DIFFERENTIAL EFFECTS OF SPECIFIC SOCIAL MEDIA PLATFORMS (TIKTOK, INSTAGRAM, YOUTUBE) ON MENTAL HEALTH OUTCOMES IN ADOLESCENTS: A SYSTEMATIC REVIEW - Aleksandra Siegmund; Marzena Chrapczyńska; Agnieszka Filarecka; Piotr Przybyszewski; Emilia Przybyszewska; Julia Gatniejewska; Martyna Sienicka; Paulina Prudzic; Weronika Winiarska; Wiktoria Bełcikowska-Skowron (International Journal of Innovative Technologies in Social Science, 2026)
Background. Social media use among children and adolescents has expanded rapidly over the past decade, but most empirical work has examined screen time as a single construct, ignoring meaningful differences between platforms. Objective. This systematic review examined whether use of TikTok, Instagram, and YouTube is associated with distinct mental health outcomes in young people aged 6–18 years. Methods. PubMed and Google Scholar were searched between January and March 2026 in line with the PRISMA 2020 guidelines. Eligible records reported quantitative or qualitative data on at least one of the three platforms in relation to depression, anxiety, body image, self-esteem, problematic or addictive use, or general wellbeing. Methodological quality was rated with the Newcastle–Ottawa Scale for observational studies and AMSTAR-2 for evidence syntheses. Of 257 identified records, 32 met the inclusion criteria. Results. TikTok use was the most consistently linked to harm: depressive and anxiety symptoms, problematic use, and body-image disturbance, with a particularly strong contribution from algorithmic content delivery. Instagram findings centred on appearance comparison, body dissatisfaction, and self-criticism, and these effects tracked content type more closely than time on the platform. YouTube produced a more heterogeneous picture, including improvements in mental health literacy alongside concerns about uneven information quality and exposure to body-related content such as mukbang videos. Conclusion. Total time on social media is a poor proxy for risk. Platform design, content type, and algorithmic curation appear to drive distinct outcomes, and policy and clinical responses should be tailored accordingly.