To disentangle between-person associations from within-person effects, we analyzed an eight-wave, large-scale, and nationally representative panel dataset (Understanding Society, the UK Household Longitudinal Study, 2009–2016) using random-intercept cross-lagged panel models (2). We adopted a specification curve analysis framework (3, 5)—a computational method which minimizes the risk that a specific profile of analytical decisions yields false-positive results. In place of a single model, we tested a wide range of theoretically grounded analysis options [data is available on the UK data service (6); code is available on the Open Science Framework (7)]…
We first examined between-person associations (Fig. 1, Left), addressing the question Do adolescents using more social media show different levels of life satisfaction compared with adolescents using less? Across all operationalizations, the median cross-sectional correlation was negative (ψ = −0.13), an effect judged as small by behavioral scientists (8). Next, we examined the within-person effects of social media use on life satisfaction (Fig. 1, Center) and of life satisfaction on social media use (Fig. 1, Right), asking the questions Does an adolescent using social media more than they do on average drive subsequent changes in life satisfaction? and To what extent is the relation reciprocal? Both median longitudinal effects were trivial in size (social media predicting life satisfaction, β = −0.05; life satisfaction predicting social media use, β = −0.02).
The effects which are observed are larger for females:
For females, however, social media was a predictor of slightly decreased life satisfaction across all domains, except satisfaction with appearance (b = −0.13 to −0.05 or β = −0.09 to −0.04; Fig. 2, Center). Furthermore, all domains of life satisfaction, except satisfaction with friends, predicted slightly reduced social media use (b = −0.17 to −0.05 or β = −0.11 to −0.07; Fig. 2, Right).
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