Private screen access in early adolescence predicts subsequent academic and social impairment at the end of high school for boys and girls
Bibliographic record
Abstract
INTRODUCTION: Youth media guidelines in Canada and the United States recommend that bedrooms should remain screen-free zones. This study aims to verify whether bedroom screens at age 12 years prospectively predict academic and social impairment by age 17 years. METHODS: Participants were from the Quebec Longitudinal Study of Child Development birth cohort (661 girls and 686 boys). Linear regression analyses estimated associations between having a bedroom screen (television or computer) at age 12 years and selfreported overall grades, dropout risk, prosocial behaviour and likelihood of having experienced a dating relationship in the past 12 months at age 17 years, while adjusting for potential individual and family confounding factors. RESULTS: For both girls and boys, bedroom screens at age 12 years predicted lower overall grades (B = -2.41, p ≤ 0.001 for boys; -1.61, p ≤ 0.05 for girls), higher dropout risk (B = 0.16, p ≤ 0.001 for boys; 0.17, p ≤ 0.001 for girls) and lower likelihood of having experienced a dating relationship (B = -0.13, p ≤ 0.001 for boys; -0.18, p ≤ 0.001 for girls) at age 17. Bedroom screens also predicted lower levels of prosocial behaviour (B = -0.52, p ≤ 0.001) at age 17 years for boys. CONCLUSION: The bedroom as an early adolescent screen-based zone does not predict long-term positive health and well-being. Pediatric recommendations to parents and youth should be more resolute about bedrooms being screen-free zones and about unlimited access in private exposures in childhood.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".