Latent Profile Analysis of Excessive Internet Use in Adolescents: Gender-Specific Pathways to Depression Through Loneliness

Excessive internet use (EIU) has emerged as a significant concern for adolescent mental health, yet existing research often overlooks the heterogeneity of its psychological impact. This study draws on a nationally representative sample of 71,640 Finnish adolescents to identify distinct EIU profiles using latent profile analysis (LPA) and to examine whether loneliness mediates the EIU–depression relationship differently across profiles and gender groups. Four EIU profiles were identified: Low-risk, Moderate-risk, High-involvement with self-control, and High-risk users. Multi-group structural equation modeling revealed substantial variation in mediation mechanisms. Notably, a novel suppression effect emerged among low-risk users, suggesting potential compensatory benefits of moderate internet engagement, while the indirect pathway via loneliness was absent among high-risk users. Gender differences were most pronounced in the loneliness–depression path, with girls consistently showing stronger associations. Findings underscore the developmental importance of gender-sensitive, person-centered approaches to understanding digital risk.