ArticleBMC public health2026
Algorithmic recommendation and adolescent mental health: a grounded theory study of social and commercial determinants.
Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Adolescents' Experiences of Social Media Content Types and Wellbeing: A Photo-Elicitation Interview Study.Journal of adolescence · 2026Article
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Authors and funding
8 authors.
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Abstract
backgroundExisting digital mental health research tends to frame social media in individualistic terms, emphasising screen-time, self-control, or personal vulnerability. Less attention has been given to the role of algorithmic recommendation systems in population mental health. We aimed to develop a grounded theory of how adolescents experience algorithmically curated feeds and how these experiences relate to mental health and wellbeing.
methodsWe conducted semi-structured, photo-elicitation interviews with 27 UK young people aged 14-19 years. Participants shared screenshots from their TikTok 'For You' and Instagram 'Explore' pages to support discussion of algorithmically recommended content. Data were analysed using constructivist grounded theory, with iterative coding, memo-writing, and theoretical sampling.
resultsWe identify algorithmically structured exposure as a central mechanism through which engagement-driven recommendation systems shape young people's digital mental health. Algorithms organised what content participants encountered, how frequently, and with what emotional intensity, within broader socioecological contexts. Three interlocking processes sustained exposure; algorithmic reinforcement of engagement, emotional feedback loops between mood and recommendations, and a persistent sense of limited control despite high awareness. Although participants developed adaptive strategies and algorithmic literacy, these were unevenly distributed and often insufficient within engagement-driven, profit-oriented systems.
conclusionsDigital mental health may be produced through interactions between individual capacities, social environments, and commercially driven platform design. Protecting population mental health therefore requires multi-level action, including developmentally appropriate social media and algorithmic literacy education alongside structural reforms to recommendation systems, transparency, and platform governance.
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