ArticleInternational journal of human-computer interaction2026
Modeling Daily Digital Experiences in Adolescents: A Multilevel Latent Class Analysis of Social Media Engagement Patterns and Exposure to Alcohol-Related Content.
Article in International journal of human-computer interaction, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This study used multilevel Latent Class Analysis (mLCA), a day-level, person-centered approach to examine adolescents' social media engagement, and associated it with exposure to alcohol-related content. Participants were 302 adolescents (Mage = 16.21) who completed 21 days of ecological momentary assessment and weekly surveys. Using multilevel latent class analysis, we identified six distinct engagement types: No Use, Passive Use, Liked/Reacted, Moderate Engagement, Discussion, and High Engagement. Sixty-one percent of adolescents spent most days in one dominant class. Exposure to alcohol-related content from peers or followed accounts predicted more active engagement days, consistent with social learning processes. Exposure from peers is related to temporary social media disengagement, whereas exposure from followed accounts predicted reactive use. Reliance on self-report and the absence of private-messaging measures are noted limitations. Findings highlight dynamic daily processes linking online engagement with substance-use risk contexts.
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