Digital dependency in higher education: Identifying critical usage thresholds and risk patterns in social media addiction among university students

This study examines how university students transition from normal to problematic social media use by identifying critical behavioral thresholds, demographic risk factors, and platform-specific usage patterns. Survey data from 705 Turkish university students were analyzed using regression discontinuity analysis, segmented regression, k-means clustering, and binary logistic regression. Two non-linear inflection points emerged in the usage–addiction relationship, marking the boundaries between low, moderate, and high addiction severity. Beyond these points, addiction severity and its academic, psychological, and social consequences increased disproportionately rather than linearly. Female undergraduates aged 18 to 19 years and students in unstable relational circumstances showed the highest vulnerability (p < 0.001). Platform-specific analyses identified TikTok as the highest-risk platform, with users reporting longer session durations, greater academic disruption, and more frequent sleep disturbances than users of other platforms. Temporal analyses further revealed that late-night and extended sessions were strongly associated with self-regulatory breakdowns. By integrating Uses and Gratifications Theory with Self-Regulation Theory, the study offers a dual-lens framework that links motivational drives to control failures in explaining digital dependency. The findings provide evidence-based benchmarks for early detection and targeted intervention, highlighting the need for universities to implement digital literacy education, self-regulation training, and platform-sensitive prevention strategies.