research on social media and mental health

Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice

Affiliations.

• 1 Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA.
• 2 CareNX Innovations, Mumbai, India.
• 3 Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA.
• 4 Department of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH.
• PMID: 33415185
• PMCID: PMC7785056
• DOI: 10.1007/s41347-020-00134-x

Social media platforms are popular venues for sharing personal experiences, seeking information, and offering peer-to-peer support among individuals living with mental illness. With significant shortfalls in the availability, quality, and reach of evidence-based mental health services across the United States and globally, social media platforms may afford new opportunities to bridge this gap. However, caution is warranted, as numerous studies highlight risks of social media use for mental health. In this commentary, we consider the role of social media as a potentially viable intervention platform for offering support to persons with mental disorders, promoting engagement and retention in care, and enhancing existing mental health services. Specifically, we summarize current research on the use of social media among mental health service users, and early efforts using social media for the delivery of evidence-based programs. We also review the risks, potential harms, and necessary safety precautions with using social media for mental health. To conclude, we explore opportunities using data science and machine learning, for example by leveraging social media for detecting mental disorders and developing predictive models aimed at characterizing the aetiology and progression of mental disorders. These various efforts using social media, as summarized in this commentary, hold promise for improving the lives of individuals living with mental disorders.

Keywords: digital health; mHealth; mental health; psychiatry; safety; social media.

Grants and funding

• K23 MH116130/MH/NIMH NIH HHS/United States
• R01 MH110965/MH/NIMH NIH HHS/United States
• U19 MH113211/MH/NIMH NIH HHS/United States

Social media use can be positive for mental health and well-being

January 6, 2020— Mesfin Awoke Bekalu , research scientist in the Lee Kum Sheung Center for Health and Happiness at Harvard T.H. Chan School of Public Health, discusses a new study he co-authored on associations between social media use and mental health and well-being.

What is healthy vs. potentially problematic social media use?

Our study has brought preliminary evidence to answer this question. Using a nationally representative sample, we assessed the association of two dimensions of social media use—how much it’s routinely used and how emotionally connected users are to the platforms—with three health-related outcomes: social well-being, positive mental health, and self-rated health.

We found that routine social media use—for example, using social media as part of everyday routine and responding to content that others share—is positively associated with all three health outcomes. Emotional connection to social media—for example, checking apps excessively out of fear of missing out, being disappointed about or feeling disconnected from friends when not logged into social media—is negatively associated with all three outcomes.

In more general terms, these findings suggest that as long as we are mindful users, routine use may not in itself be a problem. Indeed, it could be beneficial.

For those with unhealthy social media use, behavioral interventions may help. For example, programs that develop “effortful control” skills—the ability to self-regulate behavior—have been widely shown to be useful in dealing with problematic Internet and social media use.

We’re used to hearing that social media use is harmful to mental health and well-being, particularly for young people. Did it surprise you to find that it can have positive effects?

The findings go against what some might expect, which is intriguing. We know that having a strong social network is associated with positive mental health and well-being. Routine social media use may compensate for diminishing face-to-face social interactions in people’s busy lives. Social media may provide individuals with a platform that overcomes barriers of distance and time, allowing them to connect and reconnect with others and thereby expand and strengthen their in-person networks and interactions. Indeed, there is some empirical evidence supporting this.

On the other hand, a growing body of research has demonstrated that social media use is negatively associated with mental health and well-being, particularly among young people—for example, it may contribute to increased risk of depression and anxiety symptoms.

Our findings suggest that the ways that people are using social media may have more of an impact on their mental health and well-being than just the frequency and duration of their use.

What disparities did you find in the ways that social media use benefits and harms certain populations? What concerns does this raise?

My co-authors Rachel McCloud , Vish Viswanath , and I found that the benefits and harms associated with social media use varied across demographic, socioeconomic, and racial population sub-groups. Specifically, while the benefits were generally associated with younger age, better education, and being white, the harms were associated with older age, less education, and being a racial minority. Indeed, these findings are consistent with the body of work on communication inequalities and health disparities that our lab, the Viswanath lab , has documented over the past 15 or so years. We know that education, income, race, and ethnicity influence people’s access to, and ability to act on, health information from media, including the Internet. The concern is that social media may perpetuate those differences.

— Amy Roeder

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Science News

Social media harms teens’ mental health, mounting evidence shows. what now.

Understanding what is going on in teens’ minds is necessary for targeted policy suggestions

Most teens use social media, often for hours on end. Some social scientists are confident that such use is harming their mental health. Now they want to pinpoint what explains the link.

Carol Yepes/Getty Images

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By Sujata Gupta

February 20, 2024 at 7:30 am

In January, Mark Zuckerberg, CEO of Facebook’s parent company Meta, appeared at a congressional hearing to answer questions about how social media potentially harms children. Zuckerberg opened by saying: “The existing body of scientific work has not shown a causal link between using social media and young people having worse mental health.”

But many social scientists would disagree with that statement. In recent years, studies have started to show a causal link between teen social media use and reduced well-being or mood disorders, chiefly depression and anxiety.

Ironically, one of the most cited studies into this link focused on Facebook.

Researchers delved into whether the platform’s introduction across college campuses in the mid 2000s increased symptoms associated with depression and anxiety. The answer was a clear yes , says MIT economist Alexey Makarin, a coauthor of the study, which appeared in the November 2022 American Economic Review . “There is still a lot to be explored,” Makarin says, but “[to say] there is no causal evidence that social media causes mental health issues, to that I definitely object.”

The concern, and the studies, come from statistics showing that social media use in teens ages 13 to 17 is now almost ubiquitous. Two-thirds of teens report using TikTok, and some 60 percent of teens report using Instagram or Snapchat, a 2022 survey found. (Only 30 percent said they used Facebook.) Another survey showed that girls, on average, allot roughly 3.4 hours per day to TikTok, Instagram and Facebook, compared with roughly 2.1 hours among boys. At the same time, more teens are showing signs of depression than ever, especially girls ( SN: 6/30/23 ).

As more studies show a strong link between these phenomena, some researchers are starting to shift their attention to possible mechanisms. Why does social media use seem to trigger mental health problems? Why are those effects unevenly distributed among different groups, such as girls or young adults? And can the positives of social media be teased out from the negatives to provide more targeted guidance to teens, their caregivers and policymakers?

“You can’t design good public policy if you don’t know why things are happening,” says Scott Cunningham, an economist at Baylor University in Waco, Texas.

Increasing rigor

Concerns over the effects of social media use in children have been circulating for years, resulting in a massive body of scientific literature. But those mostly correlational studies could not show if teen social media use was harming mental health or if teens with mental health problems were using more social media.

Moreover, the findings from such studies were often inconclusive, or the effects on mental health so small as to be inconsequential. In one study that received considerable media attention, psychologists Amy Orben and Andrew Przybylski combined data from three surveys to see if they could find a link between technology use, including social media, and reduced well-being. The duo gauged the well-being of over 355,000 teenagers by focusing on questions around depression, suicidal thinking and self-esteem.

Digital technology use was associated with a slight decrease in adolescent well-being , Orben, now of the University of Cambridge, and Przybylski, of the University of Oxford, reported in 2019 in Nature Human Behaviour . But the duo downplayed that finding, noting that researchers have observed similar drops in adolescent well-being associated with drinking milk, going to the movies or eating potatoes.

Holes have begun to appear in that narrative thanks to newer, more rigorous studies.

In one longitudinal study, researchers — including Orben and Przybylski — used survey data on social media use and well-being from over 17,400 teens and young adults to look at how individuals’ responses to a question gauging life satisfaction changed between 2011 and 2018. And they dug into how the responses varied by gender, age and time spent on social media.

Social media use was associated with a drop in well-being among teens during certain developmental periods, chiefly puberty and young adulthood, the team reported in 2022 in Nature Communications . That translated to lower well-being scores around ages 11 to 13 for girls and ages 14 to 15 for boys. Both groups also reported a drop in well-being around age 19. Moreover, among the older teens, the team found evidence for the Goldilocks Hypothesis: the idea that both too much and too little time spent on social media can harm mental health.

“There’s hardly any effect if you look over everybody. But if you look at specific age groups, at particularly what [Orben] calls ‘windows of sensitivity’ … you see these clear effects,” says L.J. Shrum, a consumer psychologist at HEC Paris who was not involved with this research. His review of studies related to teen social media use and mental health is forthcoming in the Journal of the Association for Consumer Research.

Cause and effect

That longitudinal study hints at causation, researchers say. But one of the clearest ways to pin down cause and effect is through natural or quasi-experiments. For these in-the-wild experiments, researchers must identify situations where the rollout of a societal “treatment” is staggered across space and time. They can then compare outcomes among members of the group who received the treatment to those still in the queue — the control group.

That was the approach Makarin and his team used in their study of Facebook. The researchers homed in on the staggered rollout of Facebook across 775 college campuses from 2004 to 2006. They combined that rollout data with student responses to the National College Health Assessment, a widely used survey of college students’ mental and physical health.

The team then sought to understand if those survey questions captured diagnosable mental health problems. Specifically, they had roughly 500 undergraduate students respond to questions both in the National College Health Assessment and in validated screening tools for depression and anxiety. They found that mental health scores on the assessment predicted scores on the screenings. That suggested that a drop in well-being on the college survey was a good proxy for a corresponding increase in diagnosable mental health disorders. 

Compared with campuses that had not yet gained access to Facebook, college campuses with Facebook experienced a 2 percentage point increase in the number of students who met the diagnostic criteria for anxiety or depression, the team found.

When it comes to showing a causal link between social media use in teens and worse mental health, “that study really is the crown jewel right now,” says Cunningham, who was not involved in that research.

A need for nuance

The social media landscape today is vastly different than the landscape of 20 years ago. Facebook is now optimized for maximum addiction, Shrum says, and other newer platforms, such as Snapchat, Instagram and TikTok, have since copied and built on those features. Paired with the ubiquity of social media in general, the negative effects on mental health may well be larger now.

Moreover, social media research tends to focus on young adults — an easier cohort to study than minors. That needs to change, Cunningham says. “Most of us are worried about our high school kids and younger.” 

And so, researchers must pivot accordingly. Crucially, simple comparisons of social media users and nonusers no longer make sense. As Orben and Przybylski’s 2022 work suggested, a teen not on social media might well feel worse than one who briefly logs on. 

Researchers must also dig into why, and under what circumstances, social media use can harm mental health, Cunningham says. Explanations for this link abound. For instance, social media is thought to crowd out other activities or increase people’s likelihood of comparing themselves unfavorably with others. But big data studies, with their reliance on existing surveys and statistical analyses, cannot address those deeper questions. “These kinds of papers, there’s nothing you can really ask … to find these plausible mechanisms,” Cunningham says.

One ongoing effort to understand social media use from this more nuanced vantage point is the SMART Schools project out of the University of Birmingham in England. Pedagogical expert Victoria Goodyear and her team are comparing mental and physical health outcomes among children who attend schools that have restricted cell phone use to those attending schools without such a policy. The researchers described the protocol of that study of 30 schools and over 1,000 students in the July BMJ Open.

Goodyear and colleagues are also combining that natural experiment with qualitative research. They met with 36 five-person focus groups each consisting of all students, all parents or all educators at six of those schools. The team hopes to learn how students use their phones during the day, how usage practices make students feel, and what the various parties think of restrictions on cell phone use during the school day.

Talking to teens and those in their orbit is the best way to get at the mechanisms by which social media influences well-being — for better or worse, Goodyear says. Moving beyond big data to this more personal approach, however, takes considerable time and effort. “Social media has increased in pace and momentum very, very quickly,” she says. “And research takes a long time to catch up with that process.”

Until that catch-up occurs, though, researchers cannot dole out much advice. “What guidance could we provide to young people, parents and schools to help maintain the positives of social media use?” Goodyear asks. “There’s not concrete evidence yet.”

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• American Economic Review
• November 2022

Social Media and Mental Health

• Luca Braghieri
• Alexey Makarin
• Article Information

Additional Materials

• Replication Package
• Online Appendix (2.02 MB)
• Author Disclosure Statement(s) (370.60 KB)

JEL Classification

• L82 Entertainment; Media

• Open access
• Published: 13 March 2024

Effects of a 14-day social media abstinence on mental health and well-being: results from an experimental study

• Lea C. de Hesselle 1 &
• Christian Montag 1  

BMC Psychology volume  12 , Article number:  141 ( 2024 ) Cite this article

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Background and aim

The study investigated the effects of a 14-day social media abstinence on various mental health factors using an experimental design with follow-up assessment. Hypotheses included positive associations between problematic smartphone use (PSU) and depression, anxiety, fear of missing out (FoMO), and screentime. Decreases in screentime, PSU, depression and anxiety, and increases in body image were assumed for the abstinence group. Additionally, daily changes in FoMO and loneliness were explored.

Participants completed different questionnaires assessing PSU, FoMO, depression and anxiety, loneliness and body image and were randomized into control and social media abstinence groups. Daily questionnaires over 14 days assessed FoMO, loneliness, screentime, and depression and anxiety. 14 days after the abstinence, a follow-up questionnaire was administered. Multilevel models were used to assess changes over time.

PSU was positively associated with symptoms of depression, anxiety and FoMO, but not with screentime. Spline models identified decreased screentime and body image dissatisfaction for the intervention group. Depression and anxiety symptoms, PSU, trait and state FoMO, and loneliness, showed a decrease during the overall intervention time but no difference between the investigated groups could be observed (hence this was an overall trend). For appearance evaluation and body area satisfaction, an increase in both groups was seen. Daily changes in both loneliness and FoMO were best modelled using cubic trends, but no group differences were significant.

Results provide insights into effects of not using social media for 14 days and show that screentime and body image dissatisfaction decrease. The study also suggests areas for future studies to better understand how and why interventions show better results for some individuals.

Peer Review reports

Social media is part of everyday life with 4.76 billion users worldwide and a 3.0% annual increase [ 1 ]. The average time spent on social media is 2.5 hours, totalling 5 hours of screentime per day [ 1 ]. Simultaneously, there is a global rise in mental health issues with a 25% increase in anxiety disorders and a 28% increase in depressive symptoms, primarily affecting young adults [ 2 ]. It has already been discussed if the increase in social media use paved the way for the increase is psychopathologies, but establishing causality remains difficult [ 3 ]. Despite this, studies have linked problematic social media use to problems such as symptoms of depression and anxiety, [ 4 , 5 , 6 ] stress, negative body image and low physical activity [ 7 , 8 , 9 , 10 ].

While most studies use cross-sectional data, assessing changes over time in longitudinal data is necessary. The present study combines a longitudinal design and experimental approach to evaluate effects of a 14-day social media abstinence on several mental health factors.

Problematic smartphone use (PSU)

Smartphones enable various activities (e.g., communication, entertainment, gaming, online surfing or using social media). Excessive smartphone use which can lead to adverse consequences has been termed problematic smartphone use (PSU, [ 11 , 12 ]) This includes relying on the smartphone to regulate one’s mood, experiencing agitation in its absence, and unsuccessful attempts to reduce usage [ 11 , 12 ].

PSU has been associated with different negative life and health outcomes such as poor sleep quality, [ 13 , 14 , 15 ] impaired work and academic performance, [ 16 , 17 , 18 , 19 ] neck and shoulder pain, [ 20 , 21 ] and visual impairment [ 22 , 23 ]. Further, PSU has been positively associated with depression, anxiety, and Fear of Missing Out (FoMO) [ 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. Though simple cross-sectional associations do not allow causal interpretation, according to the Compensatory Internet Use Theory (CIUT, [ 31 ]) excessive smartphone use can be interpreted as a coping mechanism for dealing with life stressors and negative emotions. Seen this way: associations between negative affect and overuse of technology might exist due to “self-medication” principles, although such medical language needs to be further investigated regarding its fit in the realm of Internet Use Disorders [ 32 ]. Another theoretical framework which is often used in PSU research is the Interaction of Person-Affect-Cognition-Execution model (I-PACE, [ 33 , 34 ]). This model describes different core characteristics and dispositional factors (personality, history of psychopathology, genetics, etc.) which can impact on how situations are received and what the response is (cognitive biases, certain affective responses), thereby contributing to the development of PSU. It offers insights into, for example, how stressful situations might lead to heightened smartphone use (in detail: use of certain applications) as a coping mechanism for dealing with stress. Of note, the I-PACE model also presents a history of psychopathologies such as depression as a vulnerability factor within the P-variable to develop excessive online use patterns. Hence, much of the variables investigated and introduced later in this manuscript could be seen through the lens of the I-PACE model: in particular, we mention that the intervention aiming at reduction of social media use could trigger changes in cognitive and affective processes which in turn might result in lower psychopathological tendencies as recorded via several variables in the present work (e.g. depressive tendencies or body image dissatisfaction).

Though most aforementioned studies assess PSU via self-report questionnaires, some others have used objective measurements of smartphone use (screentime, screen unlocks) and found either no association between depression and screentime [ 27 ] or an inverse relationship between depression and number of screen unlocks, [ 27 , 35 ] indicating even a lower unlock frequency for depressed compared to non-depressed individuals. However, objective and subjective measures of smartphone use are only moderately associated [ 27 , 36 ].

Social media use

Social media use presents one specific form of spending (excessive) time on the smartphone as platforms enable users to share real-time pictures, videos, and other content, facilitating connections through likes, comments, and multimedia messages. A lot of daily smartphone screentime is spent on social media, potentially leading to adverse consequences. Problematic social media use (PSMU) shows itself in symptoms similar to PSU, however it applies especially to social media use. This includes maladaptive behaviours such as escalating time spent on social media and unsuccessful efforts to reduce usage, resulting in negative consequences for the user. One can see from the symptoms that an addiction framework will be used for the present work, although PSMU could also mean very different behavior such as cyberbullying online.

PSMU in terms of an addictive behavior (not officially recognized) has been linked to different health outcomes. Koc and Gulyagci [ 37 ] and Hong et al. [ 38 ] found that depressive symptoms positively predict Facebook addiction. Koc and Gulyagci [ 37 ] further identified anxiety and insomnia as positive predictors. Additionally, FoMO was identified as a strong predictor of (problematic) social media use [ 39 , 40 ] and is also linked to both higher PSMU and lower meaning in life [ 41 ]. Furthermore, associations between PSMU and depression, anxiety, stress, higher cognitive failures [ 42 ] and poor sleep quality were found [ 4 , 5 , 6 , 43 , 44 , 45 , 46 ]. Though most studies are cross-sectional, limiting causal interpretation, some longitudinal studies have been performed. One study found a bidirectional relationship between PSMU and depression and identified PSMU as predictor of insomnia, suicide related outcomes and ADHD symptoms [ 45 ]. PSMU could also lead to negative consequences such as low academic achievement, decrease in real life social participation, [ 47 , 48 ] negative work-family balance, and decreased job performance [ 49 ].

Marino et al. [ 50 ] and Montag et al. [ 51 , 52 ] showed moderate to high associations between PSU and PSMU, resulting from an overlap of both phenomena. See also other works [ 53 , 54 ], showing robust overlap between PSU and distinct forms of social media overuse. While a lot of time is spent on social media, [ 1 ] not all smartphone use can be attributed to social media use, because smartphones also serve for gaming, browsing or video watching, instead, total screentime represents all uses. In the present study, total smartphone screentime was assessed as the original intention was to focus on smartphone gaming as well (see Procedure and Sample) and the smartphone serves as the platform for both social media engagement and gaming activities. Consequently, screentime serves as a comprehensive measure, reflecting both gaming and social media usage (but also a myriad of other activities including e-mail-checking, listening to music, etc.).

Abstinence studies

Apart from assessing smartphone use and different outcomes, as mentioned above, assessing changes in outcomes due to not using the smartphone pose a possibility to infer about the causal direction of effects to answer questions such as that abstaining from smartphone and/or social media use results in less reported clinical symptoms, e.g. in the realm of depression or eating disorders. Several studies explored the effects of social media abstinence. Radtke et al. [ 55 ] found significant decreases in screen time during and after the intervention, mixed results on life satisfaction, decrease in anxiety and stress, improvement of sleep quality and mixed effects on FoMO and loneliness. However, the authors argue that different implementations of abstinence and measurements might account for the heterogeneity of findings. Another review by Fernandez et al. [ 56 ] found similar effects: increase in life satisfaction, affective well-being, decrease in perceived stress, and an increase in boredom, craving and time distortion.

Further studies – some with experimental designs – found a decrease in FoMO, increase in mental well-being and social connectedness, [ 57 ] and decreased depression and anxiety [ 58 ]. However, Vally and D’Souza [ 59 ] found a decrease in well-being, an increase in negative affect and loneliness during intervention and a nonsignificant increase in stress for the experimental group. Brailovskaia et al. [ 60 ] assessed if a full abstinence is necessary to see improvements in mental health or if a reduction of one hour per day would be enough. They found increased well-being and positive lifestyle changes in both experimental groups with stronger effects in the reduction group.

The effect sizes found in the mentioned studies are small to moderate with just few large effects.

Most of the aforementioned studies employed 7 days of abstinence with some exceptions where an abstinence of 14 days was implemented. Also, the foci of these studies were mainly on mental health variables like depression, anxiety, and FoMO. While these are key variables in the present study, another goal is to assess effects of social media abstinence on body image.

Research questions and hypotheses

This study aims to assess the effect of a 14-day social media abstinence on different mental health and well-being factors using an experimental design. A follow-up assessment 14 days after the end of the intervention was implemented to assess stability of effects. A single 14-day follow-up was chosen due to economic reasons as retaining study participants is harder, the longer a study runs. Also, previous studies [ 55 , 58 , 60 , 61 ] have realised different periods between end of intervention and follow-up (e.g. 48 hours, 4 days, 1 week, 1 month and 3 months), so using 14 days is somewhere in between, economically feasible and of the same length as the intervention period. Daily questionnaires were used to analyse changes during the intervention period.

The following hypotheses and research questions will be evaluated.

The hypotheses H1, H2.1 and H2.2 are based on baseline data collected before randomization into different groups.

H1: In the overall sample, PSU is positively associated with reported total screentime, depression and anxiety symptom severity, and FoMO, respectively.

Previous studies (but not all) showed a moderate positive association between PSU and objectively measured screentime [ 27 , 36 ]. Although participants manually input screentime (total smartphone use, not just social media), similar low to moderate associations can be expected. The present study should also be able to replicate positive associations between PSU and depression and anxiety symptoms, and FoMO.

H2.1: In the overall sample, screentime is positively but weakly associated with depression and anxiety scores, FoMO, and loneliness, respectively.

H2.2: In the overall sample, more screentime is negatively associated with body image.

Many of these associations have not been shown with screentime, but with (problematic) smartphone use [ 37 , 38 , 39 , 40 , 43 ]. This study did not assess (problematic) social media use. Instead, the variable of interest is screentime in association with different mental health outcomes. However, since a large amount of screentime also in the present participants is spent on social media, [ 1 ] it should be associated with the mentioned variables as well. Nonetheless, the correlations should be small, as Huang [ 62 ] showed in a meta-analysis that the time spent on social network sites is only weakly correlated with psychological wellbeing.

H3: Screentime decreases in the experimental group.

Since a good portion of screentime is spent on social media [ 1 ] an abstinence should reflect in overall decreased screentime. Total screentime was chosen as the measurement, because it reflects both time spent on social media and other smartphone activities.

H4: Depression and anxiety scores, and PSU scores decrease in the social media abstinence group.

Depression, anxiety, and PSU have been positively linked to problematic social media use [ 37 , 38 , 40 , 43 , 50 ]. So, reducing – or eliminating – social media should lead to decreasing symptoms. Additionally, previous abstinence studies showed decreased anxiety, stress and depression scores [ 55 , 60 ].

H5: Body image improves in the abstinence group.

Body image is negatively associated with social media use, as exposure to idealized body types and social comparison in particular on visual driven social media platforms could lead to body dissatisfaction [ 7 , 63 , 64 ]. Although social media is not the only factor contributing to a negative body image, [ 65 , 66 ] abstaining from it is likely to improve body image by reducing the exposure to social comparison.

RQ1: How does FoMO change over time?

Previous studies reported mixed results concerning changes in FoMO, [ 55 , 57 ] possibly due to different intervention durations. Potentially, FoMO increases during the first few days of social media abstinence and then decreases once participants adapt to not using social media to check up on their friends. This study aims to provide insights into the changes over time during the abstinence phase by assessing FoMO daily and comparing different trends over time.

RQ2: What is the impact of abstinence on loneliness?

Several studies assessed the effect of social media abstinence on loneliness and found mixed results [ 55 , 56 , 57 , 59 ]. Since loneliness was assessed daily, changes over the duration of abstinence can be detected and different trends can be compared.

RQ3: Are the changes observed during abstinence stable after the intervention?

Positive and negative changes due to abstinence from social media were already mentioned, but not much is known about the stability of these changes over time. Brailovskaia et al. [ 61 ] reported stable effects of changes after a 14-day gaming abstinence, however not much is known about stability after social media abstinence. Stability will be evaluated through change in scores between the end of intervention and the follow-up.

This study took place between October 2022 and February 2023. Participants were recruited via different university mailing lists, flyers posted around the university buildings, social media and eBay marketplace and underwent assessments outlined in Fig.  1 . Inclusion criteria were: legal age (18+), good knowledge of the German language, and use of smartphone and social media. This online study was conducted using the SurveyCoder website, [ 67 ] with questionnaires administered at baseline, daily, end of intervention and at follow-up. Participants received a daily link to the website via email at 4 pm. After the baseline questionnaires, participants were randomized into four groups and received intervention instructions. Since no tracking apps were used, the deinstallation of apps was not monitored. Participants were allowed to use their smartphones as normal for all other purposes and were only instructed to deinstall apps from their smartphones (other devices were not mentioned in the instruction). At the end of the intervention, participants were allowed to reinstall apps and were asked how they intend to manage their future social media consumption.

Schematic procedure. The procedure of the study is presented in the figure, the abbreviations for the included questionnaires are presented in the questionnaire section of this work

Originally, comparisons between all groups were planned, however due to data cleaning steps (see Sample), only groups 1) and 2) were used for analyses in the main body of this manuscript.

The initial sample compromised N  = 196 participants who provided combined datasets (baseline, daily, end of intervention and follow-up). After exclusion of non-users of social media or gaming apps in the experimental groups, a sample of n  = 165 participants was left. Since this sample consisted of 83.6% females and one focus of the study was the change in body image (which mainly shows effects for women), [ 68 ] only the female participants were analysed further.

From our view, this led to a too small group size for the gaming abstinence group to run robust statistics ( n  = 21). Since negative consequences due to gaming are mostly prevalent in men [ 69 ] and a small group size compared to the other groups can be problematic in analyses, this group was excluded from the main body of this manuscript (but see Supplement ). The combined abstinence group ( n  = 31) was also excluded as this would have been relevant to provide insights in particular in comparison to both the distinct gaming and social media abstinence groups. But since the gaming abstinence group was excluded, it was decided to exclude this from the manuscript as well (again, for more information see Supplement ).

Thus, the effective sample consisted of n  = 86 female participants which were randomized into control group ( n  = 35) and social media abstinence group ( n  = 51). Most participants held A-level qualifications (64.0%) or university degrees (29.1%) and were currently enrolled at university (77.9%). Groups were comparable in terms of age (m control = 23.17, s control = 6.99; m socmed =24, s socmed =4.63; t(54.233) = -0.61, p = .54), education (majority have A-levels (63% in control group; 65% in social media abstinence group); followed by university degree (28% in control group; 29% in social media abstinence group), \({\chi }^{2}\) (3) = 1.47, p = .69), and current occupational status (77% university students in control group; 78% university students in social media abstinence group; \({\chi }^{2}\) (4) = 3.33, p = .50).

Analyses including excluded groups are presented in the Supplementary Materials 1 and 5  -  10 .

Questionnaires

Fear of missing out.

Trait and online specific state FoMO was assessed using the TS FoMO scale [ 70 ] at baseline, end of the intervention and follow-up. Participants were asked to rate their agreement to 12 statements on a 5-point Likert scale (1 = “strong disagree”, 5 = “strong agree”). Mean scores for both subscales were computed and showed high internal consistency at all timepoints ( \(\alpha\)  = 0.76 – 0.83 and \(\alpha\)  = 0.77 – 0.79, respectively). The German version as provided by Wegmann et al. [ 70 ] was used in the present work.

Daily FoMO was assessed using a single item question (FoMOsf; [ 71 ]): “Do you experience FoMO (the fear of missing out)?” Riordan et al. [ 71 ] proposed this single item assessment which showed good validity. Participants rated how much this applied to them on the current day on a 5-point Likert scale (1 = “no, not true of me”, 5 = “yes, extremely true of me”).

Problematic smartphone use

PSU was assessed using the Smartphone Addiction Scale – Short Version (SAS-SV; [ 72 ]) where participants rated their agreement with different statements concerning their smartphone use. These statements include difficulty concentrating, agitation in the absence of the smartphone, persistent preoccupation with the device, exceeding intended use duration, frequent checking behaviour, experiencing physical discomfort during use, and missed work obligations due to excessive smartphone use. Agreement was provided on a 6-point Likert scale ranging from 1 = “strongly disagree” to 6 = “strongly agree” and sum scores were used in analyses (higher values = more PSU). The scale showed high internal consistencies at all time points ( \(\alpha\)  = 0.81 – 0.86). German version was used as in Haug et al. [ 73 ].

Depression and anxiety symptoms

Depression and anxiety symptoms were assessed using the 4-item Patient Health Questionnaire (PHQ-4; [ 74 ]). Participants were asked how often in the past seven days (for daily measurements: on the current day) they experienced different symptoms of depression or anxiety. Answers ranged from 0 = “no, not at all” to 3 = “nearly every day” (“nearly the whole day”) and were summed with higher values indicating more severe symptoms. The PHQ-4 demonstrated high internal consistency at all time points ( \(\alpha\)  = 0.81 - 0.87).

How often participants experienced loneliness and isolation from others was assessed using the German version of the UCLA 3-item loneliness scale [ 75 ] as in Montag et al. [ 76 ]. Answers were given on a 3-point Likert scale (1 = “hardly ever”, 3 = “often”) and summed with higher values indicating higher loneliness. The scale demonstrated good internal consistency ( \(\alpha\)  = 0.78 – 0.89).

Body Image Dissatisfaction (BID) was assessed using the BIAS-BD, [ 77 ] which presents two rows of schematic body figures ranging from 60% to 140% of the average BMI, separated for sex. Participants chose the figure best representing their actual and ideal body. Percentages were transformed into BMI equivalents and a BID score was computed as the difference between actual and ideal body size.

Further, the MBSRQ-AS [ 78 ] was used to measure different body image dimensions on 34 items: appearance evaluation (How content people are with their appearance), appearance orientation (How much attention people pay to their own appearance), body area satisfaction (How satisfied they are with different areas of their body), overweight preoccupation (How concerned they are with their weight and staying thin), and self-classified weight (How they would rate their own weight and how other people would rate their weight). Scores were summed for each dimension, and all showed good internal consistency with \(\alpha =\) 0.66 – 0.92.

Participants were asked to open the screentime feature on their smartphones and type the hours and minutes into the questionnaire. Values were converted into minutes for analysis. At baseline and follow-up, the screentime from the last seven days was averaged to represent the average daily screentime at baseline and follow-up, respectively. No differences were made between smartphone operating systems.

Fear of COVID-19

Fear of COVID-19 (FCV) was assessed at baseline using the FCV19S [ 79 , 80 ] to use as a covariate in analyses. This was due to the study being conducted amid the COVID-19 pandemic (October 2022 to February 2023), allowing for the proper consideration of various pandemic-related constraints in the analyses. The FCV19S demonstrated a good internal consistency of \(\alpha\)  = 0.83. Participants were asked to rate seven statements concerning their fear of COVID-19 on a 5-point Likert scale from 1 = “strongly disagree” to 5 = “strongly agree”. Scores were summed for analysis and higher values indicated more Fear of COVID-19. The German version used herein was by Fatfouta and Rogoza [ 80 ].

Further questionnaires

The following questionnaires were assessed but not included in the main analyses. They are included in the supplement (see Supplementary Material ): IPAQ (physical activity; [ 81 ]), PANAS – positive affect subscale, [ 82 , 83 ] Perceived Stress Scale (PSS-4; [ 84 , 85 ]) and satisfaction with life scale (SWLS; [ 86 , 87 ]). The cited German versions were used for all scales.

Data analysis

Data analysis was performed using R version 4.1.3 [ 88 ]. Apart from descriptive statistics at baseline, correlations were computed using Holm’s correction for p -values.

To model trends in outcome variables (PSU, FoMO, screentime, depression/anxiety, loneliness, body image), multilevel models were used. For the variables measured at three time points (baseline, end of intervention, follow-up), spline models were used with the knot point set to the end of intervention. This allows assessment of change between baseline values and end of intervention and between end and follow-up. Further, RQ3 can be answered using these models. For an explanation on spline models in the multilevel modelling framework, see Grimm et al. [ 89 ]. First, only the trend over time was modelled for the total sample (called model 1 for each outcome). Then, covariates were added (baseline FCV, PSU, and BID for MBSRQ-AS outcomes), and group differences were accounted for using dummy coded variables (0 = control, 1 = abstinence group; called model 2 for each outcome). Random intercepts were used for all models to allow for interindividual differences in values and where possible, random slopes were used to allow for interindividual differences in change over time. The R-packages lme4 version 1.1.28 [ 90 ] and lmerTest version 3.1.3 [ 91 ] were used.

For daily measured outcomes, several multilevel models were computed. First, a linear trend over time for all experimental groups was evaluated. This model included baseline PSU, FCV, and the respective baseline value of each outcome. Then, the group variable was added to a separate model. To further assess changes over time in FoMO and loneliness (RQ1 and RQ2), different trends over time were assumed (quadratic, cubic) and models were compared using AIC, BIC and Likelihood Ratio Tests.

Datasets and analysis scripts are available at the Open Science Framework https://osf.io/qdp8r/ .

The present study was approved by the university’s ethics committee (Ethics committee of University of Ulm) under application number 252/22.

Descriptive statistics at baseline are presented in Table 1 . Due to randomization, no group differences were expected, and t-tests were non-significant.

Correlations

Correlations at baseline are presented in Table 2 with Holm corrected p -values and 95% confidence intervals.

Multilevel models

Results from models for outcome variables measured at three time points are presented in Table 3 .

For depression and anxiety symptoms, model 1 with fixed slope showed a significant negative trend before the knot point (b = -0.60, t(160.76) = -2.52, p  = .013), but no change afterwards. Model 2 showed no significant change over time or differences between groups.

Model 1 for screentime showed nonsignificant changes across all time points. Upon incorporating covariates, no significant changes over time were observed for the control group. However, there was a significant difference in change between baseline and end of intervention between control group and abstinence group, as evidenced by one-sided testing (b = -38.905, t(159.8) = -1.685, p  = .094/2 = .047). This indicates a decrease in screentime in the abstinence group. See Fig.  2 for a graphical representation of mean values in both groups.

Plot of main results: changes in Body Image Dissatisfaction (BID) and average daily screentime

Using PSU as outcome, model 1 showed a significant negative linear trend before the knot point (b = -4.023, t(150.54) = -5.583, p  < .001) and a nonsignificant negative trend after the knot point. There was random variance for the trend over time. In model 2, only baseline FCV was added as covariate and had a significant influence on PSU. Further, the pre-knot negative trend was significant for the control group and no differences between groups were seen.

Model 1 for loneliness showed a significant negative linear change between baseline and end of intervention (b = -0.66, t(139.39) = -4.751, p  < .001), indicating an overall decrease in loneliness during the intervention. In model 2, the negative linear change between baseline and end of intervention was significant for the control group and there were no group differences.

For state FoMO, model 1 showed a significant negative trend between baseline and end of intervention (b = -0.22, t(161.11) = -3.813, p  < .001) and no change between end of intervention and follow-up. Model 2 showed no significant trend over time in the control group and no differences between groups.

There was a significant negative trend in model 1 for trait FoMO for the change between baseline and end of intervention (b = -0.52, t(157.63) = -7.30, p  < .001) and no change afterwards. Model 2 showed a significant negative pre-knot point trend for the control group. This trend did not differ between groups, however the difference in values at the knot point (end of intervention) was significantly lower for the abstinence group.

The first model assessing trend over time showed a nonsignificant decrease in BID between baseline and end of intervention and no change afterwards. Model 2 showed no significant change over time for the control group. However, the difference in change between baseline and end of intervention was significant for one-sided testing (b = -0.95, t(139.64) = -1.900, p  = .0595/2 = .029), indicating that BID values decreased more for the social media abstinence group compared to the control group. See Fig.  2 for a graphical representation of the mean values of both groups.

In model 1, appearance evaluation showed a significant increase between baseline and end of intervention (b = 0.988, t(161.02) = 2.736, p  < .001) and no change afterwards. In model 2, the positive change between baseline and end of intervention was only significant for the control group.

Overweight preoccupation showed no change over time in model 1. Upon adding covariates and a group variable, there was a significant negative trend for the change between baseline and end of intervention in the control group. No group differences were found.

Model 1 revealed an almost significant increase in body area satisfaction during the intervention (b = 0.698, t(136.24) = 1.899, p  = .0597) and no change afterwards. However, this trend was not significant in model 2 with covariates and group variable, nor was there a difference between groups.

No effect of either time or group could be identified for self-classified weight and appearance orientation.

Daily data models

For the daily data models, different trends were modelled for each variable. As covariates in all models the respective values at baseline were used as well as baseline FCV19, PSU, and BID. Results are provided in Table 4 .

For the total sample, linear (model 1) or quadratic (model 2) trend over time for screentime could not be found. Upon adding the group variable in the quadratic trend model (model 4), the interaction term for linear trend and abstinence group was almost significant (b = 8.56, t(1046.18) = 1.800, p  = .072), as well as the interaction between the quadratic trend and the abstinence group (b = -0.61, t(1045.28) = -1.727, p  = .084). This indicates a different change in screentime for the social media abstinence group than observed in the control group.

Linear (model 1) and quadratic (model 2) trends for changes in loneliness were not supported for the total sample. Model 3 assumed a cubic trend and found significant results for the linear, quadratic and cubic parts of the trend. Model comparisons between three models identified model 3 as the best fitting model (AIC = 3596.9, BIC = 3647.2, M2 vs. M3:  \({\chi }^{2}\) (1) = 6.78, p  < .01).

Models 4 (linear trend and group) and 5 (quadratic trend and group) showed no trends over time nor group differences. Model 6 – including a cubic trend – showed significant linear, quadratic and cubic trends for the control group and no differences between groups. This model fit the data best (AIC = 3597.2, BIC = 3667.6, M5 vs. M6:  \({\chi }^{2}\) (2) = 9.92, p  < .01). However, there was no significant difference between models with and without the group variable (M3 vs. M6: \({\chi }^{2}\) (4) = 7.6911, p  = .1036).

Model 1 showed no significant linear trend over time in depression and anxiety symptoms. Model 2 included the linear trend over time and the group variable and showed an almost significant negative change for the control group (b = -0.04, t(1048.51) = -1.834, p  = .067) and a significant interaction between daily change and the abstinence group (b = 0.06, t(1046.40) = 2.429, p  < .05), indicating different changes over time between both groups.

Model 1 found a significant negative linear trend with an average 0.0195 decrease per day for FoMO. Model 2 included a quadratic trend as well as the linear trend and found the linear trend to be significant (b = -0.054, t(1043) = -2.506, p  < .05). Model 3 assumed a cubic trend and found this to be significant. Model comparisons identified model 3 as best fitting (AIC = 2862.6, BIC = 2918.0, M2 vs. M3: \({\chi }^{2}\) (1) = 19.116, p  < .001).

Model 4 found a significant negative linear trend for the control group and no group differences. Model 5 (quadratic trend) found no significant linear or quadratic trend for either group. Model 6 (cubic trend) found a significant linear, quadratic and cubic trend for the control group, but no difference between the groups. Model 6 was identified as the best fitting model containing the group variable (AIC = 2866.4, BIC = 2941.9, M5 vs. M6: \({\chi }^{2}\) (2) = 20.22, p  < .001), however the fit was not significantly different from model 3 (M3 vs. M6: \({\chi }^{2}\) (4) = 4.1824, p  = .3819).

The aim of this study was to evaluate the impact of a 14-day social media abstinence on different mental health and well-being variables and body image. Results are discussed below.

Associations between variables

The study’s findings align with the expectations outlined in H1. PSU demonstrated a weak positive association with screentime, although it was not statistically significant, which is consistent with prior research [ 27 , 36 ]. This supports the notion that self-reported PSU and screentime is not necessarily the same construct and that screentime is not an appropriate measure for PSU. Furthermore, different uses and motives for smartphone use can explain why some people have high screentime but low PSU.

Motives can be evaluated using the CIUT [ 31 ]. Though literature on associations between smartphone use motives and screentime is not exhaustive, studies have found that motives like mood regulation and enjoyment are positively associated with PSU, whereas information seeking and socializing are less likely to have an influence on addictive behaviour in the realm of smartphones [ 92 , 93 ]. Additional motives for use were distress tolerance and mindfulness, [ 94 ] FoMO, [ 95 , 96 ] and boredom proneness [ 96 , 97 ].

PSU was assumed to be positively associated with depression and anxiety symptom severity (H1) and a moderate association (albeit not significant for this sample) has been found. Again, this is consistent with previous literature [ 24 , 25 , 26 , 27 ].

The hypothesized association between PSU and state FoMO was highly positive whereas the association with trait FoMO was moderately positive, supporting H1. Both can be interpreted as people experiencing more PSU symptoms also experience more FoMO. Again, these results are in accordance with previous studies identifying FoMO as a correlate of PSU [ 25 ]. Furthermore, according to the I-PACE model [ 33 , 34 ] trait FoMO can be seen as a core characteristic impacting how certain situations are received and responded to, thus, contributing to the development of PSU (please note that due to the overlap with neuroticism, it might be also seen as a trait; [ 98 ]).

Positive but weak associations were found for screentime and depression/anxiety symptom severity, FoMO, and loneliness, supporting H2.1. All associations are low (to moderate for screentime and depression/anxiety) and not significant in the present sample. This was expected, as Huang [ 62 ] reported very small associations between time spent on social network sites and mental health variables. There are different uses of smartphones that can be unproblematic but lead to high screentimes (e.g attending online meetings or using the phone to study). This should be controlled for in future studies.

Hypothesis H2.2 assumed a negative correlation between screentime and body image. This hypothesis is supported only descriptively, as no correlation is significant. Screentime showed weak negative associations with appearance evaluation and body area satisfaction, and positive associations with appearance orientation (see that also using objective screentime-measures, a recent work by Rozgonjuk et al. [ 64 ] established links between longer smartphone use and higher body dissatisfaction; in this work also patients with eating disorders were investigated). The present findings suggest that individuals who spend more time on their smartphones are a little more appearance oriented and a little less satisfied with their bodies. However, it is crucial to note that screentime and exposure to online media are not the sole factors influencing BID [ 65 , 66 ]. Studies found that the type of screentime influences development of BID, at least for TV or computers [ 99 , 100 , 101 ]. Specifically, computer use for leisure activities was positively associated with BID whereas computer use for homework showed negative associations with BID [ 99 ]. Hrafnkelsdottir et al. [ 100 ] found positive correlations between gaming, TV/DVD/internet watching and BID and low correlations between BID and online communication. This suggests that different uses of smartphones and social media might have different impacts on body image. An assessment of motives of use could provide further insight.

Changes over time

An overall decrease in screentime during the intervention, especially for the abstinence group was found, supporting hypothesis H3. Since a large portion of screentime is spent on social media, [ 1 ] abstinence from selected applications should be reflected in overall decreased screentime. These results align with previous abstinence studies which also reported decreased screentime [ 55 , 57 ]. However, on a day-to-day basis during the intervention, no significant changes in screentime were found. This could be attributed to fluctuating screentimes or compensatory behaviour, such as switching to other apps to fill the time.

Depression and anxiety scores decreased when assessing the total sample but there was no change nor difference between groups when considering the group variable. Therefore, H4 is not supported for depression and anxiety. Contrary to the hypothesis, daily models showed a decrease in the control group and an increase in the experimental group (please note that these observations are on a descriptive level only and changes were not pronounced). However, according to the CIUT, [ 31 ] smartphones and by extension social media can act as a coping mechanism and as an escape to handle negative emotions and daily hassles. If this outlet is unavailable, symptoms of depression and anxiety might increase (we are not of the opinion though that social media use should be seen as an effective way to deal with one's own problems and it is unclear how long lasting the effect around depression and anxiety would be). Motives of use are often evaluated in gaming research and escapism was identified as a strong predictor for gaming time (and gaming disorder, [ 102 ]), highlighting the tendency of dealing with negative emotions by escaping into an online world [ 103 ].

Additional analyses were conducted to examine the relationship between changes in depression and anxiety scores and baseline PSU, across groups (total sample). The results indicated a weak negative correlation, suggesting that, across groups, individuals with higher baseline PSU scores experienced more decrease in depression and anxiety scores compared to those with lower PSU scores. Since there was only a minimal difference in baseline PSU scores between the experimental groups (see Table 1 ), the association between baseline PSU values and change in depression and anxiety scores cannot be the reason for the different trends over time measured in the depression and anxiety scores.

However, when baseline depression and anxiety scores were correlated with changes in anxiety and depression scores, a moderate negative correlation emerged. The control group displayed slightly higher baseline scores than the abstinence group, although this difference was not statistically significant. This provides a possible explanation to the reduction in depression and anxiety scores in the control group compared to the abstinence group.

For PSU, an overall decrease was found during and after the intervention. However, there were no differences between groups. Possibly, the study attracted individuals seeking to change their social media habits as it was advertised as an abstinence study. Intention towards future social media use was assessed at the end of intervention and follow-up with most participants expressing a desire to reduce their social media time (end of intervention: 57% in control group, 49% in abstinence group; follow-up: 48% in control group, 66% in abstinence group). Since there was no big group difference in the number of participants with this answer, controls possibly intended to reduce their social media consumption even before their study participation and changed their behaviour, thus experiencing less PSU.

Additionally, PSU is not synonymous with social media use. Though studies found a strong positive association between PSU and PSMU, [ 50 ] PSU can develop through other smartphone uses than social media. Plus, participants were asked to abstain only from selected social media but were able to freely use their phones for other uses.

Body image was assessed using different variables. Appearance orientation and self-classified weight showed no changes over time or between groups. There was an overall increase in appearance evaluation and body area satisfaction due to the intervention, but no differences between groups. Overweight preoccupation decreased for the control group and there was no difference in changes between groups.

The BID values decreased significantly more in the abstinence group than in the control group, suggesting that taking a break from exposure on social media is helpful in decreasing BID. Overall, hypothesis H5, suggesting social media abstinence improves body image satisfaction and decreases dissatisfaction, was partially supported. However, the effect is small, as social media is not the only factor influencing body image [ 65 , 66 ]. Social comparison occurs not only on social media but in real-life interactions and through other media like TV or magazines.

Daily change in FoMO (RQ1) was best modelled using a cubic trend. Nevertheless, there were no group differences, suggesting day-to-day fluctuation in FoMO regardless of whether social media apps were used or not. Previous studies found mixed outcomes regarding intervention on FoMO, [ 55 , 57 ] but only assessed it for 7 days. Since FoMO fluctuates, assessing changes over a longer period of time offers a more comprehensive dataset for fitting appropriate models.

Trait and state FoMO decreased during intervention in both groups and remained stable afterwards. The absence of group differences can be attributed to individuals using their phones for different uses that do not necessarily influence FoMO. Elhai et al. [ 104 ] found that FoMO is more associated with non-social smartphone use like entertainment, news and relaxation compared to social smartphone use. Though PSU was positively related to both trait and state FoMO, screentime was not associated with either. This suggests that simply abstaining from social media may not lead to reduced FoMO, at least not in the here investigated time interval. Furthermore, since traits are considered relatively stable constructs, [ 105 ] it is debatable if a change in trait FoMO can be expected. Trait FoMO can be also conceptualized as dispositional factor in the I-PACE model [ 33 , 34 ] and is a stable influence on the development of PSU. Since dispositional factors are not expected to change strongly – especially not in a short time frame – the observed change was more likely an artifact in data.

A cubic trend was also the best way to model daily changes in loneliness (RQ2), though there were no significant group differences. Both groups experienced a decrease in loneliness during the intervention and no change afterwards. This suggests that overall, loneliness decreased but due to factors other than not using social media apps. This study did not assess other life events, making it challenging to explain this change fully. Furthermore, previous studies found mixed effects of abstinence on loneliness [ 55 , 56 , 57 , 59 ]. Moreover, there are different motives for social media use and not all are related to social interaction. These results can also be interpreted in the context of the uses and gratification theory [ 106 ] as the smartphone can be used to fulfil individuals needs such as representation, maintaining social networks, receiving online support, relaxing, or escaping from pressures [ 107 ]. Not all motives are related to loneliness.

The majority of spline models did not show significant changes after the intervention, indicating stability in the effects and addressing RQ3. Specifically, this applies to changes in BID and screentime, where differences between the experimental and control groups were seen. For the other variables, there were no group differences, but the changes between baseline and end of intervention measurements suggested an overall decrease (depression and anxiety, PSU, overweight preoccupation, state and trait FoMO, loneliness) or increase (appearance evaluation, body area satisfaction) and no change afterwards. However, these changes apply to both groups, meaning the control group changed as well and abstinence was not the sole reason for change, but maybe the intention to reduce consumption was.

Contribution and limitations

The present study provides novel insights into the relationships between social media use and mental health and well-being. Notably, this study used an experimental design to implement a 14-day intervention and conducted a follow-up assessment 14 days after this intervention. Furthermore, this work focussed on body image and its changes over time. This can provide information for future studies or intervention designs as it shows that body image dissatisfaction can be decreased by not using social media for 14 days. The experimental approach adds depth to the understanding of the impact of social media on body image, a topic that has primarily been explored through correlative studies. The present results can also provide a first basis for inventing and implementing interventions in the realm of eating disorders or body schema disorders, as it shows that abstaining from social media might improve body satisfaction (replication of the present findings is of importance). But: As there is currently no consensus or official diagnosis for PSU and also against the limitations mentioned below, authors refrain from proposing clinical implications based on reduced screentime during intervention at the moment.

Additionally, previous studies modelled FoMO as linear change over time and often only assessed one week of change. The present study provides more detailed insight into daily FoMO as well as daily loneliness changes and found that both can be best represented using a cubic trend.

There are several limitations. First, the original study design intended to include four groups for comparison, but due to a high percentage of women in the sample, only female participants were analysed in the main manuscript, leading to exclusion of the gaming disorder groups. Consequently, small sample sizes were used for analyses, resulting in low statistical power. While some results were directionally clear, they did not reach statistical significance in the present work. Second, PSMU was not assessed alongside PSU, which should be considered in future studies. Screentime was not objectively measured but participants manually input the information from their screentime feature (hence we have an indirect objective screentime measure, which might be prone to transfer error though but was checked for plausability). In further studies, an objective measurement could be implemented by either using tracking apps – and thus validating if participants use social media apps – or asking for screenshots of the screentime feature. Measurement of total screentime and PSU were chosen as the original intention was to include the gaming and combined abstinence groups. In that case, both screentime and PSU would be acceptable measurements for all groups, as gaming and social media use can be reflected in total screentime and can both lead to symptoms of PSU.

Aside from assessing PSMU and using an objective measure for future studies it is suggested to assess motives and uses for individual’s smartphone use because this could provide further insight into why outcomes change for some participants but not for all. This could also aid in developing more nuanced interventions that properly fit a person’s needs. Lastly, different groups with different levels of abstinence could be realized. This has previously been done by Brailovskaia et al. [ 60 ] for general smartphone use.

Using a longitudinal and experimental approach to a 14-day social media abstinence, the present study was able to show significant decreases in BID and screentime due to abstinence. Further, mental well-being factors were evaluated and showed improvement over time but did not differ between groups. Using daily assessments of FoMO and loneliness, cubic trends were identified as the best way to model fluctuation in these variables. These findings provide valuable insights into the complex dynamics of social media use and its impact on mental health and well-being and can provide information to plan future interventions addressing social media/smartphone use or body image related disorders.

Availability of data and materials

Abbreviations.

Akaike Information criterion

Bayesian information criterion

Body image dissatisfaction

Body mass index

Compensatory Internet Use Theory

Fear of Missing Out

Positive affect negative affect scale

Patient health questionnaire 4

Problematic social media use

Perceived stress scale

Research question

Smartphone Addiction Scale – short version

Satisfaction with Life scale

Trait State FoMO scale

We Are Social Ldt. We Are Social UK. 2023. Cited 2023 Mar 15. The Changing World of Digital In 2023. Available from: https://wearesocial.com/uk/blog/2023/01/the-changing-world-of-digital-in-2023/ .

Forbes Health. 2023. Cited 2023 Mar 17. Mental Health Statistics. Available from: https://www.forbes.com/health/mind/mental-health-statistics/ .

Twenge JM, Joiner TE, Rogers ML, Martin GN. Increases in Depressive Symptoms, Suicide-Related Outcomes, and Suicide Rates Among U.S. Adolescents After 2010 and Links to Increased New Media Screen Time. Clin Psychol Sci. 2018;6(1):3–17.

Article   Google Scholar  

Bashir H, Bhat S. Effects of social media on mental health: a review. Int J Indian Psychol. 2016;1(4):125–31.

Google Scholar  

Dhir A, Yossatorn Y, Kaur P, Chen S. Online social media fatigue and psychological wellbeing—A study of compulsive use, fear of missing out, fatigue, anxiety and depression. Int J Inf Manag. 2018;40:141–52.

Karim F, Oyewande AA, Abdalla LF, Ehsanullah RC, Khan S. Social Media Use and Its Connection to Mental Health: A Systematic Review. Cureus. 2020;12(6). Cited 2022 Jun 28. Available from: https://www.cureus.com/articles/31508-social-media-use-and-its-connection-to-mental-health-a-systematic-review .

Fardouly J, Vartanian LR. Social media and body image concerns: current research and future directions. Curr Opin Psychol. 2016;9:1–5.

Grimaldi-Puyana M, Fernández-Batanero JM, Fennell C, Sañudo B. Associations of objectively-assessed smartphone use with physical activity, sedentary behavior, mood, and sleep quality in young adults: a cross-sectional study. Int J Environ Res Public Health. 2020;17(10):3499.

Article   PubMed   PubMed Central   Google Scholar  

Lin ML, Wang WY, Liao CC, Luo YJ, Kao CC. Examining thevel among University Students in Taiwan. Healthcare. 2020;8(4):556.

Shimoga SV, Erlyana E, Rebello V. Associations of social media use with physical activity and sleep adequacy among adolescents: cross-sectional survey. J Med Internet Res. 2019;21(6):e14290.

Billieux J, Maurage P, Lopez-Fernandez O, Kuss DJ, Griffiths MD. Can disordered mobile phone use be considered a behavioral addiction? An update on current evidence and a comprehensive model for future research. Curr Addict Rep. 2015;2(2):156–62.

Panova T, Carbonell X. Is smartphone addiction really an addiction? J Behav Addict. 2018;7(2):252–9.

Rod NH, Dissing AS, Clark A, Gerds TA, Lund R. Overnight smartphone use: A new public health challenge? A novel study design based on high-resolution smartphone data. PLOS One. 2018;13(10):e0204811.

Sohn SY, Rees P, Wildridge B, Kalk NJ, Carter B. Prevalence of problematic smartphone usage and associated mental health outcomes amongst children and young people: a systematic review, meta-analysis and GRADE of the evidence. BMC Psychiatry. 2019;19(1):356.

Yang J, Fu X, Liao X, Li Y. Association of problematic smartphone use with poor sleep quality, depression, and anxiety: a systematic review and meta-analysis. Psychiatry Res. 2020;284:112686.

Article   PubMed   Google Scholar  

Derks D, Bakker AB. Smartphone use, work-home interference, and burnout: a diary study on the role of recovery. Appl Psychol. 2014;63(3):411–40.

Hawi NS, Samaha M. To excel or not to excel: Strong evidence on the adverse effect of smartphone addiction on academic performance. Comput Educ. 2016;1(98):81–9.

Lee W Jun, Shin S. A Comparative Study Of Smartphone Addiction Drivers’ Effect On Work Performance In The U.S. And Korea. J Appl Bus Res. 2016;32(2):507–16.

Samaha M. Relationships among smartphone addiction, stress, academic performance, and satisfaction with life. Comput Hum Behav. 2016;321–5.

Kim SY, Koo SJ. Effect of duration of smartphone use on muscle fatigue and pain caused by forward head posture in adults. J Phys Ther Sci. 2016;28(6):1669–72.

Park J, Kim J, Kim J, Kim K, Kim N, Choi I, et al. The effects of heavy smartphone use on the cervical angle, pain threshold of neck muscles and depression. Adv Sci Technol Lett. 2015;91:12–7.

McCrann S, Loughman J, Butler JS, Paudel N, Flitcroft DI. Smartphone use as a possible risk factor for myopia. Clin Exp Optom. 2021;104(1). Cited 2021 May 24. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1111/cxo.13092 .

Wang J, Li M, Zhu D, Cao Y. Smartphone overuse and visual impairment in children and young adults: systematic review and meta-analysis. J Med Internet Re. 2020;22(12):e21923.

Demirci K, Akgönül M, Akpinar A. Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. J Behav Addict. 2015;4(2):85–92.

Elhai JD, Levine JC, Dvorak RD, Hall BJ. Fear of missing out, need for touch, anxiety and depression are related to problematic smartphone use. Comput Hum Behav. 2016;63:509–16.

Elhai JD, Dvorak RD, Levine JC, Hall BJ. Problematic smartphone use: a conceptual overview and systematic review of relations with anxiety and depression psychopathology. J Affect Disord. 2017;1(207):251–9.

Rozgonjuk D, Levine JC, Hall BJ, Elhai JD. The association between problematic smartphone use, depression and anxiety symptom severity, and objectively measured smartphone use over one week. Comput Hum Behav. 2018;1(87):10–7.

Thomée S, Härenstam A, Hagberg M. Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults - a prospective cohort study. BMC Public Health. 2011;11(1):66.

Wolniewicz CA, Tiamiyu MF, Weeks JW, Elhai JD. Problematic smartphone use and relations with negative affect, fear of missing out, and fear of negative and positive evaluation. Psychiatry Res. 2018;262:618–23.

Yuan G, Elhai JD, Hall BJ. The influence of depressive symptoms and fear of missing out on severity of problematic smartphone use and Internet gaming disorder among Chinese young adults: A three-wave mediation model. Addict Behav. 2021;112: 106648.

Kardefelt-Winther D. A conceptual and methodological critique of internet addiction research: towards a model of compensatory internet use. Comput Hum Behav. 2014;1(31):351–4.

Montag C, Marciano L, Schulz PJ, Becker B. Unlocking the brain secrets of social media through neuroscience. Trends Cogn Sci. 2023;27(12):1102–4.

Brand M, Wegmann E, Stark R, Müller A, Wölfling K, Robbins TW, et al. The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behaviors: Update, generalization to addictive behaviors beyond internet-use disorders, and specification of the process character of addictive behaviors. Neurosci Biobehav Rev. 2019;1(104):1–10.

Brand M, Young KS, Laier C, Wölfling K, Potenza MN. Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model. Neurosci Biobehav Rev. 2016;1(71):252–66.

Elhai JD, Tiamiyu MF, Weeks JW, Levine JC, Picard KJ, Hall BJ. Depression and emotion regulation predict objective smartphone use measured over one week. Personal Individ Differ. 2018;133:21–8.

Boase J, Ling R. Measuring mobile phone use: self-report versus log data. J Comput-Mediat Commun. 2013;18(4):508–19.

Koc M, Gulyagci S. Facebook addiction among turkish college students: the role of psychological health, demographic, and usage characteristics. Cyberpsychology Behav Soc Netw. 2013;16(4):279–84.

Hong FY, Huang DH, Lin HY, Chiu SL. Analysis of the psychological traits, Facebook usage, and Facebook addiction model of Taiwanese university students. Telemat Inform. 2014;31(4):597–606.

Blackwell D, Leaman C, Tramposch R, Osborne C, Liss M. Extraversion, neuroticism, attachment style and fear of missing out as predictors of social media use and addiction. Pers Individ Differ. 2017;1(116):69–72.

Pontes HM, Taylor M, Stavropoulos V. Beyond, “facebook addiction”: The role of cognitive-related factors and psychiatric distress in social networking site addiction. Cyberpsychol Behav Soc Netw. 2018;21(4):240–7.

Montag C, Müller M, Pontes HM, Elhai JD. On fear of missing out, social networks use disorder tendencies and meaning in life. BMC Psychol. accepted;

Montag C, Markett S. Social media use and everyday cognitive failure: investigating the fear of missing out and social networks use disorder relationship. BMC Psychiatry. 2023;23(1):872.

Andreassen CS. Online social network site addiction: a comprehensive review. Curr Addict Rep. 2015;2(2):175–84.

Hussain Z, Griffiths MD. The associations between problematic social networking site use and sleep quality, attention-deficit hyperactivity disorder, depression, anxiety and stress. Int J Ment Health Addict. 2021;19(3):686–700.

Hussain Z, Starcevic V. Problematic social networking site use: a brief review of recent research methods and the way forward. Curr Opin Psychol. 2020;36:89–95.

Mok WT, Sing R, Jiang X, See SL. Investigation of social media on depression. In: The 9th International Symposium on Chinese Spoken Language Processing. 2014. 488–91.

Kuss DJ, Griffiths MD. Online social networking and addiction—a review of the psychological literature. Int J Environ Res Public Health. 2011;8(9):3528–52.

Ponnusamy S, Iranmanesh M, Foroughi B, Hyun SS. Drivers and outcomes of Instagram addiction: psychological well-being as moderator. Comput Hum Behav. 2020;1(107):106294.

Zivnuska S, Carlson JR, Carlson DS, Harris RB, Harris KJ. Social media addiction and social media reactions: the implications for job performance. J Soc Psychol. 2019;159(6):746–60.

Marino C, Canale N, Melodia F, Spada MM, Vieno A. The overlap between problematic smartphone use and problematic social media use: a systematic review. Curr Addict Rep. 2021;8(4):469–80.

Montag C, Sindermann C, Rozgonjuk D, Yang S, Elhai JD, Yang H. Investigating links between fear of COVID-19, neuroticism, social networks use disorder, and smartphone use disorder tendencies. Front Psychol. 2021;2(12):682837.

Montag C, Wegmann E, Sariyska R, Demetrovics Z, Brand M. How to overcome taxonomical problems in the study of Internet use disorders and what to do with “smartphone addiction”? J Behav Addict. 2021;9(4):908–14.

Sha P, Sariyska R, Riedl R, Lachmann B, Montag C. Linking internet communication and smartphone use disorder by taking a closer look at the facebook and whatsapp applications. Addict Behav Rep. 2019;1(9):100148.

Rozgonjuk D, Sindermann C, Elhai JD, Christensen AP, Montag C. Associations between symptoms of problematic smartphone, Facebook, WhatsApp, and Instagram use: an item-level exploratory graph analysis perspective. J Behav Addict. 2020;9(3):686–97.

Radtke T, Apel T, Schenkel K, Keller J, von Lindern E. Digital detox: An effective solution in the smartphone era? A systematic literature review. Mob Media Commun. 2022;10(2):190–215.

Fernandez DP, Kuss DJ, Griffiths MD. Short-term abstinence effects across potential behavioral addictions: a systematic review. Clin Psychol Rev. 2020;76:101828.

Brown L, Kuss DJ. Fear of missing out, mental wellbeing, and social connectedness: a seven-day social media abstinence trial. Int J Environ Res Public Health. 2020;17(12):4566.

Lambert J, Barnstable G, Minter E, Cooper J, McEwan D. Taking a one-week break from social media improves well-being, depression, and anxiety: a randomized controlled trial. Cyberpsychol Behav Soc Netw. 2022;25(5):287–93.

Vally Z, D’Souza CG. Abstinence from social media use, subjective well-being, stress, and loneliness. Perspect Psychiatr Care. 2019;55(4):752–9.

Brailovskaia J, Delveaux J, John J, Wicker V, Noveski A, Kim S, et al. Finding the “sweet spot” of smartphone use: Reduction or abstinence to increase well-being and healthy lifestyle?! An experimental intervention study. J Exp Psychol Appl. 2022. Cited 2022 Jun 1; Available from: https://psycnet.apa.org/fulltext/2022-50916-001.pdf .

Brailovskaia J, Meier-Faust J, Schillack H, Margraf J. A two-week gaming abstinence reduces Internet Gaming Disorder and improves mental health: an experimental longitudinal intervention study. Comput Hum Behav. 2022;1(134):107334.

Huang C. Time spent on social network sites and psychological well-being: a meta-analysis. Cyberpsychol Behav Soc Netw. 2017;20(6):346–54.

Perloff RM. Social media effects on young women’s body image concerns: theoretical perspectives and an agenda for research. Sex Roles. 2014;71(11):363–77.

Rozgonjuk D, Ignell J, Mech F, Rothermund E, Gündel H, Montag C. Smartphone and Instagram use, body dissatisfaction, and eating disorders: investigating the associations using self-report and tracked data. J Eat Disord. 2023;11(1):149.

Andsager JL. Research directions in social media and body image. Sex Roles. 2014;71(11):407–13.

Burnette CB, Kwitowski MA, Mazzeo SE. “I don’t need people to tell me I’m pretty on social media:” a qualitative study of social media and body image in early adolescent girls. Body Image. 2017;23:114–25.

Kannen C. SurveyCoder. 2020. Cited 2021 May 16. Available from: https://www.surveycoder.com/ .

Calogero RM, Thompson KJ. Gender and body image. In: Chrisler JC, McCreary DR, editors. Handbook of gender research in psychology. Springer; 2010. p. 153–84.

Chapter   Google Scholar  

Stevens MW, Dorstyn D, Delfabbro PH, King DL. Global prevalence of gaming disorder: a systematic review and meta-analysis. Aust N Z J Psychiatry. 2021;55(6):553–68.

Wegmann E, Oberst U, Stodt B, Brand M. Online-specific fear of missing out and Internet-use expectancies contribute to symptoms of Internet-communication disorder. Addict Behav Rep. 2017;1(5):33–42.

Riordan BC, Cody L, Flett JAM, Conner TS, Hunter J, Scarf D. The development of a single item FoMO (Fear of Missing Out) scale. Curr Psychol. 2020;39(4):1215–20.

Kwon M, Kim DJ, Cho H, Yang S. The Smartphone Addiction Scale: Development And Validation Of A Short Version For Adolescents. PLOS One. 2013;8(12):e83558.

Article   PubMed   PubMed Central   ADS   Google Scholar  

Haug S, Castro RP, Kwon M, Filler A, Kowatsch T, Schaub MP. Smartphone use and smartphone addiction among young people in Switzerland. J Behav Addict. 2015;4(4):299–307.

Kroenke K, Spitzer RL, Williams JBW, Löwe B. An ultra-brief screening scale for anxiety and depression: The PHQ–4. Psychosomatics. 2009;50(6):613–21.

PubMed   Google Scholar  

Hughes ME, Waite LJ, Hawkley LC, Cacioppo JT. A short scale for measuring loneliness in large surveys: results from two population-based studies. Res Aging. 2004;26(6):655–72.

Montag C, Schivinski B, Sariyska R, Kannen C, Demetrovics Z, Pontes HM. Psychopathological symptoms and gaming motives in disordered gaming—a psychometric comparison between the WHO and APA diagnostic frameworks. J Clin Med. 2019;8(10):1691.

Gardner RM, Jappe LM, Gardner L. Development and validation of a new figural drawing scale for body-image assessment: the BIAS-BD. J Clin Psychol. 2009;65(1):113–22.

Vossbeck-Elsebusch AN, Waldorf M, Legenbauer T, Bauer A, Cordes M, Vocks S. German version of the Multidimensional Body-Self Relations Questionnaire – Appearance Scales (MBSRQ-AS): Confirmatory factor analysis and validation. Body Image. 2014;11(3):191–200.

Ahorsu DK, Lin CY, Imani V, Saffari M, Griffiths MD, Pakpour AH. The fear of COVID-19 scale: development and initial validation. Int J Ment Health Addict. 2020;27:1–9.

Fatfouta R, Rogoza R. Psychometric Properties and Factor Structure of the German Version of the Fear of COVID-19 Scale. OMEGA - J Death Dying. 2021;13:00302228211062360.

Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International Physical Activity Questionnaire: 12-Country Reliability and Validity: Med Sci Sports Exerc. 2003;35(8):1381–95.

Breyer B, Bluemke M. Deutsche Version der Positive and Negative Affect Schedule PANAS (GESIS Panel). Zusammenstellung Sozialwissenschaftlicher Items Skalen ZIS. 2016. Cited 2022 Jun 1; Available from: http://zis.gesis.org/DoiId/zis242 .

Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J Pers Soc Psychol. 1988;54(6):1063–70.

Article   CAS   PubMed   Google Scholar  

Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385.

Schneider EE, Schönfelder S, Domke-Wolf M, Wessa M. Measuring stress in clinical and nonclinical subjects using a German adaptation of the Perceived Stress Scale. Int J Clin Health Psychol. 2020;20(2):173–81.

Diener E, Emmons RA, Larsen RJ, Griffin S. The Satisfaction With Life Scale. J Pers Assess. 1985;49(1):71–5.

Janke S, Glöckner-Rist A. Deutsche Version der Satisfaction with Life Scale (SWLS). Zusammenstellung Sozialwissenschaftlicher Items Skalen ZIS. 2012. Cited 2022 Jul 2; Available from: http://zis.gesis.org/DoiId/zis147 .

R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2022. Available from: https://www.R-project.org/ .

Grimm KJ, Ram N, Estabrook R. Growth modeling: structural equation and multilevel modeling approaches. New York, NY: Guilford Press; 2017. 537 p. (Methodology in the social sciences).

Bates D, Mächler M, Bolker B, Walker S. Fitting Linear Mixed-Effects Models Using lme4. J Stat Softw. 2015.;67(1). Cited 2023 Jul 23. Available from: http://www.jstatsoft.org/v67/i01/ .

Kuznetsova A, Brockhoff PB, Christensen RHB. lmerTest Package: Tests in Linear Mixed Effects Models. J Stat Softw. 2017;82(13). Cited 2023 Jul 23. Available from: http://www.jstatsoft.org/v82/i13/ .

Sullivan BM, George AM. The association of motives with problematic smartphone use: A systematic review. Cyberpsychology J Psychosoc Res Cyberspace. 2023;17(1). Cited 2023 Jul 15. Available from: https://cyberpsychology.eu/article/view/20905 .

Zhang KZK, Chen C, Lee MKO. Understanding the role of motives in smartphone addiction. In Proceeding of the 19th Pacific Asia Conference on Information Systems (PACIS 2014) Pacific Asia Conference on Information Systems. https://aisel.aisnet.org/pacis2014/131 .

Elhai JD, Levine JC, O’Brien KD, Armour C. Distress tolerance and mindfulness mediate relations between depression and anxiety sensitivity with problematic smartphone use. Comput Hum Behav. 2018;84:477–84.

Elhai JD, Yang H, Fang J, Bai X, Hall BJ. Depression and anxiety symptoms are related to problematic smartphone use severity in Chinese young adults: Fear of missing out as a mediator. Addict Behav. 2020;101:105962.

Wang Y, Yang H, Montag C, Elhai JD. Boredom proneness and rumination mediate relationships between depression and anxiety with problematic smartphone use severity. Curr Psychol. 2020; Cited 2021 Mar 9. https://doi.org/10.1007/s12144-020-01052-0 .

Elhai JD, Vasquez JK, Lustgarten SD, Levine JC, Hall BJ. Proneness to boredom mediates relationships between problematic smartphone use with depression and anxiety severity. Soc Sci Comput Rev. 2018;36(6):707–20.

Rozgonjuk D, Sindermann C, Elhai JD, Montag C. Individual differences in Fear of Missing Out (FoMO): Age, gender, and the Big Five personality trait domains, facets, and items. Personal Individ Differ. 2021;171:110546.

Añez E, Fornieles-Deu A, Fauquet-Ars J, López-Guimerà G, Puntí-Vidal J, Sánchez-Carracedo D. Body image dissatisfaction, physical activity and screen-time in Spanish adolescents. J Health Psychol. 2018;23(1):36–47.

Hrafnkelsdottir SM, Brychta RJ, Rognvaldsdottir V, Chen KY, Johannsson E, Guðmundsdottir SL, et al. Screen time and body image in Icelandic adolescents: sex-specific cross-sectional and longitudinal associations. Int J Environ Res Public Health. 2022;19(3):1308.

Tang L, Rifas-Shiman SL, Field AE, Austin SB, Haines J. Self-reported total screen time and viewing modes are associated with body dissatisfaction, disordered eating, and cosmetic surgery intentions among young adults. Nutrients. 2022;14(10):2027.

Wang HY, Cheng C. The associations between gaming motivation and internet gaming disorder: systematic review and meta-analysis. JMIR Ment Health. 2022;9(2):e23700.

de Hesselle LC, Rozgonjuk D, Sindermann C, Pontes HM, Montag C. The associations between Big Five personality traits, gaming motives, and self-reported time spent gaming. Personal Individ Differ. 2020;6:110483.

Elhai JD, Gallinari EF, Rozgonjuk D, Yang H. Depression, anxiety and fear of missing out as correlates of social, non-social and problematic smartphone use. Addict Behav. 2020;105:106335.

Anastasi A. The nature of psychological “traits.” Psychol Rev. 1948;55(3):127–38.

Katz E, Blumler JG, Gurevitch M. Uses and Gratifications Research. Public Opin Q. 1973;37(4):509–23.

Whiting A, Williams D. Why people use social media: a uses and gratifications approach. Qual Mark Res Int J. 2013;16(4):362–9.

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Dr. Montag reports no conflict of interest. However, for reasons of transparency Dr. Montag mentions that he has received (to Ulm University and earlier University of Bonn) grants from agencies such as the German Research Foundation (DFG). Dr. Montag has performed grant reviews for several agencies; has edited journal sections and articles; has given academic lectures in clinical or scientific venues or companies; and has generated books or book chapters for publishers of mental health texts. For some of these activities he received royalties, but never from gaming or social media companies. Dr. Montag mentions that he was part of a discussion circle (Digitalität und Verantwortung: https://about.fb.com/de/news/h/gespraechskreis-digitalitaet-und-verantwortung/ ) debating ethical questions linked to social media, digitalization and society/democracy at Facebook. In this context, he received no salary for his activities. Finally, he mentions that he currently functions as independent scientist on the scientific advisory board of the Nymphenburg group (Munich, Germany). This activity is financially compensated. Moreover, he is on the scientific advisory board of Applied Cognition (Redwood City, CA, USA), an activity which is also compensated.

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de Hesselle, L.C., Montag, C. Effects of a 14-day social media abstinence on mental health and well-being: results from an experimental study. BMC Psychol 12 , 141 (2024). https://doi.org/10.1186/s40359-024-01611-1

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Introduction

Social media has become a prominent fixture in the lives of many individuals facing the challenges of mental illness. Social media refers broadly to web and mobile platforms that allow individuals to connect with others within a virtual network (such as Facebook, Twitter, Instagram, Snapchat, or LinkedIn), where they can share, co-create, or exchange various forms of digital content, including information, messages, photos, or videos (Ahmed et al. 2019 ). Studies have reported that individuals living with a range of mental disorders, including depression, psychotic disorders, or other severe mental illnesses, use social media platforms at comparable rates as the general population, with use ranging from about 70% among middle-age and older individuals to upwards of 97% among younger individuals (Aschbrenner et al. 2018b ; Birnbaum et al. 2017b ; Brunette et al. 2019 ; Naslund et al. 2016 ). Other exploratory studies have found that many of these individuals with mental illness appear to turn to social media to share their personal experiences, seek information about their mental health and treatment options, and give and receive support from others facing similar mental health challenges (Bucci et al. 2019 ; Naslund et al. 2016b ).

Across the USA and globally, very few people living with mental illness have access to adequate mental health services (Patel et al. 2018 ). The wide reach and near ubiquitous use of social media platforms may afford novel opportunities to address these shortfalls in existing mental health care, by enhancing the quality, availability, and reach of services. Recent studies have explored patterns of social media use, impact of social media use on mental health and wellbeing, and the potential to leverage the popularity and interactive features of social media to enhance the delivery of interventions. However, there remains uncertainty regarding the risks and potential harms of social media for mental health (Orben and Przybylski 2019 ) and how best to weigh these concerns against potential benefits.

In this commentary, we summarized current research on the use of social media among individuals with mental illness, with consideration of the impact of social media on mental wellbeing, as well as early efforts using social media for delivery of evidence-based programs for addressing mental health problems. We searched for recent peer reviewed publications in Medline and Google Scholar using the search terms “mental health” or “mental illness” and “social media,” and searched the reference lists of recent reviews and other relevant studies. We reviewed the risks, potential harms, and necessary safety precautions with using social media for mental health. Overall, our goal was to consider the role of social media as a potentially viable intervention platform for offering support to persons with mental disorders, promoting engagement and retention in care, and enhancing existing mental health services, while balancing the need for safety. Given this broad objective, we did not perform a systematic search of the literature and we did not apply specific inclusion criteria based on study design or type of mental disorder.

Social Media Use and Mental Health

In 2020, there are an estimated 3.8 billion social media users worldwide, representing half the global population (We Are Social 2020 ). Recent studies have shown that individuals with mental disorders are increasingly gaining access to and using mobile devices, such as smartphones (Firth et al. 2015 ; Glick et al. 2016 ; Torous et al. 2014a , b ). Similarly, there is mounting evidence showing high rates of social media use among individuals with mental disorders, including studies looking at engagement with these popular platforms across diverse settings and disorder types. Initial studies from 2015 found that nearly half of a sample of psychiatric patients were social media users, with greater use among younger individuals (Trefflich et al. 2015 ), while 47% of inpatients and outpatients with schizophrenia reported using social media, of which 79% reported at least once-a-week usage of social media websites (Miller et al. 2015 ). Rates of social media use among psychiatric populations have increased in recent years, as reflected in a study with data from 2017 showing comparable rates of social media use (approximately 70%) among individuals with serious mental illness in treatment as compared with low-income groups from the general population (Brunette et al. 2019 ).

Similarly, among individuals with serious mental illness receiving community-based mental health services, a recent study found equivalent rates of social media use as the general population, even exceeding 70% of participants (Naslund et al. 2016 ). Comparable findings were demonstrated among middle-age and older individuals with mental illness accessing services at peer support agencies, where 72% of respondents reported using social media (Aschbrenner et al. 2018b ). Similar results, with 68% of those with first episode psychosis using social media daily were reported in another study (Abdel-Baki et al. 2017 ).

Individuals who self-identified as having a schizophrenia spectrum disorder responded to a survey shared through the National Alliance of Mental Illness (NAMI) and reported that visiting social media sites was one of their most common activities when using digital devices, taking up roughly 2 h each day (Gay et al. 2016 ). For adolescents and young adults ages 12 to 21 with psychotic disorders and mood disorders, over 97% reported using social media, with average use exceeding 2.5 h per day (Birnbaum et al. 2017b ). Similarly, in a sample of adolescents ages 13–18 recruited from community mental health centers, 98% reported using social media, with YouTube as the most popular platform, followed by Instagram and Snapchat (Aschbrenner et al. 2019 ).

Research has also explored the motivations for using social media as well as the perceived benefits of interacting on these platforms among individuals with mental illness. In the sections that follow (see Table 1 for a summary), we consider three potentially unique features of interacting and connecting with others on social media that may offer benefits for individuals living with mental illness. These include: (1) Facilitate social interaction; (2) Access to a peer support network; and (3) Promote engagement and retention in services.

Facilitate Social Interaction

Social media platforms offer near continuous opportunities to connect and interact with others, regardless of time of day or geographic location. This on demand ease of communication may be especially important for facilitating social interaction among individuals with mental disorders experiencing difficulties interacting in face-to-face settings. For example, impaired social functioning is a common deficit in schizophrenia spectrum disorders, and social media may facilitate communication and interacting with others for these individuals (Torous and Keshavan 2016 ). This was suggested in one study where participants with schizophrenia indicated that social media helped them to interact and socialize more easily (Miller et al. 2015 ). Like other online communication, the ability to connect with others anonymously may be an important feature of social media, especially for individuals living with highly stigmatizing health conditions (Berger et al. 2005 ), such as serious mental disorders (Highton-Williamson et al. 2015 ).

Studies have found that individuals with serious mental disorders (Spinzy et al. 2012 ) as well as young adults with mental illness (Gowen et al. 2012 ) appear to form online relationships and connect with others on social media as often as social media users from the general population. This is an important observation because individuals living with serious mental disorders typically have few social contacts in the offline world and also experience high rates of loneliness (Badcock et al. 2015 ; Giacco et al. 2016 ). Among individuals receiving publicly funded mental health services who use social media, nearly half (47%) reported using these platforms at least weekly to feel less alone (Brusilovskiy et al. 2016 ). In another study of young adults with serious mental illness, most indicated that they used social media to help feel less isolated (Gowen et al. 2012 ). Interestingly, more frequent use of social media among a sample of individuals with serious mental illness was associated with greater community participation, measured as participation in shopping, work, religious activities, or visiting friends and family, as well as greater civic engagement, reflected as voting in local elections (Brusilovskiy et al. 2016 ).

Emerging research also shows that young people with moderate to severe depressive symptoms appear to prefer communicating on social media rather than in-person (Rideout and Fox 2018 ), while other studies have found that some individuals may prefer to seek help for mental health concerns online rather than through in-person encounters (Batterham and Calear 2017 ). In a qualitative study, participants with schizophrenia described greater anonymity, the ability to discover that other people have experienced similar health challenges and reducing fears through greater access to information as important motivations for using the Internet to seek mental health information (Schrank et al. 2010 ). Because social media does not require the immediate responses necessary in face-to-face communication, it may overcome deficits with social interaction due to psychotic symptoms that typically adversely affect face-to-face conversations (Docherty et al. 1996 ). Online social interactions may not require the use of non-verbal cues, particularly in the initial stages of interaction (Kiesler et al. 1984 ), with interactions being more fluid and within the control of users, thereby overcoming possible social anxieties linked to in-person interaction (Indian and Grieve 2014 ). Furthermore, many individuals with serious mental disorders can experience symptoms including passive social withdrawal, blunted affect, and attentional impairment, as well as active social avoidance due to hallucinations or other concerns (Hansen et al. 2009 ), thus potentially reinforcing the relative advantage, as perceived by users, of using social media over in person conversations.

Access to a Peer Support Network

There is growing recognition about the role that social media channels could play in enabling peer support (Bucci et al. 2019 ; Naslund et al. 2016b ), referred to as a system of mutual giving and receiving where individuals who have endured the difficulties of mental illness can offer hope, friendship, and support to others facing similar challenges (Davidson et al. 2006 ; Mead et al. 2001 ). Initial studies exploring use of online self-help forums among individuals with serious mental illnesses have found that individuals with schizophrenia appeared to use these forums for self-disclosure and sharing personal experiences, in addition to providing or requesting information, describing symptoms, or discussing medication (Haker et al. 2005 ), while users with bipolar disorder reported using these forums to ask for help from others about their illness (Vayreda and Antaki 2009 ). More recently, in a review of online social networking in people with psychosis, Highton-Williamson et al. ( 2015 ) highlight that an important purpose of such online connections was to establish new friendships, pursue romantic relationships, maintain existing relationships or reconnect with people, and seek online peer support from others with lived experience (Highton-Williamson et al. 2015 ).

Online peer support among individuals with mental illness has been further elaborated in various studies. In a content analysis of comments posted to YouTube by individuals who self-identified as having a serious mental illness, there appeared to be opportunities to feel less alone, provide hope, find support and learn through mutual reciprocity, and share coping strategies for day-to-day challenges of living with a mental illness (Naslund et al. 2014 ). In another study, Chang ( 2009 ) delineated various communication patterns in an online psychosis peer-support group (Chang 2009 ). Specifically, different forms of support emerged, including “informational support” about medication use or contacting mental health providers, “esteem support” involving positive comments for encouragement, “network support” for sharing similar experiences, and “emotional support” to express understanding of a peer’s situation and offer hope or confidence (Chang 2009 ). Bauer et al. ( 2013 ) reported that the main interest in online self-help forums for patients with bipolar disorder was to share emotions with others, allow exchange of information, and benefit by being part of an online social group (Bauer et al. 2013 ).

For individuals who openly discuss mental health problems on Twitter, a study by Berry et al. ( 2017 ) found that this served as an important opportunity to seek support and to hear about the experiences of others (Berry et al. 2017 ). In a survey of social media users with mental illness, respondents reported that sharing personal experiences about living with mental illness and opportunities to learn about strategies for coping with mental illness from others were important reasons for using social media (Naslund et al. 2017 ). A computational study of mental health awareness campaigns on Twitter provides further support with inspirational posts and tips being the most shared (Saha et al. 2019 ). Taken together, these studies offer insights about the potential for social media to facilitate access to an informal peer support network, though more research is necessary to examine how these online interactions may impact intentions to seek care, illness self-management, and clinically meaningful outcomes in offline contexts.

Promote Engagement and Retention in Services

Many individuals living with mental disorders have expressed interest in using social media platforms for seeking mental health information (Lal et al. 2018 ), connecting with mental health providers (Birnbaum et al. 2017b ), and accessing evidence-based mental health services delivered over social media specifically for coping with mental health symptoms or for promoting overall health and wellbeing (Naslund et al. 2017 ). With the widespread use of social media among individuals living with mental illness combined with the potential to facilitate social interaction and connect with supportive peers, as summarized above, it may be possible to leverage the popular features of social media to enhance existing mental health programs and services. A recent review by Biagianti et al. ( 2018 ) found that peer-to-peer support appeared to offer feasible and acceptable ways to augment digital mental health interventions for individuals with psychotic disorders by specifically improving engagement, compliance, and adherence to the interventions and may also improve perceived social support (Biagianti et al. 2018 ).

Among digital programs that have incorporated peer-to-peer social networking consistent with popular features on social media platforms, a pilot study of the HORYZONS online psychosocial intervention demonstrated significant reductions in depression among patients with first episode psychosis (Alvarez-Jimenez et al. 2013 ). Importantly, the majority of participants (95%) in this study engaged with the peer-to-peer networking feature of the program, with many reporting increases in perceived social connectedness and empowerment in their recovery process (Alvarez-Jimenez et al. 2013 ). This moderated online social therapy program is now being evaluated as part of a large randomized controlled trial for maintaining treatment effects from first episode psychosis services (Alvarez-Jimenez et al. 2019 ).

Other early efforts have demonstrated that use of digital environments with the interactive peer-to-peer features of social media can enhance social functioning and wellbeing in young people at high risk of psychosis (Alvarez-Jimenez et al. 2018 ). There has also been a recent emergence of several mobile apps to support symptom monitoring and relapse prevention in psychotic disorders. Among these apps, the development of PRIME (Personalized Real-time Intervention for Motivational Enhancement) has involved working closely with young people with schizophrenia to ensure that the design of the app has the look and feel of mainstream social media platforms, as opposed to existing clinical tools (Schlosser et al. 2016 ). This unique approach to the design of the app is aimed at promoting engagement and ensuring that the app can effectively improve motivation and functioning through goal setting and promoting better quality of life of users with schizophrenia (Schlosser et al. 2018 ).

Social media platforms could also be used to promote engagement and participation in in-person services delivered through community mental health settings. For example, the peer-based lifestyle intervention called PeerFIT targets weight loss and improved fitness among individuals living with serious mental illness through a combination of in-person lifestyle classes, exercise groups, and use of digital technologies (Aschbrenner et al. 2016b , c ). The intervention holds tremendous promise as lack of support is one of the largest barriers towards exercise in patients with serious mental illness (Firth et al. 2016 ), and it is now possible to use social media to counter such. Specifically, in PeerFIT, a private Facebook group is closely integrated into the program to offer a closed platform where participants can connect with the lifestyle coaches, access intervention content, and support or encourage each other as they work towards their lifestyle goals (Aschbrenner et al. 2016a ; Naslund et al. 2016a ). To date, this program has demonstrated preliminary effectiveness for meaningfully reducing cardiovascular risk factors that contribute to early mortality in this patient group (Aschbrenner, Naslund, Shevenell, Kinney, et al., 2016), while the Facebook component appears to have increased engagement in the program, while allowing participants who were unable to attend in-person sessions due to other health concerns or competing demands to remain connected with the program (Naslund et al. 2018 ). This lifestyle intervention is currently being evaluated in a randomized controlled trial enrolling young adults with serious mental illness from real world community mental health services settings (Aschbrenner et al. 2018a ).

These examples highlight the promise of incorporating the features of popular social media into existing programs, which may offer opportunities to safely promote engagement and program retention, while achieving improved clinical outcomes. This is an emerging area of research, as evidenced by several important effectiveness trials underway (Alvarez-Jimenez et al. 2019 ; Aschbrenner et al. 2018a ), including efforts to leverage online social networking to support family caregivers of individuals receiving first episode psychosis services (Gleeson et al. 2017 ).

Challenges with Social Media for Mental Health

The science on the role of social media for engaging persons with mental disorders needs a cautionary note on the effects of social media usage on mental health and wellbeing, particularly in adolescents and young adults. While the risks and harms of social media are frequently covered in the popular press and mainstream news reports, careful consideration of the research in this area is necessary. In a review of 43 studies in young people, many benefits of social media were cited, including increased self-esteem and opportunities for self-disclosure (Best et al. 2014 ). Yet, reported negative effects were an increased exposure to harm, social isolation, depressive symptoms, and bullying (Best et al. 2014 ). In the sections that follow (see Table 1 for a summary), we consider three major categories of risk related to use of social media and mental health. These include: (1) Impact on symptoms; (2) Facing hostile interactions; and (3) Consequences for daily life.

Impact on Symptoms

Studies consistently highlight that use of social media, especially heavy use and prolonged time spent on social media platforms, appears to contribute to increased risk for a variety of mental health symptoms and poor wellbeing, especially among young people (Andreassen et al. 2016 ; Kross et al. 2013 ; Woods and Scott 2016 ). This may partly be driven by the detrimental effects of screen time on mental health, including increased severity of anxiety and depressive symptoms, which have been well documented (Stiglic and Viner 2019 ). Recent studies have reported negative effects of social media use on mental health of young people, including social comparison pressure with others and greater feeling of social isolation after being rejected by others on social media (Rideout and Fox 2018 ). In a study of young adults, it was found that negative comparisons with others on Facebook contributed to risk of rumination and subsequent increases in depression symptoms (Feinstein et al. 2013 ). Still, the cross-sectional nature of many screen time and mental health studies makes it challenging to reach causal inferences (Orben and Przybylski 2019 ).

Quantity of social media use is also an important factor, as highlighted in a survey of young adults ages 19 to 32, where more frequent visits to social media platforms each week were correlated with greater depressive symptoms (Lin et al. 2016 ). More time spent using social media is also associated with greater symptoms of anxiety (Vannucci et al. 2017 ). The actual number of platforms accessed also appears to contribute to risk as reflected in another national survey of young adults where use of a large number of social media platforms was associated with negative impact on mental health (Primack et al. 2017 ). Among survey respondents using between 7 and 11 different social media platforms compared with respondents using only 2 or fewer platforms, there were 3 times greater odds of having high levels of depressive symptoms and a 3.2 times greater odds of having high levels of anxiety symptoms (Primack et al. 2017 ).

Many researchers have postulated that worsening mental health attributed to social media use may be because social media replaces face-to-face interactions for young people (Twenge and Campbell 2018 ) and may contribute to greater loneliness (Bucci et al. 2019 ) and negative effects on other aspects of health and wellbeing (Woods and Scott 2016 ). One nationally representative survey of US adolescents found that among respondents who reported more time accessing media such as social media platforms or smartphone devices, there were significantly greater depressive symptoms and increased risk of suicide when compared with adolescents who reported spending more time on non-screen activities, such as in-person social interaction or sports and recreation activities (Twenge et al. 2018 ). For individuals living with more severe mental illnesses, the effects of social media on psychiatric symptoms have received less attention. One study found that participation in chat rooms may contribute to worsening symptoms in young people with psychotic disorders (Mittal et al. 2007 ), while another study of patients with psychosis found that social media use appeared to predict low mood (Berry et al. 2018 ). These studies highlight a clear relationship between social media use and mental health that may not be present in general population studies (Orben and Przybylski 2019 ) and emphasize the need to explore how social media may contribute to symptom severity and whether protective factors may be identified to mitigate these risks.

Facing Hostile Interactions

Popular social media platforms can create potential situations where individuals may be victimized by negative comments or posts. Cyberbullying represents a form of online aggression directed towards specific individuals, such as peers or acquaintances, which is perceived to be most harmful when compared with random hostile comments posted online (Hamm et al. 2015 ). Importantly, cyberbullying on social media consistently shows harmful impact on mental health in the form of increased depressive symptoms as well as worsening of anxiety symptoms, as evidenced in a review of 36 studies among children and young people (Hamm et al. 2015 ). Furthermore, cyberbullying disproportionately impacts females as reflected in a national survey of adolescents in the USA, where females were twice as likely to be victims of cyberbullying compared with males (Alhajji et al. 2019 ). Most studies report cross-sectional associations between cyberbullying and symptoms of depression or anxiety (Hamm et al. 2015 ), though one longitudinal study in Switzerland found that cyberbullying contributed to significantly greater depression over time (Machmutow et al. 2012 ).

For youth ages 10 to 17 who reported major depressive symptomatology, there were over 3 times greater odds of facing online harassment in the last year compared with youth who reported mild or no depressive symptoms (Ybarra 2004 ). Similarly, in a 2018 national survey of young people, respondents ages 14 to 22 with moderate to severe depressive symptoms were more likely to have had negative experiences when using social media and, in particular, were more likely to report having faced hostile comments or being “trolled” from others when compared with respondents without depressive symptoms (31% vs. 14%) (Rideout and Fox 2018 ). As these studies depict risks for victimization on social media and the correlation with poor mental health, it is possible that individuals living with mental illness may also experience greater hostility online compared to individuals without mental illness. This would be consistent with research showing greater risk of hostility, including increased violence and discrimination, directed towards individuals living with mental illness in in-person contexts, especially targeted at those with severe mental illnesses (Goodman et al. 1999 ).

A computational study of mental health awareness campaigns on Twitter reported that while stigmatizing content was rare, it was actually the most spread (re-tweeted) demonstrating that harmful content can travel quickly on social media (Saha et al. 2019 ). Another study was able to map the spread of social media posts about the Blue Whale Challenge, an alleged game promoting suicide, over Twitter, YouTube, Reddit, Tumblr, and other forums across 127 countries (Sumner et al. 2019 ). These findings show that it is critical to monitor the actual content of social media posts, such as determining whether content is hostile or promotes harm to self or others. This is pertinent because existing research looking at duration of exposure cannot account for the impact of specific types of content on mental health and is insufficient to fully understand the effects of using these platforms on mental health.

Consequences for Daily Life

The ways in which individuals use social media can also impact their offline relationships and everyday activities. To date, reports have described risks of social media use pertaining to privacy, confidentiality, and unintended consequences of disclosing personal health information online (Torous and Keshavan 2016 ). Additionally, concerns have been raised about poor quality or misleading health information shared on social media and that social media users may not be aware of misleading information or conflicts of interest especially when the platforms promote popular content regardless of whether it is from a trustworthy source (Moorhead et al. 2013 ; Ventola 2014 ). For persons living with mental illness, there may be additional risks from using social media. A recent study that specifically explored the perspectives of social media users with serious mental illnesses, including participants with schizophrenia spectrum disorders, bipolar disorder, or major depression, found that over one third of participants expressed concerns about privacy when using social media (Naslund and Aschbrenner 2019 ). The reported risks of social media use were directly related to many aspects of everyday life, including concerns about threats to employment, fear of stigma and being judged, impact on personal relationships, and facing hostility or being hurt (Naslund and Aschbrenner 2019 ). While few studies have specifically explored the dangers of social media use from the perspectives of individuals living with mental illness, it is important to recognize that use of these platforms may contribute to risks that extend beyond worsening symptoms and that can affect different aspects of daily life.

In this commentary, we considered ways in which social media may yield benefits for individuals living with mental illness, while contrasting these with the possible harms. Studies reporting on the threats of social media for individuals with mental illness are mostly cross-sectional, making it difficult to draw conclusions about direction of causation. However, the risks are potentially serious. These risks should be carefully considered in discussions pertaining to use of social media and the broader use of digital mental health technologies, as avenues for mental health promotion or for supporting access to evidence-based programs or mental health services. At this point, it would be premature to view the benefits of social media as outweighing the possible harms, when it is clear from the studies summarized here that social media use can have negative effects on mental health symptoms, can potentially expose individuals to hurtful content and hostile interactions, and can result in serious consequences for daily life, including threats to employment and personal relationships. Despite these risks, it is also necessary to recognize that individuals with mental illness will continue to use social media given the ease of accessing these platforms and the immense popularity of online social networking. With this in mind, it may be ideal to raise awareness about these possible risks so that individuals can implement necessary safeguards, while highlighting that there could also be benefits. Being aware of the risks is an essential first step, before then recognizing that use of these popular platforms could contribute to some benefits like finding meaningful interactions with others, engaging with peer support networks, and accessing information and services.

To capitalize on the widespread use of social media and to achieve the promise that these platforms may hold for supporting the delivery of targeted mental health interventions, there is need for continued research to better understand how individuals living with mental illness use social media. Such efforts could inform safety measures and also encourage use of social media in ways that maximize potential benefits while minimizing risk of harm. It will be important to recognize how gender and race contribute to differences in use of social media for seeking mental health information or accessing interventions, as well as differences in how social media might impact mental wellbeing. For example, a national survey of 14- to 22-year olds in the USA found that female respondents were more likely to search online for information about depression or anxiety and to try to connect with other people online who share similar mental health concerns when compared with male respondents (Rideout and Fox 2018 ). In the same survey, there did not appear to be any differences between racial or ethnic groups in social media use for seeking mental health information (Rideout and Fox 2018 ). Social media use also appears to have a differential impact on mental health and emotional wellbeing between females and males (Booker et al. 2018 ), highlighting the need to explore unique experiences between gender groups to inform tailored programs and services. Research shows that lesbian, gay, bisexual, or transgender individuals frequently use social media for searching for health information and may be more likely compared with heterosexual individuals to share their own personal health experiences with others online (Rideout and Fox 2018 ). Less is known about use of social media for seeking support for mental health concerns among gender minorities, though this is an important area for further investigation as these individuals are more likely to experience mental health problems and online victimization when compared with heterosexual individuals (Mereish et al. 2019 ).

Similarly, efforts are needed to explore the relationship between social media use and mental health among ethnic and racial minorities. A recent study found that exposure to traumatic online content on social media showing violence or hateful posts directed at racial minorities contributed to increases in psychological distress, PTSD symptoms, and depression among African American and Latinx adolescents in the USA (Tynes et al. 2019 ). These concerns are contrasted by growing interest in the potential for new technologies including social media to expand the reach of services to underrepresented minority groups (Schueller et al. 2019 ). Therefore, greater attention is needed to understanding the perspectives of ethnic and racial minorities to inform effective and safe use of social media for mental health promotion efforts.

Research has found that individuals living with mental illness have expressed interest in accessing mental health services through social media platforms. A survey of social media users with mental illness found that most respondents were interested in accessing programs for mental health on social media targeting symptom management, health promotion, and support for communicating with health care providers and interacting with the health system (Naslund et al. 2017 ). Importantly, individuals with serious mental illness have also emphasized that any mental health intervention on social media would need to be moderated by someone with adequate training and credentials, would need to have ground rules and ways to promote safety and minimize risks, and importantly, would need to be free and easy to access.

An important strength with this commentary is that it combines a range of studies broadly covering the topic of social media and mental health. We have provided a summary of recent evidence in a rapidly advancing field with the goal of presenting unique ways that social media could offer benefits for individuals with mental illness, while also acknowledging the potentially serious risks and the need for further investigation. There are also several limitations with this commentary that warrant consideration. Importantly, as we aimed to address this broad objective, we did not conduct a systematic review of the literature. Therefore, the studies reported here are not exhaustive, and there may be additional relevant studies that were not included. Additionally, we only summarized published studies, and as a result, any reports from the private sector or websites from different organizations using social media or other apps containing social media–like features would have been omitted. Although, it is difficult to rigorously summarize work from the private sector, sometimes referred to as “gray literature,” because many of these projects are unpublished and are likely selective in their reporting of findings given the target audience may be shareholders or consumers.

Another notable limitation is that we did not assess risk of bias in the studies summarized in this commentary. We found many studies that highlighted risks associated with social media use for individuals living with mental illness; however, few studies of programs or interventions reported negative findings, suggesting the possibility that negative findings may go unpublished. This concern highlights the need for a future more rigorous review of the literature with careful consideration of bias and an accompanying quality assessment. Most of the studies that we described were from the USA, as well as from other higher income settings such as Australia or the UK. Despite the global reach of social media platforms, there is a dearth of research on the impact of these platforms on the mental health of individuals in diverse settings, as well as the ways in which social media could support mental health services in lower income countries where there is virtually no access to mental health providers. Future research is necessary to explore the opportunities and risks for social media to support mental health promotion in low-income and middle-income countries, especially as these countries face a disproportionate share of the global burden of mental disorders, yet account for the majority of social media users worldwide (Naslund et al. 2019 ).

Future Directions for Social Media and Mental Health

As we consider future research directions, the near ubiquitous social media use also yields new opportunities to study the onset and manifestation of mental health symptoms and illness severity earlier than traditional clinical assessments. There is an emerging field of research referred to as “digital phenotyping” aimed at capturing how individuals interact with their digital devices, including social media platforms, in order to study patterns of illness and identify optimal time points for intervention (Jain et al. 2015 ; Onnela and Rauch 2016 ). Given that most people access social media via mobile devices, digital phenotyping and social media are closely related (Torous et al. 2019 ). To date, the emergence of machine learning, a powerful computational method involving statistical and mathematical algorithms (Shatte et al. 2019 ), has made it possible to study large quantities of data captured from popular social media platforms such as Twitter or Instagram to illuminate various features of mental health (Manikonda and De Choudhury 2017 ; Reece et al. 2017 ). Specifically, conversations on Twitter have been analyzed to characterize the onset of depression (De Choudhury et al. 2013 ) as well as detecting users’ mood and affective states (De Choudhury et al. 2012 ), while photos posted to Instagram can yield insights for predicting depression (Reece and Danforth 2017 ). The intersection of social media and digital phenotyping will likely add new levels of context to social media use in the near future.

Several studies have also demonstrated that when compared with a control group, Twitter users with a self-disclosed diagnosis of schizophrenia show unique online communication patterns (Birnbaum et al. 2017a ), including more frequent discussion of tobacco use (Hswen et al. 2017 ), symptoms of depression and anxiety (Hswen et al. 2018b ), and suicide (Hswen et al. 2018a ). Another study found that online disclosures about mental illness appeared beneficial as reflected by fewer posts about symptoms following self-disclosure (Ernala et al. 2017 ). Each of these examples offers early insights into the potential to leverage widely available online data for better understanding the onset and course of mental illness. It is possible that social media data could be used to supplement additional digital data, such as continuous monitoring using smartphone apps or smart watches, to generate a more comprehensive “digital phenotype” to predict relapse and identify high-risk health behaviors among individuals living with mental illness (Torous et al. 2019 ).

With research increasingly showing the valuable insights that social media data can yield about mental health states, greater attention to the ethical concerns with using individual data in this way is necessary (Chancellor et al. 2019 ). For instance, data is typically captured from social media platforms without the consent or awareness of users (Bidargaddi et al. 2017 ), which is especially crucial when the data relates to a socially stigmatizing health condition such as mental illness (Guntuku et al. 2017 ). Precautions are needed to ensure that data is not made identifiable in ways that were not originally intended by the user who posted the content as this could place an individual at risk of harm or divulge sensitive health information (Webb et al. 2017 ; Williams et al. 2017 ). Promising approaches for minimizing these risks include supporting the participation of individuals with expertise in privacy, clinicians, and the target individuals with mental illness throughout the collection of data, development of predictive algorithms, and interpretation of findings (Chancellor et al. 2019 ).

In recognizing that many individuals living with mental illness use social media to search for information about their mental health, it is possible that they may also want to ask their clinicians about what they find online to check if the information is reliable and trustworthy. Alternatively, many individuals may feel embarrassed or reluctant to talk to their clinicians about using social media to find mental health information out of concerns of being judged or dismissed. Therefore, mental health clinicians may be ideally positioned to talk with their patients about using social media and offer recommendations to promote safe use of these sites while also respecting their patients’ autonomy and personal motivations for using these popular platforms. Given the gap in clinical knowledge about the impact of social media on mental health, clinicians should be aware of the many potential risks so that they can inform their patients while remaining open to the possibility that their patients may also experience benefits through use of these platforms. As awareness of these risks grows, it may be possible that new protections will be put in place by industry or through new policies that will make the social media environment safer. It is hard to estimate a number needed to treat or harm today given the nascent state of research, which means the patient and clinician need to weigh the choice on a personal level. Thus, offering education and information is an important first step in that process. As patients increasingly show interest in accessing mental health information or services through social media, it will be necessary for health systems to recognize social media as a potential avenue for reaching or offering support to patients. This aligns with growing emphasis on the need for greater integration of digital psychiatry, including apps, smartphones, or wearable devices, into patient care and clinical services through institution-wide initiatives and training clinical providers (Hilty et al. 2019 ). Within a learning healthcare environment where research and care are tightly intertwined and feedback between both is rapid, the integration of digital technologies into services may create new opportunities for advancing use of social media for mental health.

As highlighted in this commentary, social media has become an important part of the lives of many individuals living with mental disorders. Many of these individuals use social media to share their lived experiences with mental illness, to seek support from others, and to search for information about treatment recommendations, accessing mental health services and coping with symptoms (Bucci et al. 2019 ; Highton-Williamson et al. 2015 ; Naslund et al. 2016b ). As the field of digital mental health advances, the wide reach, ease of access, and popularity of social media platforms could be used to allow individuals in need of mental health services or facing challenges of mental illness to access evidence-based treatment and support. To achieve this end and to explore whether social media platforms can advance efforts to close the gap in available mental health services in the USA and globally, it will be essential for researchers to work closely with clinicians and with those affected by mental illness to ensure that possible benefits of using social media are carefully weighed against anticipated risks.

Abdel-Baki, A., Lal, S., Charron, D.-C., Stip, E., & Kara, N. (2017). Understanding access and use of technology among youth with first-episode psychosis to inform the development of technology-enabled therapeutic interventions. Early Intervention in Psychiatry, 11 (1), 72–76.

PubMed   Google Scholar  

Ahmed, Y. A., Ahmad, M. N., Ahmad, N., & Zakaria, N. H. (2019). Social media for knowledge-sharing: a systematic literature review. Telematics and Informatics, 37 , 72–112.

Google Scholar  

Alhajji, M., Bass, S., & Dai, T. (2019). Cyberbullying, mental health, and violence in adolescents and associations with sex and race: data from the 2015 youth risk behavior survey. Global Pediatric Health, 6 , 2333794X19868887.

PubMed   PubMed Central   Google Scholar  

Alvarez-Jimenez, M., Bendall, S., Lederman, R., Wadley, G., Chinnery, G., Vargas, S., Larkin, M., Killackey, E., McGorry, P., & Gleeson, J. F. (2013). On the HORYZON: moderated online social therapy for long-term recovery in first episode psychosis. Schizophrenia Research, 143 (1), 143–149.

Alvarez-Jimenez, M., Gleeson, J., Bendall, S., Penn, D., Yung, A., Ryan, R., et al. (2018). Enhancing social functioning in young people at ultra high risk (UHR) for psychosis: a pilot study of a novel strengths and mindfulness-based online social therapy. Schizophrenia Research, 202 , 369–377.

Alvarez-Jimenez, M., Bendall, S., Koval, P., Rice, S., Cagliarini, D., Valentine, L., et al. (2019). HORYZONS trial: protocol for a randomised controlled trial of a moderated online social therapy to maintain treatment effects from first-episode psychosis services. BMJ Open, 9 (2), e024104.

Andreassen, C. S., Billieux, J., Griffiths, M. D., Kuss, D. J., Demetrovics, Z., Mazzoni, E., & Pallesen, S. (2016). The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: a large-scale cross-sectional study. Psychology of Addictive Behaviors, 30 (2), 252.

Aschbrenner, K. A., Naslund, J. A., & Bartels, S. J. (2016a). A mixed methods study of peer-to-peer support in a group-based lifestyle intervention for adults with serious mental illness. Psychiatric Rehabilitation Journal, 39 (4), 328–334.

Aschbrenner, K. A., Naslund, J. A., Shevenell, M., Kinney, E., & Bartels, S. J. (2016b). A pilot study of a peer-group lifestyle intervention enhanced with mHealth technology and social media for adults with serious mental illness. The Journal of Nervous and Mental Disease, 204 (6), 483–486.

Aschbrenner, K. A., Naslund, J. A., Shevenell, M., Mueser, K. T., & Bartels, S. J. (2016c). Feasibility of behavioral weight loss treatment enhanced with peer support and mobile health technology for individuals with serious mental illness. Psychiatric Quarterly, 87 (3), 401–415.

Aschbrenner, K. A., Naslund, J. A., Gorin, A. A., Mueser, K. T., Scherer, E. A., Viron, M., et al. (2018a). Peer support and mobile health technology targeting obesity-related cardiovascular risk in young adults with serious mental illness: protocol for a randomized controlled trial. Contemporary Clinical Trials, 74 , 97–106.

Aschbrenner, K. A., Naslund, J. A., Grinley, T., Bienvenida, J. C. M., Bartels, S. J., & Brunette, M. (2018b). A survey of online and mobile technology use at peer support agencies. Psychiatric Quarterly , 1–10.

Aschbrenner, K. A., Naslund, J. A., Tomlinson, E. F., Kinney, A., Pratt, S. I., & Brunette, M. F. (2019). Adolescents’ use of digital technologies and preferences for mobile health coaching in mental health settings. Frontiers in Public Health. 7 , 178.

Badcock, J. C., Shah, S., Mackinnon, A., Stain, H. J., Galletly, C., Jablensky, A., & Morgan, V. A. (2015). Loneliness in psychotic disorders and its association with cognitive function and symptom profile. Schizophrenia Research, 169 (1–3), 268–273.

Batterham, P. J., & Calear, A. J. (2017). Preferences for internet-based mental health interventions in an adult online sample: findings from ann online community survey. JMIR Mental Health, 4 (2), e26.

Bauer, R., Bauer, M., Spiessl, H., & Kagerbauer, T. (2013). Cyber-support: an analysis of online self-help forums (online self-help forums in bipolar disorder). Nordic Journal of Psychiatry, 67 (3), 185–190.

Berger, M., Wagner, T. H., & Baker, L. C. (2005). Internet use and stigmatized illness. Social Science & Medicine, 61 (8), 1821–1827.

Berry, N., Lobban, F., Belousov, M., Emsley, R., Nenadic, G., & Bucci, S. (2017). # WhyWeTweetMH: understanding why people use Twitter to discuss mental health problems. Journal of Medical Internet Research, 19 (4), e107.

Berry, N., Emsley, R., Lobban, F., & Bucci, S. (2018). Social media and its relationship with mood, self-esteem and paranoia in psychosis. Acta Psychiatrica Scandinavica, 138 , 558–570.

Best, P., Manktelow, R., & Taylor, B. (2014). Online communication, social media and adolescent wellbeing: a systematic narrative review. Children and Youth Services Review, 41 , 27–36.

Biagianti, B., Quraishi, S. H., & Schlosser, D. A. (2018). Potential benefits of incorporating peer-to-peer interactions into digital interventions for psychotic disorders: a systematic review. Psychiatric Services, 69 (4), 377–388.

Bidargaddi, N., Musiat, P., Makinen, V.-P., Ermes, M., Schrader, G., & Licinio, J. (2017). Digital footprints: facilitating large-scale environmental psychiatric research in naturalistic settings through data from everyday technologies. Molecular Psychiatry, 22 (2), 164.

Birnbaum, M. L., Ernala, S. K., Rizvi, A. F., De Choudhury, M., & Kane, J. M. (2017a). A collaborative approach to identifying social media markers of schizophrenia by employing machine learning and clinical appraisals. Journal of Medical Internet Research, 19 (8), e289.

Birnbaum, M. L., Rizvi, A. F., Correll, C. U., Kane, J. M., & Confino, J. (2017b). Role of social media and the Internet in pathways to care for adolescents and young adults with psychotic disorders and non-psychotic mood disorders. Early Intervention in Psychiatry, 11 (4), 290–295.

Booker, C. L., Kelly, Y. J., & Sacker, A. (2018). Gender differences in the associations between age trends of social media interaction and well-being among 10-15 year olds in the UK. BMC Public Health, 18 (1), 321.

Brunette, M., Achtyes, E., Pratt, S., Stilwell, K., Opperman, M., Guarino, S., & Kay-Lambkin, F. (2019). Use of smartphones, computers and social media among people with SMI: opportunity for intervention. Community Mental Health Journal , 1–6.

Brusilovskiy, E., Townley, G., Snethen, G., & Salzer, M. S. (2016). Social media use, community participation and psychological well-being among individuals with serious mental illnesses. Computers in Human Behavior, 65 , 232–240.

Bucci, S., Schwannauer, M., & Berry, N. (2019). The digital revolution and its impact on mental health care. Psychology and Psychotherapy: Theory, Research and Practice, 92 (2), 277–297.

Chancellor, S., Birnbaum, M. L., Caine, E. D., Silenzio, V. M., & De Choudhury, M. (2019). A taxonomy of ethical tensions in inferring mental health states from social media. In Proceedings of the Conference on Fairness, Accountability, and Transparency, 79–88.

Chang, H. J. (2009). Online supportive interactions: using a network approach to examine communication patterns within a psychosis social support group in Taiwan. Journal of the American Society for Information Science and Technology, 60 (7), 1504–1517.

Davidson, L., Chinman, M., Sells, D., & Rowe, M. (2006). Peer support among adults with serious mental illness: a report from the field. Schizophrenia Bulletin, 32 (3), 443–450.

De Choudhury, M., Gamon, M., & Counts, S. (2012). Happy, nervous or surprised? classification of human affective states in social media. Paper presented at the sixth international Association for Advancement of Artificial Intelligence (AAAI) Conference on Weblogs and Social Meedia, 435–438.

De Choudhury, M., Gamon, M., Counts, S., & Horvitz, E. (2013). Predicting depression via social media. Paper presented at the seventh international Association for Advancement of Artificial Intelligence (AAAI) Conference on Weblogs and Social Media, 128–137.

Docherty, N. M., Hawkins, K. A., Hoffman, R. E., Quinlan, D. M., Rakfeldt, J., & Sledge, W. H. (1996). Working memory, attention, and communication disturbances in schizophrenia. Journal of Abnormal Psychology, 105 (2), 212–219.

Ernala, S. K., Rizvi, A. F., Birnbaum, M. L., Kane, J. M., & De Choudhury, M. (2017). Linguistic markers indicating therapeutic outcomes of social media disclosures of schizophrenia. Proceedings of the ACM on Human-Computer Interaction, 1 (1), 43.

Feinstein, B. A., Hershenberg, R., Bhatia, V., Latack, J. A., Meuwly, N., & Davila, J. (2013). Negative social comparison on Facebook and depressive symptoms: rumination as a mechanism. Psychology of Popular Media Culture, 2 (3), 161.

Firth, J., Cotter, J., Torous, J., Bucci, S., Firth, J. A., & Yung, A. R. (2015). Mobile phone ownership and endorsement of “mHealth” among people with psychosis: a meta-analysis of cross-sectional studies. Schizophrenia Bulletin, 42 (2), 448–455.

Firth, J., Rosenbaum, S., Stubbs, B., Gorczynski, P., Yung, A. R., & Vancampfort, D. (2016). Motivating factors and barriers towards exercise in severe mental illness: a systematic review and meta-analysis. Psychological Medicine, 46 (14), 2869–2881.

Gay, K., Torous, J., Joseph, A., Pandya, A., & Duckworth, K. (2016). Digital technology use among individuals with schizophrenia: results of an online survey. JMIR Mental Health, 3 (2), e15.

Giacco, D., Palumbo, C., Strappelli, N., Catapano, F., & Priebe, S. (2016). Social contacts and loneliness in people with psychotic and mood disorders. Comprehensive Psychiatry, 66 , 59–66.

Gleeson, J., Lederman, R., Herrman, H., Koval, P., Eleftheriadis, D., Bendall, S., Cotton, S. M., & Alvarez-Jimenez, M. (2017). Moderated online social therapy for carers of young people recovering from first-episode psychosis: study protocol for a randomised controlled trial. Trials, 18 (1), 27.

Glick, G., Druss, B., Pina, J., Lally, C., & Conde, M. (2016). Use of mobile technology in a community mental health setting. Journal of Telemedicine and Telecare, 22 (7), 430–435.

Goodman, L. A., Thompson, K. M., Weinfurt, K., Corl, S., Acker, P., Mueser, K. T., & Rosenberg, S. D. (1999). Reliability of reports of violent victimization and posttraumatic stress disorder among men and women with serious mental illness. Journal of Traumatic Stress: Official Publication of the International Society for Traumatic Stress Studies, 12 (4), 587–599.

Gowen, K., Deschaine, M., Gruttadara, D., & Markey, D. (2012). Young adults with mental health conditions and social networking websites: seeking tools to build community. Psychiatric Rehabilitation Journal, 35 (3), 245–250.

Guntuku, S. C., Yaden, D. B., Kern, M. L., Ungar, L. H., & Eichstaedt, J. C. (2017). Detecting depression and mental illness on social media: an integrative review. Current Opinion in Behavioral Sciences, 18 , 43–49.

Haker, H., Lauber, C., & Rössler, W. (2005). Internet forums: a self-help approach for individuals with schizophrenia? Acta Psychiatrica Scandinavica, 112 (6), 474–477.

Hamm, M. P., Newton, A. S., Chisholm, A., Shulhan, J., Milne, A., Sundar, P., Ennis, H., Scott, S. D., & Hartling, L. (2015). Prevalence and effect of cyberbullying on children and young people: a scoping review of social media studies. JAMA Pediatrics, 169 (8), 770–777.

Hansen, C. F., Torgalsbøen, A.-K., Melle, I., & Bell, M. D. (2009). Passive/apathetic social withdrawal and active social avoidance in schizophrenia: difference in underlying psychological processes. The Journal of Nervous and Mental Disease, 197 (4), 274–277.

Highton-Williamson, E., Priebe, S., & Giacco, D. (2015). Online social networking in people with psychosis: a systematic review. International Journal of Social Psychiatry, 61 (1), 92–101.

Hilty, D. M., Chan, S., Torous, J., Luo, J., & Boland, R. J. (2019). Mobile health, smartphone/device, and apps for psychiatry and medicine: competencies, training, and faculty development issues. Psychiatric Clinics, 42 (3), 513–534.

Hswen, Y., Naslund, J. A., Chandrashekar, P., Siegel, R., Brownstein, J. S., & Hawkins, J. B. (2017). Exploring online communication about cigarette smoking among Twitter users who self-identify as having schizophrenia. Psychiatry Research, 257 , 479–484.

Hswen, Y., Naslund, J. A., Brownstein, J. S., & Hawkins, J. B. (2018a). Monitoring online discussions about suicide among Twitter users with schizophrenia: exploratory study. JMIR Mental Health, 5 (4), e11483.

Hswen, Y., Naslund, J. A., Brownstein, J. S., & Hawkins, J. B. (2018b). Online communication about depression and anxiety among twitter users with schizophrenia: preliminary findings to inform a digital phenotype using social media. Psychiatric Quarterly, 89 (3), 569–580.

Indian, M., & Grieve, R. (2014). When Facebook is easier than face-to-face: social support derived from Facebook in socially anxious individuals. Personality and Individual Differences, 59 , 102–106.

Jain, S. H., Powers, B. W., Hawkins, J. B., & Brownstein, J. S. (2015). The digital phenotype. Nature Biotechnology, 33 (5), 462–463.

Kiesler, S., Siegel, J., & McGuire, T. W. (1984). Social psychological aspects of computer-mediated communication. American Psychologist, 39 , 1123–1134.

Kross, E., Verduyn, P., Demiralp, E., Park, J., Lee, D. S., Lin, N., Shablack, H., Jonides, J., & Ybarra, O. (2013). Facebook use predicts declines in subjective well-being in young adults. PLoS One, 8 (8), e69841.

Lal, S., Nguyen, V., & Theriault, J. (2018). Seeking mental health information and support online: experiences and perspectives of young people receiving treatment for first-episode psychosis. Early Intervention in Psychiatry, 12 (3), 324–330.

Lin, L. Y., Sidani, J. E., Shensa, A., Radovic, A., Miller, E., Colditz, J. B., Hoffman, B. L., Giles, L. M., & Primack, B. A. (2016). Association between social media use and depression among US young adults. Depression and Anxiety, 33 (4), 323–331.

Machmutow, K., Perren, S., Sticca, F., & Alsaker, F. D. (2012). Peer victimisation and depressive symptoms: can specific coping strategies buffer the negative impact of cybervictimisation? Emotional and Behavioural Difficulties, 17 (3–4), 403–420.

Manikonda, L., & De Choudhury, M. (2017). Modeling and understanding visual attributes of mental health disclosures in social media. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 170–181.

Mead, S., Hilton, D., & Curtis, L. (2001). Peer support: a theoretical perspective. Psychiatric Rehabilitation Journal, 25 (2), 134–141.

Mereish, E. H., Sheskier, M., Hawthorne, D. J., & Goldbach, J. T. (2019). Sexual orientation disparities in mental health and substance use among Black American young people in the USA: effects of cyber and bias-based victimisation. Culture, Health & Sexuality, 21 (9), 985–998.

Miller, B. J., Stewart, A., Schrimsher, J., Peeples, D., & Buckley, P. F. (2015). How connected are people with schizophrenia? Cell phone, computer, email, and social media use. Psychiatry Research, 225 (3), 458–463.

Mittal, V. A., Tessner, K. D., & Walker, E. F. (2007). Elevated social Internet use and schizotypal personality disorder in adolescents. Schizophrenia Research, 94 (1–3), 50–57.

Moorhead, S. A., Hazlett, D. E., Harrison, L., Carroll, J. K., Irwin, A., & Hoving, C. (2013). A new dimension of health care: systematic review of the uses, benefits, and limitations of social media for health communication. Journal of Medical Internet Research, 15 (4), e85.

Naslund, J. A., & Aschbrenner, K. A. (2019). Risks to privacy with use of social media: understanding the views of social media users with serious mental illness. Psychiatric Services, 70 (7), 561–568.

Naslund, J. A., Grande, S. W., Aschbrenner, K. A., & Elwyn, G. (2014). Naturally occurring peer support through social media: the experiences of individuals with severe mental illness using YouTube. PLoS One, 9 (10), e110171.

Naslund, J. A., Aschbrenner, K. A., & Bartels, S. J. (2016). How people living with serious mental illness use smartphones, mobile apps, and social media. Psychiatric Rehabilitation Journal, 39 (4), 364–367.

Naslund, J. A., Aschbrenner, K. A., Marsch, L. A., & Bartels, S. J. (2016a). Feasibility and acceptability of Facebook for health promotion among people with serious mental illness. Digital Health, 2 , 2055207616654822.

PubMed Central   Google Scholar  

Naslund, J. A., Aschbrenner, K. A., Marsch, L. A., & Bartels, S. J. (2016b). The future of mental health care: peer-to-peer support and social media. Epidemiology and Psychiatric Sciences, 25 (2), 113–122.

Naslund, J. A., Aschbrenner, K. A., McHugo, G. J., Unützer, J., Marsch, L. A., & Bartels, S. J. (2019). Exploring opportunities to support mental health care using social media: A survey of social media users with mental illness. Early Intervention in Psychiatry, 13 (3), 405–413.

Naslund, J. A., Aschbrenner, K. A., Marsch, L. A., McHugo, G. J., & Bartels, S. J. (2018). Facebook for supporting a lifestyle intervention for people with major depressive disorder, bipolar disorder, and schizophrenia: an exploratory study. Psychiatric Quarterly, 89 (1), 81–94.

Naslund, J. A., Gonsalves, P. P., Gruebner, O., Pendse, S. R., Smith, S. L., Sharma, A., & Raviola, G. (2019). Digital innovations for global mental health: opportunities for data science, task sharing, and early intervention. Current Treatment Options in Psychiatry , 1–15.

Onnela, J.-P., & Rauch, S. L. (2016). Harnessing smartphone-based digital phenotyping to enhance behavioral and mental health. Neuropsychopharmacology, 41 (7), 1691–1696.

Orben, A., & Przybylski, A. K. (2019). The association between adolescent well-being and digital technology use. Nature Human Behaviour, 3 (2), 173–182.

Patel, V., Saxena, S., Lund, C., Thornicroft, G., Baingana, F., Bolton, P., et al. (2018). The Lancet Commission on global mental health and sustainable development. The Lancet, 392 (10157), 1553–1598.

Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., & James, A. E. (2017). Use of multiple social media platforms and symptoms of depression and anxiety: a nationally-representative study among US young adults. Computers in Human Behavior, 69 , 1–9.

Reece, A. G., & Danforth, C. M. (2017). Instagram photos reveal predictive markers of depression. EPJ Data Science, 6 (1), 15.

Reece, A. G., Reagan, A. J., Lix, K. L., Dodds, P. S., Danforth, C. M., & Langer, E. J. (2017). Forecasting the onset and course of mental illness with Twitter data. Scientific Reports, 7 (1), 13006.

Rideout, V., & Fox, S. (2018). Digital health practices, social media use, and mental well-being among teens and young adults in the U.S. Retrieved from San Francisco, CA: https://www.hopelab.org/reports/pdf/a-national-survey-by-hopelab-and-well-being-trust-2018.pdf . Accessed 10 Jan 2020.

Saha, K., Torous, J., Ernala, S. K., Rizuto, C., Stafford, A., & De Choudhury, M. (2019). A computational study of mental health awareness campaigns on social media. Translational behavioral medicine, 9 (6), 1197–1207.

Schlosser, D. A., Campellone, T., Kim, D., Truong, B., Vergani, S., Ward, C., & Vinogradov, S. (2016). Feasibility of PRIME: a cognitive neuroscience-informed mobile app intervention to enhance motivated behavior and improve quality of life in recent onset schizophrenia. JMIR Research Protocols, 5 (2).

Schlosser, D. A., Campellone, T. R., Truong, B., Etter, K., Vergani, S., Komaiko, K., & Vinogradov, S. (2018). Efficacy of PRIME, a mobile app intervention designed to improve motivation in young people with schizophrenia. Schizophrenia Bulletin, 44 (5), 1010–1020.

Schrank, B., Sibitz, I., Unger, A., & Amering, M. (2010). How patients with schizophrenia use the internet: qualitative study. Journal of Medical Internet Research, 12 (5), e70.

Schueller, S. M., Hunter, J. F., Figueroa, C., & Aguilera, A. (2019). Use of digital mental health for marginalized and underserved populations. Current Treatment Options in Psychiatry, 6 (3), 243–255.

Shatte, A. B., Hutchinson, D. M., & Teague, S. J. (2019). Machine learning in mental health: a scoping review of methods and applications. Psychological Medicine, 49 (9), 1426–1448.

Spinzy, Y., Nitzan, U., Becker, G., Bloch, Y., & Fennig, S. (2012). Does the Internet offer social opportunities for individuals with schizophrenia? A cross-sectional pilot study. Psychiatry Research, 198 (2), 319–320.

Stiglic, N., & Viner, R. M. (2019). Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews. BMJ Open, 9 (1), e023191.

Sumner, S. A., Galik, S., Mathieu, J., Ward, M., Kiley, T., Bartholow, B., et al. (2019). Temporal and geographic patterns of social media posts about an emerging suicide game. Journal of Adolescent Health, 65 (1), 94–100.

Torous, J., & Keshavan, M. (2016). The role of social media in schizophrenia: evaluating risks, benefits, and potential. Current Opinion in Psychiatry, 29 (3), 190–195.

Torous, J., Chan, S. R., Tan, S. Y.-M., Behrens, J., Mathew, I., Conrad, E. J., et al. (2014a). Patient smartphone ownership and interest in mobile apps to monitor symptoms of mental health conditions: a survey in four geographically distinct psychiatric clinics. JMIR Mental Health, 1 (1), e5.

Torous, J., Friedman, R., & Keshavan, M. (2014b). Smartphone ownership and interest in mobile applications to monitor symptoms of mental health conditions. JMIR mHealth and uHealth, 2 (1), e2.

Torous, J., Wisniewski, H., Bird, B., Carpenter, E., David, G., Elejalde, E., et al. (2019). Creating a digital health smartphone app and digital phenotyping platform for mental health and diverse healthcare needs: an interdisciplinary and collaborative approach. Journal of Technology in Behavioral Science, 4 (2), 73–85.

Trefflich, F., Kalckreuth, S., Mergl, R., & Rummel-Kluge, C. (2015). Psychiatric patients' internet use corresponds to the internet use of the general public. Psychiatry Research, 226 , 136–141.

Twenge, J. M., & Campbell, W. K. (2018). Associations between screen time and lower psychological well-being among children and adolescents: evidence from a population-based study. Preventive Medicine Reports, 12 , 271–283.

Twenge, J. M., Joiner, T. E., Rogers, M. L., & Martin, G. N. (2018). Increases in depressive symptoms, suicide-related outcomes, and suicide rates among US adolescents after 2010 and links to increased new media screen time. Clinical Psychological Science, 6 (1), 3–17.

Tynes, B. M., Willis, H. A., Stewart, A. M., & Hamilton, M. W. (2019). Race-related traumatic events online and mental health among adolescents of color. Journal of Adolescent Health, 65 (3), 371–377.

Vannucci, A., Flannery, K. M., & Ohannessian, C. M. (2017). Social media use and anxiety in emerging adults. Journal of Affective Disorders, 207 , 163–166.

Vayreda, A., & Antaki, C. (2009). Social support and unsolicited advice in a bipolar disorder online forum. Qualitative Health Research, 19 (7), 931–942.

Ventola, C. L. (2014). Social media and health care professionals: benefits, risks, and best practices. Pharmacy and Therapeutics, 39 (7), 491–520.

We Are Social. (2020). Digital in 2020. Retrieved from https://wearesocial.com/global-digital-report-2019 . Accessed 10 Jan 2020.

Webb, H., Jirotka, M., Stahl, B. C., Housley, W., Edwards, A., Williams, M., ... & Burnap, P. (2017). The ethical challenges of publishing Twitter data for research dissemination . Paper presented at the proceedings of the 2017 ACM on Web Science Conference, 339–348.

Williams, M. L., Burnap, P., & Sloan, L. (2017). Towards an ethical framework for publishing twitter data in social research: taking into account users’ views, online context and algorithmic estimation. Sociology, 51 (6), 1149–1168.

Woods, H. C., & Scott, H. (2016). # Sleepyteens: social media use in adolescence is associated with poor sleep quality, anxiety, depression and low self-esteem. Journal of Adolescence, 51 , 41–49.

Ybarra, M. L. (2004). Linkages between depressive symptomatology and internet harassment among young regular Internet users. Cyberpsychology & Behavior, 7 (2), 247–257.

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Dr. Naslund is supported by a grant from the National Institute of Mental Health (U19MH113211). Dr. Aschbrenner is supported by a grant from the National Institute of Mental Health (1R01MH110965-01).

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Naslund, J.A., Bondre, A., Torous, J. et al. Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice. J. technol. behav. sci. 5 , 245–257 (2020). https://doi.org/10.1007/s41347-020-00134-x

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Coyne SM , Weinstein E , Sheppard JA, et al. Analysis of Social Media Use, Mental Health, and Gender Identity Among US Youths. JAMA Netw Open. 2023;6(7):e2324389. doi:10.1001/jamanetworkopen.2023.24389

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Analysis of Social Media Use, Mental Health, and Gender Identity Among US Youths

• 1 School of Family Life, Brigham Young University, Provo, Utah
• 2 Harvard Graduate School of Education, Cambridge, Massachusetts

Question   Is gender identity associated with social media use and mental health among youths?

Findings   This cross-sectional study of 1231 transgender, gender nonbinary, and cisgender youths found that gender identity moderated both the effect size and the direction of the association between social media use and mental health.

Meaning   These results suggest that gender identity is a key moderator when examining youth social media use and mental health and should be included in studies moving forward.

Importance   Mental health among children and adolescents is a critical public health issue, and transgender and gender nonbinary youths are at an even greater risk. Social media has been consistently associated with youth mental health, but little is known about how gender identity interacts with this association.

Objective   To use a risk and resilience approach to examine the association between social media use and mental health among transgender, gender nonbinary, and cisgender youths.

Design, Setting, and Participants   This cross-sectional study analyzed data collected from an online survey between May and August 2021. Participants included a random sample of US youths; eligibility requirements included being aged 10 to 17 years and residing in the US. Statistical analysis was performed from February to April 2022.

Main Outcomes and Measures   Social media use (time, type of use, favorite site, social comparisons, mindfulness, taking intentional breaks, cleaning and curating feeds, problematic use, and media literacy programs at their school) and mental health (depression, emotional problems, conduct problems, and body image) as main outcomes.

Results   Participants included 1231 youths aged 10 to 17 years from a national quota sample from the United States; 675 (54.8%) identified as cisgender female, 479 (38.9%) as cisgender male, and 77 (6.3%) as transgender, gender nonbinary, or other; 4 (0.3%) identified as American Indian or Alaska Native, 111 (9.0%) as Asian, 185 (15.0%) as Black, 186 (15.1%) as Hispanic or Latinx, 1 (0.1%) as Pacific Islander, 703 (57.1%) as White, and 41 (3.3%) as mixed and/or another race or ethnicity. Gender identity moderated both the strength and the direction of multiple associations between social media practices and mental health: active social media use (eg, emotional problems: B  = 1.82; 95% CI, 0.16 to 3.49; P  = .03), cleaning and/or curating social media feeds (eg, depression: B  = −0.91; 95% CI, −1.98 to −0.09; P  = .03), and taking intentional breaks (eg, depression: B  = 1.03; 95% CI, 0.14 to 1.92; P  = .02).

Conclusions and Relevance   In this cross-sectional study of gender identity, social media, and mental health, gender identity was associated with youths’ experiences of social media in ways that may have distinct implications for mental health. These results suggest that research about social media effects on youths should attend to gender identity; directing children and adolescents to spend less time on social media may backfire for those transgender and gender nonbinary youths who are intentional about creating safe spaces on social media that may not exist in their offline world.

The percentage of transgender and nonbinary (TGNB) youths coming out in the US has doubled in the last decade, 1 with 1.4% as transgender and 3.0% as nonbinary. 2 Despite studies documenting an association between gender, social media use (SMU), and indicators of mental health, 3 - 5 and that TGNB youths are at a higher risk for mental health issues than cisgender youths, 6 - 8 relatively little research has examined the association between SMU and mental health among TGNB youths. 9 Consequently, this study aimed to directly explore the interplay between gender identity, SMU, and indicators of mental health, including internalizing (emotional problems, depression, and body image), and externalizing problems (conduct problems).

Gender identity is an individual’s deeply felt sense of being a man, woman, or an alternate gender (eg, nonbinary), which sometimes may not align with the sex assigned at birth. 10 TGNB individuals may experience gender dysphoria, an intense distress because of the disconnect between one’s assigned sex and internal gender identity. 10 , 11 TGNB individuals may also experience high levels of minority stress, 12 , 13 the stress of being a minority in a majority social environment 14 - 16 fostered through social processes, institutions, and structures that harass and/or discriminate. 13 , 17 For TGNB youths, minority stress can manifest through violence due to gender nonconformity, 18 - 20 gender dysphoria, 21 family tension, and emotional distress from fear of rejection 21 , 22 and is associated with increased mental health struggles and greater risk for suicide. 17 , 23 - 25 Currently, 25% to 32% of TGNB youths attempt suicide. 18 , 26 Though there are public concerns about the effects of SMU on adolescent mental health, research on TGNB youths suggests social media may be a protective factor instead of a risk for mental health. 9

The research on SMU and mental health tends to be mixed. Some studies suggest time spent on social media is associated with mental health problems, 4 , 27 , 28 while others find no link. 29 - 31 Certain variables may moderate the association between SMU and mental health, including SMU context and content, problematic behaviors, 32 and gender (associations greater for girls than boys 33 ), suggesting gender identity as a potential moderator. 34 School media literacy may also help youths use social media in ways that might benefit their mental health; however, this is understudied with gender minority youths. 35

TGNB individuals engage with media in various ways for multiple reasons. 9 , 12 While general media represents TGNB individuals less frequently and accurately than cisgender individuals, 36 - 39 social media allows TGNB individuals to portray themselves how they see fit. TGNB youths access social media for a variety of content, building positive connections 38 and creating support systems protective against mental illness, based on common interests and experiences. 9 , 40 - 42 Little is known, however, about how TGNB youths use social media in general outside of gender identity exploration and development.

Acknowledging continued interest in the association between social media and mental health, elevated mental health risks relevant to TGNB youths, and the potential effects of social media in the lives of TGNB youths, our study aimed to examine the association between SMU and mental health as moderated by gender identity. Following minority stress theory, we hypothesized that positive social media practices may be more protective for TGNB youths (compared with cisgender youths) as it may reduce feelings of minority stress.

The survey was approved by the Brigham Young University institutional review board and participants were treated under the human participants’ guidelines from the American Psychological Association. Informed consent was obtained online. Parents gave consent for their minor children to participate. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline for cross-sectional studies by having multiple TGNB individuals as authors and addressing potential bias via qualitative focus groups with TGNB youths.

Participants included a national quota sample of 1231 youths aged 10 to 17 years obtained using a Qualtrics panel and collected between May and August 2021. The panel consisted of youths from all 50 states. We gave Qualtrics quotas for race and ethnicity based on recent US Census data, and they recruited based on those estimates. We chose this age group to examine because many youths begin using social media during this age. Additionally, there is substantial gender identity development during adolescence.

Race and ethnicity were self-reported; categories included American Indian or Alaska Native, Asian, Black, Hispanic or Latinx, Pacific Islander, White, and mixed or another race or ethnicity. Self-reported gender categories included cisgender female, cisgender male, and transgender, nonbinary, or other. Household income data were also collected.

The data were skewed for outcome measures. Descriptions of transformations and reliability statistics are included in Table 1 .

The patient health questionnaire (PHQ-8) measured participant depression. 43 Youths reported how frequently they experienced 8 symptoms within the last 2 weeks. A sample item of the PHQ-8 included “Feeling down, depressed, or hopeless.” Responses ranged from 1 (not at all) to 4 (nearly every day).

Five items measuring emotional problems were completed from the Strengths and Difficulties Questionnaire (SDQ). 44 Items were rated on a 3-point scale, 1 (not true) to 3 (certainly true), and a sample item included “I worry a lot.”

Five items measuring conduct problems from the SDQ were also completed. The same rating scale was used, and a sample item included, “I take things that are not mine.”

Youths reported how often they agreed with 3 statements about body image 45 using a 5-point Likert-scale: 1 (never) to 5 (always). A sample item included, “I’m pretty happy about the way I look.”

Participants were first asked if they had ever used social media. Seventy-two participants (5.8%) reported they had never used social media and were omitted from all future analyses. Participants who reported they used social media estimated the hours they spent on social media in a typical day. This was measured on a scale of 1 (none) to 8 (more than 8 hours). Though only moderate indicators of SMU, self-reports of screen time provide information about youths’ perceptions of their screen time and differentiates between light and heavy users. 46

For youths who had a smartphone, they were asked how old they were when they got their first smartphone. These answers ranged from age 5 to 17 years.

Youths were asked how often they participated in certain habits while on social media to determine if they were active or passive social media users. Three items measured active use (eg, “Make comments or like other people’s posts”), while 1 item measured passive use (“Mostly scroll through other people’s posts without commenting or posting myself”). Responses were measured on a 5-point Likert scale, 1 (never) to 5 (all the time).

Youths were asked to report the frequency of 3 social comparison behaviors when visiting their most used social media site 47 on a 5-point Likert-type scale, 1 (never) to 5 (always). A sample item included, “Compare my life with other people’s lives.”

Youths were asked how often they take intentional breaks from their smartphones (eg, by putting their smartphone on airplane mode or leaving it in another room). Responses were measured on a 6-point Likert scale, 1 (never or rarely) to 6 (every day or almost every day).

Youths were first asked if they used either social media or video games more frequently. Then, youths who reported that they used social media more responded how much they agreed with 7 items related to their social media habits (those who chose video games were excluded from this scale only). This scale was adapted 48 from a scale that originally assessed problematic cell phone use. 49 Participants were asked to rate how much they agreed with a series of statements regarding their SMU (eg, “When I am not using social media, I am thinking about using it or planning the next time I can use it”). Items were rated using a 5-point Likert scale, 1 (strongly disagree) to 5 (strongly agree).

Youths rated on a 5-point Likert scale how much they agreed with the statement, “My school tries to help us learn how to use our phones or social media in healthy ways.” Items were rated from 1 (strongly disagree) to 5 (strongly agree).

A modified Mindfulness Attention Awareness Scale 50 was used to measure mindfulness around SMU. Youths were asked to think about the last time they were on social media and how much certain behaviors were present (eg, “I was engaging with social media without really paying attention”). Items were rated on a 6-point Likert scale, 1 (not at all) to 6 (very much). This was recoded so a higher score indicated more mindful media use.

Participants were asked 2 items about how regularly they cleaned or curated their social media feed or followers (eg, by muting or unfollowing certain accounts). Items were rated on a 6-point Likert scale, 1 (never) to 6 (about once a week).

Member checking is often considered a hallmark of careful and culturally considerate research. 35 To aid with interpretation of the quantitative results, 7 adolescents were recruited as an advisory board via 2 focus groups centered on cointerpreting the findings. The advisory group was not designed for further data collection nor to change study results. Rather, the process emphasized cointerpretation with adolescents who have relevant lived experience, allowing insider perspectives to expand the interpretation and potential directions for future research.

The first group consisted of 4 cisgender adolescents aged 14 to 17 years and the second of 3 TGNB adolescents aged 14 to 16 years, all residing in the US. Both focus groups took place over a video call and were led by 1 cisgender and 2 TGNB adults while a team of 4 individuals assisted in note taking. After brief introductions, group facilitators presented the survey findings and asked the participants to provide their interpretations and asked follow-up questions for clarity.

Basic descriptive statistics were first conducted for all major variables based on gender identity. This was done using multivariate analysis of variance (MANOVA). We then conducted 4 logistic regressions, with outcomes being emotional problems, depression, conduct problems, and body image. Independent variables assessed included social media time and the aforementioned contextual social media factors. Covariates included race, age, income, and family structure. We also explored gender identity as a moderator in each model. Sex as a biological variable correlated highly with gender identity and was not included as a covariate. Statistical significance was determined at 2-sided P  < .05. Missing data were handled using the maximum likelihood method in Mplus (Muthén & Muthén). Statistical analysis was performed from February to April 2022 using Stata version 17 (StataCorp).

Participants included 1231 youths from a national quota sample from the United States; 675 (54.8%) identified as cisgender female, 479 (38.9%) as cisgender male, and 77 (6.3%) as transgender, gender nonbinary, or other; 4 (0.3%) identified as American Indian or Alaska Native, 111 (9.0%) as Asian, 185 (15.0%) as Black, 186 (15.1%) as Hispanic or Latinx, 1 (0.1%) as Pacific Islander, 703 (57.1%) as White, and 41 (3.3%) as mixed and/or another race or ethnicity; age ranged from 10 to 17 years with a mean (SD) of 14.5 (2.0) years. Average household income was between $60 000 and $75 000 per year (with 308 [25.0%] below $50 000 per year and 431 [35.0%] above $100 000 per year).

A series of MANOVAs explored gender identity differences in outcomes and SMU. There was a significant multivariate effect of gender identity differences for all outcomes measured in the study ( F 8, 2452  = 30.32; P  < .001; η 2  = 0.09). TGNB youths had the highest levels of depression, emotional problems, conduct problems, and the worst body image compared with other youths (eg, mean [SD] depression measures were 2.22 [0.87] for female, 2.07 [0.93] for male, and 2.80 [0.91] for TGNB; P  < .001). See Table 1 for full statistics and mean comparisons.

For media variables, cisgender male youths tended to have higher levels of active SMU, problematic SMU, and social comparisons than cisgender female youths or TGNB youths (eg, mean [SD] active SMU measures were 2.97 [0.95] for female, 3.45 [1.00] for male, and 2.98 [0.90] for TGNB; P  < .001); they also perceived having schools with stronger digital literacy programs. Additionally, TGNB youths reported higher levels of cleaning or curating their social media feed than other youths (mean [SD] level of cleaning and/or curating social media feeds were 3.29 [1.40] for female, 3.41 [1.50] for male, and 3.70 [1.39] for TGNB; P  < .001) ( Table 1 ).

In general, time spent on social media and age at receiving first smartphone were not associated with any outcomes. Attending a school with what students perceived as strong digital literacy training, active SMU, low levels of social comparisons, and low levels of problematic SMU (eg, depression: B  = 1.02; 95% CI, 0.66-1.38; P  < .001) were associated with lower risk of mental health problems ( Table 2 ). Four results were significantly moderated by gender identity; given the focus of the study, we focus on these 4 results.

First, there was a significant interaction between gender identity and active SMU for emotional problems ( B  = 1.82; 95% CI, 0.16 to 3.49; P  = .03). Specifically, active media use was more associated with lower emotional problems for TGNB youths than for cisgender youths ( Figure 1 ). Second, there was a significant moderation between gender identity and taking intentional breaks for depression ( B  = 1.03; 95% CI, 0.14 to 1.92; P  = .02) and emotional problems ( B  = 1.51; 95% CI, 0.37 to 2.65; P  = .009). Taking intentional social media breaks was positively associated with depression for TGNB, but negatively associated with cisgender participants ( Figure 2 ). Third, there was a significant moderation between gender identity and cleaning or curating feeds for depression ( B  = −0.91; 95% CI, −1.98 to −0.09; P  = .03) and conduct problems ( B  = −0.64; 95% CI, −1.18 to −0.11; P  = .02). Specifically, depression and conduct problems were lower for TGNB youths when they reported regularly cleaning or curating their social media feed, but both depression and conduct disorders were higher for cisgender youths when they engaged in this same activity ( Figure 3 ). Finally, we found a significant interaction between school media literacy and gender identity for depression ( B  = −1.07; 95% CI, −1.98 to −0.15; P  = .02) with school media literacy being more associated with lower rates of depression for TGNB youths vs cisgender youths.

There were significant gender identity differences for all health outcomes measured in the study. TGNB youths had the highest levels of depression, emotional problems, conduct problems, and negative body image compared with cisgender youths. However, TGNB youths’ use of social media was differentially associated with mental health.

Aligning with previous research on SMU, 51 , 52 this study found that active media use was associated with lower rates of mental health problems, especially for TGNB youths. As our advisory board suggested, TGNB youths may be more intentional about creating online spaces that are free from the negative interactions that can plague them in school 53 or at home. 9 One TGNB youth shared, “On social media, I am able to choose to be around the people that don’t make me uncomfortable, that don’t make me hate myself.” TGNB youths can actively be themselves (present themselves) in a way that aligns with their identity via pictures and pronouns.

Relatedly, cleaning and/or curating feeds was associated with lower levels of depression for TGNB youths but higher levels for cisgender youths. TGNB youths are more likely to be bullied or harassed online and offline and may therefore have a greater need to curate safe spaces for themselves on social media. Illustrating this point, one TGNB youth said, “Real life isn’t safe for LGBTQ people, but online there is more control where I can find people who have similar beliefs.” Conversely, cleaning and/or curating feeds appeared to have an opposite pattern for cisgender youths, a finding which merits further investigation: perhaps cisgender youths fear offending peers by unfollowing those in their social circle, and thus benefit from a social media break by uninstalling apps entirely rather than curating feeds.

Taking intentional technology breaks was significantly associated with increases in depression and emotional problems for TGNB youths but not for cisgender youths, again suggesting the balance of risks and benefits of youths’ SMU differs by gender identity. For TGNB youths for whom social media is a key venue for social acceptance, breaks could cut this off and potentially be detrimental to health. 9 As a TGNB advisory board adolescent explained, “I’m fine taking breaks because I already have a support group that is super nice to me. For others, when they delete it, [they delete] their safe place. That’s why they feel bad…they don’t have that community anymore.”

Attending a school with a perceived strong media literacy program was also associated with positive outcomes for all youths, 54 , 55 and again particularly so for TGNB youths. Given the apparent importance of online spaces for TGNB youths, these programs may contribute to protective practices and facilitate even greater intentionality around SMU. 38

Parents could be less concerned about screen time potentially causing mental health struggles in their TGNB youth and instead focus on how social media may be a resource for their children in the face of everyday minority stress. Policy makers and school officials worried about the link between social media and mental health should consider the differential associations of social media by gender identity and take a more person-centered approach. Blanket policies that severely limit SMU among youths may have different (and more negative) impacts for TGNB youths. We encourage policies (at school, state, and national levels) that focus on supporting school media literacy programs as opposed to only limiting screen time. Pediatricians might consider asking detailed questions around media use beyond screen time at well-child checkups. Clinical and medical professionals treating adolescents might consider discussing social media practices and may take a more nuanced approach depending on patient gender identity.

This study had limitations. Major limitations included the self-report and cross-sectional nature of the data, and there were a relatively low number of TGNB youths.

The association between social media and mental health is complex and nuanced. The present findings indicate that TGNB youths are at an elevated risk for negative health outcomes compared with cisgender youths. 56 , 57 These differences do not seem to reflect their time on social media. Rather, SMU appears to be associated with lower levels of mental health problems for TGNB youths, 9 reaffirming that person-specific differences are key when examining social media and health and pointing to the importance of deliberate attention to gender identity. 58 Although TGNB youths are among the highest risk for mental health struggles and suicidality, social media might be protective for some TGNB youths, particularly when used in protective ways.

Accepted for Publication: May 31, 2023.

Published: July 24, 2023. doi:10.1001/jamanetworkopen.2023.24389

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2023 Coyne SM et al. JAMA Network Open .

Corresponding Author: Sarah M. Coyne, PhD, School of Family Life, Brigham Young University, JFSB 2086C, Provo, UT 84602 ( [email protected] ).

Author Contributions: Drs Coyne and James had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Coyne, Weinstein, James, Ririe, Monson.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Coyne, Sheppard, Van Alfen, Ririe, Monson, Ashby, Weston, Banks.

Critical revision of the manuscript for important intellectual content: Coyne, Weinstein, Sheppard, James, Gale, Van Alfen, Ashby.

Statistical analysis: Coyne, James.

Obtained funding: Coyne.

Administrative, technical, or material support: Coyne, Sheppard, James.

Supervision: Coyne, Van Alfen, Ririe.

Conflict of Interest Disclosures: Dr Coyne reported being retained as an expert witness by Meta for future court proceedings (based on her existing research). Dr Weinstein reported that she has previously received payment for invited presentation(s) to TikTok, as well as for consulting work with Common Sense Media. No other disclosures were reported.

Funding/Support: This project was funded by the Wheatley Institute at Brigham Young University.

Role of the Funder/Sponsor: The Wheatley Institute helped with the design and conduct of the study and paid for data collection. Dr Weinstein was paid a stipend from the Wheatley Institute for her involvement in the study. Dr James and Dr Coyne are both fellows of the Wheatley Institute and were paid for data management, analysis, interpretation of the data, preparation, review, and approval of the manuscript; and decision to submit the manuscript for publication. Ms Van Alfen was a student fellow of the Wheatley Institute and received a scholarship for her involvement in the study.

Disclaimer: All information and materials in this manuscript are original. Portions of this manuscript were published as a public scholarship report on the Wheatley Institute website. However, this report focused on social media in general and not on TGNB youths.

Meeting Presentation: A version of this paper was presented at the Society for Research on Adolescence (SRA) Conference; April 13, 2023; San Diego, California.

Data Sharing Statement: See the Supplement .

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Exploring what works, what doesn’t, and why.

How to calm The Anxious Generation

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When it comes to our young people and their mental health, the news is not good. Suicide is the second-leading cause of death for people under 24 in the U.S., and a Centers for Disease Control and Prevention report last year found 20 percent of the country’s 12- to 17-year-olds had had at least one major depressive episode —results unlike anything the CDC had seen in thirty years of collecting such data. Its director of adolescent and school health, Kathlee Ethie, called the findings “devastating.” She said, “Young people are telling us they are in crisis . The data really call on us to act.”

There are plenty of recommendations for action in Jonathan Haidt’s new book, The Anxious Generation: How the Great Rewiring of Childhood is Causing an Epidemic of Mental Illness . Haidt, a psychologist at New York University, starts by giving a readers a baseline on kids, why girls have higher rates of mood disorders and self-harming behavior, and why today’s boys are more at risk of “failure to launch” (that is, transition from adolescence to adulthood). And—perhaps not surprising, from the author of The Coddling of the American Mind —he argues that parents are overprotecting their kids in the real, physical world and underprotecting them in the Wild West online.

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Haidt makes a strong case that social media—as distinct from the internet at large—is severely harming young people. Rates of mood disorders among U.S. college undergraduates suddenly spiked in the early 2010s. The number of kids reporting depression and anxiety rose steadily every year of that decade, till rates were up 134 percent and 106 percent, respectively, by 2020. Similar statistics are being seen in countries around the world. It’s probably no accident that Apple introduced its first front-facing camera phone in summer of 2010, and Instagram, which worked only on smartphones at the time, launched later that year. After Facebook purchased Instagram, its user base exploded, from 10 million users at the end of 2011 to 90 million by early 2013. The result, Haidt says: “Gen Z became the first generation in history to go through puberty with a portal in their pockets that called them away from the people nearby and into an alternative universe that was exciting, addictive, unstable, and … unsuitable for children and adolescents.”

Few of us have healthy relationships with our phones, but kids are especially vulnerable. Their brains are still developing; they’re still learning impulse control and values. Haidt cites a range of studies that help to make his case. Half of all teens reported feeling “addicted” to their phones in a survey published in 2016, for instance, while three out of five parents felt their kids were addicted. A more recent Pew Research Center study found nearly 100 percent of American teens have a smartphone, and roughly half say they’re online “constantly.”

It’s that level of attachment that leads Haidt to say a computerized device doesn’t simply correlate with the youth mental health crisis; it drives it. In 2022, he testified before Congress that one to two hours a day of social media use isn’t associated with a decline in mental health—but three or four hours a day is. In his book, he also cites studies establishing a causal relationship between Facebook adoption and depression and anxiety—particularly for girls. (To help understand why that might be, consider that internal research for Instagram led to a report saying, “We make body image issues worse for one in three teen girls.”)

Haidt also rebuts the idea that social media helps kids who feel out of place or marginalized by connecting them to peer groups and social support. “Unlike the extensive evidence of harm found in correlational, longitudinal, and experimental studies, there is very little evidence showing benefits to adolescent mental health from long-term or heavy social media use,” he writes.

Parental “safetyism”—i.e., keeping children away from anything the least bit risky, especially unsupervised outdoor play, is also part of the problem, both for younger children and adolescents. “A healthy human childhood with a lot of autonomy,” he writes, “sets children’s brains to operate mostly in ‘discover mode,’ with a well-developed attachment system and an ability to handle the risks of daily life.”

As for what we can do, Haidt makes plenty of cogent suggestions. My favorite was probably to make schools phone-free. Haidt holds up Mountain Middle School, located in an area of Colorado with some of the highest teen suicide rates in the state, as an example. A new principal at the charter school saw students suffering from cyberbullying, excessive social comparison, and phone-related sleep deprivation; he banned phones at school. The effects were nearly instantaneous—and dramatic. Kids talked to each other more. They lived in the moment, rather than on their phones. Soon enough they also reported being happier and less stressed . The school, still phone-free, was subsequently awarded Colorado’s highest academic performance rating.

Haidt calls on all of us to ask local and federal government to implement changes such as raising the age of legal “internet adulthood” from 13 to 16. He offers sensible, easy suggestions for parents, starting with telling your child, “ Do something new, on your own .” It can be something as simple as making a meal, climbing a tree, or taking the dog for a walk. You’ll see the results immediately, he says.

Haidt begins his book by saying we’d never pack our kids off to an unfamiliar planet where humans hadn’t lived before. And yet, he says our kids are basically living on another planet right here on Earth because they no longer grow up engaged in physical play, physically surrounded by other human beings and communities. He ends his book by saying, “Let’s bring our children home.” Let us indeed.

Book cover courtesy of Penguin Random House

More in Mental Health

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Living Better

The truth about teens, social media and the mental health crisis.

Michaeleen Doucleff

For years, the research picture on how social media affects teen mental health has been murky. That is changing as scientists find new tools to answer the question. Olivier Douliery /AFP via Getty Images hide caption

For years, the research picture on how social media affects teen mental health has been murky. That is changing as scientists find new tools to answer the question.

Back in 2017, psychologist Jean Twenge set off a firestorm in the field of psychology.

Twenge studies generational trends at San Diego State University. When she looked at mental health metrics for teenagers around 2012, what she saw shocked her. "In all my analyses of generational data — some reaching back to the 1930s — I had never seen anything like it," Twenge wrote in the Atlantic in 2017.

Twenge warned of a mental health crisis on the horizon. Rates of depression, anxiety and loneliness were rising. And she had a hypothesis for the cause: smartphones and all the social media that comes along with them. "Smartphones were used by the majority of Americans around 2012, and that's the same time loneliness increases. That's very suspicious," Twenge told NPR in 2017.

But many of her colleagues were skeptical. Some even accused her of inciting a panic with too little — and too weak — data to back her claims.

Now, six years later, Twenge is back. She has a new book out this week, called Generations , with much more data backing her hypothesis. At the same time, several high-quality studies have begun to answer critical questions, such as does social media cause teens to become depressed and is it a key contributor to a rise in depression?

In particular, studies from three different types of experiments, altogether, point in the same direction. "Indeed, I think the picture is getting more and more consistent," says economist Alexey Makarin , at the Massachusetts Institute of Technology.

Shots - Health News

How to help young people limit screen time — and feel better about how they look, a seismic change in how teens spend their time.

In Generations , Twenge analyzes mental health trends for five age groups, from the Silent Generation, who were born between 1925 and 1945, to Gen Z, who were born between 1995 and 2012. She shows definitively that "the way teens spend their time outside of school fundamentally changed in 2012," as Twenge writes in the book.

Take for instance, hanging out with friends, in person. Since 1976, the number of times per week teens go out with friends — and without their parents — held basically steady for nearly 30 years. In 2004, it slid a bit. Then in 2010, it nosedived.

"It was just like a Black Diamond ski slope straight down," Twenge tells NPR. "So these really big changes occur."

At the same time, around 2012, time on social media began to soar. In 2009, only about half of teens used social media every day, Twenge reports. In 2017, 85% used it daily. By 2022, 95% of teens said they use some social media, and about a third say they use it constantly, a poll from Pew Research Center found .

"Now, in the most recent data, 22% of 10th grade girls spend seven or more hours a day on social media," Twenge says, which means many teenage girls are doing little else than sleeping, going to school and engaging with social media.

Not surprisingly, all this screen time has cut into many kids' sleep time. Between 2010 and 2021, the percentage of 10th and 12th graders who slept seven or fewer hours each night rose from a third to nearly one-half. "That's a big jump," Twenge says. "Kids in that age group are supposed to sleep nine hours a night. So less than seven hours is a really serious problem."

Teen girls and LGBTQ+ youth plagued by violence and trauma, survey says

On its own, sleep deprivation can cause mental health issues. "Sleep is absolutely crucial for physical health and for mental health. Not getting enough sleep is a major risk factor for anxiety and depression and self-harm," she explains. Unfortunately, all of those mental health problems have continued to rise since Twenge first sounded the alarm six years ago.

"Nuclear bomb" on teen social life

"Every indicator of mental health and psychological well-being has become more negative among teens and young adults since 2012," Twenge writes in Generations . "The trends are stunning in their consistency, breadth and size."

Across the board, since 2010, anxiety, depression and loneliness have all increased . "And it's not just symptoms that rose, but also behaviors," she says, "including emergency room visits for self-harm, for suicide attempts and completed suicides." The data goes up through 2019, so it doesn't include changes due to COVID-19.

All these rapid changes coincide with what, Twenge says, may be the most rapid uptake in a new technology in human history: the incorporation of smartphones into our lives, which has allowed nearly nonstop engagement with social media apps. Apple introduced the first iPhones in 2007, and by 2012, about 50% of American adults owned a smartphone, the Pew Research Center found .

The timing is hard to ignore, says data scientist Chris Said , who has a Ph.D. in psychology from Princeton University and has worked at Facebook and Twitter. "Social media was like a nuclear bomb on teen social life," he says. "I don't think there's anything in recent memory, or even distant history, that has changed the way teens socialize as much as social media."

Murky picture becomes clearer on causes of teen depression

But the timing doesn't tell you whether social media actually causes depression in teens.

In the past decade, scientists have published a whole slew of studies trying to answer this question, and those studies sparked intense debate among scientists and in the media. But, Said says, what many people don't realize is scientists weren't using — or didn't even have — the proper tools to answer the question. "This is a very hard problem to study," he says. "The data they were analyzing couldn't really solve the problem."

Mental Health

The mental health of teen girls and lgbtq+ teens has worsened since 2011.

So the findings have been all over the place. They've been murky, noisy, inconclusive and confusing. "When you use tools that can't fully answer the question, you're going to get weak answers," he says. "So I think that's one reason why really strong evidence didn't show up in the data, at least early on."

On top of it, psychology has a bad track record in this field, Said points out. For nearly a century, psychologists have repeatedly blamed new technologies for mental and physical health problems of children, even when they've had little — or shady — data to back up their claims.

For example, in the 1940s, psychologists worried that children were becoming addicted to radio crime dramas, psychologist Amy Orben at the University of Cambridge explains in her doctoral thesis. After that, they raised concerns about comic books, television and — eventually — video games. Thus, many researchers worried that social media may simply be the newest scapegoat for children's mental health issues.

A handful of scientists, including MIT's Alexey Makarin, noticed this problem with the data, the tools and the field's past failures, and so they took the matter into their own hands. They went out and found better tools.

Hundreds of thousands of more college students depressed

Over the past few years, several high-quality studies have come that can directly test whether social media causes depression. Instead of being murky and mixed, they support each other and show clear effects of social media. "The body of literature seems to suggest that indeed, social media has negative effects on mental health, especially on young adults' mental health," says Makarin, who led what many scientists say is the best study on the topic to date.

In that study, Makarin and his team took advantage of a once-in-a-lifetime opportunity: the staggered introduction of Facebook across U.S. colleges from 2004 to 2006. Facebook rolled out into society first on college campuses, but not all campuses introduced Facebook at the same time.

For Makarin and his colleagues, this staggered rollout is experimental gold.

"It allowed us to compare students' mental health between colleges where Facebook just arrived to colleges where Facebook had not yet arrived," he says. They could also measure how students' mental health shifted on a particular campus when people started to spend a bunch of their time on social media.

Luckily, his team could track mental health at the time because college administrators were also conducting a national survey that asked students an array of questions about their mental health, including diagnoses, therapies and medications for depression, anxiety and eating disorders. "These are not just people's feelings," Makarin says. "These are actual conditions that people have to report."

They had data on a large number of students. "The data comes from more than 350,000 student responses across more than 300 colleges," Makarin says.

This type of study is called a quasi-experiment, and it allows scientists to estimate how much social media actually changes teens' mental health, or as Makarin says, "We can get causal estimates of the impact of Facebook on mental health."

So what happened? "Almost immediately after Facebook arrives on campus, we see an uptick in mental health issues that students report," Makarin says. "We especially find an impact on depression rates, anxiety disorders and other questions associated with depression in general."

And the effect isn't small, he says. Across the population, the rollout of Facebook caused about 2% of college students to become clinically depressed. That may sound modest, but with more than 17 million college students in the U.S. at the time, that means Facebook caused more than 300,000 young adults to suffer from depression.

For an individual, on average, engaging with Facebook decreases their mental health by roughly 22% of the effect of losing one's job, as reported by a previous meta-analysis, Makarin and his team found.

Facebook's rollout had a larger effect on women's mental health than on men's mental health, the study showed. But the difference was small, Makarin says.

He and his colleagues published their findings last November in the American Economic Review . "I love that paper," says economist Matthew Gentzkow at Stanford University, who was not involved in the research. "It's probably the most convincing study I've seen. I think it shows a clear effect, and it's really credible. They did a good job of isolating the effect of Facebook, which isn't easy."

Of course, the study has limitations, Gentzkow says. First off, it's Facebook, which teens are using less and less. And the version of Facebook is barebones. In 2006, the platform didn't have a "like" button" or a "newsfeed." This older version probably wasn't as "potent" as social media now, says data scientist Chris Said. Furthermore, students used the platform only on a computer because smartphones weren't available yet. And the study only examined mental health impacts over a six-month period.

Nevertheless, the findings in this study bolster other recent studies, including one that Gentzkow led.

Social media is "like the ocean" for kids

Back in 2018, Gentzkow and his team recruited about 2,700 Facebook users ages 18 or over. They paid about half of them to deactivate their Facebook accounts for four weeks. Then Gentzkow and his team looked to see how a Facebook break shifted their mental health. They reported their findings in March 2020 in the American Economic Review.

This type of study is called a randomized experiment, and it's thought of as the best way to estimate whether a variable in life causes a particular problem. But with social media, these randomized experiments have big limitations. For one, the experiments are short-term — here only four weeks. Also, people use social media in clusters, not as individuals. So having individuals quit Facebook won't capture the effect of having an entire social group quit together. Both of these limitations could underestimate the impact of social media on an individual and community.

Nevertheless, Gentzkow could see how deactivating Facebook made people, on average, feel better. "Being off Facebook was positive across well-being outcomes," he says. "You see higher happiness, life satisfaction, and also lower depression, lower anxiety, and maybe a little bit lower loneliness."

Gentzkow and his team measured participants' well-being by giving them a survey at the end of the experiment but also asking questions, via text message, through the experiment. "For example, we sent people text messages that say, 'Right now, would you say you're feeling happy or not happy,'" he explains.

Again, as with Makarin's experiment, the effect was moderate. Gentzkow and his colleagues estimate that temporarily quitting Facebook improves a person's mental health by about 30% of the positive effect seen by going to therapy. "You could view that meaning these effects are pretty big," he explains, "or you could also see that as meaning that the effects of therapy are somewhat small. And I think both of those things are true to an extent."

Scientists still don't know to what extent social media is behind the rising mental health issues among teenagers and whether it is the primary cause. "It seems to be the case — like it's a big factor," says MIT's Alexey Makarin, "but that's still up for debate."

Still, though, other specifics are beginning to crystallize. Scientists are narrowing in on what aspects of social media are most problematic. And they can see that social media won't hurt every teen — or hurt them by the same amount. The data suggests that the more hours a child devotes to social media, the higher their risk for mental health problems.

Finally, some adolescents are likely more vulnerable to social media, and children may be more vulnerable at particular ages. A study published in February 2022 looked to see how time spent on social media varies with life satisfaction during different times in a child's life (see the graphic).

The researchers also looked to see if a child's present use of social media predicted a decrease of life satisfaction one year later. That data suggests two windows of time when children are most sensitive to detrimental effects of social media, especially heavy use of it. For girls, one window occurs at ages 11 through 13. And for boys, one window occurs at ages 14 and 15. For both genders, there's a window of sensitivity around age 19 — or near the time teenagers enter college. Amy Orben and her team at the University of Cambridge reported the findings in Nature Communications .

This type of evidence is known as a correlative. "It's hard to draw conclusions from these studies," Gentzkow says, because many factors contribute to life satisfaction, such as environmental factors and family backgrounds. Plus, people may use social media because they're depressed (and so depression could be the cause, not the outcome of social media use).

"Nevertheless, these correlative studies, together with the evidence from the causal experiments, paint a picture that suggests we should take social media seriously and be concerned," Gentzkow adds.

Psychologist Orben once heard a metaphor that may help parents understand how to approach this new technology. Social media for children is a bit like the ocean, she says, noting that it can be an extremely dangerous place for children. Before parents let children swim in any open water, they make sure the child is well-prepared and equipped to handle problems that arise. They provide safety vests, swimming lessons, often in less dangerous waters, and even then parents provide a huge amount of supervision.

Alyson Hurt created the graphic. Jane Greenhalgh and Diane Webber edited the story.

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Social Media and Teen Mental Health: A Complex Mix

There is strong evidence to suggest that teenagers in the United States are collectively in the midst of a mental health crisis, as rates of both depression and suicide have climbed in recent years. Could the popularity of social media among young people be to blame?

Melissa DuPont-Reyes, PhD, MPH is an Assistant Professor of Sociomedical Sciences and Epidemiology

Melissa DuPont-Reyes , assistant professor of sociomedical sciences and epidemiology, says the answer may not be as simple as you think. She is leading a new study that takes a holistic perspective, broadening the focus from how the use of TikTok, Instagram, and other social media platforms can harm mental health to include an understanding of how they can be protective, too.

The National Institutes of Mental Health -funded longitudinal study is focused on Latinx adolescents, who use social media more than all other racial/ethnic or age groups, nationally. Beyond a simple measure of the frequency of social media use, Dupont-Reyes and colleagues will drill down into the diverse content young people encounter, including Spanish-language, Latinx-tailored, and English-language posts on a variety of platforms.

The study will collect data on both protective aspects like anti-stigma awareness campaigns and symptom support, as well as negative effects such as stigmatizing content, hate speech, and cyber-bullying. Researchers will examine how these exposures drive youths’ self-perception, help-seeking, and mental health outcomes, as well as the mediating role played by peers and family members.

To accomplish her study objective, in part, Dupont-Reyes will utilize validated, culturally appropriate survey assessments she developed as part of a project funded through a Robert Wood Johnson Foundation Pioneering Ideas Award. As part of the new study, young people will have the chance to research the question and have a say in how to address it through a process called Youth Participatory Action Research.

When it comes to social media’s effects on an adolescent mental health, Dupont-Reyes hypothesizes that context matters quite a lot. Her preliminary work has shown that for some youth, social media can be a lifeline. For instance, youth who are unaccompanied minors migrating, are LGBTQI+ in nontolerant settings, have a disability such as a speech impediment or even mental illness, or have experienced police brutality, all report that social media can be empowering as a tool to make their voices heard while also lending support and resources.

“I hope that my project demonstrates a more diverse portrait of adolescents in the U.S., and globally, as well as the social media that they encounter, and specifies the contexts in which social media can be beneficial to mental health and the contexts in which it might be harmful,” she says.

DuPont-Reyes says the evidence generated from the project could inform policies that are more equitable, accountable, and transparent—ultimately to create a safer technological landscape for diverse populations to promote mental health on a population level. At the same time, its findings can reach parents, teachers, the tech industry, health care providers, and others with its message that vilifying social media is not the answer.

“I hope my research can inform a more holistic and equitable approach to creating a safer social media environment for youth that doesn’t solely require restricting technology,” she says.

Related Information

Meet our team, melissa dupont-reyes, phd, mph.

Health Research 4 U

Safe To Play

Social Media and Adolescents’ and Young Adults’ Mental Health

Elina Mir, Andrea Sun, National Center for Health Research

Most adolescents and young adults use social media; 35% report using at least one social media platform “almost constantly,” and 54% say it is difficult to “give up” social media. [1] Not surprisingly, 36% admit to spending excessive time on it, compared to 8% who report spending too little time. [1] Given the widespread usage, this article explores the use of social media use among teens and young adults.

What are the different social media platforms and how are they used?

According to surveys, the most popular social media platforms are YouTube (95%), TikTok (67%), Instagram (62%), Snapchat(59%), and Facebook (32%). [1]

YouTube allows users to share original videos, such as music, cooking, make-up tutorials, and vlogs (video blogs).

TikTok allows users to create 15-to-60-second short-form videos, primarily focused on entertainment and comedy but increasingly used for infotainment purposes. Influencers on TikTok attract a dedicated audience by providing brief advice, tips, and engaging in self-promotion.

Instagram offers a “stories” feature that lasts for 24 hours, in addition to sharing photos and videos that remain on a user’s profile. Unless an Instagram account is set to “private,” anyone can view posted photos and videos. Many people use Instagram as a platform for photo blogging, showcasing videos from vacations, daily life, and sharing interests in art, cooking, and other activities.

Snapchat allows users to share photos that disappear after being viewed, as well as “stories” that vanish after 24 hours. These “stories” enable users to share their experiences through videos or photos with all their followers.

Facebook allows users to share photos, videos, articles, and personal information, as well as chat with friends and more.

All of these social media platforms are used to communicate with friends and are popular sources of news and celebrity updates. an overview of the percentage of U.S. adolescents who have used each social media platform. [1]

The benefits of social media

On the plus side, according to a 2022 survey, 32% of adolescents believe that social media has a mostly positive impact on their lives, compared to 9% who report mostly negative impacts. Most respondents (59%) report “neither positive nor negative”. [2] During adolescence, social connections with peers become increasingly important, and social media provides opportunities for such connections. [3] It can help young people form communities, stay in touch with friends who are not nearby, and provide them with social support. Social media can also serve as a tool for adolescents to mitigate stress, particularly for marginalized youth, such as racial, ethnic, sexual, and gender minorities. For instance, 70% of adolescent girls of color find race-affirming content on social media platforms. The majority of teenagers report feeling more accepted (58%), supported (67%), creative (71%), and connected with friends (80%) with the help of social media content. [3]

Additionally, there is evidence that utilizing social media and other digital platforms for mental health interventions can encourage help-seeking behaviors and act as a gateway to initiating mental health care for children and adolescents. [3]

Can social media increase mental health problems?

Although social media can allow people to reach out and connect with others, it can also make some people feel worse. Almost 25% of adolescents believe that social media has a mostly negative effect. [2]

With 13% of 12-17-year-olds reporting depression and 32% reporting anxiety, mental illness is a concern for adolescent health. [4] It is a concern for young adults as well, since 33.7% of 18-25-year-olds report having some form of mental illness. Depression is particularly increasing among girls. [5] Some researchers have suggested that this increase in mental illness is, at least in part, connected to the rise of social media use among adolescents and young adults. [3]

How might social media harm mental health? Many studies have found an association between time spent on social media as well as the number of social media platforms used, and symptoms of depression and anxiety. [3] Most of these studies indicate that time spent on social media is correlated with depression and anxiety, but that doesn’t necessarily mean that social media causes these problems. It is unclear whether using social media leads to depression and anxiety symptoms, or if people who are already more depressed or more anxious use social media more than their peers do. However, there is research that suggests that social media use might, at least to some degree, lead to these symptoms. For example, in one study from 2020, people who deactivated their Facebook account for a month reported lower depression and anxiety, as well as increases in happiness and life satisfaction. [6] 

Researchers believe that one problem is that social media use can disrupt sleep, and poor sleep can lead to anxiety and depression. [3] Social media use at night disrupts sleep in a number of ways: People stay up late online, the light from the screen can disrupt one’s circadian rhythm, and many people wake up in the night in order to check or respond to messages. Adolescents report that they use social media at night, even when it affects their sleep. They worry that if they do not use their phone at night, they will miss out on potential social interactions online, which they believe would have a negative effect on their in-person social relationships. [3] Also, adolescents report that their peers expect them to be online and available at night. There is a social norm to respond to messages quickly, and they don’t want to violate that norm by sleeping through their messages. Many adolescents report sleeping with their phone and checking it constantly at night.

In fact, teens and young adults often worry about what they call FoMO, which stands for “fear of missing out,” which is anxiety about missing out on experiences. Social media can worsen feelings of FoMO, for example, if someone sees posts about a party that they were not invited to. Adolescents may be particularly vulnerable to potential negative impacts of social media because social connectedness is important for their development. Browsing social media can lead to FoMO, and the feeling of being excluded can lead to negative feelings. [7]

Anxiety and depression are not the only mental health problems associated with social media use. Research on adolescents has found that body image, for girls and boys, is harmed by social media use. [1] Higher social media use leads to “body surveillance,” which refers to monitoring one’s own body and becoming judgmental of it. People who do more body surveillance report feeling more shame about their bodies. Looking at profiles of attractive people leads to more negative body image. There are many “fitspiration” accounts on Instagram, posting about diet and exercise in order to be thin, and it is common for people to filter or photoshop their posts on Instagram in order to remove blemishes. People compare themselves to these ideals or these edited images and feel like they do not measure up. This can cause poor body image. In 2021, leaked documents revealed that researchers at Instagram found that using the app was harmful to teen girls’ and boys’ body image. About 1 out of 3 teen girls felt worse about their bodies due to using the app, and so did 14% of boys. [8]

Certain social media platforms also display real-time instances of self-harming behaviors, such as self-cutting, which can cause substantial bleeding and scarring. Studies indicate conversation around or displaying this content can normalize self-harming actions, including establishing suicide agreements or posting self-harm templates for others to immitate. [1] 

Another harmful aspect of social media is cyberbullying, which is bullying that occurs online. As many as 72% of teens say that they have been cyberbullied at some point. [9] Cyberbullying is more strongly correlated with suicide attempts than face-to-face bullying. [10] Unlike bullying that takes place in person, victims of cyberbullying cannot get away from it, it stays online, and it happens out of sight of teachers and parents.

In addition, social media platforms can serve as a breeding ground for predatory actions and harmful interactions with ill-intentioned individuals who prey on children and teenagers. [1] This includes adults exploiting children sexually, threatening or distributing intimate images for financial extortion, or illicitly selling substances like fentanyl. Adolescent girls and transgender youth are disproportionately affected by online harassment and abuse, leading to feelings of sadness, anxiety, or worry. [1] Almost 60% of adolescent girls report having been approached by strangers on certain social media platforms in ways that made them feel uneasy. [1] 

Social media can adversely impact the critical brain development phase of adolescents aged 10 to 19. [1] Their brain development, particularly susceptible during early adolescence, can be influenced by societal pressures, peer views, and comparisons with others who seem more attractive or popular. Frequent social media use may lead to changes in their brains, especially in areas controlling emotions and impulses, and heighten their sensitivity to social cues. This could make them more emotional and unhappy, notably in girls aged 11 to 13 and boys aged 14 to 15. [1] Therefore, the influence of social media during this vulnerable stage is particularly important and requires further scrutiny.

What can parents do?

Because children are not good at self-regulation and are susceptible to peer pressure, social media sites can be risky places to “hang out.” The Children’s Online Privacy Protection Act prohibits websites from collecting information on children younger than 13 without parental permission. However, age is based on self-report, so children younger than 13 can simply lie about their age and open accounts. The New York Board of Education has a resource guide to help children over the age of 13 use the internet safely and in a healthy manner.

Many parents do not know the popular social media sites and how they work. Many parents’ busy schedules may leave kids unsupervised on the internet, which can lead to problems. Parental supervision is as valuable online as it is offline when it comes to instilling values and safeguards. Several resources are meant to help teach parents about social media sites and how they work. Connect Safely has developed “parent guides” for understanding different social media platforms. Also, Common Sense Media has a list of “red flags” to be on the lookout for when your children are using various social media platforms.

Parents should check in regularly with their children to ensure that their online behavior is appropriate. Although it is tempting to accomplish this through frequent monitoring, that can result in distrust between parent and child. Parents should talk about appropriate media use early and build a relationship of trust surrounding social media. It is also important for adults to model good digital behavior by avoiding social media during family time, setting limits for themselves, discussing social media use with their children, and taking breaks from social media as a family to discuss the challenges and temptations associated with it openly. [11] This way, your teen will be more likely to talk to you when there is a problem.

Be vigilant for signs of problematic social media use in your child, such as disruptions to their daily routines, prioritizing social media over in-person interactions, insufficient sleep and physical activity, persistent desire to use social media, and deceptive behavior. If you suspect any issues, have an open conversation with your child, establish new limits on social media usage, and seek guidance from a mental health professional if needed to ensure healthier engagement with the digital world. [11] Additionally, create a safe environment for your children by regularly checking in with them about their online experiences, reassuring them that they can approach you if they encounter cyberbullying. Safe Teens has developed a website with information about cyberbullying. You can read and discuss this webpage with your children.

Another important conversation to have with your children is about how social media can affect their feelings. As noted earlier in this article, many people get depressed or have poor body image when they start comparing themselves to others and feeling like they do not measure up. When a person compares his or her whole life to the positive “highlight reels” they see other people posting, it probably seems that other people’s lives are better and easier. It is important to remind your children that people on social media are putting their best foot forward, and sometimes they are even posting photos that are edited in order to make themselves look better.

Tips for managing social media use

• Pick a time at night after which you will not check your phone, and if possible, recharge your phone in another room while you sleep.
• Use an alarm clock instead of relying on your phone as an alarm to prevent you from using your phone the minute you wake up.
• Choose one day a week when you take a day off from social media and focus on other things.
• Turn off your notifications for at least a few hours each day (which you can gradually increase); put your phone in “Airplane” mode or “Do Not Disturb”.
• Set boundaries or only certain times when you can check your notifications.
• Take a break from apps that you notice contribute to unhealthy body image or feelings of inadequacy. Instead, you can try apps meant to help you feel better about yourself, such as meditation apps.
• Use apps that block certain other apps and tell you about your usage. This will help to increase your awareness of how much you are engaging with social media and help you focus on other activities.
• Start a habit of placing your phone near the door when you come home — doing it with a friend, partner, or family member can help you stay motivated and accountable! Make a plan with a group of friends to spend more time hanging out in person and less time interacting via social media.
• Consider putting your phone in grayscale. This makes your phone less enticing to look at. With the colorful apps and notifications changed to gray, they may be easier to ignore.
• Reach out for help if you encounter online harassment or abuse. People you trust, such as family members, friends, teachers, or counselors, can help if you experienced any forms of online harassment and abuse. Some sites, such as gov , provide helpful information on reporting instances of cyberbullying.
• Be cautious with sharing information online, as it can be stored permanently and you will be unable to delete it. When in doubt about posting something, it is generally a good idea to refrain from doing so. Consult a family member or trusted adult to seek their opinion on whether you should proceed.

If you are a parent wanting to learn more about how to limit your child or teenager’s social media use, check out these additional tips from the American Academy of Pediatrics.

Ideally, how would you like to spend your time ? Ask yourself: How much time do I want to spend using social media? How can I connect with people I care about in other ways, such as talking on the phone or meeting in person? Learn to balance your social media use and incorporate some of these tips into your life. If you find yourself experiencing anxiety and depression, it is also important to seek treatment. You can use this website in order to find a therapist in your area.

These articles may also provide helpful information:

Suicide Awareness and Prevention

Do Antidepressants Increase Suicide Attempts? Do They Have Other Risks?

Mood Gym: An Online Program for Adolescents to Fight Depression

Self-Injury Is Increasing in Teenage Girls: What Can Parents Do?

All articles are reviewed and approved by Dr. Diana Zuckerman and other senior staff.

The National Center for Health Research is a nonprofit, nonpartisan research, education and advocacy organization that analyzes and explains the latest medical research and speaks out on policies and programs. We do not accept funding from pharmaceutical companies or medical device manufacturers. Find out how you can support us here.

References: 

• Vogels, Emily. Gelles-Wtnick, Risa, and Massarat, Navid. Teens, Social Media and Technology 2022. Pew Research Center. 2022. https://www.pewresearch.org/internet/2022/08/10/teens-social-media-and-technology-2022/ . 2022.
• Vogels, Emily., Gelles-Watnick, Risa. Teens and social media: Key findings from Pew Research Center Surveys. https://www.pewresearch.org/short-reads/2023/04/24/teens-and-social-media-key-findings-from-pew-research-center-surveys/ . 2023.
• S. Surgeon General’s Advisory. Social Media and Youth Mental Health. https://www.hhs.gov/sites/default/files/sg-youth-mental-health-social-media-advisory.pdf. 2023 . 2023.
• S. Department of Health & Human Services. Common Mental Health Disorders in Adolescence. Hhs.gov.  https://www.hhs.gov/ash/oah/adolescent-development/mental-health/adolescent-mental-health-basics/common-disorders/index.html . Updated Jul. 2023.
• National Institute of Mental Health. Mental Illness.  nih.gov .  https://www.nimh.nih.gov/health/statistics/mental-illness.shtml . Updated February 2023.
• Allcott, H., Braghieri, L., Eichmeyer, S., & Gentzkow, M. The welfare effects of social media. American Economic Review, 2020; 110(3), 629-76.
• Barry CT, Sidoti CL, Briggs SM, Reiter SR, Lindsey RA. Adolescent social media use and mental health from adolescent and parent perspectives. Journal of Adolescence. 2017; 61:1-1.
• Breheny Wallace J. Instagram is even worse than we thought for kids. What do we do about it?.The Washington Post. September 17, 2021. https://www.washingtonpost.com/lifestyle/2021/09/17/instagram-teens-parent-advice/
• Selkie EM, Fales JL, Moreno MA. Cyberbullying prevalence among US middle and high school–aged adolescents: A systematic review and quality assessment. Journal of Adolescent Health. 2016; 58(2):125-33.
• Kuehn KS, Wagner A, Velloza J. Estimating the magnitude of the relation between bullying, e-bullying, and suicidal behaviors among United States youth, 2015. Crisis: The Journal of Crisis Intervention and Suicide Prevention. 2018.
• American Psychological Association. Keeping teens safe on social media: What parents should know to protect their kids. https://www.apa.org/topics/social-media-internet/social-media-parent-tips . 2023.

Students Think Social Media Is Fine, But Teachers See a Mental Health Minefield

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Many adults—from teachers to the U.S. surgeon general —will tell you that social media has the potential to dangerously erode K-12 students’ mental health.

School districts and lawmakers alike have responded to the growing chorus of concern. More than 200 districts (and counting) have sued major social media companies while lawmakers at the federal and state levels have been crafting legislation that would greatly curtail youth access to social media .

But there’s one constituency that policymakers, educators, and parents may not be listening to enough: students.

Nearly three quarters of high school students say that social media either has no impact or a positive impact on their mental health and well-being, according to a new EdWeek Research Center survey. Students who responded to the survey also point to many benefits arising from their social media use, such as making new friends, promoting creativity, and learning about other cultures and people.

The EdWeek Research Center surveyed a nationally representative sample of 1,056 high school students in February and March.

That doesn’t mean all teens are having a positive experience—29 percent of high schoolers said social media has a negative impact.

Whatever adults may think of how kids view social media, experts say it’s important to understand teens’ perspectives in order to teach students the social-emotional and digital- and media-literacy skills they need to use these platforms in a productive and healthy way.

“Often the question [adults are always asking] is, ‘What is technology doing to young people?’” said Ioana Literat, an associate professor at Columbia University, Teachers College, and the associate director of the school’s Media and Social Change Lab. “I like to ask, ‘What are young people doing with technology?’”

The answer: Teenagers say they are doing a lot. Forty-one percent said they have used social media to make new friends or build positive friendships, according to EdWeek’s survey. Around a quarter have used social media to develop a hobby, acquire knowledge or skills related to what they’re studying in school, and gain a better understanding of what they want to pursue after high school.

‘Peer connection or peer support on social media’

Teens also say they have connected with mentors and developed their communication and entrepreneurial skills through social media.

Nearly 1 in 3 high schoolers in the EdWeek survey said that social media has made them feel less alone.

Social media can especially be a lifeline for certain groups of students, said Chelsea Olson, a research scientist in the University of Wisconsin—Madison’s pediatrics department and a member of the university’s Social Media and Adolescent Health Research Team. LGBTQ+ youth, for example, are more likely to be bullied and struggle with depression and anxiety.

“And so, social media is a way that they can find community, they can connect with others, they can learn about themselves, they can seek resources online,” she said. “It could also be youth with chronic illnesses, especially illnesses that are rare or complicated. They might be able to go find others who are experiencing the same thing, getting that peer connection or peer support on social media, joining support groups, accessing information about their illness that they may not be able to find elsewhere.”

Even youth who are socially anxious can benefit from social media, Olson said, using it as a lower-stakes venue to practice social skills.

That’s not to say that teenagers’ social media experiences are all rosy. Nearly a quarter of high schoolers reported believing fake information they saw on social media and not getting enough sleep—the two most common answers when students were asked in the EdWeek Research Center survey about the negative consequences of their social media use.

Building a rapport with students to discuss the potential harm of social media

Understanding teens’ complicated relationship with social media is an important step to building a rapport with them that will allow educators to discuss the harm social media can cause, said Merve Lapus, the vice president of education outreach and engagement for Common Sense Media, a nonprofit research and advocacy organization that provides curricula and ratings on technology and media.

“The more we try to push our perspective without trying to take theirs into account, the more you build a rift between you as an educator and the students,” he said. “As a teacher, if I can’t try to authentically connect with how my kids are thinking, then there’s no way I’m going to be able to get them to connect to the way I’m thinking.”

And educators’ thoughts on the issue are decidedly more negative than teens’. The overwhelming majority of educators in a separate EdWeek Research Center survey said that social media has had a negative impact on students’ mental health and self-esteem. The nationally representative survey polled 595 teachers, school leaders, and district leaders and was conducted Dec. 2023 to Jan. 2024.

Ninety-one percent of educators said social media has had a negative impact on how students treat people in real life.

Educators are also far more concerned than teenagers about how the content that high schoolers post on social media today could jeopardize their future employment. Eight in 10 educators are very or somewhat concerned while only 4 in 10 teens are.

A quarter of educators indicated in the survey that they could not think of any positive outcomes their students experienced as a result of using social media, compared with 14 percent of students in the student survey.

“The biggest challenge here is that young people, especially those in middle and high school, need both autonomy and guidance,” said Heather Schwartz, a practice specialist at the Collaborative for Social Emotional Learning, or CASEL, in an email interview. “They are more expert in social media than many of their teachers, and they do not respond well when they feel they are being talked down to.”

‘It’s just another day in 8th grade’

The fact that educators see social media as such a threat to students’ mental health fits historical trends, said Columbia’s Literat.

“Whenever there is a communications technology that has a huge social impact, there is a tendency to panic. Often when we see these moral panics, the objects of the panic are young people and women,” she said, while acknowledging that the enormous scope of social media means that any negative impact from its use will be far reaching for all ages and genders.

All of this isn’t to say that educators’ opinions on how social media affects kids are wrong, said Lapus. Teens may not fully understand how social media might be impacting their mental health and well-being.

“In general, [teens] don’t have a comparison,” he said. “Educators, parents, you know a time of what school was like [before social media] when all the same dramas occurred, but they didn’t follow you home in the same capacity they do now. That has major effects on your mental health. We can see that, but for them, it’s just another day in 8th grade.”

Where there is more agreement among educators and students on the issue of social media and mental health and well-being is educators’ roles in helping students learn to navigate the challenges. Majorities of both groups—65 percent of educators and 75 percent of students—think that teachers should be responsible for helping students learn how to use social media in ways that will support students’ mental health and well-being.

But only a little more than half the students reported in the survey that a teacher has ever discussed the topic with them.

One simple step to make things better

One simple step that educators—and all adults—can take to help promote healthier social media habits among the young people they interact with is to model good behavior, experts say. That means showing respect to others on social media, not using their cellphones during class, and not posting photos or information about students without their permission (or their parents’ permission).

But to really help students reap the benefits of social media while minimizing the harm, schools need to teach digital-literacy skills—such as understanding the addictive design features of social media—paired with social-emotional skills such as self-regulation, self-awareness, empathy, and relationship-building skills.

“Self-awareness includes understanding our own identities,” Schwartz said in an email interview. “Self-management includes agency, or a sense that what we do makes a difference. This also means understanding when something is getting under their skin, and pausing before responding.”

Just as students’ views on social media are nuanced, so, too, should educators’ approaches to discussing the platforms that have become an indispensable venue for teens’ communication, socialization, and identity-formation, experts emphasize.

For example, while it’s important for schools to teach social-emotional skills, educators should acknowledge that it’s not always easy for students to apply them in real life. Social media often creates a tension with the explicit SEL skills schools are teaching, said Emily Weinstein, the executive director of the Center for Digital Thriving at Harvard University.

“It gets complicated when kids want to disconnect, but they have a friend who needs to talk: Their self-regulation and need for sleep, if it’s late at night, is pitted against their empathy,” said Weinstein. “It can be hard to figure this out in a world where you’re connected 24/7.”

The message educators should be driving home, said Lapus of Common Sense Media, is this: Yes, social media can be a positive force in students’ lives. But these platforms are also designed to override many of the social-emotional skills that help students protect their well-being, he said.

For instance, social media features such as the “like” button make it hard for users to exercise self-control, said Lapus, because they’re designed to keep users engaged on the app. “You see the number of likes and see people commenting, the impulse to not feel left out is real, and the ease of responding is built in by design.”

Teachers, he said, should encourage students to examine what’s important to them and how social media can help support those values. (For example, if family is important to a student, social media can help them stay connected with relatives who live far away.)

The goal, Lapus said, is to help students identify when social media isn’t serving their interests. “It’s up to you to be able to continue the cycle that’s helpful or break the cycle because it’s not giving you what you hope to get out of it,” he said.

Data analysis for this article was provided by the EdWeek Research Center. Learn more about the center’s work.

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The role social media plays in mental health

What’s driving your social media use, signs that social media is impacting your mental health, modifying social media use to improve mental health step 1: reduce time online, step 2: change your focus, step 3: spend more time with offline friends, step 4: express gratitude, helping a child or teen with unhealthy social media use, social media and mental health.

While many of us enjoy staying connected on social media, excessive use can fuel feelings of addiction, anxiety, depression, isolation, and FOMO. Here’s how to modify your habits and improve your mood.

Human beings are social creatures. We need the companionship of others to thrive in life, and the strength of our connections has a huge impact on our mental health and happiness. Being socially connected to others can ease stress, anxiety, and depression, boost self-worth, provide comfort and joy, prevent loneliness, and even add years to your life. On the flip side, lacking strong social connections can pose a serious risk to your mental and emotional health.

In today’s world, many of us rely on social media platforms such as Facebook, Twitter, Snapchat, YouTube, and Instagram to find and connect with each other. While each has its benefits, it’s important to remember that social media can never be a replacement for real-world human connection. It requires in-person contact with others to trigger the hormones that alleviate stress and make you feel happier, healthier, and more positive. Ironically for a technology that’s designed to bring people closer together, spending too much time engaging with social media can actually make you feel more lonely and isolated—and exacerbate mental health problems such as anxiety and depression .

If you’re spending an excessive amount of time on social media and feelings of sadness, dissatisfaction, frustration, or loneliness are impacting your life, it may be time to re-examine your online habits and find a healthier balance.  

Speak to a Licensed Therapist

BetterHelp is an online therapy service that matches you to licensed, accredited therapists who can help with depression, anxiety, relationships, and more. Take the assessment and get matched with a therapist in as little as 48 hours.

The positive aspects of social media

While virtual interaction on social media doesn’t have the same psychological benefits as face-to-face contact, there are still many positive ways in which it can help you stay connected and support your wellbeing.

Social media enables you to:

• Communicate and stay up to date with family and friends around the world.
• Find new friends and communities; network with other people who share similar interests or ambitions.
• Join or promote worthwhile causes; raise awareness on important issues.
• Seek or offer emotional support during tough times.
• Find vital social connection if you live in a remote area, for example, or have limited independence, social anxiety, or are part of a marginalized group.
• Find an outlet for your creativity and self-expression.
• Discover (with care) sources of valuable information and learning.

The negative aspects of social media

Since it’s a relatively new technology, there’s little research to establish the long-term consequences, good or bad, of social media use. However, multiple studies have found a strong link between heavy social media and an increased risk for depression, anxiety, loneliness, self-harm , and even suicidal thoughts .

Social media may promote negative experiences such as:

Inadequacy about your life or appearance . Even if you know that images you’re viewing on social media are manipulated, they can still make you feel insecure about how you look or what’s going on in your own life. Similarly, we’re all aware that other people tend to share just the highlights of their lives, rarely the low points that everyone experiences. But that doesn’t lessen those feelings of envy and dissatisfaction when you’re scrolling through a friend’s airbrushed photos of their tropical beach holiday or reading about their exciting new promotion at work.

Fear of missing out (FOMO) and social media addiction . While FOMO has been around far longer than social media, sites such as Facebook and Instagram seem to exacerbate feelings that others are having more fun or living better lives than you are. The idea that you’re missing out on certain things can impact your self-esteem, trigger anxiety, and fuel even greater social media use, much like an addiction. FOMO can compel you to pick up your phone every few minutes to check for updates, or compulsively respond to each and every alert—even if that means taking risks while you’re driving, missing out on sleep at night, or prioritizing social media interaction over real world relationships. 

Isolation . A study at the University of Pennsylvania found that high usage of Facebook, Snapchat, and Instagram increases rather decreases feelings of loneliness . Conversely, the study found that reducing social media usage can actually make you feel less lonely and isolated and improve your overall wellbeing.

Depression and anxiety . Human beings need face-to-face contact to be mentally healthy. Nothing reduces stress and boosts your mood faster or more effectively than eye-to-eye contact with someone who cares about you. The more you prioritize social media interaction over in-person relationships, the more you’re at risk for developing or exacerbating mood disorders such as anxiety and depression .

Cyberbullying. About 10 percent of teens report being bullied on social media and many other users are subjected to offensive comments. Social media platforms such as Twitter can be hotspots for spreading hurtful rumors, lies, and abuse that can leave lasting emotional scars.

Self-absorption.  Sharing endless selfies and all your innermost thoughts on social media can create an unhealthy self-centeredness and distance you from real-life connections.

These days, most of us access social media via our smartphones or tablets. While this makes it very convenient to keep in touch, it also means that social media is always accessible. This round-the-clock, hyper connectivity can trigger impulse control problems, the constant alerts and notifications affecting your concentration and focus, disturbing your sleep, and making you a slave to your phone .

Social media platforms are designed to snare your attention, keep you online, and have you repeatedly checking your screen for updates. It’s how the companies make money. But, much like a gambling compulsion or an addiction to nicotine, alcohol, or drugs, social media use can create psychological cravings. When you receive a like, a share, or a favorable reaction to a post, it can trigger the release of dopamine in the brain, the same “reward” chemical that follows winning on a slot machine, taking a bite of chocolate, or lighting up a cigarette, for example. The more you’re rewarded, the more time you want to spend on social media, even if it becomes detrimental to other aspects of your life.

Other causes of unhealthy social media use

A fear of missing out (FOMO) can keep you returning to social media over and over again. Even though there are very few things that can’t wait or need an immediate response, FOMO will have you believing otherwise. Perhaps you’re worried that you’ll be left out of the conversation at school or work if you miss the latest news or gossip on social media? Or maybe you feel that your relationships will suffer if you don’t immediately like, share, or respond to other people’s posts? Or you could be worried you’ll miss out on an invitation or that other people are having a better time than you.

Many of us use social media as a “security blanket”. Whenever we’re in a social situation and feel anxious, awkward, or lonely, we turn to our phones and log on to social media. Of course, interacting with social media only denies you the face-to-face interaction that can help to ease anxiety .

Your heavy social media use could be masking other underlying problems , such as stress, depression, or boredom. If you spend more time on social media when you’re feeling down, lonely, or bored, you may be using it as a way to distract yourself from unpleasant feelings or self-soothe your moods. While it can be difficult at first, allowing yourself to feel can open you up to finding healthier ways to manage your moods .

The vicious cycle of unhealthy social media use

Excessive social media use can create a negative, self-perpetuating cycle:

• When you feel lonely, depressed, anxious, or stressed, you use social media more often—as a way to relieve boredom or feel connected to others.
• Using social media more often, though, increases FOMO and feelings of inadequacy, dissatisfaction, and isolation.
• In turn, these feelings negatively affect your mood and worsen symptoms of depression, anxiety, and stress.
• These worsening symptoms cause you to use social media even more, and so the downward spiral continues.

Everyone is different and there is no specific amount of time spent on social media, or the frequency you check for updates, or the number of posts you make that indicates your use is becoming unhealthy. Rather, it has to do with the impact time spent on social media has on your mood and other aspects of your life, along with your motivations for using it.

For example, your social media use may be problematic if it causes you to neglect face-to-face relationships, distracts you from work or school, or leaves you feeling envious, angry, or depressed. Similarly, if you’re motivated to use social media just because you’re bored or lonely, or want to post something to make others jealous or upset, it may be time to reassess your social media habits.

Indicators that social media may be adversely affecting your mental health include:

Spending more time on social media than with real world friends . Using social media has become a substitute for a lot of your offline social interaction. Even if you’re out with friends, you still feel the need to constantly check social media, often driven by feelings that others may be having more fun than you.

Comparing yourself unfavorably with others on social media . You have low self-esteem or negative body image. You may even have patterns of disordered eating.

Experiencing cyberbullying . Or you worry that you have no control over the things people post about you.

Being distracted at school or work . You feel pressure to post regular content about yourself, get comments or likes on your posts, or respond quickly and enthusiastically to friends’ posts.

Having no time for self-reflection . Every spare moment is filled by engaging with social media, leaving you little or no time for reflecting on who you are, what you think, or why you act the way that you do—the things that allow you to grow as a person.

Engaging in risky behavior in order to gain likes , shares, or positive reactions on social media. You play dangerous pranks, post embarrassing material, cyberbully others, or access your phone while driving or in other unsafe situations.  

[ Read: Dealing with Revenge Porn and “Sextortion” ]

Suffering from sleep problems . Do you check social media last thing at night, first thing in the morning, or even when you wake up in the night? The light from phones and other devices can disrupt your sleep , which in turn can have a serious impact on your mental health.

Worsening symptoms of anxiety or depression . Rather than helping to alleviate negative feelings and boost your mood, you feel more anxious, depressed, or lonely after using social media.

A 2018 University of Pennsylvania study found that reducing social media use to 30 minutes a day resulted in a significant reduction in levels of anxiety, depression, loneliness, sleep problems, and FOMO. But you don’t need to cut back on your social media use that drastically to improve your mental health. The same study concluded that just being more mindful of your social media use can have beneficial results on your mood and focus.  

While 30 minutes a day may not be a realistic target for many of us—let alone a full “social media detox”— we can still benefit from reducing the amount of time we spend on social media. For most of us, that means reducing how much we use our smartphones. The following tips can help:

• Use an app to track how much time you spend on social media each day. Then set a goal for how much you want to reduce it by.
• Turn off your phone at certain times of the day, such as when you’re driving, in a meeting, at the gym, having dinner, spending time with offline friends, or playing with your kids. Don’t take your phone with you to the bathroom.
• Don’t bring your phone or tablet to bed . Turn devices off and leave them in another room overnight to charge.
• Disable social media notifications. It’s hard to resist the constant buzzing, beeping, and dinging of your phone alerting you to new messages. Turning off notifications can help you regain control of your time and focus.
• Limit checks. If you compulsively check your phone every few minutes, wean yourself off by limiting your checks to once every 15 minutes. Then once every 30 minutes, then once an hour. There are apps that can automatically limit when you’re able to access your phone.
• Try removing social media apps from your phone so you can only check Facebook, Twitter and the like from your tablet or computer. If this sounds like too drastic a step, try removing one social media app at a time to see how much you really miss it.

For more tips on reducing your overall phone use, read Smartphone Addiction .

Many of us access social media purely out of habit or to mindlessly kill moments of downtime. But by focusing on your motivation for logging on, you can not only reduce the time you spend on social media, you can also improve your experience and avoid many of the negative aspects.

If you’re accessing social media to find specific information, check on a friend who’s been ill, or share new photos of your kids with family, for example, your experience is likely to be very different than if you’re logging on simply because you’re bored, you want to see how many likes you got from a previous post, or to check if you’re missing out on something.

Next time you go to access social media, pause for a moment and clarify your motivation for doing so.

Are you using social media as a substitute for real life? Is there a healthier substitute for your social media use? If you’re lonely, for example, invite a friend out for coffee instead. Feeling depressed? Take a walk or go to the gym. Bored? Take up a new hobby. Social media may be quick and convenient, but there are often healthier, more effective ways to satisfy a craving.

Are you an active or a passive user on social media? Passively scrolling through posts or anonymously following the interaction of others on social media doesn’t provide any meaningful sense of connection. It may even increase feelings of isolation. Being an active participant, though, will offer you more engagement with others.

Does social media leave you feeling inadequate or disappointed about your life? You can counter symptoms of FOMO by focusing on what you have, rather than what you lack. Make a list of all the positive aspects of your life and read it back when you feel you’re missing out on something better. And remember: no one’s life is ever as perfect as it seems on social media. We all deal with heartache, self-doubt, and disappointment, even if we choose not to share it online.  

We all need the face-to-face company of others to be happy and healthy. At its best, social media is a great tool for facilitating real-life connections. But if you’ve allowed virtual connections to replace real-life friendships in your life, there are plenty of ways to build meaningful connections without relying on social media.

Set aside time each week to interact offline with friends and family. Try to make it a regular get-together where you always keep your phones off.

If you’ve neglected face-to-face friendships, reach out to an old friend (or an online friend) and arrange to meet up. If you both lead busy lives, offer to run errands or exercise together .

Join a club . Find a hobby, creative endeavor, or fitness activity you enjoy and join a group of like-minded individuals that meet on a regular basis.

Don’t let social awkwardness stand in the way . Even if you’re shy, there are proven techniques to  overcome insecurity and build friendships .

If you don’t feel that you have anyone to spend time with, reach out to acquaintances . Lots of other people feel just as uncomfortable about making new friends as you do—so be the one to break the ice. Invite a coworker out for lunch or ask a neighbor or classmate to join you for coffee.

Interact with strangers . Look up from your screen and connect with people you cross paths with on public transport, at the coffee shop, or in the grocery store. Simply smiling or saying hello will improve how you feel—and you never know where it may lead.

Feeling and expressing gratitude about the important things in your life can be a welcome relief to the resentment, animosity, and discontent sometimes generated by social media.

Take time for reflection . Try keeping a gratitude journal or using a gratitude app. Keep track of all the great memories and positives in your life—as well as those things and people you’d miss if they were suddenly absent from your life. If you’re more prone to venting or negative posts, you can even express your gratitude on social media—although you may benefit more from private reflection that isn’t subject to the scrutiny of others. 

[Read: Gratitude: The Benefits and How to Practice It]

Practice mindfulness . Experiencing FOMO and comparing yourself unfavorably to others keeps you dwelling on life’s disappointments and frustrations. Instead of being fully engaged in the present, you’re focused on the “what ifs” and the “if onlys” that prevent you from having a life that matches those you see on social media. By practicing mindfulness , you can learn to live more in the present moment, lessen the impact of FOMO, and improve your overall mental wellbeing.

Volunteer . Just as human beings are hard-wired to seek social connection, we’re also hard-wired to give to others. Helping other people or animals not only enriches your community and benefits a cause that’s important to you, but it also makes you feel happier and more grateful.

Childhood and the teenage years can be filled with developmental challenges and social pressures. For some kids, social media has a way of exacerbating those problems and fueling anxiety, bullying, depression, and issues with self-esteem. If you’re worried about your child’s social media use, it can be tempting to simply confiscate their phone or other device. But that can create further problems, separating your child from their friends and the positive aspects of social media. Instead, there are other ways to help your child use Facebook, Instagram, and other platforms in a more responsible way.

Monitor and limit your child’s social media use. The more you know about how your child is interacting on social media, the better you’ll be able to address any problems. Parental control apps can help limit your child’s data usage or restrict their phone use to certain times of the day. You can also adjust privacy settings on the different platforms to limit their potential exposure to bullies or predators.

Talk to your child about underlying issues. Problems with social media use can often mask deeper issues. Is your child having problems fitting in at school? Are they suffering from shyness or social anxiety? Are problems at home causing them stress?

Enforce “social media” breaks. For example, you could ban social media until your child has completed their homework in the evening, not allow phones at the dinner table or in their bedroom, and plan family activities that preclude the use of phones or other devices. To prevent sleep problems, always insist phones are turned off at least one hour before bed.

Teach your child how social media is not an accurate reflection of people’s lives. They shouldn’t compare themselves or their lives negatively to others on social media. People only post what they want others to see. Images are manipulated or carefully posed and selected. And having fewer friends on social media doesn’t make your child less popular or less worthy.

Encourage exercise and offline interests. Get your child away from social media by encouraging them to pursue physical activities and hobbies that involve real-world interaction. Exercise is great for relieving anxiety and stress , boosting self-esteem, and improving mood—and is something you can do as a family. The more engaged your child is offline, the less their mood and sense of self-worth will be dependent on how many friends, likes, or shares they have on social media. 

More Information

• Social media use increases depression and loneliness - Details study linking time spent on social media with decreased wellbeing. (Penn Today, University of Pennsylvania)
• Social media, young people and mental health - Briefing paper analyzing the impact of social media. (Centre for Mental Health)
• Does Social Media Cause Depression? - How heavy Instagram and Facebook use may be affecting kids negatively. (Child Mind Institute)
• Hunt, Melissa G., Rachel Marx, Courtney Lipson, and Jordyn Young. “No More FOMO: Limiting Social Media Decreases Loneliness and Depression.” Journal of Social and Clinical Psychology 37, no. 10 (December 2018): 751–68. Link
• Riehm, Kira E., Kenneth A. Feder, Kayla N. Tormohlen, Rosa M. Crum, Andrea S. Young, Kerry M. Green, Lauren R. Pacek, Lareina N. La Flair, and Ramin Mojtabai. “Associations Between Time Spent Using Social Media and Internalizing and Externalizing Problems Among US Youth.” JAMA Psychiatry 76, no. 12 (December 1, 2019): 1266. Link
• Anderson, Monica. (2018, September 27). A majority of teens have been the target of cyberbullying, with name-calling and rumor-spreading being the most common forms of harassment. Pew Research Center: Internet, Science & Tech. Link
• Kross, Ethan, Philippe Verduyn, Emre Demiralp, Jiyoung Park, David Seungjae Lee, Natalie Lin, Holly Shablack, John Jonides, and Oscar Ybarra. “Facebook Use Predicts Declines in Subjective Well-Being in Young Adults.” PLOS ONE 8, no. 8 (August 14, 2013): e69841. Link
• Twenge, Jean M., Thomas E. Joiner, Megan L. Rogers, and Gabrielle N. Martin. “Increases in Depressive Symptoms, Suicide-Related Outcomes, and Suicide Rates Among U.S. Adolescents After 2010 and Links to Increased New Media Screen Time.” Clinical Psychological Science 6, no. 1 (January 1, 2018): 3–17. Link
• Ilakkuvan, Vinu, Amanda Johnson, Andrea C. Villanti, W. Douglas Evans, and Monique Turner. “Patterns of Social Media Use and Their Relationship to Health Risks Among Young Adults.” Journal of Adolescent Health 64, no. 2 (February 2019): 158–64. Link
• Primack, Brian A., Ariel Shensa, Jaime E. Sidani, Erin O. Whaite, Liu Yi Lin, Daniel Rosen, Jason B. Colditz, Ana Radovic, and Elizabeth Miller. “Social Media Use and Perceived Social Isolation Among Young Adults in the U.S.” American Journal of Preventive Medicine 53, no. 1 (July 2017): 1–8. Link

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‘Social media is like driving with no speed limits’: the US surgeon general fighting for youngsters’ happiness

Dr Vivek Murthy is urging governments to regulate social media as study shows screen use and isolation has caused widespread discontent

• Youngsters suffering ‘equivalent of midlife crisis’
• Six Dagenham teenagers on their future prospects

It was the hush that worried the US’s top doctor as he toured the country’s university campuses last year.

Dr Vivek Murthy went to places including Duke, University of Texas and Arizona State, but so many youngsters were plugged into earphones and gazing into laptops and phones that it was incredibly quiet in the communal areas. Where was the loud chatter Murthy remembered from his college days?

“Students said to me, ‘how are we supposed to start a conversation?’” the US surgeon general told the Guardian. “It’s just not the culture any more to talk to one another. It’s an indictment of the trends that we’ve seen.”

Figures published on Wednesday reveal one possible impact of that screen obsession : for the first time since the data was first collected in 2012, 15- to 24-year-olds in North America say they are less happy than older generations. The gap is closing in western European nations and in March Murthy flew to London to further his campaign against falling levels of happiness, particularly among the young. He is also worried about youth wellbeing in Japan, South Korea and India.

The replacement of person-to-person social connection, whether through clubs, sports teams, volunteering or faith groups, is a particular concern to the Yorkshire-born medic. Education, housing and transport initiatives that do not focus on improving wellbeing are also a worry.

But perhaps the biggest problem in his opinion is the explosion of social media use , which has caused “extraordinary harms”.

It is notable that Murthy is focusing so hard on this social issue. At a conference at the LSE in London on Monday, academics and researchers in the fast-developing field of wellbeing science gave him a standing ovation.

There are clear physical impacts of misery for world leaders to consider. Social disconnection in the US has led to “a 29% increase in the risk of heart disease, a 32% increase in the risk of stroke and a 50% increase in the risk of dementia among older individuals,” he said.

Last year, Murthy, who was first appointed to his role by Barack Obama and again by Joe Biden, issued a formal US-wide warning that social media presented “a profound risk of harm” to the mental health and wellbeing of children and adolescents. “We do not yet have enough evidence to determine if social media is sufficiently safe” for them to use, it said.

“I’m still waiting for companies to show us data that tells us that their platforms are actually safe,” he added.

He compared tech companies to 20th-century car giants producing vehicles without seatbelts and airbags until legislation mandated it.

“What’s happening in social media is the equivalent of having children in cars that have no safety features and driving on roads with no speed limits,” he said. “No traffic lights and no rules whatsoever. And we’re telling them: ‘you know what, do your best – figure out how to manage it.’ It is insane if you think about it.”

The result is that parents feel “this whole thing [managing the impact of social media] has been dumped on their shoulders”.

Murthy said that between 2000 and 2020 there has been a 70% decrease in the amount of in-person time young people in the US spent with their friends. Meanwhile, “our recent data is telling us that adolescents are spending on average 4.8 hours a day on social media … a third of adolescents are staying up till midnight or later on weeknights on their devices”.

Last Sunday, he met with a group of young people in a park in west London and concluded their phones were feeding them a diet of “headlines that are constantly telling them that the world is broken, and that the future is bleak”.

“And they said: you receive that again and again and again. You start to internalise that. You sort of lose a sense of hope.”

He is interested, too, in how burgeoning social media use fuels “hustle culture” that teaches young people that they ought to build a “personal brand” and even an income stream alongside studying and growing up.

“I ask [young people] what hustle culture is telling you success is,” he said. “They say some version of fame, followers and fortune. I have had too many young people say what they feel like they’ve really got to do right now is build their brand. And they don’t say that ironically.”

He said social media companies should limit or eliminate “features that try to get kids to drive towards other people liking, reposting and commenting on their posts”, such as buttons and infinite scroll mechanisms that can be addictive, damage self-esteem and erode time available for other activities.

“The platforms have the power to do that,” he said.

Governments have been slow to install mandatory guardrails on social media platforms and should have done so 10 years ago, he said. “What has happened is a fundamental failure of governments to protect young people from the harmful effects of a new technology and it’s not new any more.”

To counteract the trend, Murthy wants governments to start measuring their policies in terms of their impact on real world social connection.

“Think about policies that carve up our cities and towns with highways and roadways and separate us from one another,” he said. “Think about the power of policy to actually put public transportation in place and bring people back together. Housing design can have a powerful impact on how people come together.”

In 2021, the leader of the UK opposition, Keir Starmer, said a Labour government would weigh spending plans based on their effect on wellbeing in addition to national income.

But for now he compares the status quo with social media to a doctor being allowed to run a hospital where floors are so slippery that people fall and break their hips, patients suffer blood clots because medicine is not being administered and become infected because dirty equipment is being used. His point is it would not happen. Protections are needed immediately, he said.

“If you’ve got a 12-year-old and a 15-year-old, you don’t have three to five years to wait,” he said. “Our kids’ childhoods are happening right now. I worry that there isn’t enough of a sense of urgency in government.”

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Social media and mental health.

Social media has been on the rise for decades as a way for people to connect to one another. In more recent years it has become a platform for people to share their lives with the entire world. Careers have been made out of this type of sharing and has created a new branch of influencers. Almost all generations can admit they keep up with social media and influencers in some capacity. Although this was formed as a way of connecting to benefit people it has been the cause of many mental health problems across younger generations.

Instagram’s recent restriction on likes may be a small step in the right direction, but it is not a complete solution to mental health issues. Social media has a reinforcing nature, activating the brain’s reward center by releasing dopamine, a “feel-good chemical” linked to pleasurable activities. The platform is designed to be addictive and is associated with anxiety, depression, and physical ailments. According to the Pew Research Center, 69% of adults and 81% of teens in the U.S. use social media, putting a large population at an increased risk of feeling anxious, depressed, or ill over their use. The unpredictable outcome of social media platforms keeps users engaged, as they post content with the hope of receiving positive feedback. Comparisons and FOMO (fear of missing out) also play a role in this behavior. A 2018 British study linked social media use to decreased, disrupted, and delayed sleep, which is associated with depression, memory loss, and poor academic performance (Sperling,2024)

Social media platforms have a significant impact on mental health, particularly for females, who often express aggression physically and are prone to excluding others and sharing hurtful comments. Social media also puts a distorted lens on appearances and reality, with unrealistic, filtered photos available on platforms like Facebook, Instagram, and Snapchat. This can make it difficult for teens to distinguish between reality and reality, especially during middle school and puberty when their brains are not fully developed and relationships become more important. Adults are also vulnerable to this, with plastic surgeons seeing an increase in requests for filtered photos. It is crucial to be mindful of the potential harm caused by social media use and its impact on mental health. If adults can also suffer from this and have the ability to have fully developed thoughts it can be even more detrimental to children who do not have the ability to think a certain way yet.

Parents can limit device usage and teach kids healthy media use and sleep hygiene. They can ask teens to turn in their phones at night, monitor their online activity, and remember that their content is a permanent fingerprint. Some families can modify their social media usage to encourage sharing without focusing on appearance. This is important especially with younger children because the more comparison they have to people on social media the more likely they can suffer from self-esteem issues which leads to body image problems and could end up in eating disorders.

Sperling, J. (2024, February 14). The Social Dilemma: Social Media and Your Mental Health . Www.mcleanhospital.org; McLean Hospital. https://www.mcleanhospital.org/essential/it-or-not-social-medias-affecting-your-mental-health

This entry was posted on Monday, March 18th, 2024 at 1:36 pm and is filed under Uncategorized . You can follow any comments to this entry through the RSS 2.0 feed. You can leave a comment , or trackback from your own site.

It’s fascinating and a bit scary to see how much social media we consume in our daily lives, isn’t it? On one hand, it’s incredible that we can stay connected with friends and family worldwide, not to mention the whole influencer culture that has sprouted up, giving people new ways to express themselves and even make a living. But on the flip side, the mental health implications, especially for the younger crowd, are concerning.

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Social media and mental health challenges

Kalpana srivastava.

Department of Psychiatry, Dr. DY Patil Medical College, Dr. DY Patil University, Pune, Maharashtra, India

Suprakash Chaudhury

Jyoti prakash.

1 Department of Psychiatry, AFMC, Pune, Maharashtra, India

Sana Dhamija

Mental health in current scenario has faced many challenges. A recent upsurge in the use of media alerted to invigilate its relationship with mental health. The term “social media” is a part and parcel of day-to-day happenings. It is important to understand its encroachment and extension in our lives. Social media refers to a computer-driven technology that facilitates the sharing of ideas, thoughts, and information by connecting with virtual networks and communities. By design, social media is internet based and gives users a quick electronic communication of content. Content includes personal information, documents, videos, and photographs. Users engage with social media via computer, tablet, or smartphone via web-based software or web application, often utilizing it for messaging.[ 1 ] Digital media is any media that are encoded in machine-readable formats. Digital media refer to any information that is broadcast to us through a screen. This includes text, audio, video, and graphics that is transmitted over the Internet, for viewing on the Internet.[ 2 ]

There is a huge growth of technology interface in communication. The first E-mail was delivered in 1971. It was considered to be the harbinger of the digital revolution. The first mobile phone was launched in 1984. The first smartphone supporting voice calls and E-mails was introduced in 1994. There were few important milestones in the development of digital platforms. Broadband which provided much faster internet access was introduced in 2000. LinkedIn and Friendster were launched in 2002, Pocketbucket and Myspace in 2003, Facebook (FB) and Flickr in 2004, YouTube in 2005, and Twitter in 2006. The innovation in technology impacted print media and it saw a downward trend. The reading habits emphasized by all scholars came under a big jolt. Letters came under the endangered list, and greeting cards have been replaced by ecards. Even more dramatic was the vulnerable telegram, the163 years old but fast and dependable purveyor of ecstatic or wretched news, became extinct in 2013 without a whimper; in fact the earth shaking event went unnoticed.

In the last five decades after that seminal event of 1971, the spread of digital media has been phenomenal, aided to a large extent by smartphones. Over one in four people worldwide are on FB, Twitter, LinkedIn, Instagram, and other social networking sites (SNSs). Globally, the SNS users were estimated to be 2.95 billion in 2019.[ 3 ] People are spending increasing amounts of time on digital media. The use of social media is varied, wide, and almost inescapable. World over, the ubiquitous presence of social media is noted. India has a phenomenal demographic advantage and therefore has a huge list of social media users. On an average, Indians spend an estimated 3½ h daily using traditional media and 1 h and 29 min daily using social media, with the bulk of that time (76%) accessing SNSs through smartphones. As a result, there has been a steep increase in the number of smartphone users.[ 4 , 5 ]

PSYCHOLOGICAL UNDERPINNINGS OF THE USE OF SOCIAL MEDIA

Despite the ever-increasing popularity of the social media, the explanations for snowballing use are not clearly established. Theoretical postulates propose that the self-disclosure made on SNSs activates the intrinsic reward system due to which the behavior is repeated. High rates of disclosure are driven by motivation to share one’s beliefs and knowledge about the world, suggesting that this could be part of the intrinsic drive to disclose about self to others. Opportunities to disclose one’s thoughts are hypothesized to be as a powerful form of subjective reward,[ 6 ] and the primary motivation for using SNSs are a need to belong and a need for self-presentation. It is also promulgated that FB profiles help satisfy individuals’ need for self-worth and appreciation.[ 7 , 8 ]

The user gratification theory emphasizes self-discovery, entertainment value, social enhancement, and the need to maintain interpersonal connectivity through the construct of behavioral intentions. Social influence is a process of internalization and identification, and it has positive impacts on the use of social media. Greater levels of engagement with social media were observed in students from more individualistic cultures compared to their counterparts from collectivist cultures.[ 9 ] The reasons for using social media also vary with age. Those younger than 30, are focused on connecting with friends and relations, entertainment, identity formation, and maintaining interpersonal connections.[ 10 ] In contrast, middle-aged and older adults use social media to connect with others with common interests and hobbies.[ 11 , 12 ]

MERITS OF SOCIAL MEDIA

The biggest boon of use of social media is that it provides quick access to and also mitigates the barrier of distance. The virtual meetings and discussions on digital platform save money and investment of time, which also has distinct positive outcomes specifically for sharing the mutual interests and exploring the possibility of learning new things.[ 13 ]

Different types of social capital, including social ties, are positively associated with the indices of psychological well-being, such as self-esteem.[ 14 ] Researchers attest that social media networks enhance the chance to create and/or maintain offline social capital. Social media will foster a way of social inclusion in online communities. Persons with psychiatric disorders may share personal stories in a perceived safer space, thereby gaining peer support for developing coping strategies. Digital media has immense potential for improving mental health care that is being explored with telepsychiatry and telecounseling and providing psychological interventions. In fact for conducting research also, they are used widely.[ 15 ]

ADVERSE EFFECTS OF SOCIAL MEDIA USE

Excessive use of social media is considered to be detrimental for mental health and well-being. The link of social media and increased depression, anxiety, loneliness, and addiction is highlighted by researchers. The burgeoning use of social media especially by young adults raises concerns about these negative effects. A national survey of U.S. young adults, found that compared with individuals who use 0 to 2 social media platforms, individuals who use 7 to 11 social media platforms have substantially higher odds of getting increased levels of depression and anxiety symptoms. In a sample of adolescents and their parents throughout the U.S., social media use was moderately and positively associated with adolescent-reported fear of missing out and loneliness, as well as with parent-reported hyperactivity/impulsivity, anxiety, and depression.[ 16 , 17 ] Evaluation of FB usage among college-age students revealed that one or more FB usage variables (number of friends and use for image management) were associated with major depressive disorder, dysthymia, bipolar-mania, and narcissism in the user.[ 18 ]

This can be qualified by the fact that the time spent in face-to-face interaction and interpersonal relationships has been replaced by computer screens. This may lead to reduction in family time spent together and a feeling of loneliness. Though social networks may help in establishing a large number of networks, it may not be satisfying in the exact sense.[ 19 ]

SOCIAL MEDIA AND DEPRESSION

Depression and use of media has a negatively reinforcing outcome. In fact, the lower response on social network may make a person feel more dejected and it may validate his/her poor self-esteem. Depressive ruminations are associated with more negative and fewer positive social networking interactions, ad thereby making people feel more depressed. Sometimes, social media may help in understanding the feelings of a person based on the declared status or self-disclosure, hence its two different perspectives must be considered.

Studies carried out among students found that higher number of FB friends lead to the feeling of lower emotional adjustment to university life. It is important to note that it is not the number but the quality of social media interactions which is an important predictor of mental wellness.[ 20 , 21 ] In a study carried out among high school students, a statistically significant positive correlation was found between depressive symptoms and time spent on SNS. The happiness and success of others being compared to self may not cause depression as found in a study carried out on 425 undergraduate students, however individuals having certain depressive predispositions are negatively impacted by the comparison of self by the success of others.[ 22 ] Hence, it is not the time being spent on social media which may be contributing toward negative mood rather negative social interactions in general, associated with increases in depressive symptoms over time.

SOCIAL MEDIA AND ANXIETY

Once social media use becomes part of lifestyle, it becomes almost like a routine to follow. Several studies have linked social media to anxiety and compulsive behavior. Among British adults, 45% felt worried or uncomfortable once they were unable to access their E-mail or SNSs.[ 23 ] Out of this constant connectivity, a new medical term has emerged namely phantom vibration syndrome (PVS) which is defined as perceived vibration from a mobile phone that is not vibrating. PVS is not uncommon and is probably a symptom of the anxiety that mobile phones elicit in those that are obsessed about signing in on their social media.[ 24 ] At present, around 66% of the world population is using a mobile phone, and approximately 1.16 billion mobile phone users are present in India[ 25 ] PVS is found to be positively correlated with the duration of smartphone use. Studies have yielded evidence to that the long-term use of smartphones can lead to the development of symptoms such as headache, extreme irritation, increase in carelessness, forgetfulness, decrease of reflexes, and clicking sound in ears.[ 26 ] This association of individuals with their smartphones has led to the emergence of a new kind of psychological disorder called phantom syndrome characterized by a frequent false feeling of ringing and vibration from the smartphones.[ 27 ]

CYBERBULLYING

Cyberbullying exists in different forms. It can include the posting of hurtful comments online, threats, and intimidation toward others within the online space and posting photographs or videos that are intended to cause distress or disgust, inciting others to make hurtful comments aimed at a person, or sending hurtful text messages on a smartphone. The incidence of cyberbullying across seven European countries in children aged 8–16 increased from 8% to 12% between 2010 and 2014. Similar increases were shown within the USA and Brazil.[ 28 ] Cyberbullying essentially differs from face-to-face bullying in several ways. First, one cannot escape from it by staying at home as it occurs via mobile phones or net. Second, the bullying is witnessed by a very large audience; messages/images/videos being in the public domain can be forwarded again and again, resulting in victims experiencing the abuse on multiple occasions. Third, because the material used in the abuse is permanently stored online, they are a permanent reminder of the abuse and can result in abuse being continually experienced by the victim.[ 29 ]

Cyberbullying using digital or social media has adverse effects on mental health. For the victim, this could be significantly humiliating and causes a loss of confidence and self-worth. They may experience depression, anxiety, loss of sleep, self-harm, and feelings of loneliness.[ 30 ] Victims may have lower self-esteem, increased suicidal ideation, decreased motivation for usual hobbies, and a range of emotional responses, including being scared, frustrated, angry, anxious, or depressed and may distance themselves from friends and relatives.[ 31 ]

Identification of vulnerability factors for the development of SNS addiction is of interest to clinicians and researchers. The Interaction of Person-Affect-Cognition-Execution Model proposes the interaction of personal (P), affective (A), cognitive (C), and executive (E) variables in the emergence of a specific internet use disorder. One of the P factors implicated in the model is personality which may create a vulnerability or resilience to the development of a specific internet use disorder.[ 32 ] A cross-national meta-analysis of personality factors and SNS addiction revealed that FB use disorder was positively associated with neuroticism and negatively with conscientiousness.[ 33 ] Similar findings have been reported for problematic internet use and problematic smartphone use.[ 34 ]

SOCIAL NETWORKING AND SELF-ESTEEM

Early studies reported that longer time spent on FB was associated with lower self-esteem. A study of 100 FB users at a university indicated that individuals with lower self-esteem are more active online.[ 35 ] However, Gonzales and Hancock showed the positive effects of FB on self-esteem supporting the “Hyperpersonal Model,” in which selective self-presentation positively impacts self-esteem.[ 36 ] The objective self-awareness theory proposes that any stimulus causing the self to become the object (instead the subject) of the consciousness (e.g., looking at oneself in a mirror, hearing one’s own voice, and writing one’s own curriculum vitae) will cause a diminished impression of the self. A typical FB user makes multiple visits to their profile page daily during which he/she will view his/her previously posted photographs, biographical data, and so on, which can cause a short-term or a long-term reduction in self-esteem.[ 37 ]

SOCIAL MEDIA AND NARCISSISM

Narcissism significantly positively predicts the personal importance placed on FB,[ 38 ] emotional attachment to FB,[ 39 ] the requirement for admiration by FB friends,[ 40 ] and intentions to post digitally altered images of the self on FB.[ 41 ] Narcissists also report more use of FB for creating new acquaintances. A meta-analysis of 62 studies (2010–2016) revealed that trait narcissism is positively associated with time spent on social media; number of friends (e.g., FB) and followers (e.g., Twitter or Instagram); and frequency of posting status updates (FB), tweets (Twitter), pictures of the self, and selfies.[ 42 ]

SOCIAL MEDIA USE, SELF-HARM, AND SUICIDE

The link between social media use, self-harm, and even suicide is a matter of concern. The undeniable fact that adolescents can access distressing content online that promotes self-harm and suicide is a significant cause for concern. This content attempts to “normalize” self-harm and suicide and may end in adolescents replicating the actions that they are exposed to.

Social media has immense benefits if used with discretion. Social media is pervasive and has infiltrated numerous areas of activity including government, business, commerce, education, and information technology. The harmful effects of social media may have profound consequences for young persons. This area requires continued research globally so that not only the harmful effects are identified but also prevention and treatment is explored. Technology is here to stay. We have to learn to optimize its use and coexist.