research on the effects of social media on mental health

Open access
Published: 06 July 2023

Pros & cons: impacts of social media on mental health

Ágnes Zsila 1 , 2 &
Marc Eric S. Reyes ORCID: orcid.org/0000-0002-5280-1315 3

BMC Psychology volume 11 , Article number: 201 ( 2023 ) Cite this article

474k Accesses

18 Citations

119 Altmetric

Metrics details

The use of social media significantly impacts mental health. It can enhance connection, increase self-esteem, and improve a sense of belonging. But it can also lead to tremendous stress, pressure to compare oneself to others, and increased sadness and isolation. Mindful use is essential to social media consumption.

Social media has become integral to our daily routines: we interact with family members and friends, accept invitations to public events, and join online communities to meet people who share similar preferences using these platforms. Social media has opened a new avenue for social experiences since the early 2000s, extending the possibilities for communication. According to recent research [ 1 ], people spend 2.3 h daily on social media. YouTube, TikTok, Instagram, and Snapchat have become increasingly popular among youth in 2022, and one-third think they spend too much time on these platforms [ 2 ]. The considerable time people spend on social media worldwide has directed researchers’ attention toward the potential benefits and risks. Research shows excessive use is mainly associated with lower psychological well-being [ 3 ]. However, findings also suggest that the quality rather than the quantity of social media use can determine whether the experience will enhance or deteriorate the user’s mental health [ 4 ]. In this collection, we will explore the impact of social media use on mental health by providing comprehensive research perspectives on positive and negative effects.

Social media can provide opportunities to enhance the mental health of users by facilitating social connections and peer support [ 5 ]. Indeed, online communities can provide a space for discussions regarding health conditions, adverse life events, or everyday challenges, which may decrease the sense of stigmatization and increase belongingness and perceived emotional support. Mutual friendships, rewarding social interactions, and humor on social media also reduced stress during the COVID-19 pandemic [ 4 ].

On the other hand, several studies have pointed out the potentially detrimental effects of social media use on mental health. Concerns have been raised that social media may lead to body image dissatisfaction [ 6 ], increase the risk of addiction and cyberbullying involvement [ 5 ], contribute to phubbing behaviors [ 7 ], and negatively affects mood [ 8 ]. Excessive use has increased loneliness, fear of missing out, and decreased subjective well-being and life satisfaction [ 8 ]. Users at risk of social media addiction often report depressive symptoms and lower self-esteem [ 9 ].

Overall, findings regarding the impact of social media on mental health pointed out some essential resources for psychological well-being through rewarding online social interactions. However, there is a need to raise awareness about the possible risks associated with excessive use, which can negatively affect mental health and everyday functioning [ 9 ]. There is neither a negative nor positive consensus regarding the effects of social media on people. However, by teaching people social media literacy, we can maximize their chances of having balanced, safe, and meaningful experiences on these platforms [ 10 ].

We encourage researchers to submit their research articles and contribute to a more differentiated overview of the impact of social media on mental health. BMC Psychology welcomes submissions to its new collection, which promises to present the latest findings in the emerging field of social media research. We seek research papers using qualitative and quantitative methods, focusing on social media users’ positive and negative aspects. We believe this collection will provide a more comprehensive picture of social media’s positive and negative effects on users’ mental health.

Data Availability

Not applicable.

Statista. (2022). Time spent on social media [Chart]. Accessed June 14, 2023, from https://www.statista.com/chart/18983/time-spent-on-social-media/ .

Pew Research Center. (2023). Teens and social media: Key findings from Pew Research Center surveys. Retrieved June 14, 2023, from https://www.pewresearch.org/short-reads/2023/04/24/teens-and-social-media-key-findings-from-pew-research-center-surveys/ .

Boer, M., Van Den Eijnden, R. J., Boniel-Nissim, M., Wong, S. L., Inchley, J. C.,Badura, P.,… Stevens, G. W. (2020). Adolescents’ intense and problematic social media use and their well-being in 29 countries. Journal of Adolescent Health , 66(6), S89-S99. https://doi.org/10.1016/j.jadohealth.2020.02.011.

Marciano L, Ostroumova M, Schulz PJ, Camerini AL. Digital media use and adolescents’ mental health during the COVID-19 pandemic: a systematic review and meta-analysis. Front Public Health. 2022;9:2208. https://doi.org/10.3389/fpubh.2021.641831 .

Article Google Scholar

Naslund JA, Bondre A, Torous J, Aschbrenner KA. Social media and mental health: benefits, risks, and opportunities for research and practice. J Technol Behav Sci. 2020;5:245–57. https://doi.org/10.1007/s41347-020-00094-8 .

Article PubMed PubMed Central Google Scholar

Harriger JA, Thompson JK, Tiggemann M. TikTok, TikTok, the time is now: future directions in social media and body image. Body Image. 2023;44:222–6. https://doi.org/10.1016/j.bodyim.2021.12.005 .

Article PubMed Google Scholar

Chi LC, Tang TC, Tang E. The phubbing phenomenon: a cross-sectional study on the relationships among social media addiction, fear of missing out, personality traits, and phubbing behavior. Curr Psychol. 2022;41(2):1112–23. https://doi.org/10.1007/s12144-022-0135-4 .

Valkenburg PM. Social media use and well-being: what we know and what we need to know. Curr Opin Psychol. 2022;45:101294. https://doi.org/10.1016/j.copsyc.2020.101294 .

Bányai F, Zsila Á, Király O, Maraz A, Elekes Z, Griffiths MD, Urbán R, Farkas J, Rigó P Jr, Demetrovics Z. Problematic social media use: results from a large-scale nationally representative adolescent sample. PLoS ONE. 2017;12(1):e0169839. https://doi.org/10.1371/journal.pone.0169839 .

American Psychological Association. (2023). APA panel issues recommendations for adolescent social media use. Retrieved from https://apa-panel-issues-recommendations-for-adolescent-social-media-use-774560.html .

Download references

Acknowledgements

Ágnes Zsila was supported by the ÚNKP-22-4 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund.

Author information

Authors and affiliations.

Institute of Psychology, Pázmány Péter Catholic University, Budapest, Hungary

Ágnes Zsila

Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary

Department of Psychology, College of Science, University of Santo Tomas, Manila, 1008, Philippines

Marc Eric S. Reyes

You can also search for this author in PubMed Google Scholar

Contributions

AZ conceived and drafted the Editorial. MESR wrote the abstract and revised the Editorial. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Marc Eric S. Reyes .

Ethics declarations

Ethics approval and consent to participate, consent for publication, competing interests.

The authors have no competing interests to declare relevant to the content of this article.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Zsila, Á., Reyes, M.E.S. Pros & cons: impacts of social media on mental health. BMC Psychol 11 , 201 (2023). https://doi.org/10.1186/s40359-023-01243-x

Download citation

Received : 15 June 2023

Accepted : 03 July 2023

Published : 06 July 2023

DOI : https://doi.org/10.1186/s40359-023-01243-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Social media
Mental health

BMC Psychology

ISSN: 2050-7283

General enquiries: [email protected]

research on the effects of social media on mental health

The Impact of social media on Mental Health: Understanding the Role of Online Platforms in Psychological Well-being

Discover the world's research

25+ million members
160+ million publication pages
2.3+ billion citations

Manjunath Reddy
Nikolaos Tzenios

Poh Omasyarifa Binti Jamal

Omasyarifa Binti Jamal Poh
Recruit researchers
Join for free
Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings
My Bibliography
Collections
Citation manager

Save citation to file

Email citation, add to collections.

Create a new collection
Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed.

Search in PubMed
Search in NLM Catalog
Add to Search

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.

PubMed Disclaimer

Conflict of interest statement

Conflict of Interest The authors have nothing to disclose.

Related information

Cited in Books

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

LinkOut - more resources

Full text sources.

Europe PubMed Central
PubMed Central

Miscellaneous

NCI CPTAC Assay Portal
Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

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

Published: 20 April 2020
Volume 5 , pages 245–257, ( 2020 )

Cite this article

John A. Naslund 1 ,
Ameya Bondre 2 ,
John Torous 3 &
Kelly A. Aschbrenner 4

389k Accesses

204 Citations

169 Altmetric

19 Mentions

Explore all metrics

Avoid common mistakes on your manuscript.

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.

Download references

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).

Author information

Authors and affiliations.

Department of Global Health and Social Medicine, Harvard Medical School, 641 Huntington Avenue, Boston, MA, 02115, USA

John A. Naslund

Digital Mental Health Research Consultant, Mumbai, India

Ameya Bondre

Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA

John Torous

Department of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA

Kelly A. Aschbrenner

You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to John A. Naslund .

Ethics declarations

Conflict of interest.

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

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

Download citation

Received : 19 October 2019

Revised : 24 February 2020

Accepted : 17 March 2020

Published : 20 April 2020

Issue Date : September 2020

DOI : https://doi.org/10.1007/s41347-020-00134-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Find a journal
Publish with us
Track your research

Information

Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

Active Journals
Find a Journal
Proceedings Series
For Authors
For Reviewers
For Editors
For Librarians
For Publishers
For Societies
For Conference Organizers
Open Access Policy
Institutional Open Access Program
Special Issues Guidelines
Editorial Process
Research and Publication Ethics
Article Processing Charges
Testimonials
Preprints.org
SciProfiles
Encyclopedia

Article Menu

Subscribe SciFeed
Recommended Articles
Google Scholar
on Google Scholar
Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

Body perceptions and psychological well-being: a review of the impact of social media and physical measurements on self-esteem and mental health with a focus on body image satisfaction and its relationship with cultural and gender factors.

1. Introduction

Methodology, 2. theoretical framework on body image, 2.1. objectification theory, 2.2. social comparison theory, 2.3. self-discrepancy theory, 3. influence of social media on body image and mental health, 3.1. social media as a catalyst for comparison, 3.2. the role of self-presentation on social media, 3.3. the impact of social media on adolescents and young adults, 3.4. cultural and gender differences in social media’s impact, 3.5. mitigating the negative impact of social media, 4. impact of physical measurements on psychological well-being, 4.1. societal standards and their psychological impacts, 4.2. weight and self-esteem, 4.3. height, body image, and mental health, 4.4. the complex role of bmi, 4.5. addressing the psychological effects of physical measurements, 5. body image satisfaction, 5.1. factors contributing to body image satisfaction, 5.2. importance of body image satisfaction, 5.3. gender differences in body image satisfaction, 5.3.1. women and body image satisfaction, 5.3.2. men and body image satisfaction, 5.4. cultural influences on body image satisfaction, 5.5. enhancing body image satisfaction, 6. cultural influences on body image, 6.1. cultural norms and body image, 6.2. intersectionality: gender and culture, 6.3. the impact on psychological well-being, 6.4. mitigating cultural and gender influences, 7. impact of body image on psychological well-being, 7.1. relationship between body image satisfaction/dissatisfaction and mental health outcomes, 7.2. psychological disorders associated with poor body image, 7.3. addressing the impact of body image on psychological well-being, 7.4. the importance of body image in self-evaluation and its psychological impact, 8. methodological approaches in body image research, 8.1. quantitative research methods, 8.2. qualitative research methods, 8.3. mixed methods approaches, 8.4. longitudinal studies, 8.5. strengths and limitations, 9. interventions and strategies for improving body image, 9.1. interventions and strategies, 9.2. prevention and intervention strategies, 9.2.1. universal interventions, 9.2.2. targeted interventions, 9.2.3. indicated interventions, 9.2.4. multisectoral collaboration, 10. policy implications and future directions, 10.1. implications for health policy and practice, 10.2. suggestions for future research, 11. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

Franchina, V.; Coco, G.L. The Influence of Social Media Use on Body Image Concerns. Int. J. Psychoanal. Educ. 2018 , 10 , 5–14. [ Google Scholar ]
Hogue, J.V.; Mills, J.S. The Effects of Active Social Media Engagement with Peers on Body Image in Young Women. Body Image 2019 , 28 , 1–5. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Fardouly, J.; Vartanian, L.R. Social Media and Body Image Concerns: Current Research and Future Directions. Curr. Opin. Psychol. 2016 , 9 , 1–5. [ Google Scholar ] [ CrossRef ]
Rounsefell, K.; Gibson, S.; McLean, S.; Blair, M.; Molenaar, A.; Brennan, L.; Truby, H.; McCaffrey, T.A. Social Media, Body Image and Food Choices in Healthy Young Adults: A Mixed Methods Systematic Review. Nutr. Diet. 2020 , 77 , 19–40. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Vandenbosch, L.; Fardouly, J.; Tiggemann, M. Social Media and Body Image: Recent Trends and Future Directions. Curr. Opin. Psychol. 2022 , 45 , 101289. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Burnette, C.B.; Kwitowski, M.A.; Mazzeo, S.E. “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 , 114–125. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Tylka, T.L.; Wood-Barcalow, N.L. What is and what is not positive body image? Conceptual foundations and construct definition. Body Image 2015 , 14 , 118–129. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Tylka, T.L.; Wood-Barcalow, N.L. The Body Appreciation Scale-2: Item refinement and psychometric evaluation. Body Image 2015 , 12 , 53–67. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Alleva, J.M.; Tylka, T.L. Body functionality: A review of the literature. Body Image 2021 , 36 , 149–171. [ Google Scholar ] [ CrossRef ]
Slater, A.; Tiggemann, M. Body Image and Disordered Eating in Adolescent Girls and Boys: A Test of Objectification Theory. Sex Roles 2010 , 63 , 42–49. [ Google Scholar ] [ CrossRef ]
Calogero, R.M. Objectification Theory, Self-Objectification, and Body Image. In Encyclopedia of Body Image and Human Appearance ; Elsevier Academic Press: Amsterdam, The Netherlands, 2012; Volume 2. [ Google Scholar ] [ CrossRef ]
Moradi, B.; Huang, Y.P. Objectification Theory and Psychology of Women: A Decade of Advances and Future Directions. Psychol. Women Q. 2008 , 32 , 377–398. [ Google Scholar ] [ CrossRef ]
Slater, A.; Tiggemann, M. A Test of Objectification Theory in Adolescent Girls. Sex Roles 2002 , 46 , 343–349. [ Google Scholar ] [ CrossRef ]
Fredrickson, B.L.; Roberts, T.A.; Noll, S.M.; Quinn, D.M.; Twenge, J.M. That Swimsuit Becomes You: Sex Differences in Self-Objectification, Restrained Eating, and Math Performance. J. Personal. Soc. Psychol. 1998 , 75 , 269. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Fredrickson, B.L.; Roberts, T. Objectification Theory: Toward Understanding Women’s Lived Experiences and Mental Health Risks. Psychol. Women Q. 1997 , 21 , 173–206. [ Google Scholar ] [ CrossRef ]
Calogero, R.M.; Tylka, T.L.; Siegel, J.A.; Pina, A.; Roberts, T.A. Smile Pretty and Watch Your Back: Personal Safety Anxiety and Vigilance in Objectification Theory. J. Personal. Soc. Psychol. 2021 , 121 , 1195. [ Google Scholar ] [ CrossRef ]
Winn, L.; Cornelius, R. Self-Objectification and Cognitive Performance: A Systematic Review of the Literature. Front. Psychol. 2020 , 11 , 20. [ Google Scholar ] [ CrossRef ]
Buunk, A.P.; Gibbons, F.X. Social Comparison: The End of a Theory and the Emergence of a Field. Organ. Behav. Hum. Decis. Process. 2007 , 102 , 3–21. [ Google Scholar ] [ CrossRef ]
Morrison, T.G.; Kalin, R.; Morrison, M.A. Body-Image Evaluation and Body-Image Investment among Adolescents: A Test of Sociocultural and Social Comparison Theories. Adolescence 2004 , 39 , 155. [ Google Scholar ]
Krayer, A.; Ingledew, D.K.; Iphofen, R. Social Comparison and Body Image in Adolescence: A Grounded Theory Approach. Health Educ. Res. 2008 , 23 , 892–903. [ Google Scholar ] [ CrossRef ]
Lewallen, J.; Behm-Morawitz, E. Pinterest or Thinterest?: Social Comparison and Body Image on Social Media. Soc. Media Soc. 2016 , 2 , 2056305116640559. [ Google Scholar ] [ CrossRef ]
Heinberg, L.J.; Thompson, J.K. Social Comparison: Gender, Target Importance Ratings, and Relation to Body Image Disturbance. J. Soc. Behav. Personal. 1992 , 7 , 335. [ Google Scholar ]
Tsiantas, G.; King, R.M. Similarities in Body Image in Sisters: The Role of Sociocultural Internalization and Social Comparison. Eat. Disord. 2001 , 9 , 141–158. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Crusius, J.; Corcoran, K.; Mussweiler, T. Social Comparison: A Review of Theory, Research, and Applications. In Theories in Social Psychology ; Wiley Online Library: Hoboken, NJ, USA, 2022. [ Google Scholar ]
Cherry, K. Social Comparison Theory in Psychology ; Verywellmind.Com., 2018; Available online: https://www.verywellmind.com/the-stress-of-social-comparison-4154076 (accessed on 1 May 2024).
Marsh, H.W. Cognitive Discrepancy Models: Actual, Ideal, Potential, and Future Self-Perspectives of Body Image. Soc. Cogn. 1999 , 17 , 46–75. [ Google Scholar ] [ CrossRef ]
Szymanski, M.L.; Cash, T.F. Body-Image Disturbances and Self-Discrepancy Theory: Expansion of the Body-Image Ideals Questionnaire. J. Soc. Clin. Psychol. 1995 , 14 , 134–146. [ Google Scholar ] [ CrossRef ]
Valkenburg, P.M.; van Driel, I.I.; Beyens, I. The associations of active and passive social media use with well-being: A critical scoping review. New Media Soc. 2022 , 24 , 530–549. [ Google Scholar ] [ CrossRef ]
Yu, U.J.; Jung, J. Effects of Self-Discrepancy and Self-Schema on Young Women’s Body Image and Self-Esteem after Media Image Exposure. Fam. Consum. Sci. Res. J. 2018 , 47 , 142–160. [ Google Scholar ] [ CrossRef ]
Bodroža, B.; Obradović, V.; Ivanović, S. Active and Passive Selfie-Related Behaviors: Implications for Body Image, Self-Esteem and Mental Health. Cyberpsychology 2022 , 16 , 2. [ Google Scholar ] [ CrossRef ]
Cussins, A.M. The Role of Body Image in Women’s Mental Health. Fem. Rev. 2001 , 68 , 105–114. [ Google Scholar ] [ CrossRef ]
Thompson, J.K.; Heinberg, L.J.; Altabe, M.; Tantleff-Dunn, S. Exacting Beauty: Theory, Assessment, and Treatment of Body Image Disturbance ; American Psychological Association: Washington, DC, USA, 1999. [ Google Scholar ] [ CrossRef ]
Vincente-Benito, I.; Ramírez-Durán, M.D.V. Influence of Social Media Use on Body Image and Well-Being Among Adolescents and Young Adults A Systematic Review. J. Psychosoc. Nurs. Ment. Health Serv. 2023 , 61 , 11–18. [ Google Scholar ] [ CrossRef ]
Fardouly, J.; Magson, N.R.; Rapee, R.M.; Johnco, C.J.; Oar, E.L. The Use of Social Media by Australian Preadolescents and Its Links with Mental Health. J. Clin. Psychol. 2020 , 76 , 1304–1326. [ Google Scholar ] [ CrossRef ]
Steinsbekk, S.; Wichstrøm, L.; Stenseng, F.; Nesi, J.; Hygen, B.W.; Skalická, V. The Impact of Social Media Use on Appearance Self-Esteem from Childhood to Adolescence—A 3Wave Community Study. Comput. Human Behav. 2021 , 114 , 106528. [ Google Scholar ] [ CrossRef ]
Greenwood, D. Gender Considerations of Media Content, Uses, and Impact on Well-Being. In The Routledge Handbook of Media Use and Well-Being: International Perspectives on Theory and Research on Positive Media Effects ; Routledge: London, UK, 2016. [ Google Scholar ] [ CrossRef ]
Arrivillaga, C.; Rey, L.; Extremera, N. A Mediated Path from Emotional Intelligence to Problematic Social Media Use in Adolescents: The Serial Mediation of Perceived Stress and Depressive Symptoms. Addict. Behav. 2022 , 124 , 107095. [ Google Scholar ] [ CrossRef ]
Prieler, M.; Choi, J. Broadening the Scope of Social Media Effect Research on Body Image Concerns. Sex Roles 2014 , 71 , 378–388. [ Google Scholar ] [ CrossRef ]
Ryding, F.C.; Kuss, D.J. The Use of Social Networking Sites, Body Image Dissatisfaction, and Body Dysmorphic Disorder: A Systematic Review of Psychological Research. Psychol. Pop. Media 2020 , 9 , 412. [ Google Scholar ] [ CrossRef ]
Lee, H.R.; Lee, H.E.; Choi, J.; Kim, J.H.; Han, H.L. Social Media Use, Body Image, and Psychological Well-Being: A Cross-Cultural Comparison of Korea and the United States. J. Health Commun. 2014 , 19 , 1343–1358. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Hjetland, G.J.; Finserås, T.R.; Sivertsen, B.; Colman, I.; Hella, R.T.; Skogen, J.C. Focus on Self-Presentation on Social Media across Sociodemographic Variables, Lifestyles, and Personalities: A Cross-Sectional Study. Int. J. Environ. Res. Public Health 2022 , 19 , 11133. [ Google Scholar ] [ CrossRef ]
Mann, R.B.; Blumberg, F. Adolescents and Social Media: The Effects of Frequency of Use, Self-Presentation, Social Comparison, and Self Esteem on Possible Self Imagery. Acta Psychol. 2022 , 228 , 103629. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Skogen, J.C.; Hjetland, G.J.; Bøe, T.; Hella, R.T.; Knudsen, A.K. Through the Looking Glass of Social Media. Focus on Self-Presentation and Association with Mental Health and Quality of Life. A Cross-Sectional Survey-Based Study. Int. J. Environ. Res. Public Health 2021 , 18 , 3319. [ Google Scholar ] [ CrossRef ]
Khalaf, A.M.; Alubied, A.A.; Khalaf, A.M.; Rifaey, A.A. The Impact of Social Media on the Mental Health of Adolescents and Young Adults: A Systematic Review. Cureus 2023 , 15 , e42990. [ Google Scholar ] [ CrossRef ]
Jarman, H.K.; McLean, S.A.; Griffiths, S.; Teague, S.J.; Rodgers, R.F.; Paxton, S.J.; Austen, E.; Harris, E.; Steward, T.; Shatte, A.; et al. Critical Measurement Issues in the Assessment of Social Media Influence on Body Image. Body Image 2022 , 40 , 225–236. [ Google Scholar ] [ CrossRef ]
Shannon, H.; Bush, K.; Villeneuve, P.J.; Hellemans, K.G.C.; Guimond, S. Problematic Social Media Use in Adolescents and Young Adults: Systematic Review and Meta-Analysis. JMIR Ment. Health 2022 , 9 , e33450. [ Google Scholar ] [ CrossRef ]
Weir, K. Social Media Brings Benefits and Risks to Teens. In Here’s How Psychology Can Help Identify a Path Forward ; American Psychological Association: Washington, DC, USA, 2023. [ Google Scholar ]
Nagar, P. Digital Detriments: Unraveling the Psychological Consequences of Social Media. Lloyd Bus. Rev. 2023 , 2 , 1–14. [ Google Scholar ] [ CrossRef ]
Dias, I.; Hernâni-Eusébio, J.; Silva, R. “How Many Likes?”: The Use of Social Media, Body Image Insatisfaction and Disordered Eating. Eur. Psychiatry 2021 , 64 (Suppl. S1), S698. [ Google Scholar ] [ CrossRef ]
Vidal, C.; Lhaksampa, T.; Miller, L.; Platt, R. Social Media Use and Depression in Adolescents: A Scoping Review. Int. Rev. Psychiatry 2020 , 32 , 235–253. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Twenge, J.M.; Martin, G.N. Gender Differences in Associations between Digital Media Use and Psychological Well-Being: Evidence from Three Large Datasets. J. Adolesc. 2020 , 79 , 91–102. [ Google Scholar ] [ CrossRef ]
Vogelzang, J.L. Gender and Age-Specific Use of Social Media. In Effective Use of Social Media in Public Health ; Academic Press: New York, NY, USA, 2023. [ Google Scholar ] [ CrossRef ]
Reyes, M.E.S.; Morales, B.C.C.; Javier, G.E.; Ng, R.A.E.; Zsila, Á. Social Networking Use Across Gender: Its Association with Social Connectedness and Happiness Amidst the COVID19 Pandemic. J. Technol. Behav. Sci. 2022 , 7 , 396–405. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Santoniccolo, F.; Trombetta, T.; Paradiso, M.N.; Rollè, L. Gender and Media Representations: A Review of the Literature on Gender Stereotypes, Objectification and Sexualization. Int. J. Environ. Res. Public Health 2023 , 20 , 5770. [ Google Scholar ] [ CrossRef ]
He, L.; Firdaus, A.; Gong, J.; Dharejo, N.; Aksar, I.A. How the Social Media Impact Women’s Psychological Well-Being in the Patriarchal Structure? The Moderating Effect of Social Capital. BMC Public Health 2024 , 24 , 581. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Greenwood, D.N.; Lippman, J.R. Gender and Media: Content, Uses, and Impact. In Handbook of Gender Research in Psychology ; Springer: Berlin/Heidelberg, Germany, 2010. [ Google Scholar ] [ CrossRef ]
Karatsoli, M.; Nathanail, E. Examining Gender Differences of Social Media Use for Activity Planning and Travel Choices. Eur. Transp. Res. Rev. 2020 , 12 , 44. [ Google Scholar ] [ CrossRef ]
Arias-Rodriguez, A.; Sánchez-Bello, A. Informal Learning with a Gender Perspective Transmitted by Influencers through Content on YouTube and Instagram in Spain. Soc. Sci. 2022 , 11 , 341. [ Google Scholar ] [ CrossRef ]
Singh, H. The Impact of Media on Youth Mental Health Status. Int. J. Physiol. 2020 , 5 , 108. [ Google Scholar ]
AbiJaoude, E.; Naylor, K.T.; Pignatiello, A. Smartphones, Social Media Use and Youth Mental Health. CMAJ 2020 , 192 , E136–E141. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Gupta, C.; Jogdand, S.; Kumar, M. Reviewing the Impact of Social Media on the Mental Health of Adolescents and Young Adults. Cureus 2022 , 14 , e30143. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Bell, I.H.; Thompson, A.; Valentine, L.; Adams, S.; Alvarez-Jimenez, M.; Nicholas, J. Ownership, Use of, and Interest in Digital Mental Health Technologies among Clinicians and Young People across a Spectrum of Clinical Care Needs: Cross-Sectional Survey. JMIR Ment. Health 2022 , 9 , e30716. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Griffioen, N.; Scholten, H.; Lichtwarck-Aschoff, A.; van Rooij, M.; Granic, I. Everyone Does It—Differently: A Window into Emerging Adults’ Smartphone Use. Humanit. Soc. Sci. Commun. 2021 , 8 , 177. [ Google Scholar ] [ CrossRef ]
Gansner, M.; Nisenson, M.; Lin, V.; Pong, S.; Torous, J.; Carson, N. Problematic Internet Use before and during the COVID19 Pandemic in Youth in Outpatient Mental Health Treatment: App-Based Ecological Momentary Assessment Study. JMIR Ment. Health 2022 , 9 , e33114. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Aschbrenner, K.A.; Naslund, J.A.; Tomlinson, E.F.; Kinney, A.; Pratt, S.I.; Brunette, M.F. Adolescents’ Use of Digital Technologies and Preferences for Mobile Health Coaching in Public Mental Health Settings. Front. Public Health 2019 , 7 , 178. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Wong, S.M.; Chen, E.Y.; Wong, C.S.; Suen, Y.N.; Chan, D.L.; Tsang, S.H.; Wong, T.Y.; Cheung, C.; Chan, K.T.; Lui, S.S.; et al. Impact of Smartphone Overuse on 1Year Severe Depressive Symptoms and Momentary Negative Affect: Longitudinal and Experience Sampling Findings from a Representative Epidemiological Youth Sample in Hong Kong. Psychiatry Res. 2022 , 318 , 114939. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Granero-Jiménez, J.; López-Rodríguez, M.M.; Dobarrio-Sanz, I.; Cortés-Rodríguez, A.E. Influence of Physical Exercise on Psychological Well-Being of Young Adults: A Quantitative Study. Int. J. Environ. Res. Public Health 2022 , 19 , 4282. [ Google Scholar ] [ CrossRef ]
Datta Gupta, N.; Etcoff, N.L.; Jaeger, M.M. Beauty in Mind: The Effects of Physical Attractiveness on Psychological Well-Being and Distress. J. Happiness Stud. 2016 , 17 , 1313–1325. [ Google Scholar ] [ CrossRef ]
Jin, S.; Zhang, J. The Effects of Physical and Psychological Well-Being on Suicidal Ideation. J. Clin. Psychol. 1998 , 54 , 401–413. [ Google Scholar ] [ CrossRef ]
Fox, K.R. The Influence of Physical Activity on Mental Well-Being. Public Health Nutr. 1999 , 2 , 411–418. [ Google Scholar ] [ CrossRef ]
Parfitt, G.; Eston, R.G. The Relationship between Children’s Habitual Activity Level and Psychological Well-Being. Acta Paediatr. Int. J. Paediatr. 2005 , 94 , 1791–1797. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Pressman, S.D.; Matthews, K.A.; Cohen, S.; Martire, L.M.; Scheier, M.; Baum, A.; Schulz, R. Association of Enjoyable Leisure Activities with Psychological and Physical Well-Being. Psychosom. Med. 2009 , 71 , 725–732. [ Google Scholar ] [ CrossRef ]
Norris, R.; Carroll, D.; Cochrane, R. The Effects of Physical Activity and Exercise Training on Psychological Stress and Well-Being in an Adolescent Population. J. Psychosom. Res. 1992 , 36 , 55–65. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Saadeh, M.; Welmer, A.K.; Dekhtyar, S.; Fratiglioni, L.; Calderón-Larrañaga, A. The Role of Psychological and Social Well-Being on Physical Function Trajectories in Older Adults. J. Gerontol. Ser. A Biol. Sci. Med. Sci. 2021 , 75 , 1579–1585. [ Google Scholar ] [ CrossRef ]
Hassmén, P.; Koivula, N.; Uutela, A. Physical Exercise and Psychological Well-Being: A Population Study in Finland. Prev. Med. 2000 , 30 , 17–25. [ Google Scholar ] [ CrossRef ]
Klitzman, S.; Stellman, J.M. The Impact of the Physical Environment on the Psychological Well-Being of Office Workers. Soc. Sci. Med. 1989 , 29 , 733–742. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Greenleaf, C.; Petrie, T.A.; Martin, S.B. Relationship of Weight-Based Teasing and Adolescents’ Psychological Well-Being and Physical Health. J. Sch. Health 2014 , 84 , 49–55. [ Google Scholar ] [ CrossRef ]
Phillips, L.R.S. The Relationship between Psychological Well-Being and Physical Activity: The Impact of Measurement. 2013. Available online: https://ore.exeter.ac.uk/repository/handle/10871/12106 (accessed on 1 May 2024).
Liu, E.; Chang, S.H. Self-Esteem and Weight Status of Young Adults: Findings from a Pilot Study. J. Educ. Health Promot. 2022 , 11 , 263. [ Google Scholar ] [ CrossRef ]
Robinson, E.; Haynes, A.; Sutin, A.; Daly, M. Self-Perception of Overweight and Obesity: A Review of Mental and Physical Health Outcomes. Obes. Sci. Pract. 2020 , 6 , 552–561. [ Google Scholar ] [ CrossRef ] [ PubMed ]
VanWormer, J.J.; French, S.A.; Pereira, M.A.; Welsh, E.M. The Impact of Regular Self-Weighing on Weight Management: A Systematic Literature Review. Int. J. Behav. Nutr. Phys. Act. 2008 , 5 , 54. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Meland, E.; Breidablik, H.J.; Thuen, F.; Samdal, G.B. How Body Concerns, Body Mass, Self-Rated Health and Self-Esteem Are Mutually Impacted in Early Adolescence: A Longitudinal Cohort Study. BMC Public Health 2021 , 21 , 496. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Pila, E.; Sabiston, C.M.; Brunet, J.; Castonguay, A.L.; O’Loughlin, J. Do Body-Related Shame and Guilt Mediate the Association between Weight Status and Self-Esteem? J. Health Psychol. 2015 , 20 , 659–669. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Elran-Barak, R. Self-Esteem, Weight Status, and Trying to Lose Weight During Young Adulthood: The Roles of Sex and Ethnicity/Race. Ethn. Dis. 2019 , 29 , 485–494. [ Google Scholar ] [ CrossRef ]
Lasikiewicz, N.; Myrissa, K.; Hoyland, A.; Lawton, C.L. Psychological Benefits of Weight Loss Following Behavioural and/or Dietary Weight Loss Interventions. A Systematic Research Review. Appetite 2014 , 72 , 123–137. [ Google Scholar ] [ CrossRef ]
Jach, L.; Kryston, S. Self-Reported Body Weight and Weight-Related Stigmatization Experiences among Young Adult Women-Two Contexts, but Similar Attitudes Related to Body Image, Mental Self-Schemas, Self-Esteem, and Stereotypes of People with Obesity. PeerJ 2021 , 9 , e12047. [ Google Scholar ] [ CrossRef ]
Frayon, S.; Swami, V.; Wattelez, G.; Todd, J.; Galy, O. Associations between weight status, body satisfaction, ethnic identity and self-esteem in Oceanian adolescents. Pediatr. Obes. 2021 , 16 , e12824. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Rodgers, R.F.; Laveway, K.; Campos, P.; de Carvalho, P.H.B. Body image as a global mental health concern. Glob. Ment. Health 2023 , 10 , e9. [ Google Scholar ] [ CrossRef ]
Dane, A.; Bhatia, K. The Social Media Diet: A Scoping Review to Investigate the Association between Social Media, Body Image and Eating Disorders amongst Young People. PLOS Glob. Public Health 2023 , 3 , e0001091. [ Google Scholar ] [ CrossRef ]
A Limbers, C.; Baskin, A.; Cohen, L.A. Disordered Eating and Body Image Concerns in Young Adult Women with Scoliosis. Clin. Med. InsightsArthritis Musculoskelet. Disord. 2023 , 16 , 11795441231166010. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Czepczor-Bernat, K.; Modrzejewska, A.; Modrzejewska, J.; Pękała, M. A Preliminary Study of Body Image and Depression among Adults during COVID19: A Moderation Model. Arch. Psychiatr. Nurs. 2021 , 36 , 55–61. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Yazdani, N.; Hosseini, S.V.; Amini, M.; Sobhani, Z.; Sharif, F.; Khazraei, H. Relationship between Body Image and Psychological Well-Being in Patients with Morbid Obesity. Int. J. Community Based Nurs. Midwifery 2018 , 6 , 175–184. [ Google Scholar ] [ PubMed ]
Scheffers, M.; van Busschbach, J.T.; Bosscher, R.J.; Aerts, L.C.; Wiersma, D.; Schoevers, R.A. Body Image in Patients with Mental Disorders: Characteristics, Associations with Diagnosis and Treatment Outcome. Compr. Psychiatry 2017 , 74 , 53–60. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Grogan, S. Body Image and Health: Contemporary Perspectives. J. Health Psychol. 2006 , 11 , 523–530. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Milton, A.; Hambleton, A.; Roberts, A.; Davenport, T.; Flego, A.; Burns, J.; Hickie, I. Body Image Distress and Its Associations from an International Sample of Men and Women across the Adult Life Span: Web-Based Survey Study. JMIR Form. Res. 2021 , 5 , e25329. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Ahadzadeh, A.S.; Rafik-Galea, S.; Alavi, M.; Amini, M. Relationship between Body Mass Index, Body Image, and Fear of Negative Evaluation: Moderating Role of Self-Esteem. Heal. Psychol. Open 2018 , 5 , 2055102918774251. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Ishikawa, M.; Yokoyama, T.; Nishi, N.; Miura, H. Study of the Relationship between Body Mass Index, Body Image, and Lifestyle Behaviors: A Community Survey in Fiji. JMA J. 2019 , 3 , 41–50. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Gutin, I. In BMI We Trust: Reframing the Body Mass Index as a Measure of Health. Soc. Theory Health 2018 , 16 , 256. [ Google Scholar ] [ CrossRef ]
Wilson, R.E.; Latner, J.D.; Hayashi, K. More than Just Body Weight: The Role of Body Image in Psychological and Physical Functioning. Body Image 2013 , 10 , 644–647. [ Google Scholar ] [ CrossRef ]
Liang, G.; Barnhart, W.R.; Cheng, Y.; Lu, T.; He, J. The Interplay among BMI, Body Dissatisfaction, Body Appreciation, and Body Image Inflexibility in Chinese Young Adults: A Network Perspective. J. Context. Behav. Sci. 2023 , 29 , 192–201. [ Google Scholar ] [ CrossRef ]
Sudhir, P.; Delma, D. Comparison of Body Image Perception and the Actual BMI and Correlation with Self esteem and Mental Health: A Cross sectional Study among Adolescents Sudhir. Int. J. Health Allied Sci. 2018 , 7 , 145–149. [ Google Scholar ]
Robinson, E.; Roberts, C.; Vainik, U.; Jones, A. The Psychology of Obesity: An Umbrella Review and Evidence-Based Map of the Psychological Correlates of Heavier Body Weight. Neurosci. Biobehav. Rev. 2020 , 119 , 468–480. [ Google Scholar ] [ CrossRef ]
Tort-Nasarre, G.; Pocallet, M.P.; Artigues-Barberà, E. The Meaning and Factors That Influence the Concept of Body Image: Systematic Review and Meta-Ethnography from the Perspectives of Adolescents. Int. J. Environ. Res. Public Health 2021 , 18 , 1140. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Gualdi-Russo, E.; Rinaldo, N.; Zaccagni, L. Physical Activity and Body Image Perception in Adolescents: A Systematic Review. Int. J. Environ. Res. Public Health 2022 , 19 , 13190. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Palenzuela-Luis, N.; Duarte-Clíments, G.; Gómez-Salgado, J.; Rodríguez-Gómez, J.Á.; Sánchez-Gómez, M.B. International Comparison of Self-Concept, Self-Perception and Lifestyle in Adolescents: A Systematic Review. Int. J. Public Health 2022 , 67 , 1604954. [ Google Scholar ] [ CrossRef ]
Foley Davelaar, C.M. Body Image and Its Role in Physical Activity: A Systematic Review. Cureus 2021 , 13 , e13379. [ Google Scholar ] [ CrossRef ]
Kling, J.; Kwakkenbos, L.; Diedrichs, P.C.; Rumsey, N.; Frisén, A.; Brandão, M.P.; Silva, A.G.; Dooley, B.; Rodgers, R.F.; Fitzgerald, A. Systematic Review of Body Image Measures. Body Image 2019 , 30 , 170–211. [ Google Scholar ] [ CrossRef ]
Shunmuga Sundaram, C.; Dhillon, H.M.; Butow, P.N.; Sundaresan, P.; Rutherford, C. A Systematic Review of Body Image Measures for People Diagnosed with Head and Neck Cancer (HNC). Support. Care Cancer 2019 , 27 , 3657–3666. [ Google Scholar ] [ CrossRef ]
Richardson, M.; Madzima, T.; Nepocatych, S. Differences in Body Composition Affect Weight Control Practices and Body Image Satisfaction in College Students. Phys. Act. Health 2019 , 3 , 1–10. [ Google Scholar ] [ CrossRef ]
Asimakopoulou, E.; Zavrides, H.; Askitis, T. The Impact of Aesthetic Plastic Surgery on Body Image, Body Satisfaction and Self-Esteem. Acta Chir. Plast. 2019 , 61 , 3–9. [ Google Scholar ]
Lemes, D.C.M.; Câmara, S.G.; Alves, G.G.; Aerts, D. Body Image Satisfaction and Subjective Wellbeing among Ninth-Grade Students Attending State Schools in Canoas, Brazil. Cienc. E Saude Coletiva 2018 , 23 , 4289. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Rodrigues, F.; Monteiro, D.; Flores, P.; Forte, P. On Redefining the Body Image Satisfaction Questionnaire: A Preliminary Test of Multidimensionality. Healthcare 2021 , 9 , 876. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Farias, R.R.; Martins, R.B.; Ulrich, V.; Kanan, J.H.C.; Silva Filho, I.G.D.; Resende, T.D.L. Body Image Satisfaction, Sociodemographic, Functional and Clinical Aspects of Community-Dwelling Older Adults. Dement. E Neuropsychol. 2018 , 12 , 306–313. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Rica, R.L.; Gama, E.F.; Machado, A.F.; Alonso, A.C.; Evangelista, A.L.; Figueira-Junior, A.; Zanetti, M.; Brandão, R.; Miranda, M.L.d.J.; Alves, J.V.; et al. Does Resistance Training Improve Body Image Satisfaction among the Elderly? A Cross-Sectional Study. Clinics 2018 , 73 , e290. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Kavehfarsani, Z.; Kelishadi, R.; Beshlideh, K. Study of the Effect of Family Communication and Function, and Satisfaction with Body Image, on Psychological Well-Being of Obese Girls: The Mediating Role of Self-Esteem and Depression. Child Adolesc. Psychiatry Ment. Health 2020 , 14 , 39. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Owen-Smith, A.A.; Gerth, J.; Sineath, R.C.; Barzilay, J.; Becerra-Culqui, T.A.; Getahun, D.; Giammattei, S.; Hunkeler, E.; Lash, T.L.; Millman, A.; et al. Association Between Gender Confirmation Treatments and Perceived Gender Congruence, Body Image Satisfaction, and Mental Health in a Cohort of Transgender Individuals. J. Sex. Med. 2018 , 15 , 591–600. [ Google Scholar ] [ CrossRef ] [ PubMed ]
van den Brink, F.; Vollmann, M.; Smeets, M.A.M.; Hessen, D.J.; Woertman, L. Relationships between Body Image, Sexual Satisfaction, and Relationship Quality in Romantic Couples. J. Fam. Psychol. 2018 , 32 , 466–474. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Watson, L.B.; Lewis, J.A.; Moody, A.T. A Sociocultural Examination of Body Image among Black Women. Body Image 2019 , 31 , 280–287. [ Google Scholar ] [ CrossRef ]
Burke, N.L.; Schaefer, L.M.; Karvay, Y.G.; Bardone-Cone, A.M.; Frederick, D.A.; Schaumberg, K.; Klump, K.L.; Anderson, D.A.; Thompson, J.K. Does the Tripartite Influence Model of Body Image and Eating Pathology Function Similarly across Racial/Ethnic Groups of White, Black, Latina, and Asian Women? Eat. Behav. 2021 , 42 , 101519. [ Google Scholar ] [ CrossRef ]
Frederick, D.A.; Reynolds, T.A.; Barrera, C.A.; Murray, S.B. Demographic and Sociocultural Predictors of Face Image Satisfaction: The U.S. Body Project I. Body Image 2022 , 41 , 1–16. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Arjona, Á.; Monserrat, M.; Checa, J.C. Use of Social Media, Satisfaction with Body Image, and the Risk of Manifesting Eating Disorders. Soc. Sci. 2024 , 13 , 105. [ Google Scholar ] [ CrossRef ]
Ellis, M.A.; Sterba, K.R.; Brennan, E.A.; Maurer, S.; Hill, E.G.; Day, T.A.; Graboyes, E.M. A Systematic Review of Patient-Reported Outcome Measures Assessing Body Image Disturbance in Patients with Head and Neck Cancer. Otolaryngol. Neck Surg. 2019 , 160 , 941–954. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Guest, E.; Zucchelli, F.; Costa, B.; Bhatia, R.; Halliwell, E.; Harcourt, D. A Systematic Review of Interventions Aiming to Promote Positive Body Image in Children and Adolescents. Body Image 2022 , 42 , 58–74. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Bertuccelli, M.; Cantele, F.; Masiero, S. Body Image and Body Schema in Adolescents with Idiopathic Scoliosis: A Scoping Review. Adolesc. Res. Rev. 2023 , 8 , 97–115. [ Google Scholar ] [ CrossRef ]
Kristensen, J.K.; Nielsen, C.; Haloob, N. Patient Reported Outcome Measures (PROMS) for Body Image in Dermatology: A Systematic Review. Ski. Health Dis. 2022 , 2 , e167. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Prnjak, K.; Jukic, I.; Mitchison, D.; Griffiths, S.; Hay, P. Body Image as a Multidimensional Concept: A Systematic Review of Body Image Facets in Eating Disorders and Muscle Dysmorphia. Body Image 2022 , 42 , 347–360. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Mahon, C.; Seekis, V. Systematic Review of Digital Interventions for Adolescent and Young Adult Women’s Body Image. Front. Glob. Women’s Health 2022 , 3 , 832805. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Wu, Y.; Kemps, E.; Prichard, I. Digging into Digital Buffets: A Systematic Review of EatingRelated Social Media Content and Its Relationship with Body Image and Eating Behaviours. Body Image 2024 , 48 , 101650. [ Google Scholar ] [ CrossRef ]
Sakellariou, C. The Effect of Body Image Perceptions on Life Satisfaction and Emotional Wellbeing of Adolescent Students. Child Indic. Res. 2023 , 16 , 1679–1708. [ Google Scholar ] [ CrossRef ]
He, J.; Sun, S.; Zickgraf, H.F.; Lin, Z.; Fan, X. Meta-Analysis of Gender Differences in Body Appreciation. Body Image 2020 , 33 , 90–100. [ Google Scholar ] [ CrossRef ] [ PubMed ]
He, J.; Sun, S.; Lin, Z.; Fan, X. The Association between Body Appreciation and Body Mass Index among Males and Females: A Meta-Analysis. Body Image 2020 , 34 , 10–26. [ Google Scholar ] [ CrossRef ]
Goldbach, C.; Lindley, L.; Anzani, A.; Galupo, M.P. Resisting Trans Medicalization: Body Satisfaction and Social Contextual Factors as Predictors of Sexual Experiences among Trans Feminine and Nonbinary Individuals. J. Sex Res. 2022 , 60 , 868–879. [ Google Scholar ] [ CrossRef ]
Barene, S.; Ruud-Tronsmoen, A.; Johansen, P.F. Associations between Demographic Characteristics, Lifestyle Factors and School-Related Conditions and Symptoms of Mental Health Problems in Norwegian Upper Secondary School Students. Int. J. Environ. Res. Public Health 2022 , 19 , 9575. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Kayathri, S.A.; Mohan, A.M.I. Nutritional Status and Body Image Satisfaction among Adolescent Girls. Int. J. Res. Rev. 2021 , 8 , 77–82. [ Google Scholar ] [ CrossRef ]
Phoosuwan, N.; Lundberg, P.C. Life Satisfaction, Body Image and Associated Factors among Women with Breast Cancer after Mastectomy. Psychooncology 2023 , 32 , 610–618. [ Google Scholar ] [ CrossRef ]
Imankulova, I.A.; Kudaibergenova, S.K. Women’s Body Image Satisfaction: Connection with Age and SelfEsteem. J. Psychol. Sociol. 2021 , 77 , 28–37. [ Google Scholar ] [ CrossRef ]
Moreno-Domínguez, S.; Raposo, T.; Elipe, P. Body Image and Sexual Satisfaction: Differences among Heterosexual, Bisexual and Lesbian Women. Front. Psychol. 2019 , 10 , 903. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Ruiz-Turrero, J.; Massar, K.; Kwasnicka, D.; Hoor, G.A.T. The Relationship between Compulsive Exercise, Self-Esteem, Body Image and Body Satisfaction in Women: A Cross-Sectional Study. Int. J. Environ. Res. Public Health 2022 , 19 , 1857. [ Google Scholar ] [ CrossRef ]
Thomas, H.N.; Hamm, M.; Borrero, S.; Hess, R.; Thurston, R.C. Body Image, Attractiveness, and Sexual Satisfaction among Midlife Women: A Qualitative Study. J. Women’s Health 2019 , 28 , 100–106. [ Google Scholar ] [ CrossRef ]
Horvath, Z.; Smith, B.H.; Sal, D.; Hevesi, K.; Rowland, D.L. Body Image, Orgasmic Response, and Sexual Relationship Satisfaction: Understanding Relationships and Establishing Typologies Based on Body Image Satisfaction. Sex. Med. 2020 , 8 , 740–751. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Moin, V.; Duvdevany, I.; Mazor, D. Sexual Identity, Body Image and Life Satisfaction among Women with and without Physical Disability. Sex. Disabil. 2009 , 27 , 83–95. [ Google Scholar ] [ CrossRef ]
Cowles, E.; Guest, E.; Slater, A. Imagery versus Captions: The Effect of Body Positive Instagram Content on Young Women’s Mood and Body Image. Body Image 2023 , 44 , 120–130. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Quittkat, H.L.; Hartmann, A.S.; Düsing, R.; Buhlmann, U.; Vocks, S. Body Dissatisfaction, Importance of Appearance, and Body Appreciation in Men and Women Over the Lifespan. Front. Psychiatry 2019 , 10 , 864. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Flaherty, M. Influence of Yoga on Body Image Satisfaction in Men. Percept. Mot. Ski. 2014 , 119 , 203–214. [ Google Scholar ] [ CrossRef ]
Tiggemann, M.; Anderberg, I. Muscles and Bare Chests on Instagram: The Effect of Influencers’ Fashion and Fitspiration Images on Men’s Body Image. Body Image 2020 , 35 , 237–244. [ Google Scholar ] [ CrossRef ]
Sommantico, M.; Gioia, F.; Boursier, V.; Iorio, I.; Parrello, S. Body Image, Depression, and Self-Perceived Pornography Addiction in Italian Gay and Bisexual Men: The Mediating Role of Relationship Satisfaction. Mediterr. J. Clin. Psychol. 2021 , 9 . Available online: https://www.researchgate.net/publication/351194364_Body_Image_Depression_and_Self-Perceived_Pornography_Addiction_in_Italian_Gay_and_Bisexual_Men_The_Mediating_Role_of_Relationship_Satisfaction (accessed on 1 May 2024).
Barron, A.M.; Krumrei-Mancuso, E.J.; Harriger, J.A. The Effects of Fitspiration and Self-Compassion Instagram Posts on Body Image and Self-Compassion in Men and Women. Body Image 2021 , 37 , 14–27. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Alleva, J.M.; Paraskeva, N.; Craddock, N.; Stuijfzand, B.G.; Diedrichs, P.C. A Longitudinal Study Investigating Positive Body Image, Eating Disorder Symptoms, and Other Related Factors among a Community Sample of Men in the UK. Body Image 2022 , 41 , 384–395. [ Google Scholar ] [ CrossRef ]
Daniel, S.; Bridges, S.K. The Relationships among Body Image, Masculinity, and Sexual Satisfaction in Men. Psychol. Men Masculinities 2013 , 14 , 345–351. [ Google Scholar ] [ CrossRef ]
Barnett, M.D.; Moore, J.M.; Edzards, S.M. Body Image Satisfaction and Loneliness among Young Adult and Older Adult Age Cohorts. Arch. Gerontol. Geriatr. 2020 , 89 , 104088. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Murnen, S.K.; Karazsia, B.T. A Review of Research on Men’s Body Image and Drive for Muscularity. In The Psychology of Men and Masculinities ; American Psychological Association: Washington, DC, USA, 2017. [ Google Scholar ] [ CrossRef ]
Parent, M.C. Clinical Considerations in Etiology, Assessment, and Treatment of Men’s MuscularityFocused Body Image Disturbance. Psychol. Men. Masc. 2013 , 14 , 88–100. [ Google Scholar ] [ CrossRef ]
Stojcic, I.; Dong, X.; Ren, X. Body Image and Sociocultural Predictors of Body Image Dissatisfaction in Croatian and Chinese Women. Front. Psychol. 2020 , 11 , 731. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Azevedo, A.; Azevedo, Â.S. Implications of Socio-Cultural Pressure for a Thin Body Image on Avoidance of Social Interaction and on Corrective, Compensatory or Compulsive Shopping Behaviour. Int. J. Environ. Res. Public Health 2023 , 20 , 3567. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Mills, J.S.; Minister, C.; Samson, L. Enriching Sociocultural Perspectives on the Effects of Idealized Body Norms: Integrating Shame, Positive Body Image, and Self-Compassion. Front. Psychol. 2022 , 13 , 983534. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Mohamed, B.A.A.; Idrees, M.H.D. Body Image Dissatisfaction and Its Relation to Body Mass Index among Female Medical Students in Sudan: Across-Sectional Study 2020–2021. BMC Women’s Health 2023 , 23 , 593. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Guo, S.; Izydorczyk, B.; Lipowska, M.; Kamionka, A.; Lizińczyk, S.; Sajewicz-Radtke, U.; Radtke, B.M.; Liu, T.; Lipowski, M. Socio-Cultural Attitudes toward the Body as a Predictor of Motivation for Physical Activity in Young People Brought up in Asian and European Culture—Chinese-Polish Comparison. BMC Sports Sci. Med. Rehabil. 2023 , 15 , 52. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Wang, G.; Liu, X.; Lei, J. Association between Body-Image Satisfaction and Anxiety, Depressive Symptoms among Women with PCOS: The Mediating Role of Emotion Regulation Strategies. J. Psychol. 2023 , 158 , 200–214. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Burnell, K.; Kurup, A.R.; Underwood, M.K. Snapchat Lenses and Body Image Concerns. New Media Soc. 2021 , 24 , 2088–2106. [ Google Scholar ] [ CrossRef ]
Kim, H.M. What Do Others’ Reactions to Body Posting on Instagram Tell Us? The Effects of Social Media Comments on Viewers’ Body Image Perception. New Media Soc. 2021 , 23 , 3448–3465. [ Google Scholar ] [ CrossRef ]
Godoy-Izquierdo, D.; González-Hernández, J.; Rodríguez-Tadeo, A.; Lara, R.; Ogallar, A.; Navarrón, E.; Ramírez, M.J.; López-Mora, C.; Arbinaga, F. Body Satisfaction, Weight Stigma, Positivity, and Happiness among Spanish Adults with Overweight and Obesity. Int. J. Environ. Res. Public Health 2020 , 17 , 4186. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Alessi, N.; Coleman, H.; Rayner, G. Body Image Dissatisfaction: A Novel Predictor of Poor Quality of Life in Epilepsy. Epilepsy Behav. 2023 , 141 , 109149. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Fornaini, E.; Matera, C.; Nerini, A.; Policardo, G.R.; Di Gesto, C. The Power of Words: Appearance Comments from One’s Partner Can Affect Men’s Body Image and Women’s Couple Relationship. Int. J. Environ. Res. Public Health 2021 , 18 , 9319. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Jung, E.H.; Jun, M.K. Factors Affecting Body Image Distortion in Adolescents. Children 2022 , 9 , 1944. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Hyun, M.Y.; Jung, Y.E.; Kim, M.D.; Kwak, Y.S.; Hong, S.C.; Bahk, W.M.; Yoon, B.H.; Yoon, H.W.; Yoo, B. Factors Associated with Body Image Distortion in Korean Adolescents. Neuropsychiatr. Dis. Treat. 2014 , 10 , 797–802. [ Google Scholar ] [ CrossRef ]
Dalhoff, A.W.; Romero Frausto, H.; Romer, G.; Wessing, I. Perceptive Body Image Distortion in Adolescent Anorexia Nervosa: Changes After Treatment. Front. Psychiatry 2019 , 10 , 748. [ Google Scholar ] [ CrossRef ]
Tremblay, S.C.; Essafi Tremblay, S.; Poirier, P. From Filters to Fillers: An Active Inference Approach to Body Image Distortion in the Selfie Era. AI Soc. 2021 , 36 , 33–48. [ Google Scholar ] [ CrossRef ]
Provenzano, L.; Porciello, G.; Ciccarone, S.; Lenggenhager, B.; Tieri, G.; Marucci, M.; Dazzi, F.; Loriedo, C.; Bufalari, I. Characterizing Body Image Distortion and Bodily Self-Plasticity in Anorexia Nervosa via Visuo-Tactile Stimulation in Virtual Reality. J. Clin. Med. 2019 , 9 , 98. [ Google Scholar ] [ CrossRef ]
Shang, Y.; Xie, H.D.; Yang, S.Y. The Relationship between Physical Exercise and Subjective Well-Being in College Students: The Mediating Effect of Body Image and Self-Esteem. Front. Psychol. 2021 , 12 , 658935. [ Google Scholar ] [ CrossRef ]
Cohen, R.; Irwin, L.; Newton-John, T.; Slater, A. #bodypositivity: A Content Analysis of Body Positive Accounts on Instagram. Body Image 2019 , 29 , 47–57. [ Google Scholar ] [ CrossRef ]
Marengo, D.; Longobardi, C.; Fabris, M.A.; Settanni, M. Highly-Visual Social Media and Internalizing Symptoms in Adolescence: The Mediating Role of Body Image Concerns. Comput. Hum. Behav. 2018 , 82 , 63–69. [ Google Scholar ] [ CrossRef ]
Kleemans, M.; Daalmans, S.; Carbaat, I.; Anschütz, D. Picture Perfect: The Direct Effect of Manipulated Instagram Photos on Body Image in Adolescent Girls. Media Psychol. 2016 , 21 , 93–110. [ Google Scholar ] [ CrossRef ]
Irvine, K.R.; McCarty, K.; McKenzie, K.J.; Pollet, T.V.; Cornelissen, K.K.; Tovée, M.J.; Cornelissen, P.L. Distorted Body Image Influences Body Schema in Individuals with Negative Bodily Attitudes. Neuropsychologia 2019 , 122 , 38–50. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Cohen, R.; Fardouly, J.; Newton-John, T.; Slater, A. #BoPo on Instagram: An Experimental Investigation of the Effects of Viewing Body Positive Content on Young Women’s Mood and Body Image. New Media Soc. 2019 , 21 , 1546–1564. [ Google Scholar ] [ CrossRef ]
Swami, V.; Barron, D. Translation and Validation of Body Image Instruments: Challenges, Good Practice Guidelines, and Reporting Recommendations for Test Adaptation. Body Image 2018 , 31 , 204–220. [ Google Scholar ] [ CrossRef ]
Fardouly, J.; Willburger, B.K.; Vartanian, L.R. Instagram Use and Young Women’s Body Image Concerns and Self-Objectification: Testing Mediational Pathways. New Media Soc. 2017 , 20 , 1380–1395. [ Google Scholar ] [ CrossRef ]
Shomali, A.Y. Book Review: Body Image: Understanding Body Dissatisfaction in Men, Women, and Children, 3rd Edition by Sarah Grogan. Fem. Psychol. 2021 , 31 , 605–608. [ Google Scholar ] [ CrossRef ]
Grogan, S. Body Image: Understanding Body Dissatisfaction in Men, Women and Children , 4th ed.; Taylor & Francis: London, UK, 2021. [ Google Scholar ] [ CrossRef ]
Aimé, A.; Fuller-Tyszkiewicz, M.; Dion, J.; Markey, C.H.; Strodl, E.; McCabe, M.; Mellor, D.; Granero Gallegos, A.; Pietrabissa, G.; Alcaraz-Ibánez, M.; et al. Assessing Positive Body Image, Body Satisfaction, Weight Bias, and Appearance Comparison in Emerging Adults: A Cross-Validation Study across Eight Countries. Body Image 2020 , 35 , 320–332. [ Google Scholar ] [ CrossRef ]
Rodgers, R.F.; Wertheim, E.H.; Paxton, S.J.; Tylka, T.L.; Harriger, J.A. #Bopo: Enhancing Body Image through Body Positive Social Media Evidence to Date and Research Directions. Body Image 2022 , 41 , 367–374. [ Google Scholar ] [ CrossRef ]
Frederick, D.A.; Garcia, J.R.; Gesselman, A.N.; Mark, K.P.; Hatfield, E.; Bohrnstedt, G. The Happy American Body 2.0: Predictors of Affective Body Satisfaction in Two U.S. National Internet Panel Surveys. Body Image 2019 , 32 , 70–84. [ Google Scholar ] [ CrossRef ]
O’Dea, J.A.; Abraham, S. Improving the Body Image, Eating Attitudes, and Behaviors of Young Male and Female Adolescents: A New Educational Approach That Focuses on Self Esteem. Int. J. Eat. Disord. 2000 , 28 , 43–57. [ Google Scholar ] [ CrossRef ]
Jarman, H.K.; Marques, M.D.; McLean, S.A.; Slater, A.; Paxton, S.J. Social Media, Body Satisfaction and Well-Being among Adolescents: A Mediation Model of Appearance-Ideal Internalization and Comparison. Body Image 2020 , 36 , 139–148. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Hartman-Munick, S.M.; Gordon, A.R.; Guss, C. Adolescent Body Image: Influencing Factors and the Clinician’s Role. Curr. Opin. Pediatr. 2020 , 32 , 455–460. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Mahon, C.; Hevey, D. Processing Body Image on Social Media: Gender Differences in Adolescent Boys’ and Girls’ Agency and Active Coping. Front. Psychol. 2021 , 12 , 626763. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Gonzales, M.; Blashill, A.J. Ethnic/Racial and Gender Differences in Body Image Disorders among a Diverse Sample of Sexual Minority U.S. Adults. Body Image 2021 , 36 , 64–73. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Lowy, A.S.; Rodgers, R.F.; Franko, D.L.; Pluhar, E.; Webb, J.B. Body Image and Internalization of Appearance Ideals in Black Women: An Update and Call for Culturally-Sensitive Research. Body Image 2021 , 39 , 313–327. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Hardie, A.; Oshiro, K.F.; Dixon, M.A. Understanding Body Image Perceptions of Former Female Athletes: A Qualitative Analysis. Body Image 2022 , 43 , 393–407. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Gallinat, C.; Stürmlinger, L.L.; Schaber, S.; Bauer, S. Pathological Skin Picking: Phenomenology and Associations with Emotions, Self-Esteem, Body Image, and Subjective Physical Well-Being. Front. Psychiatry 2021 , 12 , 732717. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Fernández-Bustos, J.G.; Infantes-Paniagua, Á.; Cuevas, R.; Contreras, O.R. Effect of Physical Activity on Self-Concept: Theoretical Model on the Mediation of Body Image and Physical Self-Concept in Adolescents. Front. Psychol. 2019 , 10 , 1537. [ Google Scholar ] [ CrossRef ]
Konara Mudiyanselage, S.P.; Wu, Y.L.; Kukreti, S.; Chen, C.C.; Lin, C.N.; Tsai, Y.T.; Ku, H.C.; Fang, S.Y.; Der Wang, J.; Ko, N.Y. Dynamic Changes in Quality of Life, Psychological Status, and Body Image in Women Who Underwent a Mastectomy as Compared with Breast Reconstruction: An 8Year Follow Up. Breast Cancer 2023 , 30 , 226–240. [ Google Scholar ] [ CrossRef ]
Eddolls, W.T.B.; McNarry, M.A.; Lester, L.; Winn, C.O.N.; Stratton, G.; Mackintosh, K.A. The Association between Physical Activity, Fitness and Body Mass Index on Mental Well-Being and Quality of Life in Adolescents. Qual. Life Res. 2018 , 27 , 2313–2320. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Swami, V.; Weis, L.; Barron, D.; Furnham, A. Positive Body Image Is Positively Associated with Hedonic (Emotional) and Eudaimonic (Psychological and Social) Well-Being in British Adults. J. Soc. Psychol. 2018 , 158 , 541–552. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Sherlock, M.; Wagstaff, D.L. Exploring the Relationship Between Frequency of Instagram Use, Exposure to Idealized Images, and Psychological Well-Being in Women. Psychol. Pop. Media Cult. 2019 , 8 , 482–490. [ Google Scholar ] [ CrossRef ]
Tylka, T.L. Overview of the Field of Positive Body Image. In Body Positive: Understanding and Improving Body Image in Science and Practice ; Cambridge University Press: Cambridge, UK, 2018. [ Google Scholar ] [ CrossRef ]
Longhurst, P. Incorporating Positive Body Image in Therapeutic Practice: An Overview of Construct Definitions, Concepts and Theoretical Foundations. Couns. Psychother. Res. 2022 , 22 , 257–266. [ Google Scholar ] [ CrossRef ]
Gillen, M.M.; Markey, C.H.; Daniels, E.A. Introduction: Becoming Positive Our Growing Understanding of Positive Body Image. In Body Positive: Understanding and Improving Body Image in Science and Practice ; Cambridge University Press: Cambridge, UK, 2018. [ Google Scholar ] [ CrossRef ]
Wilksch, S. Media Literacy Interventions to Facilitate Positive Body Image and Embodiment. In Handbook of Positive Body Image and Embodiment ; Oxford University Press: New York, NY, USA, 2019. [ Google Scholar ] [ CrossRef ]
Mackson, S.B.; Brochu, P.M.; Schneider, B.A. Instagram: Friend or Foe? The Application’s Association with Psychological WellBeing. New Media Soc. 2019 , 21 , 2160–2182. [ Google Scholar ] [ CrossRef ]
Kochkodan, J.; Telem, D.A.; Ghaferi, A.A. Physiologic and Psychological Gender Differences in Bariatric Surgery. Surg. Endosc. 2018 , 32 , 1382–1388. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Sattin, D.; Parma, C.; Lunetta, C.; Zulueta, A.; Lanzone, J.; Giani, L.; Vassallo, M.; Picozzi, M.; Parati, E.A. An Overview of the Body Schema and Body Image: Theoretical Models, Methodological Settings and Pitfalls for Rehabilitation of Persons with Neurological Disorders. Brain Sci. 2023 , 13 , 1410. [ Google Scholar ] [ CrossRef ]
Springmann, M.L.; Svaldi, J.; Kiegelmann, M. Theoretical and Methodological Considerations for Research on Eating Disorders and Gender. Front. Psychol. 2020 , 11 , 586196. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Misterska, E.; Górski, F.; Tomaszewski, M.; Buń, P.; Gapsa, J.; Słysz, A.; Głowacki, M. “Scoliosis 3D”—A Virtual-Reality-Based Methodology Aiming to Examine AIS Females’ Body Image. Appl. Sci. 2023 , 13 , 2374. [ Google Scholar ] [ CrossRef ]
Silva, D.; Ferriani, L.; Viana, M.C. Depression, Anthropometric Parameters, and Body Image in Adults: A Systematic Review. Rev. Da Assoc. Medica Bras. 2019 , 65 , 731–738. [ Google Scholar ] [ CrossRef ]
Lovell, H.; Banfield, J. Implicit Influence on Body Image: Methodological Innovation for Research into Embodied Experience. Qual. Res. 2022 , 22 , 40–55. [ Google Scholar ] [ CrossRef ]
Guest, E.; Costa, B.; Williamson, H.; Meyrick, J.; Halliwell, E.; Harcourt, D. The Effectiveness of Interventions Aiming to Promote Positive Body Image in Adults: A Systematic Review. Body Image 2019 , 30 , 10–25. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Fuller-Tyszkiewicz, M. Body Image States in Everyday Life: Evidence from Ecological Momentary Assessment Methodology. Body Image 2019 , 31 , 245–272. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Rahimi-Ardabili, H.; Reynolds, R.; Vartanian, L.R.; McLeod, L.V.D.; Zwar, N. A Systematic Review of the Efficacy of Interventions That Aim to Increase Self-Compassion on Nutrition Habits, Eating Behaviours, Body Weight and Body Image. Mindfulness 2018 , 9 , 388–400. [ Google Scholar ] [ CrossRef ]
Sabiston, C.M.; Pila, E.; Vani, M.; Thogersen-Ntoumani, C. Body Image, Physical Activity, and Sport: A Scoping Review. Psychol. Sport Exerc. 2019 , 42 , 48–57. [ Google Scholar ] [ CrossRef ]
Konijn, E.A.; Veldhuis, J.; Plaisier, X.S.; Goodyear, V.A.; Armour, K.M.; Wood, H.; Dijkstra, P.; Barelds, D.P.H.; van Brummen-Girigori, O.; Sharp, D.C.; et al. The Relationship between Self-Esteem, Online Peer Influence, Social Networking Site Usage and Body Satisfaction for Teen Girls in the United States. Body Image 2020 , 33 , 4. [ Google Scholar ]
Mills, J.S.; Musto, S.; Williams, L.; Tiggemann, M. “Selfie” Harm: Effects on Mood and Body Image in Young Women. Body Image 2018 , 27 , 86–92. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Seekis, V.; Bradley, G.L.; Duffy, A.L. Does a Facebook-Enhanced Mindful Self-Compassion Intervention Improve Body Image? An Evaluation Study. Body Image 2020 , 34 , 259–269. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Willemse, H.; Geenen, R.; Egberts, M.R.; Engelhard, I.M.; Van Loey, N.E. Perceived Stigmatization and Fear of Negative Evaluation: Two Distinct Pathways to Body Image Dissatisfaction and Self-Esteem in Burn Survivors. Psychol. Health 2023 , 38 , 445–458. [ Google Scholar ] [ CrossRef ]
Saiphoo, A.N.; Vahedi, Z. A Meta-Analytic Review of the Relationship between Social Media Use and Body Image Disturbance. Comput. Hum. Behav. 2019 , 101 , 259–275. [ Google Scholar ] [ CrossRef ]
Mingoia, J.; Hutchinson, A.D.; Wilson, C.; Gleaves, D.H. The Relationship between Social Networking Site Use and the Internalization of a Thin Ideal in Females: A Meta-Analytic Review. Front. Psychol. 2017 , 8 , 1351. [ Google Scholar ] [ CrossRef ] [ PubMed ]

Click here to enlarge figure

Positive Psychological Outcomes	Negative Psychological Outcomes
Lower rates of depression and anxiety Enhanced self-esteem Improved quality of life Healthier sexual functioning	Eating disorders Depression and low self-esteem Unhealthy behaviors Social avoidance

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

Merino, M.; Tornero-Aguilera, J.F.; Rubio-Zarapuz, A.; Villanueva-Tobaldo, C.V.; Martín-Rodríguez, A.; Clemente-Suárez, V.J. Body Perceptions and Psychological Well-Being: A Review of the Impact of Social Media and Physical Measurements on Self-Esteem and Mental Health with a Focus on Body Image Satisfaction and Its Relationship with Cultural and Gender Factors. Healthcare 2024 , 12 , 1396. https://doi.org/10.3390/healthcare12141396

Merino M, Tornero-Aguilera JF, Rubio-Zarapuz A, Villanueva-Tobaldo CV, Martín-Rodríguez A, Clemente-Suárez VJ. Body Perceptions and Psychological Well-Being: A Review of the Impact of Social Media and Physical Measurements on Self-Esteem and Mental Health with a Focus on Body Image Satisfaction and Its Relationship with Cultural and Gender Factors. Healthcare . 2024; 12(14):1396. https://doi.org/10.3390/healthcare12141396

Merino, Mariana, José Francisco Tornero-Aguilera, Alejandro Rubio-Zarapuz, Carlota Valeria Villanueva-Tobaldo, Alexandra Martín-Rodríguez, and Vicente Javier Clemente-Suárez. 2024. "Body Perceptions and Psychological Well-Being: A Review of the Impact of Social Media and Physical Measurements on Self-Esteem and Mental Health with a Focus on Body Image Satisfaction and Its Relationship with Cultural and Gender Factors" Healthcare 12, no. 14: 1396. https://doi.org/10.3390/healthcare12141396

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

View all journals
Explore content
About the journal
Publish with us
Sign up for alerts
14 February 2023

How social media affects teen mental health: a missing link

Amy Orben 0 &
Sarah-Jayne Blakemore 1

Amy Orben is a programme leader track scientist at the MRC Cognition and Brain Sciences Unit, University of Cambridge, UK.

You can also search for this author in PubMed Google Scholar

Sarah-Jayne Blakemore is professor of psychology and cognitive neuroscience at the Department of Psychology, University of Cambridge, UK.

Depression, anxiety and suicidality have all sharply increased in adolescents over the past decade 1 . So, too, has the amount of time that young people spend online (see ‘Troubling trends’). Partly because of fears that there’s a link between these trends, governments around the world are under pressure to do more to regulate technology companies.

Access options

Access Nature and 54 other Nature Portfolio journals

Get Nature+, our best-value online-access subscription

24,99 € / 30 days

cancel any time

Subscribe to this journal

Receive 51 print issues and online access

185,98 € per year

only 3,65 € per issue

Rent or buy this article

Prices vary by article type

Prices may be subject to local taxes which are calculated during checkout

Nature 614 , 410-412 (2023)

doi: https://doi.org/10.1038/d41586-023-00402-9

Office of the Surgeon General. Protecting Youth Mental Heath: The US Surgeon General’s Advisory (US Department of Health and Human Services, 2021).

Google Scholar

Odgers, C. L. & Jensen, M. R. J. Child Psychol. Psychiatry 61 , 336–348 (2020).

Article PubMed Google Scholar

Valkenburg, P. M., Meier, A. & Beyens, I. Curr. Opin. Psychol. 44 , 58–68 (2022).

Ellis, D. A. Comput. Human Behav. 97 , 60–66 (2019).

Article Google Scholar

Valkenburg, P. M. & Peter, J. J. Commun. 63 , 221–243 (2013).

Orben, A., Przybylski, A. K., Blakemore, S.-J. & Kievit, R. A. Nature Commun. 13 , 1649 (2022).

Pfeifer, J. H. & Allen, N. B. Biol. Psychiatry 89 , 99–108 (2021).

Beyens, I., Pouwels, J. L., van Driel, I. I., Keijsers, L. & Valkenburg, P. M. Sci. Rep. 10 , 10763 (2020).

Nesi, J., Choukas-Bradley, S. & Prinstein, M. J. Clin. Child Fam. Psychol. Rev. 21 , 267–294 (2018).

Weinstein, E. & James, C. Behind Their Screens: What Teens are Facing (and Adults Are Missing) (Blackstone, 2022).

Crone, E. A. & Konijn, E. A. Nature Commun. 9 , 588 (2018).

Blakemore, S.-J. & Mills, K. L. Annu. Rev. Psychol. 65 , 187–207 (2014).

Rodman, A. M., Powers, K. E. & Somerville, L. H. Proc. Natl Acad. Sci. USA 114 , 13158–13163 (2017).

Peters, S. et al. Dev. Cogn. Neurosci. 48 , 100921 (2021).

Sebastian, C., Viding, E., Williams, K. D. & Blakemore, S.-J. Brain Cogn. 72 , 134–145 (2010).

Granic, I., Morita, H. & Scholten, H. Psychol. Inquiry 31 , 195–223 (2020).

Maza, M. T. et al. JAMA Pediatr. 177 , 160–167 (2023).

Burnett Heyes, S. et al. Child Dev. 86 , 1489–1506 (2015).

Will, G.-J., Rutledge, R. B., Moutoussis, M. & Dolan, R. J. eLife 6 , e28098 (2017).

Solmi, M. et al. Mol. Psychiatry 27 , 281–295 (2022).

Download references

Reprints and permissions

Competing Interests

A.O. is an unpaid member of governmental and non-governmental organizations (including the UK Department for Culture, Media and Sport, and The British Academy). She has also provided unpaid and paid talks and consultancy work to organizations that will not gain or lose financially from this publication. S.-J.B. currently receives funding from Wellcome, the MRC, the Jacobs Foundation, the Wellspring Foundation and the University of Cambridge. In the past five years, S.-J.B. engaged in a paid consultancy with Cognita International Schools Group and has provided paid expert witness work for UK charities, legal organisations in the UK and USA and the UK government. S.-J.B. is the author of two books related to the brain, education and learning, for which she received an advance and royalties. S.-J.B. gives talks in schools, in the state and private sector, as well as at education conferences and for education organizations, and other public, private and third sector organizations (some talks are remunerated). S.-J.B. is a member of the Rethinking Assessment group, the Steering Committee of the Cambridge Centre of Science Policy, the Technical Advisory Group for the UK Government Department of Education 'Education and Outcomes Panel-C Study' and the Singapore Government National Research Foundation Scientific Advisory Board. She was a member of the Times Education Commission in 2021-22.

Psychiatric disorders

The ‘PhD influencers’ logging lab life on TikTok and Instagram

News Feature 17 JUL 24

Microbiologist wins case against university over harassment during COVID

News 12 JUL 24

Spy on millions of sleeping butterflies and more — June’s best science images

News 02 JUL 24

Freezer holding world’s biggest ancient-ice archive to get ‘future-proofed’

News 16 JUL 24

Your reagent is past its use-by date. Should you bin it?

Technology Feature 15 JUL 24

Ex-Meta scientists debut gigantic AI protein design model

News 08 JUL 24

To explain biological sex, look to evolution

Correspondence 09 JUL 24

Neuroscientists must not be afraid to study religion

Comment 02 JUL 24

Megastudy shows that reminders boost vaccination but adding free rides does not

Article 26 JUN 24

Quick links

Explore articles by subject
Guide to authors
Editorial policies

Every print subscription comes with full digital access

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

A teen scrolls through social media alone on her phone.

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

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.”

The world has water problems. This book has solutions

Art of people walking around beside rulers

Does social status shape height?

Skiers gliding down an artificial snow slope

In ‘Warming Up,’ the sports world’s newest opponent is climate change

A black-and-white woodcut engraving depicting Phoenician sea traders, who thrived after the Bronze Age

‘After 1177 B.C.’ describes how societies fared when the Bronze Age ended

‘Cull of the Wild’ questions sacrificing wildlife in the name of conservation

Art of a police officer questioning a woman in a red dress. In the back, there are two crime scene technicians analyzing evidence. A splash of blood appears behind the woman.

Scientists are fixing flawed forensics that can lead to wrongful convictions

Close up of a woman holding a smartphone

Privacy remains an issue with several women’s health apps

A screenshot of a fake website, showing a young girl hugging an older woman. The tagline says "Be the favorite grandkid forever"

Should we use AI to resurrect digital ‘ghosts’ of the dead?

Subscribers, enter your e-mail address for full access to the Science News archives and digital editions.

Not a subscriber? Become one now .

Is social media use bad for young people’s mental health? It’s complicated.

July 17, 2023 – On May 23, U.S. Surgeon General Vivek Murthy issued an advisory warning about the potential dangers of social media for the mental health of children and teens . Laura Marciano , postdoctoral research fellow at the Lee Kum Sheung Center for Health and Happiness and in the Department of Social and Behavioral Sciences at Harvard T.H. Chan School of Public Health, says that social media use might be detrimental for young people’s well-being but can also have positive effects.

Q: What are your thoughts on the Surgeon General’s advisory?

A: The advisory highlighted compelling evidence published during the last decade on the potential harmful impact of social media on children and adolescents. Some of what young people experience online—including cyberbullying, online harassment and abuse, predatory behaviors, and exposure to violent, sexual, and hate-based content—can undoubtedly be negative. But social media experiences are not limited to these types of content.

Much of the scientific literature on the effects of social media use has focused on negative outcomes. But the link between social media use and young people’s mental health is complicated. Literature reviews show that study results are mixed: Associations between social media use and well-being can be positive, negative, and even largely null when advanced data analyses are carried out, and the size of the effects is small. And positive and negative effects can co-exist in the same individual. We are still discovering how to compare the effect size of social media use with the effects of other behavioral habits—such as physical activity, sleep, food consumption, life events, and time spent in offline social connections—and psychological processes happening offline. We are also still studying how social media use may be linked positively with well-being.

It’s important to note that many of the existing studies relied on data from people living in so-called WEIRD countries (Western, Educated, Industrialized, Rich and Democratic), thus leaving out the majority of the worldwide population living in the Global South. In addition, we know that populations like minorities, people experiencing health disparities and chronic health conditions , and international students can find social media extremely helpful for creating and maintaining social communities to which they feel they belong.

A number of large cohort studies have measured social media use according to time spent on various platforms. But it’s important to consider not just time spent, but whether that time is displacing time for other activities promoting well-being, like physical activity and sleep. Finally, the effects of social media use are idiosyncratic, meaning that each child and adolescent might be affected differently, which makes it difficult to generalize about the effects.

Literature reviews on interventions limiting social media use present a more balanced picture. For example, one comprehensive review on the effects of digital detox—refraining from using devices such as smartphones—wasn’t able to draw any clear conclusions about whether such detox could be effective at promoting a healthy way of life in the digital era, because the findings were mixed and contradictory.

Q: What has your research found regarding the potential risks and benefits of social media use among young people?

A: In my work with Prof. Vish Viswanath , we have summarized all the papers on how social media use is related to positive well-being measures, to balance the ongoing bias of the literature on negative outcomes such as depression and anxiety. We found both positive and negative correlations between different social media activities and well-being. The most consistent results show a link between social media activities and hedonic well-being (positive emotions) and social well-being. We also found that social comparison—such as comparing how many likes you have with how many someone else has, or comparing yourself to digitally enhanced images online—drives the negative correlation with well-being.

Meanwhile, I am working on the “ HappyB ” project, a longitudinal project based in Switzerland, through which I have collected data from more than 1,500 adolescents on their smartphone and social media use and well-being. In a recent study using that cohort, we looked at how social media use affects flourishing , a construct that encompasses happiness, meaning and purpose, physical and mental health, character, close social relationships, and financial stability. We found that certain positive social media experiences are associated with flourishing. In particular, having someone to talk to online when feeling lonely was the item most related to well-being. That is not surprising, considering that happiness is related to the quality of social connections.

Our data suggest that homing in on the psychological processes triggered during social media use is key to determining links with well-being. For example, we should consider if a young person feels appreciated and part of a group in a particular online conversation. Such information can help us shed light on the dynamics that shape young people’s well-being through digital activities.

In our research, we work to account for the fact that social media time is a sedentary behavior. We need to consider that any behavior that risks diminishing the time spent on physical activity and sleep—crucial components of brain development and well-being—might be detrimental. Interestingly, some studies suggest that spending a short amount of time using social media, around 1-2 hours, is beneficial, but—as with any extreme behavior—it can cause harm if the time spent online dominates a child’s or adolescent’s day.

It’s also important to consider how long the effects of social media last. Social media use may have small ephemeral effects that can accumulate over time. A step for future research is to disentangle short- versus long-term effects and how long each last. In addition, we should better understand how digital media usage affects the adolescent brain. Colleagues and I have summarized existing neuroscientific studies on the topic, but more multidisciplinary research is needed.

Q: What are some steps you’d recommend to make social media use safer for kids?

A: I’ll use a metaphor to answer this question. Is a car safe for someone that is not able to drive? To drive safely, we need to learn how to accelerate, recognize road signs, make safe decisions according to certain rules, and wear safety belts. Similarly, to use social media safely, I think we as a society—including schools, educators, and health providers—should provide children and families with clear, science-based information on both its positive and negative potential impacts.

We can also ask social media companies to pay more attention to how some features—such as the number of “likes”—can modulate adolescent brain activity, and to think about ways to limit negative effects. We might even ask adolescents to advise designers on how to create social media platforms specifically for them. It would be extremely valuable to ask them which features would be best for them and which ones they would like to avoid. I think that co-designing apps and conducting research with the young people who use the platforms is a crucial step.

For parents, my suggestion is to communicate with your children and promote a climate of safety and empathy when it comes to social media use. Try to use these platforms along with them, for example by explaining how a platform works and commenting on the content. Also, I would encourage schools and parents to collaborate on sharing information with young people about social media and well-being.

Also, to offset children’s sedentary time spent on social media, parents could offer them alternative extracurricular activities to provide some balance. But it’s important to remember that social well-being depends on the quality of social connections, and that social media can help to promote this kind of well-being. So I’d recommend trying to keep what is good—according to my research that would include instant messaging, the chance to talk to people when someone is feeling lonely, and funny or inspirational content—and minimizing what’s negative, such as too much sedentary time or too much time spent on social comparison.

– Karen Feldscher

Dressed in a yellow shirt and blue jeans, and sitting on outdoor cement steps, a teenage girl stares at her cellphone.

Mounting research documents the harmful effects of social media use on mental health, including body image and development of eating disorders

Assistant Professor of Psychiatry, University of Colorado Anschutz Medical Campus

Disclosure statement

Emily Hemendinger does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

University of Colorado Anschutz Medical Campus provides funding as a member of The Conversation US.

View all partners

Media influences and conventional beauty standards have long plagued society.

This issue took on new urgency in May 2023 when the U.S. surgeon general issued a major public advisory over the links between social media and youth mental health .

Research shows that images of beauty as depicted in movies, television and magazines can lead to mental illness , issues with disordered eating and body image dissatisfaction .

These trends have been documented in women and men , in the LGBTQ+ community and in people of different racial and ethnic backgrounds.

Experts have long suspected that social media may be playing a role in the growing mental health crisis in young people . However, the surgeon general’s warning is one of the first public warnings supported by robust research .

Social media can be harmful

Body dissatisfaction among children and adolescents is commonplace and has been linked to decreased quality of life, worsened mood and unhealthy eating habits.

As an eating disorder and anxiety specialist , I regularly work with clients who experience eating disorder symptoms, self-esteem issues and anxiety related to social media .

I also have firsthand experience with this topic : I am 15 years post-recovery from an eating disorder, and I grew up when people were beginning to widely use social media. In my view, the impact of social media on diet and exercise patterns needs to be further researched to inform future policy directions, school programming and therapeutic treatment.

The mental health of adolescents and teens has been declining for the past decade , and the COVID-19 pandemic contributed to worsening youth mental health and brought it into the spotlight. As the mental health crisis surges, researchers have been taking a close look at the role of social media in these increasing mental health concerns.

The pros and cons of social media

About 95% of children and adolescents in the U.S. between the ages of 10 and 17 are using social media almost constantly .

Research has shown that social media can be beneficial for finding community support . However, studies have also shown that the use of social media contributes to social comparisons, unrealistic expectations and negative mental health effects .

In addition, those who have preexisting mental health conditions tend to spend more time on social media. People in that category are more likely to self-objectify and internalize the thin body ideal . Women and people with preexisting body image concerns are more likely to feel worse about their bodies and themselves after they spend time on social media.

A breeding ground for eating disorders

A recent review found that, as with mass media, the use of social media is a risk factor for the development of an eating disorder , body image dissatisfaction and disordered eating. In this review, social media use was shown to contribute to negative self-esteem, social comparisons, decreased emotional regulation and idealized self-presentation that negatively influenced body image.

Another study, called the Dove Self-Esteem Project , published in April 2023, found that 9 in 10 children and adolescents ages 10 to 17 are exposed to toxic beauty content on social media and 1 in 2 say that this has an impact on their mental health.

Eating disorders are complex mental illnesses that develop because of biological, social and psychological factors. Eating disorder hospitalizations and the need for treatment have dramatically increased during the pandemic .

Some reasons for this include isolation, food scarcity, boredom and social media content related to weight gain, such as the “ quarantine15 .” That was a reference to the weight gain some people were experiencing at the beginning of the pandemic, similar to the “freshman 15” belief that one will gain 15 pounds in the first year of college. Many teens whose routines were disrupted by the pandemic turned to eating disorder behaviors for an often-false sense of control or were influenced by family members who held unhealthy beliefs around food and exercise.

Researchers have also found that increased time at home during the pandemic led to more social media use by young people and therefore more exposure to toxic body image and dieting social media content.

While social media alone will not cause eating disorders, societal beliefs about beauty , which are amplified by social media, can contribute to the development of eating disorders.

‘Thinspo’ and ‘fitspo’

Toxic beauty standards online include the normalization of cosmetic and surgical procedures and pro-eating-disorder content, which promotes and romanticizes eating disorders. For instance, social media sites have promoted trends such as “thinspo,” which is focused on the thin ideal, and “fitspo,” which perpetuates the belief of there being a perfect body that can be achieved with dieting, supplements and excessive exercise.

Research has shown that social media content encouraging “clean eating ” or dieting through pseudoscientific claims can lead to obsessive behavior around dietary patterns. These unfounded “wellness” posts can lead to weight cycling, yo-yo dieting , chronic stress, body dissatisfaction and higher likelihood of muscular and thin-ideal internalization .

Some social media posts feature pro-eating-disorder content , which directly or indirectly encourages disordered eating. Other posts promote deliberate manipulation of one’s body, using harmful quotes such as “nothing tastes as good as thin feels.” These posts provide a false sense of connection, allowing users to bond over a shared goal of losing weight, altering one’s appearance and continuing patterns of disordered eating.

While young people can often recognize and understand toxic beauty advice’s effects on their self-esteem, they may still continue to engage with this content. This is in part because friends, influencers and social media algorithms encourage people to follow certain accounts.

How policy changes could help

Legislators across the U.S. are proposing different regulations for social media sites .

Policy recommendations include increased transparency from social media companies, creation of higher standards of privacy for children’s data and possible tax incentives and social responsibility initiatives that would discourage companies and marketers from using altered photos.

Phone-free zones

Small steps at home to cut down on social media consumption can also make a difference. Parents and caregivers can create phone-free periods for the family. Examples of this include putting phones away while the family watches a movie together or during mealtimes.

Adults can also help by modeling healthy social media behaviors and encouraging children and adolescents to focus on building connections and engaging in valued activities .

Mindful social media consumption is another helpful approach. This requires recognizing what one is feeling during social media scrolling. If spending time on social media makes you feel worse about yourself or seems to be causing mood changes in your child, it may be time to change how you or your child interact with social media.

Social media
Eating disorders
Youth mental health
Body dissatisfaction
Cyberbullying
Self-esteem
Eating disorders and pandemic
Body dysmorphia
Body image disorders
Eating disorders in teens

Apply for State Library of Queensland's next round of research opportunities

Associate Professor, Psychology

Professor and Head of School, School of Communication and Arts

Senior Graduate Research Officer (Admissions and Scholarships)

Management Information Systems & Analytics – Limited Term Contract

Environment
Foreign Policy
Health & Healthcare
Privacy Policy
Sponsored Content & Advertorials

Mounting Research Documents the Harmful Effects of Social Media Use on Mental Health

Negative Impacts Include Poor Body Image and Development of Eating Disorders

Media influences and conventional beauty standards have long plagued society.

This issue took on new urgency in May 2023 when the U.S. surgeon general issued a major public advisory over the links between social media and youth mental health .

Research shows that images of beauty as depicted in movies, television and magazines can lead to mental illness , issues with disordered eating and body image dissatisfaction .

These trends have been documented in women and men , in the LGBTQ+ community and in people of different racial and ethnic backgrounds.

Social media can be toxic

Body dissatisfaction among children and adolescents is commonplace and has been linked to decreased quality of life, worsened mood and unhealthy eating habits.

As an eating disorder and anxiety specialist , I regularly work with clients who experience eating disorder symptoms, self-esteem issues and anxiety related to social media .

The pros and cons of social media

About 95% of children and adolescents in the U.S. between the ages of 10 and 17 are using social media almost constantly .

A breeding ground for eating disorders

While social media alone will not cause eating disorders, societal beliefs about beauty , which are amplified by social media, can contribute to the development of eating disorders.

‘Thinspo’ and ‘fitspo’

How policy changes could help

Legislators across the U.S. are proposing different regulations for social media sites .

Phone-free zones

Adults can also help by modeling healthy social media behaviors and encouraging children and adolescents to focus on building connections and engaging in valued activities .

Emily Hemendinger , Assistant Professor of Psychiatry, University of Colorado Anschutz Medical Campus

This article is republished from The Conversation under a Creative Commons license. Read the original article .

OUR NONPROFIT NEWSROOM IS NEARLY 100% SUPPORTED BY READERS. PLEASE CONSIDER A DONATION TODAY.

Emily Hemendinger, University of Colorado

Emily Hemendinger, LCSW, MPH, CPH, ACS is currently an Assistant Professor, Clinical Director, and DBS Coordinator with the OCD Program, at the University of Colorado. Emily completed her dual degree program (MSW/MPH) from the University of Pittsburgh. She has over 10 years of clinical experience working with OCD, anxiety disorders, perfectionism, body image concerns, and eating disorders. Emily has a background in behavioral and community health sciences, health education, and health promotion. She is dedicated to combining her mental health and public health work to increase access to affordable and inclusive specialized mental health care. Her other passions include smashing mental health stigma, climbing mountains, and spending time with her aussie-corgi mix, Harrison Ford Hemendinger.

Comments are closed.

Type above and press Enter to search. Press Esc to cancel.

Is teen social media use a crisis or moral panic?

Diverse group of young people standing in a circle, all looking at their phones, shot from below their hands

Jonathan Haidt’s New York Times bestseller The Anxious Generation: How the Great Rewiring of Childhood is Causing an Epidemic of Mental Illness has resonated with tens of thousands of parents who are concerned about the addict-like behavior of their kids when it comes to their smartphones. And it’s not only people with children who are concerned: The American Psychological Association , Common Sense Media , and U.S. Surgeon General Vivek Murthy, who has called for social media platforms to come with warning labels, are all on high alert regarding the effect of smartphones and social media on adolescents’ mental health.

Still, Haidt’s claim—that Gen Z kids are different from their predecessors in terms of mental health because they’ve grown up on smartphones—as well as his suggestions for dialing it back , have prompted much pushback.

Frequent Haidt critic Andrew Przybylski, an Oxford professor, told Platformer , “Extraordinary claims require extraordinary evidence. Right now, I’d argue he doesn’t have that.” Chris Ferguson, at Stetson University, attempted to take some wind out of Haidt’s sails by pointing out that America’s recent suicide increase is not a phenomenon specific to teens. And Candice Odgers of the University of California Irvine, in her Nature journal critique of his book, said Haidt is adding to a “rising hysteria” around phones and that he is “telling stories that are unsupported by research.”

But Haidt and his chief researcher, Zach Rausch, are holding their ground in what Rausch calls “a normal academic debate.”

What they are trying to explain, Rausch tells Fortune , is “a very specific change that happened in a very specific time among a specific subset of kids.” Besides, he offers, “I’m totally open to the idea that maybe we’re somewhat wrong about just how much it can explain the change over the last decade. But I certainly think that we are on very strong footing to say that [smartphones and social media] have led to a pretty substantial increase in anxiety and depression and self-harm among young people.”

Here, Rausch lays out the theories of The Anxious Generation and responds to criticisms.

What is the Anxious Generation claiming ?

The core idea of the book is that something changed in the lives of American young people somewhere around 2010 to 2015. “What we’re trying to explain in the book is what changed during this period to help explain why Gen Z is so different. And the specific things in which they’re different are often related to their mental health, anxiety, rates of anxiety, depression, self harm, even suicide,” says Rausch.

He and Haidt point to a slew of findings, including that the percentage of U.S. teens who say they’ve had one “major depressive episode” in the past year has increased by more than 150% since 2010, with most happening pre-pandemic. And that, among American girls between 10 and 14, emergency room visits for self-harm grew by 188% during that period, while deaths by suicide increased by 167%; for boys, ER visits for self-harm increased by 48% and suicide by 91%.

“We see this in the United States,” Rausch adds. “We see this across the Anglosphere, the English speaking countries, and well-being and mental health measures in many countries around the world are showing similar declines around the same time. So that’s the big thing that we’re trying to address.”

What they theorize is that one of the fundamental things that changed in the period in question—specifically among young people and most especially among adolescent girls—is “the movement of social life onto smartphones and social media, where now they move from spending very little time on platforms like Instagram , which came out in 2010, [to] spending upwards of four, five hours a day on these platforms by 2015.”

It’s changed the way kids relate to each other, as well as to family and strangers. “That’s what we mean by the rewiring of childhood,” says Rausch. “It is a rewiring of the way that we interact. It’s our social ecosystem and how that really changed, and that it makes it very different from other technologies. Television didn’t rewire our relationships with everybody.”

Debate has swirled around three questions

First, Rausch says, skeptics ask: Is there a mental health crisis, and to what extent does it exist? Second: Is it international or is it just happening in the United States? And third: If you agree there is a mental health crisis, what is the role of social media?

But even if you disagree that there is such a crisis, Rausch notes, “social media could still not be safe for kids, right? This is something that I feel like gets missed, like with the Surgeon General report , where the focus is all about, ‘Can it explain this huge rise?’ But there are all sorts of consumer products for kids that kill 50 kids a year that we immediately take off the market.”

Sticking points: Moral panic, lack of evidence

One consistent argument against the book, Rausch says, is that “there are a number of people who have studied media effects for a while and are very attuned to past panics around technologies, whether that be video games or comic books, and there is a justified skepticism and worry that maybe this is happening again.”

In response, he stresses, they try to make the case that, simply, “This is this time. It really is different.”

The second detail they get called out on involves the evidence that Raush and Haidt point to, by collecting every study they could find, all of which they’ve collected in public Google Documents . That amounts to “hundreds and hundreds … a lot of them low-quality, some better quality,” says Rausch. Some critics point to the studies showing correlation rather than causation between, for example, social media and mental health issues.

But doing actual experiments on young people that might show cause is tricky, he explains. “One, social media is relatively new, especially in the kind that we’re talking about, which is constantly evolving every year.” Plus, “You don’t do experiments, generally, on kids. And to do the kind of experiment that maybe you would want to do to really test this out is completely unethical and would never happen—assigning a group of kids to have one kind of childhood and another group to have another.”

It’s why arriving at a very precise, conclusive scientific claim is difficult. “And this is kind of the nature of social science,” he says, “and why there is so much debate.”

To bolster their arguments, Rausch and Haidt try to draw on various lines of evidence, including firsthand accounts from Gen Z, parents, and teachers—as well as internal documents from social media companies themselves, such as Instagram’s documentation of teen girls reporting that using the platform makes their body image and mental health worse.

The researchers have also zeroed in on their belief that social media, especially with heavy use, has “addictive-like qualities,” and will, in turn, cause withdrawal when stopped.

“A large part of the story is that we’re trying to tell about what happens when an entire group of people move their lives onto addictive-like platforms,” he says.

Other reasons for pushback

“There are camps of people that are very techno-optimist—you have a lot of faith that technology, and believe that more technology will solve the world’s problems,” Rausch says. And for those who strongly feel that way, Anxious Generation ’s findings might prompt a feeling that “it’s just a little bump in the road. Things are going to get better as we make more technology to solve problems that technology creates, and we’ll kind of keep going in that direction.”

There’s also the “very real concern” of government control of social media, which Rausch calls “more of a libertarian critique.”

Finally, he says, there’s the worry that these issues are getting too much attention as compared with just-as-important subjects of other researchers—from poverty to the opioid epidemic.

But all arguments aside, he says, much of what Anxious Generation has focused on is “irrefutable.” That includes not only the correlation between heavier social media use and anxiety or depression , but the “large portion of harm that happens on these platforms,” including the rise in sextortion cases, or teens being coerced into sending explicit photos online.

And what always reassures Rausch that they’re on the right track is talking to a teen, parent, or teacher. “Whenever I have doubt,” he says, “I go to the source.”

Latest in Family

closeup of teen girls eating burgers and wearing sunglasses

How ‘big back,’ ‘fatty,’ and other ‘fatphobic’ slang is damaging your teen’s mental health

Olympian Allyson Felix is headed to Paris with athlete parents top of mind.

Track star and entrepreneur Allyson Felix will launch the Olympic Village’s first nursery: ‘The systems aren’t in place for mothers whatsoever’

In the age of longevity, we’re familiar with many novel biohacking lifestyle choices. But there’s a new frontier we’ve yet to hear about: the biohacking dating market.

A biohacker’s love story: This 33-year-old asked her date for health labs before meeting—now they’re married

July has the highest number of drowning deaths. Here’s how to keep kids safe around water

young boy sitting in the dark on his smartphone

4 smartphone rules parents should follow, according to a social psychologist who has studied the Gen Z mental health crisis

Fatphobia is back with a vengeance among Gen Z girls. Here’s how slang like ‘big back’ and ‘fatty’ is damaging, say experts

Did social media really fuel the youth mental health crisis? ‘The Anxious Generation’ researcher calls the correlation ‘irrefutable’

Teens are spending the equivalent of a 40-hour work week on their devices. Here’s how to help them find the right balance

Colorectal cancer cases have tripled in teens—and jumped by 500% in kids. What you need to know

The longest, happiest marriages have these 6 defining traits

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

Advanced Search
Journal List
Int J Environ Res Public Health

The Relationship between Social Media and the Increase in Mental Health Problems

Associated data.

The data presented in this study are available on request from the corresponding author.

Social media has become an indispensable aspect of young people’s digital interactions, as they use it mostly for entertainment and communication purposes. Consequently, it has the potential to have both positive and negative effects on them. Deterioration in mental health is one of the side effects stemming from social media overuse. This study investigates the relationship between social media and the increase in mental health problems in Saudi Arabia. The population considered for analysis includes young people from Saudi Arabia, with a sample size of 385. A closed-ended survey questionnaire was used to collect data on different social media features and criteria. Using the Analytical Hierarchical Process (AHP), the researcher analyzed data to compare the effect of different social media features on mental health. The social media features included in this paper are private chats and calls, group chats and calls, browsing posts, games, media sharing, adverts, likes/comments/followers, and pages. The researcher adopted entertainment, information, social interaction, privacy, esteem, and communication as the criteria in the AHP process. Among these criteria, the study found that entertainment was the most significant, while privacy was the least significant. Findings suggested that likes, comments, and followers were the biggest contributors to poor mental health (total utility = 56.24). The least effective feature was ‘games’ (total utility = 2.56). The researcher recommends that social media users be cautious when interacting with social media features, especially likes, comments, followers, media, and posts, because of their significant effect on mental health.

1. Introduction

Mental health is a crucial aspect of human wellbeing, yet it is often overlooked and stigmatized. According to the World Health Organization, the prevalence of mental health problems is increasing at a rate of 13% per year [ 1 ]. Anxiety and depression are the most common mental health issues, affecting 264 million and 280 million people worldwide, respectively [ 2 , 3 ]. In addition, an estimated 269 million people were struggling with drug and substance abuse by the end of 2018 [ 4 ]. These numbers are likely to continue to rise due to a variety of factors. One factor that has been identified as contributing to the increase in mental health challenges is the use of technologies, including social media. Social media refers to applications that allow users to interact with each other through the creation and exchange of media, text, and calls within a network [ 5 ]. Some examples of social media platforms include Facebook, Twitter, Instagram, and TikTok. Key social media features considered in this investigation are private chats, group chats, browsing posts, adverts, media sharing, calls, likes and comments, and pages. Social media has been linked to poor sleep patterns, depression, and anxiety [ 6 ]. In addition, ref. [ 7 ] warns of the negative impact that excessive social media use can have on the mental health of young people.

Saudi Arabia has a high level of social media usage, with 82.3% of the population (29.5 million people) using social media in 2022 [ 8 ]. Young people, who make up 36.74% of the population, are the biggest users of social media in Saudi Arabia, with 98.43% of young people using social networking sites [ 9 ]. The top three reasons given by Saudis for using social media are keeping in touch with friends and family, use of free time, and finding products to purchase [ 8 ]. The prevalence of mental health issues in the KSA is estimated to be around 20.2% [ 10 ]. Depression is the most common mental health condition, affecting 21% of the population, followed by anxiety (17.5%) and stress (12.6%) [ 11 ]. Research has shown that social media use in Saudi Arabia is correlated with increased mental health issues [ 12 ]. High social media exposure has also been found to be associated with a higher risk of depression and anxiety in the kingdom [ 12 ]. Studies have also shown a significant correlation between the use of social networking sites and the increase in depression-related conditions in Saudi Arabia [ 13 ].

The aim of this study is to examine the impact of social media on mental health in Saudi Arabia and to identify which social media features have the greatest impact on increasing mental health issues. The study uses an Analytical Hierarchical Process (AHP) to analyze several social media features and determine their impacts on mental health. By understanding the specific features that contribute to mental health problems, individuals and policymakers can take steps to alleviate mental health issues and reduce the negative effects of social media. The results of this study will provide valuable insights into the impact of social media on mental health in Saudi Arabia and can inform the development of strategies to mitigate these effects.

2. Literature Review

One of the primary features of social media is chatting. As a social network, chats are a powerful method of communication among social media users. They may take the form of group or private chats. According to [ 14 ], young people with psychological issues tend to worsen their conditions by participating in social media chatrooms. Private chats are not exempted, as ref. [ 15 ] found that constant chatting with other people without feeling their physical presence is one reason for the increase in mental health issues among social media users. The outcome is more loneliness, a common factor in psychological deterioration. While chatting may not directly cause depression and other mental health problems, it can exacerbate an individual’s symptoms if one engages in long chats [ 16 ]. The studies further caution that young people must be careful when chatting with their peers on social media.

Browsing posts and advertisements are equally part of social media. Social media posts often portray falsehoods by allowing one to elevate their good qualities and suppress their negative ones [ 17 ]. Young people may not understand this fact, and they are likely to think that something is wrong with themselves because they do not look as good as the posts made by their friends. The authors of [ 18 ] found that social media influencers significantly contribute to the poor mental health of social media users. Advertisements power most social networking platforms, and users have had to embrace the presence of ads alongside their digital social lives. Because of their wide viewership, ads shape the psychology and opinions of young people on these platforms [ 19 ]. An advertisement portraying a muscular individual may depress a social media user who does not have similar body features. Similarly, ads with tall girls may negatively impact young girls psychologically because of social projection.

Sharing media, playing games on digital social networks, and interacting on video conferencing channels may negatively impact an individual’s mental health. In some cases, ref. [ 14 ] found that the sharing of media and interactions on social media prompts users to think less of themselves. Some users may not have good enough videos because their equipment, such as cameras, is not as good as their friends’ devices. Moreover, watching videos on social media can be an addictive habit if left unchecked. The authors of [ 20 ] argue that the active watching of and commenting on YouTube videos makes the platform overly addictive compared to people who passively watch videos without associated interactions. The authors advise that people’s interactions on video-based social media platforms should be minimal. Regarding games, ref. [ 21 ] argues that high involvement in social media games can result in addiction. Such a condition may make an individual overly dependent on these games, which distorts their mental health.

An individual’s following and the intensity with which people react to their posts can impact their mental health. For example, ref. [ 22 ] reports that users who update more frequently on their social media pages tend to receive more feedback in the form of likes and comments. This feedback is important, as it enhances the self-esteem of post authors. Moreover, ref. [ 23 ] observes that people receiving negative feedback from their social media posts are more susceptible to emotional distress. The study affirms that technologies aiding young people in comparing social statuses present a risk to their mental wellbeing. Some turn to social media to increase followers and gain a sense of gratification to compensate for their emotional and psychological challenges [ 24 ]. This leads them further down the path of a graver depression.

3. Methodology

This section provides an explanation of the methodological processes that the researcher used in order to acquire data and analyze them. The research design of this study is described in Section 3.1 , which is then followed by the population, the sampling method, and the survey instrument. The phases of the Analytical Hierarchical Process (AHP) used in the research are explained in the following subsections.

3.1. Research Design

The specific approach taken by the researcher is the Analytical Hierarchical Process (AHP). It is a decision-making model that uses paired comparisons to determine the most significant factors that affect a decision [ 25 ]. In this case, the researcher wished to identify and rank social media factors impacting mental health. This ranking will help in prioritizing which aspects of social media use to manage at a personal level. The elements of social media in this study are private chats, group chats, browsing posts, adverts, media sharing, calls, likes and comments, and pages. The study undertakes a survey that asks respondents to indicate how useful these social media features are to them and how each element may lead to mental health problems.

3.2. Population, Sampling, and Survey Instrument

This study considered Saudi Arabia as the unit of study, while the study population was Saudi youth aged between 18 and 35. The United Nations defines youth as persons between 18 and 24. However, the researcher sought a more accommodating criterion regarding respondent ages. The selection of young people as the target population was motivated by the fact that 98.43% of them are on social media [ 9 ]. In addition, ref. [ 9 ] also reports that 7,623,336 young people belong to this demographic. The computed sample size from this population is 385 using Yamane’s formula [ 26 ]. Gender-wise, the researcher allowed respondents to indicate whether they were male, female, or non-binary. All respondents selected either the male or female category. Hence, the researcher analyzed the results in this fashion. The sample for this study was selected using simple random sampling on social media platforms such as Facebook and Twitter. This sampling method involves selecting participants randomly from the target population, which in this case were young people in Saudi Arabia who use social media. This helped to ensure that the sample was representative of the target population and that the responses were accurate and reliable. To ensure the content validity of the questionnaire, a pre-test of the survey was performed, since it is in the researcher’s best interest to have expert evaluations and reviews of the comprehensibility and clarity of the used research instrument. Several questions were altered, reworded, or eliminated in response to positive comments and ideas for small modifications. The amended questionnaire was forwarded to the collaborating academics for review and evaluation to confirm the instrument’s face validity. This questionnaire’s question types were determined by their degree of relevance to each identified concept. The Content Validity Index (CVI) was calculated to be 1, indicating that all three questions were relevant and appropriate for the study. This suggests that the questionnaire was valid and that it measured the variables of interest in a reliable and accurate manner.

The researcher used social media platforms to reach a diverse and representative sample of young people in the country. The social media platforms used in communication with participants (personal and business) included Facebook, Instagram, Twitter, and Snapchat. The researcher sent out a post including all the details about the research, and a link was included to direct the participants to the questionnaire page. The questionnaire was hosted on Google Forms to facilitate distribution, and it was left open for one month to allow respondents to respond at their convenience. The final questionnaire had a two-part structure, including demographic questions and three main questions with selective options for participants. Appendix A shows the list of questions asked to the respondents.

3.3. Analytical Hierarchical Process

The Analytical Hierarchical Process involves four primary steps, which are

Identifying decisions, options, and criteria;
Conducting pairwise comparisons;
Computing weights for the criteria;
Calculating utility values.

3.3.1. Identifying Decisions, Options, and Criteria

The decision is determining which social media features have the biggest effect on increasing mental health problems. The options were the eight social media features, namely private chats, group chats, browsing posts, adverts, media sharing, calls, likes and comments, and pages. The criteria for determining which features are the most influential were the importance of a feature to an individual, the time spent interacting with the feature, and the recency of interaction.

3.3.2. Pairwise Comparison

Pairwise comparisons involve comparing two criteria simultaneously to build a square n × n matrix, where n is the number of criteria. The comparison is structured in such a way that the value entered in a cell represents the number of times one criterion is more important relative to the other. Because the two criteria being compared are the same, the relative value of each criterion is equal to one when they are compared to each other [ 25 ]. The maximum possible score is n, and larger numbers indicate that a criterion is becoming essential. The pairwise comparison will compare time spent on a feature, recency in using the feature, and the overall importance of the feature to the respondents.

3.3.3. Importance Weights

After populating the matrix, it is used to compute the importance weights. They signal to an analyst the extent to which each criterion will affect their ultimate decision. The researcher gave the biggest weight to the item with the most significant importance. The study computed the geometric mean of the criteria to ensure objectivity in the computation in the first step, as suggested by [ 27 ]. In the second step, the relative composition of the criterion values was determined, which was used to determine their weights [ 28 ]. In order to complete the procedure, the computation of the ratio of the value of each criterion to the overall value is needed.

3.3.4. Calculating Utility Values

Computing the utility is the final step in the analytical hierarchal process. It involves establishing the ‘utiles’ associated and multiplying them by their corresponding importance scores [ 27 ]. The ‘utiles’ are obtained using respondents’ subjective evaluation of how each feature instigates mental health challenges. ‘Utility’ is a quantitative value that indicates how useful something is to an individual. This figure helps in selecting the most significant option. It is possible to represent utility as a percentage. It is argued that a criterion’s usefulness increases as its advantages or benefits increase. Depending on the criterion, it is conceivable that utility will be computed differently. The importance of the criteria selected for investigation and the utility attached to the criterion were multiplied to show the utility calculation for each criterion. The values for each criterion were added to determine the total utility of each social media feature.

4.1. Analysis of Demographic Characteristics

This section analyzes the age, gender, and occupations of the study participants. The findings reveal that the most populous age group was that of members aged between 18 and 25, as they constituted 60.3% (232) of the study population. Male respondents accounted for 55.3% (213) of the sampled participants. The most dominant group by occupation was students, as they accounted for 41.8% (161) of the sampled participants. Table 1 provides further details about the demographic characteristics of the respondents.

Respondents’ demographic characteristics.

Demographics		Frequency	Percentage (%)
Gender
	Male	213	55.3
	Female	172	44.7
Age
	18–25	232	60.3
	26–30	114	29.6
	31–35	39	10.1
Occupation
	Student	161	41.8
	Unemployed	138	35.8
	Employed	86	22.3
	Total	385	100%

4.2. Favorite Features of Respondents

The researcher first examined which of the selected social media features were favored by the respondents. The findings suggested that likes, comments, and followers were the most relevant aspects of social media that the respondents liked, obtaining a mean score of 7.29/8.00. The least favorite feature was gaming, scoring a mean of 2.05/8.00. Table 2 shows the performance of the different features.

Ranking the relevance of social media features to respondents.

Feature	Mean Relevance
Likes, Comments, and Followers	7.29
Media Sharing and Consuming	7.16
Browsing Posts	6.33
Group Chats and Calls	4.80
Private Chats and Calls	3.98
Pages	3.11
Games	2.05
Adverts	1.26

4.3. Pairwise Comparison

The researcher established the criteria comparison matrix using the responses to questions that asked participants to rank the factors influencing their sentiments on social media features. The ranking was based on the mean score obtained from the 385 responses regarding their criteria ranking. In this case, the highest ranked criteria by the respondents scored higher values in Table 3 . Evidence suggests that people decided which social media feature they valued mostly based on its entertainment value (value = 6) and less so based on the feature’s privacy (value = 1).

Criteria importance.

Key	Feature	Value
ENT	Entertainment	6
INF	Information	2
SOC	Social Interaction	5
PRI	Privacy	1
EST	Esteem	4
COM	Communication	3

The computation of matrix values in Table 4 was based on the values established in Table 3 above. The basis of the values is the mean ranks of the criteria, as expressed by the respondents. In this case, the matrix values indicated the number of times one criterion was more important than the corresponding criterion [ 28 ]. For example, the highlighted pair in Table 4 shows that esteem was two times more important that the corresponding information criterion.

Pairwise comparison matrix.

	Ranks →	6	2	5	1	4	3
Ranks ↓		ENT	INF	SOC	PRI	EST	COM	V	W
6	ENT	1.00	3.00	1.20	6.00	1.50	2.00	2.004	0.28571
2	INF	0.33	1.00	0.40	2.00	0.50	0.67	0.668	0.09524
5	SOC	0.83	2.50	1.00	5.00	1.25	1.67	1.670	0.23810
1	PRI	0.17	0.50	0.20	1.00	0.25	0.33	0.334	0.04762
4	EST	0.67	2.00	0.80	4.00	1.00	1.33	1.336	0.19048
3	COM	0.50	1.50	0.60	3.00	0.75	1.00	1.002	0.14286

4.4. Importance Weights

The first step involves the computation of the criteria’s geometric mean [ 28 ] to determine their influence on the final decision. In this case, it is the sixth root of the product of the row elements in Table 4 . Below is the basic formula used in computing the weights of the criteria, assuming n criteria:

V i : Geometric mean for criterion i ;
X i 1 : Pairwise importance of criterion i relative to criterion 1;
X i 2 : Pairwise importance of criterion i relative to criterion 2;
X in : Pairwise importance of criterion i relative to criterion n ;
n : Number of criteria.

The second step involves finding the proportionate composition of the criteria values, which will count as their weights [ 28 ]. The procedure requires the computation of the ratio of each criterion’s value against the total value:

W i : Weights for criterion i .

4.5. Computing Utility Values

The researcher computed the feature utiles by first ranking their respective mean responses. The findings in Table 5 show that respondents thought that likes, comments, and followers on social media would often cause people’s mental health problems. Other similarly high-risk features are browsing posts and adverts.

Utility values.

Feature	Utiles
Private Chats and Calls	2.26
Group Chats and Calls	3.48
Browsing Posts	7.11
Games	1.25
Media Sharing and Consuming	3.55
Adverts	5.75
Likes, Comments, and Followers	7.71
Pages	4.89

4.6. Comparing Social Media’s Effects on Mental Health

This study computed the total utility as the product of the utiles (feature strengths), importance weights (criteria weights), and how favored the features were by the respondents (relevance). In Table 6 , each feature’s strength is multiplied by the criteria weights to obtain the cell values. The row values are then added and multiplied by a feature’s importance to determine the total utility. The total utility is obtained using the following formula:

TU i : Total Utility for criterion i ;
W i : Weights for criterion i ;
UV j = Utility Value for feature j ;
MR i : Mean Relevance for criterion i ;
i from 1 to 8, j from 1 to 6.

Estimating the effect of social media features on mental health problems.

			Criterion Weights
			0.29	0.10	0.24	0.05	0.19	0.14
			ENT	INF	SOC	PRI	EST	COM	Mean Relevance	Total Utility
Feature Strength (Utility Value)	7.71	LCF	2.20	0.73	1.84	0.37	1.47	1.10	7.29	56.24416
	7.11	BRP	2.03	0.68	1.69	0.34	1.35	1.02	6.33	45.03454
	3.55	MDS	1.01	0.34	0.84	0.17	0.68	0.51	7.16	25.39835
	3.48	GCC	1.00	0.33	0.83	0.17	0.66	0.50	4.80	16.72801
	4.89	PGS	1.40	0.47	1.16	0.23	0.93	0.70	3.11	15.20282
	2.26	PCC	0.65	0.22	0.54	0.11	0.43	0.32	3.98	9.024443
	5.75	ADV	1.64	0.55	1.37	0.27	1.09	0.82	1.26	7.241052
	1.25	GMS	0.36	0.12	0.30	0.06	0.24	0.18	2.05	2.561511

The findings suggest that the feature with the most significant negative effect on mental health is ‘likes, comments, and followers.’ This feature scored a total utility of 56.24. On the other hand, the feature with the least significant negative effect on mental health is ‘social media games’. This study found the feature to have a total utility of 2.56. While the respondents had opined in Table 3 that adverts substantially contribute to mental instability, the criteria weights for this feature were too low to significantly impact the feature’s total utility.

5. Discussion

In this study, the researcher found that social media has a significant negative impact on the mental health of Saudi Arabian youth. The feature that had the greatest impact was likes, comments, and followers, with a utility value of 56.24. This suggests that individuals who are seeking validation and social esteem through social media may be more prone to experiencing stress, depression, and anxiety. Browsing posts and media sharing were also identified as significant features that negatively impact mental health, with utility values of 45.03 and 25.40, respectively. These findings align with previous research that has identified the presence of influencers on social media as a potential source of stress and depression for regular users who may feel pressure to emulate these individuals [ 18 ]. Additionally, excessive exposure to social media videos has been linked to negative mental health outcomes [ 20 ].

On the other hand, this study found that social media games had the least impact on mental health, with a utility value of only 2.05. This finding differs from previous research that has identified games on social media as highly addictive and potentially harmful to mental health [ 21 ]. However, it is important to note that this study only compared the negative impact of different social media features on mental health, and it is possible that social media games may have a greater impact when studied in isolation. These findings highlight the need for caution in the use of social media, particularly among young people in Saudi Arabia. While social media can provide a sense of connection and support, it is important to be aware of its potential negative impacts on mental health. In light of these findings, it may be beneficial for individuals to set limits on their social media use and prioritize activities that promote mental wellbeing, such as physical exercise and social interaction with friends and family.

One potential implication of these findings is the need for greater education and awareness about the potential dangers of social media. This could involve educating people about the importance of finding validation from sources other than social media, as well as helping people to develop healthy habits when it comes to their social media use. This could involve setting limits on the amount of time spent on social media, being selective about the content that is consumed, and finding ways to disconnect from social media when necessary. Overall, these findings highlight the need for caution when using social media, particularly for youth in Saudi Arabia. While social media can be a useful tool for communication and connection, it is important to be mindful of the potential negative effects on mental health. It may be helpful for individuals to limit the attention they pay to certain features, such as likes, comments, and followers, and to engage in passive rather than active consumption of media. Further research is needed to understand the specific mechanisms by which social media impacts mental health and to identify effective interventions to mitigate negative effects.

There are several potential limitations to this study that should be considered when interpreting the results. First, the sample size of 385 participants may not be representative of the larger population of Saudi Arabian youth. Additionally, the self-reported nature of the data may be subject to bias, as individuals may not accurately recall or report their social media habits. Finally, the cross-sectional design of the study means that it is not possible to establish cause-and-effect relationships between social media use and mental health. Another limitation of this study is that the definition of “youth” is not explicitly stated. It is possible that the experiences and activities of respondents aged 18 and those aged 35 may differ significantly. Additionally, the study did not explicitly consider the potential impact of gender on the relationship between social media use and mental health. Future research should aim to further explore these demographic variables in order to better understand the specific effects of social media on mental health among different populations. Such investigations should consider using larger and more diverse samples, as well as more robust research designs to further explore the relationship between social media and mental health.

6. Conclusions

The purpose of this study was to examine the effects of social media on mental health among young people. Social media has become an integral part of modern society, with platforms such as Facebook, Twitter, and Instagram offering a range of features including messaging, media sharing, and gaming. However, there is growing concern that the use of social media may have negative effects on mental health, particularly among young people who are more likely to use these platforms extensively. The study aimed to identify the specific features of social media that have the greatest impact on mental health and to examine the underlying reasons for these effects. To achieve these objectives, the study used AHP to assess the relevance and importance of eight social media features to 385 respondents aged between 18 and 35. The findings showed that likes, comments, and followers were the most relevant features to respondents, while gaming was the least favorite feature. In terms of the criteria influencing the respondents’ sentiments, entertainment was the most important factor, while privacy was the least important. The study concludes that social media can have both positive and negative effects on mental health, depending on how it is used and the specific features that are engaged with. It is therefore important for young people to be aware of the potential risks and to use social media in a balanced and responsible manner.

Appendix A. List of Questions Asked to the Respondents

Question 1: Rank the importance of the following social media features as they occur to you as (1) for the least important and (8) for the most important.
Question 2: How do you determine the importance of social media features to you? Rank how the following factors influence your sentiments as (1) for least significant Determinant and (6) for the most significant Determinant.
Question 3: On a scale of 1 to 8, rate the effect of the below social media features in inducing mental health issues as (1) for Smallest Effect and (8) for Biggest Effect

Funding Statement

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The author declares no conflict of interest.

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

ChatGPT: Disruptive or Constructive?

Thursday, Jul 18, 2024 • Jeremiah Valentine : [email protected]

What is Chat GPT?

ChatGPT is a popular emerging technology using Artificial Intelligence. GPT stands for Generative Pre-trained Transformer, which describes an AI program that looks for patterns in language and data learning to predict the next word in a sentence or the next paragraph in an essay. The website has a friendly interface that allows users to interact with AI in a n efficient conversational tone . ChatGPT provides another opportunity for students, instructors, researchers, workers, and others to find practical solutions to everyday and complicated problems.

At the root of this conversation is Artificial Intelligence. I plan to explore applicable uses of AI and ChatGPT in the classroom , entrepreneurial potential uses, and applications in industry .

Everyday Uses of Artificial Intelligence

The use of Artificial I ntelligence varies based on the user and their end goal. While many individuals will use certain programs or websites to meet specific objectives , many companies and apps have begun to utilize this emerging technology to better meet their customer's needs.

Duolingo is a popular foreign language learning application that I use to supplement my Spanish studies . The app uses Artificial Intelligence to assess users' knowledge and understanding as they interact with the program , thus streamlining users learning outcomes.

As another example, Khan Academy is a free online resource that helps teachers and students learn any level of math or other grade school topics for free. They have created Khanmigo , using AI. The model acts as a tutor that helps work through a problem while not directly providing the answer. It can assist in writing an essay or solving a complex math problem step by step.

These everyday applications continue a trend of companies implementing this new technolog y into students and teachers' lives . . This new AI technology also allows business professionals to enhance aspects of their processes.

Entrepreneurs, A.I. and the Advantages

While AI already provides companies and organizations with new ways to interact with and better support their customers, AI could also provide emerging industries and entrepreneurs with new paths to business success.

According to Entrpreneur.com, most businesses currently use AI for customer service purposes , however , AI could also help entrepreneurs create effective spreadsheets cataloging useful data with accuracy that can be incredibly specific or broad. Specifically with customer service, AI can quickly find what a customer needs and solve their problems efficiently. It could also analyze how effective marketing campaigns are influencing customers’ purchases.

As I researched for more information about this topic, I found an article in The Journal of Business Venturing Insights published in March 2023, sharing different techniques business students can use ChatGPT as an asset to generate entrepreneurial business pitches. The article titled “ The Artificially Intelligent Entrepreneur” written by Cole Short, an Assistant Professor of Strategy at Pepperdine University, and Jeremy C. Short, a UTA alumni and Professor at the University of North Texas at Denton, showcased different elevator pitch scenarios.

Students and entrepreneurs study CEOs who have impacted an industry dynamically; the CEO's mentality is an asset . I had the opportunity to question Dr. Jeremy Short on how he arrived at the initial question of using AI as a CEO archetype business consultant. An archetype is a symbol, term, or pattern of behavior which others have replicated or emulated.

He responded, “ We used this existing framework and selected a CEO from each archetype and used ChatGPT to create elevator pitches, social media pitches, and crowdfunding pitches. The strength of ChatGPT is based largely on the creativity of the prompt, which is where we aim as authors.”

CEO Archetypes and Prompt Engineering

ChatGPT allows the user to understand the archetypes of successful CEOs and collaborate with entrepreneurial styles. These archetypes are accessible options to consult with AI. Let ’ s break down different CEO archetypes students used during this study:

Creator CEOs are typically serial entrepreneurs and serve during the growth stages of developing new businesses. These individuals are risk takers recognizing opportunities that others don ’ t see. Elon Musk, CEO of Tesla, SpaceX, and Twitter is the creator archetype.

Transformer CEOs are created by climbing the ladder of a successful business and adding new ideas . They have a firm understanding of the company's culture and work to dramatically change the company, separating it from missteps in the past. Indra Nooyi CEO of PepsiCo is the transformer archetype.

Savior CEOs rescue businesses on the verge of failure with disciplined actions, unique experience and insights they forge a successful path forward for declining businesses. Lisa Su, CEO of AMD is the savior archetype.

ChatGPT was prompted to write an elevator pitch in the style of the previously listed CEOs.

The response for Elon Musk included language about “ building” a product with “ cutting-edge technology.”

Indra Nooyi ’s response included phrases like “ the world is changing” and making “ a positive impact in the world.”

Lisa Su's response produced a pitch speaking about being “ accountable, tough and disciplined” with an emphasis on “ a strong focus on efficiency and performance.”

However, I believe these positions can help entrepreneurs develop their own successful business practices; creating a product your former employer could use to gain an advantage over the competition is disruptive. B uying a company on the brink of bankruptcy that has been mismanaged is a scenario entrepreneurs have explored and practiced .

Prompt engineering is the description of a task AI can accomplish , with instructions embedded in the input. Using prompt engineering, users can fine-tune their input to achieve a desired output incorporating a task description to guide the AI model.

Conversation around ChatGPT and Artificial Intelligence

I asked Dr. Short about how students could use this technology as an asset that guides their learning and, additionally, how instructors can use this as well. He spoke about an assignment he is currently using in his classes. “ Chat GPT might be valuable in helping create a recipe for material that students can then refine. For example, in my social entrepreneurship class students create crowdfunding campaigns for either DonorsChoose , a platform that caters to public school teachers or GoFundMe , a service which allows a variety of project types to a larger userbase . I plan on students using ChatGPT to create a ‘rough draft’ to show me so I can see how they refine their responses for their particular campaigns this upcoming fall.” Th is approach allows students to take advantage of popular technology in a constructive way.

The journal article provided some notable conclusions about ChatGPT , i ncluding “ quality control is essential when using automated tools; a hallmark of success for large language models is their vast associative memory, this strength can also be a weakness. Specifically, models such as OpenAI’s GPT-3.5 and GPT-4 are capable of confidently generating “ hallucinated” output that appears correct but, it is incorrect or completely fabricated. ChatGPT serves as an emerging tool that can efficiently and flexibly produce a range of narrative content for entrepreneurs and serve to inspire future research at the intersection of entrepreneurship and AI.” ChatGPT ’s limitations and potential applications are continually being explored.

Industry Application

After researching various applications of AI, I spoke with Dr. George Benson, Professor and Department Chair of the Department of Management at The University of Texas at Arlington, about AI and ChatGPT from an industry perspective. His research focuses on Artificial Intelligence with Human Resource Management .

Dr. Benson told me that Artificial Intelligence is being invested heavily by human resource departments who are looking to automate hiring practices. Specifically, he mentioned “ HR is using this as a market opportunity. AI is a useful tool to sift through potential applicants by scanning their resumes for qualifications and experiences. Allowing professionals to hire applicants faster.”

This application allows the technology to handle low-level tasks, but the results generated are being handed to a human to review and act on. He spoke about the potential of A.I. “ There are a lot of unknowns, but the technology is new and getting better.” Looking towards the future, technology is already being applied in different ways . These applications are being explored in the classrooms of UTA as well.

A group of Alumni discuss rankings in a conference room.

Exploration of AI at UTA

The College of Business conduct ed a survey to understand the faculty’s attitude towards A I in the classroom. It was a part of the “Teaching with Chat GPT” workshop on Friday February 9 th , which focus ed on how to integrate Chat GPT and other AI platforms into teaching .

Dr. Kevin Carr, a Clinical Assistant Professor of Marketing at UTA, was a part of the workshop ; he currently teaches Advanced Business Communication . I talked to him about the purpose of the workshop and what he hopes to gain from the group's sessions.

Dr. Carr explained "The point of the workshop is designed to give faculty ideas for instruction and to develop classroom activities to work with students . Our goal for th e workshop is to introduce Artificial Intelligence as a teaching tool for faculty, including showing what AI can do potentially in the classroom. We are going to be very open to faculty’s direction, in terms of ongoing discu ssions and meetings.”

Personal Take

Artificial Intelligence or Chat GPT , in my view, is another useful tool in the toolbox of technology. It will take the air out of certain industries, and it will change jobs, yet every major technological advancement has the potential to do so. The automobile was considered radical, the use of plastic, computers in the workplace, and alternative energy have been impactful on society.

Alternative energy was headlined as the end of oil use. The automobile changed the way cities were formed and led to the creation of a national highway system. Society has always found a way to adapt and overcome major technological innovations, artificial intelligence is not any different.

AI is the technology of tomorrow. It reminds me of something Dr. George Benson said , “ It's cool software that is a sophisticated search engine.” Google, one of the most popular search engines, reshaped the internet, as you search for resources, it is a natural starting point. AI and ChatGPT are an evolution, for students it is a tremendous resource consulting a CEO archetype, creating business pitches, and most importantly shaping the future .

An unidentified person writes in a journal in front of an open laptop.

News & Events

College of Business News
The Business Maverick
Business Week

IMAGES

Effects of Social Media on Mental Health
(PDF) Social Media and its Effects on Mental Health
(PDF) The Impact of Social Media on Youth Mental Health: Challenges and
Effects Of Social Media On Mental Health Statistics
How Social Media Affects Our Mental Health?
The Effects of Social Media on Mental Health

VIDEO

Are social media influencers making us dumb?
Impact Of Social Media On Mental Health
Social Media has Changed the World 😅

COMMENTS

Social Media and Mental Health: Benefits, Risks, and Opportunities for
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.
The Impact of Social Media on Mental Health: a Mixed-methods Research
the implications of social media for mental health. Additionally, there has been minimal research done regarding the knowledge and preparedness of mental health clinicians to address the impact of heavy social media use on the clients' mental health. Social media's impact on mental health complicates social service delivery
Social Media Use and Its Connection to Mental Health: A Systematic
Social media are responsible for aggravating mental health problems. This systematic study summarizes the effects of social network usage on mental health. Fifty papers were shortlisted from google scholar databases, and after the application of various inclusion and exclusion criteria, 16 papers were chosen and all papers were evaluated for ...
The Impact of Social Media on the Mental Health of Adolescents and
The effects of social media on mental health are complex, ... The research on the impact of social media on mental health is still in its early stages, and more research is needed before we can make definitive recommendations for parents, educators, or institutions. Reaching young people during times of need and when assistance is required is ...
Pros & cons: impacts of social media on mental health
Benefits. The use of social media significantly impacts mental health. It can enhance connection, increase self-esteem, and improve a sense of belonging. But it can also lead to tremendous stress, pressure to compare oneself to others, and increased sadness and isolation. Mindful use is essential to social media consumption.
(PDF) The Impact of social media on Mental Health: Understanding the
The abstract provides a concise summary of the key points discussed in the paper, highlighting the negative effects of social media on mental health, such as increased anxiety and depression, and ...
Social Media and Mental Health: Benefits, Risks, and ...
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 ...
Association of Social Media Use With Social Well-Being, Positive Mental
Yet a growing body of research suggests that social media use is negatively associated with health-related outcomes. Although the relationship between social media use and health, particularly mental health, could be bidirectional, most studies in public health focus on the impact of social media use on health-related outcomes.
The mental health and well-being profile of young adults using social media
The relationship between mental health and social media has received significant research and policy attention. However, there is little population-representative data about who social media users ...
Social Media and Mental Health: Benefits, Risks, and ...
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.
Body Perceptions and Psychological Well-Being: A Review of the Impact
The impact of social media on body image and mental health varies significantly across cultural and gender lines, underscoring the complexity of these phenomena and the influence of societal norms and values in shaping individual responses to digital content. ... For instance, longitudinal research can examine the effects of pivotal life events ...
How social media affects teen mental health: a missing link
Teenagers are now spending more time on social media than ever before — coinciding with a rise in mental-health problems in this age group.Credit: Leon Neal/Getty. Depression, anxiety and ...
A systematic review: the influence of social media on depression
Impact on mental health. Understanding the impact of social media on adolescents' well-being has become a priority due to a simultaneous increase in mental health problems (Kim, Citation 2017). Problematic behaviours related to internet use are often described in psychiatric terminology, such as 'addiction'.
Social media harms teens' mental health, mounting evidence shows. What now?
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 ...
Screen Media Use and Mental Health of Children and Adolescents
Importance Excessive screen media use has been associated with poorer mental health among children and adolescents in several observational studies. However, experimental evidence supporting this hypothesis is lacking. Objective To investigate the effects of a 2-week screen media reduction intervention on children's and adolescents' mental health.
Social media brings benefits and risks to teens. Psychology can help
Even before the COVID-19 pandemic, rates of depression, anxiety, and suicide in young people were climbing. In 2021, more than 40% of high school students reported depressive symptoms, with girls and LGBTQ+ youth reporting even higher rates of poor mental health and suicidal thoughts, according to data from the U.S. Centers for Disease Control and Prevention (American Economic Review, Vol. 112 ...
Exploring adolescents' perspectives on social media and mental health
'Social media' describes online platforms that enable interactions through the sharing of pictures, comments and reactions to content (Carr & Hayes, 2015).As most teenagers regularly use social media (Anderson & Jiang, 2018), studying its effects on their mental health and psychological wellbeing is vital.The term 'psychological wellbeing' reflects the extent to which an individual can ...
Social Media Use and Mental Health: A Global Analysis
Research indicates that excessive use of social media can be related to depression and anxiety. ... Results indicated that most of the students believed there could be both a positive and negative effect of social media on mental health . Gao et al. (2020) investigated the prevalence of depression, anxiety, and a combination of depression and ...
Is social media bad for young people's mental health
July 17, 2023 - On May 23, U.S. Surgeon General Vivek Murthy issued an advisory warning about the potential dangers of social media for the mental health of children and teens. Laura Marciano, postdoctoral research fellow at the Lee Kum Sheung Center for Health and Happiness and in the Department of Social and Behavioral Sciences at Harvard T.H. Chan School of Public Health, says that social ...
Mounting research documents the harmful effects of social media use on
Research shows that social media, ... and adolescents ages 10 to 17 are exposed to toxic beauty content on social media and 1 in 2 say that this has an impact on their mental health. ...
Teens are spending nearly 5 hours daily on social media. Here are the
41%. Percentage of teens with the highest social media use who rate their overall mental health as poor or very poor, compared with 23% of those with the lowest use. For example, 10% of the highest use group expressed suicidal intent or self-harm in the past 12 months compared with 5% of the lowest use group, and 17% of the highest users expressed poor body image compared with 6% of the lowest ...
The psychological effects of social media: A double-edged sword
"However, the impact of social media usage on people's mental health remains unclear. Social media enhances communication, enables people to receive social support, and can improve their ...
Social Media Negatively Impacting Mental Health
Experts have long suspected that social media may be playing a role in the growing mental health crisis in young people. However, the surgeon general's warning is one of the first public warnings supported by robust research. The U.S. surgeon general says the youth mental health crisis is the 'defining public health challenge of our time.'.
Teen social media use
Some critics point to the studies showing correlation rather than causation between, for example, social media and mental health issues. But doing actual experiments on young people that might ...
The Relationship between Social Media and the Increase in Mental Health
Social media has been linked to poor sleep patterns, depression, and anxiety [ 6 ]. In addition, ref. [ 7] warns of the negative impact that excessive social media use can have on the mental health of young people. Saudi Arabia has a high level of social media usage, with 82.3% of the population (29.5 million people) using social media in 2022 ...
ChatGPT: Disruptive or Constructive?
The journal article provided some notable conclusions about ChatGPT, i ncluding " quality control is essential when using automated tools; a hallmark of success for large language models is their vast associative memory, this strength can also be a weakness. Specifically, models such as OpenAI's GPT-3.5 and GPT-4 are capable of confidently generating " hallucinated" output that appears ...

Pros & cons: impacts of social media on mental health

Data Availability

Acknowledgements

Author information

Contributions

Corresponding author

Ethics declarations

Additional information

Rights and permissions

About this article

Share this article

BMC Psychology

The Impact of social media on Mental Health: Understanding the Role of Online Platforms in Psychological Well-being

Save citation to file

Add to My Bibliography

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

Conflict of interest statement

Similar articles

Related information

Grants and funding

LinkOut - more resources

Miscellaneous

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

Cite this article

Introduction

Social Media Use and Mental Health

Facilitate Social Interaction

Access to a Peer Support Network

Promote Engagement and Retention in Services

Challenges with Social Media for Mental Health

Impact on Symptoms

Facing Hostile Interactions

Consequences for Daily Life

Future Directions for Social Media and Mental Health

Author information

Corresponding author

Ethics declarations

Additional information

Rights and permissions

About this article

Share this article

Information

Initiatives

Article Menu

JSmol Viewer

1. Introduction

Share and Cite

Article Metrics

How social media affects teen mental health: a missing link

Access options

Competing Interests

Related Articles

Quick links

Science News

Share this:

Increasing rigor

Cause and effect

A need for nuance

More Stories from Science News on Science & Society

The world has water problems. This book has solutions

Does social status shape height?

In ‘Warming Up,’ the sports world’s newest opponent is climate change

‘After 1177 B.C.’ describes how societies fared when the Bronze Age ended

‘Cull of the Wild’ questions sacrificing wildlife in the name of conservation

Scientists are fixing flawed forensics that can lead to wrongful convictions

Privacy remains an issue with several women’s health apps

Should we use AI to resurrect digital ‘ghosts’ of the dead?

Is social media use bad for young people’s mental health? It’s complicated.

Mounting research documents the harmful effects of social media use on mental health, including body image and development of eating disorders

Disclosure statement

Social media can be harmful

The pros and cons of social media

A breeding ground for eating disorders

‘Thinspo’ and ‘fitspo’

How policy changes could help

Phone-free zones

Apply for State Library of Queensland's next round of research opportunities

Associate Professor, Psychology

Professor and Head of School, School of Communication and Arts

Senior Graduate Research Officer (Admissions and Scholarships)