Effects of self-control and multidimensional stressors on adolescent internet addiction: An integrated perspective based on path analysis and network structure.

Abstract

As the internet has become deeply embedded in adolescents' everyday lives, Internet Addiction (IA) has emerged as a significant psychosocial concern. Previous studies have predominantly relied on undifferentiated measures, such as total scores of self-controls or negative life events, thereby obscuring the distinct roles of heterogeneous components within addiction-related processes. Grounded in the Compensatory Internet Use Model, the present study integrates mediation analysis with network analysis to systematically examine both macro-level pathways and micro-level structural characteristics associated with multidimensional self-control (self-regulation and impulse inhibition) and multidimensional negative life events in relation to IA. Based on a large-scale survey of 4305 high school students, the results indicate that self-control is significantly and negatively associated with IA, with negative life events partially mediating this relationship. Importantly, notable heterogeneity was observed across distinct stressor domains. Interpersonal stress and learning stress showed relatively stronger indirect associations linking self-control deficits to IA compared with other domains. Network analysis further revealed that learning stress occupied a central position within the network structure, while bridge expected influence analysis identified punishment-related events and health-related events as important nodes connecting different communities. Notably, a non-linear association pattern was observed within the punishment domain, where higher self-control was associated with higher IA under specific punitive stress contexts. Overall, these findings suggest differentiated association patterns across stressor domains and highlight the value of integrating network and mediation approaches to capture multi-level structural relationships in adolescent internet use behaviors.