Social Media and Adolescent Well-Being: Annotated Bibliography

Research question: How should researchers explain the relationship between adolescents' social media use and psychological well-being when large studies reach different conclusions? The three sources below were selected because they represent distinct but complementary roles: a large longitudinal trend analysis, a large cross-sectional specification-curve analysis, and a theoretical model explaining why effects vary across people and contexts.

The annotations separate what each source found from what the source can legitimately establish. That distinction matters because association, mechanism, and individual susceptibility are different claims. The bibliography is organized to help a later literature review compare methods and frameworks rather than stack three disconnected summaries.

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

Twenge and colleagues analyze large U.S. adolescent datasets to examine changes in depressive symptoms and suicide-related outcomes after 2010. The article connects those trends with the rapid expansion of new-media screen use and reports stronger associations among girls. Its value lies in the scale of the datasets and the effort to compare mental-health trends with changes in adolescents' activities over time.

The study is useful as population-level evidence, but its design does not establish that screen use directly caused the observed mental-health changes. Historical trends can move together for several reasons, and self-reported activity measures may not capture platform, content, or context. In a literature review, this source should introduce the exposure-and-harm framework while being paired with research that tests effect size and heterogeneity more directly.

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

Orben and Przybylski use data from more than 350,000 adolescents and apply specification-curve analysis to test how analytical choices affect the relationship between digital-technology use and well-being. They report a negative association, but the relationship is small and sensitive to how researchers define and model both technology use and well-being.

The article is especially credible for a methods-focused discussion because it makes analytical flexibility visible instead of presenting one preferred model as inevitable. Its limitation is that broad measures of digital use can flatten meaningful differences among active communication, passive browsing, cyberbullying, and supportive interaction. This source should serve as a counterweight to broad causal claims and support an argument for more precise measurement.

Valkenburg, P. M., & Peter, J. (2013). The differential susceptibility to media effects model. Journal of Communication, 63(2), 221–243.

Valkenburg and Peter propose the differential susceptibility to media effects model, which explains media outcomes through dispositional, developmental, and social-context differences. The model treats media effects as conditional and transactional: individual characteristics shape media use, media experiences influence later states, and those outcomes can feed back into future use.

This source does not resolve the size of social media's effect on adolescent mental health by itself. Its value is conceptual. It provides a mechanism for explaining why average effects may be small while some adolescents experience meaningful harm or benefit. In the final project, the model can organize the synthesis around moderators rather than forcing the evidence into a simple harmful-versus-harmless verdict.