| Sumario: | Highlights: What are the main findings? Male sex, older age, higher daily screen time, prior attempts to quit, and using the internet mainly for gaming were independent predictors of problematic internet use among Romanian adolescents. The model explained 43% of the variance in Internet Addiction Test (IAT) scores, highlighting distinct high-risk profiles. What are the implications of the main findings? School-based screening and targeted interventions should prioritize older male students, heavy users, and those primarily engaged in gaming. Findings provide culturally specific evidence from Eastern Europe to inform adolescent digital-health policies and preventive programs. Background: Problematic internet use among adolescents is linked to poorer mental health, academic performance, and social functioning, yet evidence from Eastern Europe remains limited. Methods: We conducted a school-based cross-sectional study at a Romanian high school (Arad County) including 308 students aged 15–18 years (154 males, 154 females). Students completed a demographic/behavioral questionnaire and the 20-item Internet Addiction Test (IAT), a widely used measure of problematic internet use. The prespecified primary analysis was a multivariable linear regression of IAT score on sex, age group, residence, daily screen time, prior attempts to reduce use, and main internet purpose; supporting analyses included t-tests, ANOVA, and Pearson correlation (α = 0.05). Results: In bivariable comparisons, males, older adolescents (17–18 years), and urban residents reported higher IAT scores; screen time correlated with IAT (r = 0.460, p < 0.001), and prior reduction attempts were associated with higher scores (Cohen's d = 0.80). In the adjusted model, male sex (β = 4.97), older age (β = 5.36), greater daily screen time (β = 1.67 per hour), prior attempts to reduce use (β = 4.13), and primarily using the internet for gaming (β = 5.71) remained significant predictors (all p ≤ 0.045); urban residence was not retained (p = 0.218). The model explained 43% of IAT variance (R2 = 0.43). Conclusions: Demographic and behavioral factors independently predict adolescent problematic internet use, highlighting high-risk profiles (older males, heavy screen time, gaming focus, prior reduction attempts). These findings support school-based screening and targeted digital-health interventions in underrepresented contexts.
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