Abstract
Concerns about the negative effect of social media on well-being have generated much interest around the development of social media interventions, which aim to change users’ interactions with social media to improve well-being. To aid the effective study and design of such interventions, we introduce a new theoretical approach, guided by self-determination theory. We review current interventions and categorize them by the context in which they intervene: social media platforms, devices, users, families and society. Drawing on established behavioural change models, we then evaluate how social media use affects the core psychological needs of autonomy, competence and relatedness. We propose theoretically grounded design features that can be applied to maximize the effectiveness of future interventions. In response to the increasing calls for interventions to counteract social media risks, our recommendations will inform future research in academia and industry, with practical applications to enhance well-being in this digital age.
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References
Allcott, H., Braghieri, L., Eichmeyer, S. & Gentzkow, M. The welfare effects of social media. Am. Econ. Rev. 110, 629–676 (2020).
Bozzola, E. et al. The use of social media in children and adolescents: scoping review on the potential risks. Int. J. Environ. Res. Public. Health 19, 9960 (2022).
Gunnell, D., Kidger, J. & Elvidge, H. Adolescent mental health in crisis. Br. Med. J. 361, k2608 (2018).
Orben, A., Lucas, R. E., Fuhrmann, D. & Kievit, R. A. Trajectories of adolescent life satisfaction. R. Soc. Open Sci. 9, 211808 (2022).
Tibber, M. S. & Silver, E. A trans-diagnostic cognitive behavioural conceptualisation of the positive and negative roles of social media use in adolescents’ mental health and wellbeing. Cogn. Behav. Ther. 15, e7 (2022).
Weinstein, N. & Przybylski, A. K. The impacts of motivational framing of technology restrictions on adolescent concealment: evidence from a preregistered experimental study. Comput. Hum. Behav. 90, 170–180 (2019).
Meier, A. & Reinecke, L. Computer-mediated communication, social media, and mental health: a conceptual and empirical meta-review. Commun. Res. 48, 1182–1209 (2021).
Radtke, T., Apel, T., Schenkel, K., Keller, J. & von Lindern, E. Digital detox: an effective solution in the smartphone era? A systematic literature review. Mob. Media Commun. 10, 190–215 (2022).
Vanden Abeele, M. M. P. Digital wellbeing as a dynamic construct. Commun. Theory 31, 932–955 (2021).
Odgers, C. L. & Jensen, M. R. Adolescent development and growing divides in the digital age. Dialogues Clin. Neurosci. 22, 143–149 (2020).
Orben, A. & Przybylski, A. K. The association between adolescent well-being and digital technology use. Nat. Hum. Behav. 3, 173–182 (2019).
Perlmutter, E., Dwyer, B. & Torous, J. Social media and youth mental health: assessing the impact through current and novel digital phenotyping methods. Curr. Treat. Options Psychiatry 11, 34–51 (2024).
Valkenburg, P. M. Social media use and well-being: what we know and what we need to know. Curr. Opin. Psychol. 45, 101294 (2022).
Griffioen, N., Van Rooij, M., Lichtwarck-Aschoff, A. & Granic, I. Toward improved methods in social media research. Technol. Mind Behav. 1, 1 (2020).
Parry, D. A. et al. Digital wellbeing applications: adoption, use and perceived effects. Comput. Hum. Behav. 139, 107542 (2023).
Kross, E. et al. Social media and well-being: pitfalls, progress, and next steps. Trends Cogn. Sci. 25, 55–66 (2021).
Orben, A., Meier, A., Dalgleish, T. & Blakemore, S.-J. Mechanisms linking social media use to adolescent mental health vulnerability. Nat. Rev. Psychol. https://doi.org/10.1038/s44159-024-00307-y (2024).
Plackett, R., Blyth, A. & Schartau, P. The impact of social media use interventions on mental well-being: systematic review. J. Med. Internet Res. 25, e44922 (2023).
Roffarello, A. M. & De Russis, L. Achieving digital wellbeing through digital self-control tools: a systematic review and meta-analysis. ACM Trans. Comput. Hum. Interact. 30, 53:1–53:66 (2023).
Leigh, S. & Flatt, S. App-based psychological interventions: friend or foe? BMJ Ment. Health 18, 97–99 (2015).
Neary, M. & Schueller, S. M. State of the field of mental health apps. Cogn. Behav. Pract. 25, 531–537 (2018).
Ryan, R. M. & Deci, E. L. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am. Psychol. 55, 68–78 (2000).
Gillison, F. B., Rouse, P., Standage, M., Sebire, S. J. & Ryan, R. M. A meta-analysis of techniques to promote motivation for health behaviour change from a self-determination theory perspective. Health Psychol. Rev. 13, 110–130 (2019).
Peters, D., Calvo, R. A. & Ryan, R. M. Designing for motivation, engagement and wellbeing in digital experience. Front. Psychol. 9, 797 (2018).
Kruzan, K. P. et al. Social media-based interventions for adolescent and young adult mental health: a scoping review. Internet Interv. 30, 100578 (2022).
Andersen, A. I. O. et al. Can social media use be more health-promoting? Description and pilot evaluation of a school-based program to increase awareness and reflection on the use of social media. Sage Open 14, 21582440241249538 (2024).
Ciarrochi, J. The coming revolution in intervention science: from standardized protocols to personalized processes. World Psychiatry 20, 385–386 (2021).
Ellison, N. & Boyd, D. M. in The Oxford Handbook of Internet Studies (ed. Dutton, W. H.) 151–172 (Oxford Univ. Press, 2013).
Weinstein, E. Adolescents’ differential responses to social media browsing: exploring causes and consequences for intervention. Comput. Hum. Behav. 76, 396–405 (2017).
Agarwal, N. The association of the ‘hide like and view counts’ feature with disordered eating, self esteem, and self image. Int. J. High. Sch. Res. 5, 93–98 (2023).
Zhang, M. R., Lukoff, K., Rao, R., Baughan, A. & Hiniker, A. Monitoring screen time or redesigning it? Two approaches to supporting intentional social media use. In Proc. 2022 CHI Conference on Human Factors in Computing Systems 1–19 (Association for Computing Machinery, 2022).
Quin, F., Weyns, D., Galster, M. & Silva, C. C. A/B testing: a systematic literature review. J. Syst. Softw. 211, 112011 (2024).
Sewall, C. J. R., Goldstein, T. R. & Rosen, D. Objectively measured digital technology use during the COVID-19 pandemic: impact on depression, anxiety, and suicidal ideation among young adults. J. Affect. Disord. 288, 145–147 (2021).
Stiglic, N. & Viner, R. M. Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews. BMJ Open 9, e023191 (2019).
Fitz, N. et al. Batching smartphone notifications can improve well-being. Comput. Hum. Behav. 101, 84–94 (2019).
Dekker, C. A., Baumgartner, S. E., Sumter, S. R. & Ohme, J. Beyond the buzz: investigating the effects of a notification-disabling intervention on smartphone behavior and digital well-being. Media Psychol. 28, 162–188 (2024).
Liao, M. & Sundar, S. S. Sound of silence: does muting notifications reduce phone use? Comput. Hum. Behav. 134, 107338 (2022).
Lyngs, U., Lukoff, K. & Slovak, P. ‘I finally felt I had the tools to control these urges’: empowering students to achieve their device use goals with the Reduce Digital Distraction Workshop. In Proc. 2024 CHI Conference on Human Factors in Computing Systems (eds Mueller, F. F. et al.) 251 (Association for Computing Machinery, 2024).
Lyngs, U. et al. Self-control in cyberspace: applying dual systems theory to a review of digital self-control tools. In Proc. 2019 CHI Conference on Human Factors in Computing Systems 131 (Association for Computing Machinery, 2019).
Lyngs, U. et al. The Goldilocks level of support: using user reviews, ratings, and installation numbers to investigate digital self-control tools. Int. J. Hum. Comput. Stud. 166, 102869 (2022).
Kim, J., Jung, H., Ko, M. & Lee, U. GoalKeeper: exploring interaction lockout mechanisms for regulating smartphone use. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3, 16:1–16:29 (2019).
Hekler, E. B., Klasnja, P., Froehlich, J. E. & Buman, M. P. Mind the theoretical gap: interpreting, using, and developing behavioral theory in HCI research. In Proc. SIGCHI Conference on Human Factors in Computing Systems 3307–3316 (Association for Computing Machinery, 2013).
Klasnja, P., Consolvo, S. & Pratt, W. How to evaluate technologies for health behavior change in HCI research. In Proc. SIGCHI Conference on Human Factors in Computing Systems 3063–3072 (Association for Computing Machinery, 2011).
Grüning, D. J., Riedel, F. & Lorenz-Spreen, P. Directing smartphone use through the self-nudge app one sec. Proc. Natl Acad. Sci. USA 120, e2213114120 (2023).
Vanman, E. J., Baker, R. & Tobin, S. J. The burden of online friends: the effects of giving up Facebook on stress and well-being. J. Soc. Psychol. 158, 496–508 (2018).
Hall, J. A., Xing, C., Ross, E. M. & Johnson, R. M. Experimentally manipulating social media abstinence: results of a four-week diary study. Media Psychol. 24, 259–275 (2021).
Hunt, M. G., Marx, R., Lipson, C. & Young, J. No more FOMO: limiting social media decreases loneliness and depression. J. Soc. Clin. Psychol. 37, 751–768 (2018).
Faulhaber, M. E., Lee, J. E. & Gentile, D. A. The effect of self-monitoring limited social media use on psychological well-being. Technol. Mind Behav. https://doi.org/10.1037/tmb0000111 (2023).
Davis, C. G. & Goldfield, G. S. Limiting social media use decreases depression, anxiety, and fear of missing out in youth with emotional distress: a randomized controlled trial. Psychol. Pop. Media https://doi.org/10.1037/ppm0000536 (2024).
Ferguson, C. J. Do social media experiments prove a link with mental health: a methodological and meta-analytic review. Psychol. Pop. Media https://doi.org/10.1037/ppm0000541 (2024).
Fardouly, J., Magson, N. R., Johnco, C. J., Oar, E. L. & Rapee, R. M. Parental control of the time preadolescents spend on social media: links with preadolescents’ social media appearance comparisons and mental health. J. Youth Adolesc. 47, 1456–1468 (2018).
Tirocchi, S., Crescenti, M. & Catozzella, D. Parental perspectives on smartphone usage: a qualitative study of the ‘smartphone usage agreement’ and other control strategies. Ital. J. Sociol. Educ. 16, 153–180 (2024).
Knopf, A. Technology addiction: 12 steps to the rescue. Alcohol. Drug Abuse Wkly https://doi.org/10.1002/adaw.33931 (2023).
Online Safety Act 2023—Parliamentary Bills. parliament.uk https://bills.parliament.uk/bills/3137 (UK Parliament, 2023).
Kids Online Safety Act, S.1409, 118th Congress. congress.gov https://www.congress.gov/bill/118th-congress/senate-bill/1409/text (2023).
Beland, L.-P. & Murphy, R. Ill communication: technology, distraction and student performance. Labour Econ. 41, 61–76 (2016).
Kessel, D., Hardardottir, H. L. & Tyrefors, B. The impact of banning mobile phones in Swedish secondary schools. Econ. Educ. Rev. 77, 102009 (2020).
Beneito, P. & Vicente-Chirivella, Ó. Banning mobile phones in schools: evidence from regional-level policies in Spain. Appl. Econ. Anal. 30, 153–175 (2022).
Edwards, E. J. & Campbell, M. We looked at all the recent evidence on mobile phone bans in schools—this is what we found. Conversation http://theconversation.com/we-looked-at-all-the-recent-evidence-on-mobile-phone-bans-in-schools-this-is-what-we-found-224848 (11 March 2024).
Gui, M., Gerosa, T., Argentin, G. & Losi, L. Mobile media education as a tool to reduce problematic smartphone use: results of a randomised impact evaluation. Comput. Educ. 194, 104705 (2023).
It’s Time to LOG OFF. LOG OFF https://www.logoffmovement.org/ (LOG OFF, 2024).
Fassi, L. et al. Social media use and internalising symptoms in clinical and community adolescent samples: a systematic review and meta-analysis. JAMA Pediatr. https://doi.org/10.1001/jamapediatrics.2024.2078 (2024).
Jensen, M., George, M. J., Russell, M. R. & Odgers, C. L. Young adolescents’ digital technology use and mental health symptoms: little evidence of longitudinal or daily linkages. Clin. Psychol. Sci. 7, 1416–1433 (2019).
Lahti, H., Kulmala, M., Lyyra, N., Mietola, V. & Paakkari, L. Problematic situations related to social media use and competencies to prevent them: results of a Delphi study. Sci. Rep. 14, 5275 (2024).
Stavropoulos, V., Motti-Stefanidi, F. & Griffiths, M. D. Risks and opportunities for youth in the digital era. Eur. Psychol. 27, 86–101 (2022).
Ryan, R. M. & Deci, E. L. Self-Determination Theory: Basic Psychological Needs in Motivation, Development, and Wellness (Guilford, 2017).
Ryan, R. M., Patrick, H., Deci, E. L. & Williams, G. C. Facilitating health behaviour change and its maintenance: interventions based on self-determination theory. Eur. Health Psychol. 10, 2–5 (2008).
Deci, E. L. & Ryan, R. M. Intrinsic Motivation and Self-Determination in Human Behavior (Springer Science & Business Media, 2013).
Calvo, R. A. & Peters, D. Positive Computing: Technology for Wellbeing and Human Potential (MIT Press, 2014).
Alberts, L., Lyngs, U. & Lukoff, K. Designing for sustained motivation: a review of self-determination theory in behaviour change technologies. Interact. Comput. https://doi.org/10.1093/iwc/iwae040 (2024).
Gagné, M. et al. Understanding and shaping the future of work with self-determination theory. Nat. Rev. Psychol. 1, 378–392 (2022).
Vansteenkiste, M., Ryan, R. M. & Soenens, B. Basic psychological need theory: advancements, critical themes, and future directions. Motiv. Emot. 44, 1–31 (2020).
Ryan, R. M. & Vansteenkiste, M. in The Oxford Handbook of Self-Determination Theory (ed. Ryan, R. M.) 3–30 (Oxford Univ. Press, 2023).
Craig, S. L., Eaton, A. D., McInroy, L. B., Leung, V. W. Y. & Krishnan, S. Can social media participation enhance LGBTQ+ youth well-being? Development of the Social Media Benefits Scale. Soc. Media Soc. 7, 2056305121988931 (2021).
Nesi, J., Choukas-Bradley, S. & Prinstein, M. J. Transformation of adolescent peer relations in the social media context: Part 1—a theoretical framework and application to dyadic peer relationships. Clin. Child Fam. Psychol. Rev. 21, 267–294 (2018).
Nesi, J., Choukas-Bradley, S. & Prinstein, M. J. Transformation of adolescent peer relations in the social media context: Part 2—application to peer group processes and future directions for research. Clin. Child Fam. Psychol. Rev. 21, 295–319 (2018).
Van Der Wal, A., Valkenburg, P. M. & Van Driel, I. I. In their own words: how adolescents use social media and how it affects them. Soc. Media Soc. 10, 20563051241248591 (2024).
Nesi, J. The impact of social media on youth mental health: challenges and opportunities. N. C. Med. J. 81, 116–121 (2020).
Peters, D. & Calvo, R. A. in The Oxford Handbook of Self-Determination Theory (ed. Ryan, R. M.) 978–999 (Oxford Univ. Press, 2023).
Van de Casteele, M. et al. Adolescents’ mental health in the social-media era: the role of offline and online need-based experiences. J. Adolesc. 96, 612–631 (2024).
Sheldon, K. M., Abad, N. & Hinsch, C. A two-process view of Facebook use and relatedness need-satisfaction: disconnection drives use, and connection rewards it. J. Pers. Soc. Psychol. 100, 766–775 (2011).
Ntoumanis, N. et al. A meta-analysis of self-determination theory-informed intervention studies in the health domain: effects on motivation, health behavior, physical, and psychological health. Health Psychol. Rev. 15, 214–244 (2021).
Ryan, R. M. & Deci, E. L. Intrinsic and extrinsic motivations: classic definitions and new directions. Contemp. Educ. Psychol. 25, 54–67 (2000).
Silva, M. N. Testing theory in practice: the example of self-determination theory-based interventions. Eur. J. Health Psychol. 16, 171–180 (2014).
Parent, N. Basic need satisfaction through social media engagement: a developmental framework for understanding adolescent social media use. Hum. Dev. 67, 1–17 (2023).
Weinstein, E. The social media see-saw: positive and negative influences on adolescents’ affective well-being. N. Media Soc. 20, 3597–3623 (2018).
Cranefield, J. et al. Partnering with AI: the case of digital productivity assistants. J. R. Soc. N. Z. 53, 95–118 (2023).
Naslund, J. A., Bondre, A., Torous, J. & Aschbrenner, K. A. Social media and mental health: benefits, risks, and opportunities for research and practice. J. Technol. Behav. Sci. 5, 245–257 (2020).
Acknowledgements
We thank C. Hood, G. Turner, L. Fassi and A. Ferguson for feedback on an earlier version of the manuscript. A.S. and A.O. were funded by the Medical Research Council (MC_UU_00030/13), the Jacobs Foundation and a UKRI Future Leaders Fellowship (MR/X034925/1). A.S. was also funded by the Cambridge Trust.
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A.S.: conceptualization, methodology, investigation, resources, data curation, writing—original draft, writing—review and editing, and visualization. A.O.: writing—review and editing, and supervision.
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Extended Data Fig. 1 Continuum of Motivation According to Self-Determination Theory.
Adapted from Peters et al., 2018 and Ryan and Deci, 2000a.
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Supplementary Information: adolescent focus groups for SMIs.
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Skeggs, A., Orben, A. Social media interventions to improve well-being. Nat Hum Behav 9, 1079–1089 (2025). https://doi.org/10.1038/s41562-025-02167-9
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DOI: https://doi.org/10.1038/s41562-025-02167-9
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