Back

Depression precedes problematic video streaming in adolescents: Prevalence trends and cross-lagged associations from a four-wave population-based study

Cloes, J.-O.; Klamert, L.; Busch, K.; Paschke, K.

2026-08-02 psychiatry and clinical psychology
10.64898/2026.07.30.26359312 medRxiv
Show abstract

Background: In the age of TikTok, YouTube, and Netflix, video streaming (VS) is highly popular among adolescents. Yet, risky to addiction-like viewing patterns (i.e., problematic (P)VS) may adversely affect well-being. Prevalence estimates based on established criteria and etiological understanding of this phenomenon remain scarce. It is associated with de-pression, a major issue within the youth mental health crisis. However, causality remains unclear. This study investigated prevalence trends of adolescent PVS and its temporal rela-tionship with depression. Methods: Population-based data were drawn from four annual waves (2022-2025) of a rep-resentative online survey among 3,477 German adolescents (aged 10-17 years). Weighted annual PVS prevalence estimates were calculated based on standardized measures applying ICD-11 criteria of behavioural addictions distinguishing pathological from hazardous behav-ioural patterns. A cross-lagged panel analysis examined the reciprocal relationship between PVS and depression over four years. Results: Prevalence of pathological VS ranged between 2 to 4% across waves. Hazardous VS prevalence was 13-14% from 2022 to 2024, before increasing to 25% in 2025. Up to 81% of adolescents with pathological VS (21% with hazardous VS) showed clinically relevant symptoms of depression, versus 8-9% of non-affected adolescents. Depression significantly predicted PVS in two of three lags ({beta}W1-W2=0.233, {beta}W2-W3=0.155), but not vice versa. Conclusions: Prevalence rates and their divergent associations with depression support dis-tinguishing hazardous from pathological VS and underline the clinical relevance of PVS. Depression preceded PVS, pointing to the role of maladaptive coping. This has direct impli-cations for effective intervention measures. Future research should clarify the mechanisms underlying this relationship.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.