A Population-Based Analysis of the Temporal Association of Screen Time and Aggressive Behaviors in Adolescents
Bibliographic record
Abstract
Objective: The recent widespread diffusion of screen-based devices among adolescents has raised questions about the effects of screen time on adolescent behavior, including aggressive behaviors. However, previous studies have been methodologically limited in their ability to distinguish between common vulnerability, concurrency, and lasting associations between screen time and aggression among adolescents, and findings are still inconsistent. To address this gap in the literature, time-varying direct and indirect associations between screen time and aggression were investigated. Method: The sample included nearly 4,000 Canadian adolescents who participated in annual surveys for 5 consecutive years. Multilevel statistical models were applied to study between-person effects (common vulnerability), within-person effects (concurrency explaining a priming effect), and lagged-within-person effects (lasting effects explaining a learning process) of screen time (ie, social media use, television viewing, video game playing, computer use) on aggressive behaviors (ie, fighting, conduct problems, hostile thoughts). Screen time effects on aggression through hostility were further studied. Results: Short-lived concurrent relations between different forms of screen time and aggressive behaviors suggested a priming effect. Social media use was further associated with longer lasting increases in conduct problems, suggesting a social learning process, while television viewing showed significant negative lagged-within-person association with hostility, showing a protective effect. Hostile thoughts mediated screen time and aggression associations mainly at between-person levels. Conclusion: The results suggest that the nature of the relation between screen time and aggressive behaviors depends on the type of digital platform through which such content is presented and suggest the need for policies focusing on protecting young users of digital media. Clinical trial registration information: Does Delaying Adolescent Substance Use Lead to Improved Cognitive Function and Reduce Risk for Addiction?; https://www.clinicaltrials.gov/: NCT01655615.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".