Quantifying gender differences in the impact of internet addiction on adolescent depression: A causal inference...

The rising prevalence of adolescent depression in China has raised concerns about internet influence. This study identified predictors of internet addiction (IA) and quantified its gender-specific impact on depression.

In April-May 2023, 8176 adolescents from six (6) junior high schools in Henan, China, were randomly sampled. IA and depression were assessed via the 20-item internet addiction test (IAT) and 10-item Center for Epidemiologic Studies Depression (CESD-10) scale, respectively. IA's impact on depression was analyzed using four approaches: IPW (confounder weighting), DML (high-dimensional control), PSM (covariate balancing), and RA (residual adjustment).

Among the males, 31.8 % reported depression and 17.7 % reported IA while females, 49.4 % reported depression and 21.3 % IA. The mean ages were 14.5 ± 0.94 (males) and 14.4 ± 0.93 (females). DML revealed the overall effect of 0.22 (95 % CI: 0.17-0.23; p < 0.001), higher in males (95 % CI: 0.23, 95 % CI: 0.18-0.31) than females (0.17, 95 % CI: 0.11-0.23). IPW estimated an effect of 0.30 (95 % CI: 0.25-0.34; p < 0.001), also higher in males (0.34, 95 % CI: 0.28-0.39) than females (0.29, 95 % CI: 0.23-0.36). PSM and RA yielded similar results. Predictors of IA included low self-esteem, history of negative life events, poor sleep quality, and one-child family status.

Internet addiction (IA) exacerbates adolescent depression, disproportionately affecting males. Addressing self-esteem, negative life events, poor sleep, and one-child family challenges can mitigate IA's effects. Gender-sensitive interventions, school-based programs, and parental guidance are critical.