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Abstract
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BACKGROUND: There is mixed evidence as to the effects of different types of social media use on mental health, but previous research has been platform-specific and has focused on an oversimplified distinction between active and passive use. This study aimed to identify different underlying subgroups of adolescent social media user based on their pattern of social media activities and test associations between user type and future mental health.
METHODS: Students from 19 schools (N = 2456) in south-west England completed an online survey measuring 13 social media activities and four psychosocial outcomes (past year self-harm, depression, anxiety and poor well-being) at age 13 years (October 2019) and repeated a year later (October 2020; aged 14 years). Latent class analysis using Mplus identified distinct classes of social media user and stability of these classes was examined using latent transition analysis. A bias-adjusted three-step model was used to test associations between class membership at baseline and mental health at follow-up. Analyses were adjusted for gender, ethnicity, sexual orientation, socioeconomic status, disability, social media screen-time and baseline mental health.
RESULTS: A four-class model of social media user at baseline was selected based on fit statistics and interpretability. User types were labelled High Communicators; Moderate Communicators; Broadcasters; and Minimal users. Users became more active over time. Broadcasters at age 13 had the poorest mental health outcomes at age 14, with mental health and well-being generally better among the High and Moderate Communicators.
CONCLUSIONS: Findings suggest that broadcasters-adolescents with high levels of content sharing in addition to messaging and browsing online-are most likely to be experiencing poor mental health a year later. Recommendations regarding social media use should expand to consider different user types, and mental health implications of their engagement with different online activities in addition to screen-time.
Language: en |