HZ: Funding acquisition, Supervision, Writing - review & editing.

Acknowledgments

Special thanks to Liyu Cao (Ph.D) for sharing his experience with time-frequency analysis, Yun Qiu for assisting in data collection.

Funding Statement

The authors declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by Autism Research Special Fund of Zhejiang Foundation for Disabled Persons (2023011), the National Natural Science Foundation of China (No. 81971245), the Zhejiang Province "Qianjiang Talent Program," Research of Basic Discipline for the 2.0 Base of Top-notch Students Training Program, and the Ministry of Education of China (20211033).

Footnotes

Conflict of interest

The authors declare 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.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnhum.2024.1383913/full#supplementary-material

References

1. Li X.-Y., Phillips M. R., Xu D., Zhang Y.-L., Yang S.-J., Tong Y.-S., et al. (2011). Reliability and validity of an adapted Chinese version of Barratt Impulsiveness Scale. Chin. Ment. Health J. 25 610-615. [Google Scholar]

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Associated Data
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Supplementary Materials

Data Availability Statement

The original contributions presented in this study are included in this article/ Supplementary material, further inquiries can be directed to the corresponding authors.

Articles from Frontiers in Human Neuroscience are provided here courtesy of Frontiers Media SA

# data[].attributes.attachment_link.title
Mobile phone short video use negatively impacts attention functions: an EEG study

# data[].attributes.attachment_link.description
The pervasive nature of short-form video platforms has seamlessly integrated into daily routines, yet it is important to recognize their potential adverse effects on both physical and mental health. Prior research has identified a detrimental impact ...

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Study shows how social media can be damaging. 

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Study shows how social media can be damaging. 

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This article discusses a study linking social media use to mental health issues, particularly in Gen Z. It suggests that Gen Z, who spend the most time on these apps, tend to use them passively, which is more damaging to mental health compared to millennials and other generations who use social media more actively.

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New data on the impact of social media use on mental health across the world shows just how damaging it is to Gen Zers.

The study, conducted by the McKinsey Health Institute, reported: "Gen Zers, on average, are more likely than other generations to cite negative feelings about social media."

It found one in four Gen Z members - those born in the late 1990s and early 2000s - connect spending a lot of time on these platforms with poorer mental health.

Kana Enomoto, the director of brain health at the McKinsey Health Institute and an author of the study, said she and her team focused on this age demographic because "Gen Z are the leaders of the future. They are the workforce of the future."

About 42,000 respondents in 26 countries across continents were surveyed about the four dimensions of health: mental, physical, social and spiritual. Gen Zers ranked worst across all of these categories.

Millennials were next, followed by Gen Xers and baby boomers. One in seven baby boomers said their mental health had declined over the past three years, compared with one in four Gen Z respondents.

Although millennials reported being more active on social media - 32% said they posted at least once a day - Gen Z spends the most amount of time on the apps, but more passively. The study shows that 35% of Gen Z respondents spend over two hours on social media daily compared with 24% of millennials and 14% of baby boomers.

Studies have shown that passive social media use, like endlessly scrolling on TikTok or Instagram, could be linked with declines in wellbeing over time. The negative impact of social media increases substantially for younger ages overall.

At 21%, female Gen Zers, in particular, were almost twice as likely to report poor mental health when compared with their male counterparts, 13% of whom reported poor mental health.

A higher portion of female Gen Zers reported poor or distorted body image and self-confidence as negative impacts of social media. The American Psychological Association found "reducing social media use significantly improves body image in teens and young adults".

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Enomoto said she hopes the study raises more awareness of mental health and its nuances.

But social media is not all bad - respondents across all generations overwhelmingly reported positive impacts of social media when it comes to self-expression and social connectivity.

And according to Enomoto, Gen Zers are also utilizing technology and social media as an avenue for mental health support and as "a source of psychological resilience".

Enomoto added: "I think many people think of mental health as something that happens to other people, or something that happens in an extreme fashion, but really, we are all dealing with our mental health."

# data[].attributes.attachment_link.title
Social media particularly damaging to mental health of Gen Zers, says study

# data[].attributes.attachment_link.description
Compared with other generations, members of Gen Z spend more time passively consuming social media

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Eating disorders in teenagers are perpetuated, and in part caused by social media

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Eating disorders in teenagers are perpetuated, and in part caused by social media

# data[].attributes.body
Young adolescents are susceptible to the pressure of social media and the opinions of others. As they become more and more active on social media as a necessary part of their teenage social life, they often stumble into echo chambers promoting disordered eating habits.

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Social media use among adolescents with eating disorders: a double-edged sword

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Eating disorders are on the rise with a significant impact on mental health. Misuse of social media platforms is likely a significant contributing factor. This trend is especially pronounced among adolescents, who are increasingly using social media ...