Social Media Use and Adolescents’ Well-Being: Developing a Typology of Person-Specific Effect Patterns

Abstract

This study investigated the effects of active private, passive private, and passive public social media use on adolescents’ well-being. Intensive longitudinal data (34,930 assessments in total) were collected through a preregistered three-week experience sampling study among 387 adolescents. Person-specific, N=1 time series were investigated, using Dynamic Structural Equation Modeling (DSEM). We identified a typology of person-specific social media effect patterns, consisting of 45% insusceptibles (i.e., adolescents who experienced no effects of the three types of social media use), 28% negative susceptibles (i.e., adolescents who only experienced negative effects), 26% positive susceptibles (i.e., adolescents who only experienced positive effects), and 1% mixed susceptibles (i.e., adolescents who experienced both positive and negative effects). Overall, the findings show that different adolescents respond to social media differently. Yet, active private, passive private, and passive public social media use only rarely yield different effects within one and the same adolescent.

Social Media Browsing and Adolescent Well-Being: Challenging the “Passive Social Media Use Hypothesis”

“…Investigating the idiographic associations of browsing with envy is consistent with theories of envy (Cohen-Charash, 2009), which argue that some individuals may experience no or little envy during or after an envy-inducing experience, whereas others may experience much envy during or after such an experience. It is also consistent with recent media effects studies that adopted an idiographic approach, which have demonstrated that the effect of browsing on well-being differs strongly from adolescent to adolescent (Beyens et al, 2020a(Beyens et al, , 2020b. Based on envy theory (Cohen-Charash, 2009) and these earlier results, it is conceivable that the association of browsing with envy also differs from adolescent to adolescent: (H1).…”

“…For example, in an experience sampling (ESM) study by Beyens et al (2020a) only 10% of adolescents experienced the hypothesized negative effect of passive use on well-being, whereas the remaining adolescents experienced no effect or even a positive effect. In a subsequent study, which is based on the same data set as used in the current study, Beyens, Pouwels, van Driel, Keijsers, and Valkenburg (2020b) found that among 11% of adolescents both active and passive use led to negative effects on well-being. Conversely, among 12% of adolescents both active and passive use led to positive effects on well-being.…”

“…It is based on a three-week ESM wave of this project, which was fielded in December 2019. It builds upon an earlier study by Beyens et al (2020b), which used data of the same ESM wave. Beyens et al (2020b) already demonstrated sizeable heterogeneity in the within-person effects of browsing (i.e., passive public social media use) on well-being.…”

“…It builds upon an earlier study by Beyens et al (2020b), which used data of the same ESM wave. Beyens et al (2020b) already demonstrated sizeable heterogeneity in the within-person effects of browsing (i.e., passive public social media use) on well-being. The current ESM study extends that of Beyens et al (2020b) in that it focuses on the person-specific effects of browsing on envy, inspiration, and enjoyment.…”

“…The aim of this study was to extend the study by Beyens et al (2020b), by examining the conditions that may explain why adolescents respond differentially to browsing. To do so, we investigated a rival hypothesis, which argues that the positivity or negativity of the effects of browsing on well-being does not depend on passive social media use per se, but on personspecific susceptibilities to how social media messages are emotionally processed.…”