Cross sectional associations of screen time and outdoor play with social skills in preschool children
Bibliographic record
Abstract
Screen time and physical activity behaviours develop during the crucial early childhood period (0-5 years) and impact multiple health and developmental outcomes, including psychosocial wellbeing. Social skills, one component of psychosocial wellbeing, are vital for children's school readiness and future mental health. This study investigates potential associations of screen time and outdoor play (as a proxy for physical activity) with social skills. Cross sectional data were available for 575 mothers with a child (54% boys) aged 2-5 years. Mothers reported their child's screen time, outdoor play time and social skills (Adaptive Social Behavior Inventory; ASBI). Multiple linear regression analyses assessed associations of screen and outdoor play time (Model 1) and compliance with screen time and physical activity recommendations (Model 2) with three ASBI subscales. Boys and girls spent a mean of 2.0 and 2.2 hours per day in screen time, and 3.3 and 2.9 hours per day in outdoor play, respectively. Girls scores for express and comply skills were significantly higher than boys (p<0.005). After applying the Benjamini-Hochberg Procedure to adjust for multiple associations, children's television/DVD/video viewing was inversely associated with their compliant scores (B = -0.35 95% CI -0.26, -0.14; p = 0.001) and outdoor play time was positively associated with both expressive (B = 0.20 95% CI 0.07, 0.34; p = 0.004) and compliant (B = 0.22 95% CI 0.08, 0.36; p = 0.002) scores. Findings indicate that television/DVD/video viewing may be adversely, and outdoor play favourably, associated with preschool children's social skills. Future research is required to identify the direction of causation and explore potential mechanisms of association.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".