| Sumario: | Highlights: What are the main findings? Problematic use of the internet (PUI) was the strongest and most consistent predictor of both weekday and weekend screen time in a clinical child and adolescent psychiatric sample. PUI alone accounted for 15.0% of the variance in weekday screen time. Externalizing symptoms predicted weekday but not weekend screen time. This pattern may reflect context-specific differences and could be related to the daily structure imposed by school obligations. What are the implications of the main findings? Clinical assessment of digital engagement in adolescents should prioritize PUI over aggregate screen time duration, as screen time alone fails to capture the compulsive quality of digital engagement in this population. Screen time reduction interventions are unlikely to be sufficient without addressing the underlying motivational and regulatory mechanisms driving excessive digital engagement, particularly PUI, in clinically referred youth. Structured daily routines in inpatient and day clinic settings may serve a protective function by limiting the expression of compulsive or symptom-driven digital engagement, a pattern that, if replicated, may have relevance for therapeutic program design. Background/Objectives: Screen time in children and adolescents has become a prominent public health concern, yet most research has focused on community samples, leaving clinically referred youth underrepresented. This study examined predictors of weekday (WD-ST) and weekend screen time (WE-ST) in a clinical child and adolescent psychiatric sample, with a particular focus on problematic use of the internet (PUI), externalizing symptoms, and fear of missing out (FoMO). Methods: A retrospective secondary analysis of pooled datasets from multiple clinical studies was conducted with 173 adolescents (66.5% female; age range 12–18 years) receiving child and adolescent psychiatric treatment at the University Hospital of Salzburg, Austria. Multivariate linear regression analyses examined self-esteem, adaptive and maladaptive emotion regulation strategies, internalizing and externalizing symptoms, FoMO, and PUI as predictors of WD-ST and WE-ST separately. p-values were adjusted for multiple comparisons using the Benjamini–Hochberg False Discovery Rate correction. Results: In the follow-up hierarchical regression models, PUI was the strongest and most consistent predictor across both models, independently explaining 15.0% of variance in WD-ST time and remaining the only significant predictor in the final WE-ST. Externalizing symptoms significantly predicted WD-ST (β = 0.219, p = 0.021) but not WE-ST. FoMO showed a consistent positive association with WD-ST across both regression models, though this did not reach statistical significance. Self-esteem, emotion regulation strategies, and internalizing symptoms were not significantly associated with screen time in either model. Conclusions: Screen time in clinical adolescent populations cannot be adequately captured by duration alone. PUI reflects a compulsive quality of digital engagement independent of broader psychopathological burden, and the observed difference in weekday versus weekend predictors is consistent with a potential role of daily structure, though this was not formally tested in the present study. Routine clinical assessment should prioritize PUI-focused evaluation over aggregate screen time as a more sensitive indicator of clinically relevant digital engagement.
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