Background: Social media use has complex associations with mental health and well-being, particularly among children, adolescents and young adults. I analysed how gender and family factors may modify associations between social media use (SMU)/phone-based interpersonal communication (PIC), self-esteem and depression over time among 10-21-year-olds in the UK and 14-18-year-olds in South Korea.

Methods: I used two longitudinal datasets, the UK Household Longitudinal Study (UKHLS) and the Korean Children and Youth Panel Survey (KCYPS) to examine whether self-esteem (UKHLS and KYCPS) and depression (KCYPS) changed over time with SMU/PIC, using linear mixed-effects modelling. A key aspect of my work investigated whether gender and family factors such as parent-child relationship quality (UKHLS) and parenting styles (KCYPS) confound or modify these associations.

Results: Using the UKHLS, female non-users had higher baseline self-esteem than light users (β = 0.34; 95% CI: [0.03, 0.64]) but moderate (β = -0.21; 95% CI: [-0.47, 0.04]) and heavy users (β = -0.30; 95% CI: [-0.62, 0.02]) had lower baseline self-esteem than light users. This association was absent in males. Family structure moderated the association between the duration of social networking site use and self-esteem at baseline in females (p=0.022).

Using the KCYPS, gender did not moderate the associations between computer SMU/PIC, self-esteem and depression (p>0.05). Higher frequency of computer SMU was associated with lower self-esteem (β = -0.48; 95% CI: [-0.71, -0.25]) and higher log-transformed depression (Model 3: β = 0.02; 95% CI: [0.01, 0.04]) at baseline. Higher frequency of PIC was associated with higher self-esteem at baseline (β = 0.38 95% CI: [0.09, 0.66]). Positive parenting moderated the associations between computer SMU/PIC and self-esteem at baseline (p=0.045 and p=0.018, respectively).
 
Conclusions: The relationships between SMU/PIC, self-esteem and depression may vary according to sociodemographic factors. A nuanced understanding of social media usage patterns could inform policies and interventions, which should consider gender-, family- and country-specific variations.