97 What is the Association Between Screen Time and Outcomes For Canadian Children?
Bibliographic record
Abstract
Background and aims To determine the association between screen time and child outcomes. Methods 706 mothers who were part of a longitudinal pregnancy cohort were mailed a questionnaire when children were 6 to 8 years of age. Mothers reported the amount of time children spent with computers, television, and video games on an average school day (screen time), BMI, child behavior, and physical activity. Using Pearson chi-square tests or independent sample t-tests, children who had more than 2 hours screen time on an average school day were compared to those who had 2 hours or less. Results 450 mothers completed the questionnaire (response rate 64%). 30% of children had more than 2 hours of screen time during school days, and these children were more likely to take longer than 30 minutes to fall asleep (25% vs. 15%, p=0.006) and less likely to exhibit prosocial behavior (mean 12.88 vs. 13.71, p=0.028). There was no association between screen time and BMI or time spent in physical activity. Compared to mothers of children had 2 hours or less of screen time, mothers of children who had more than 2 hours of screen time were less likely to be satisfied with their child’s level of physical activity (76% vs. 89%, p<0.001). Conclusions The Canadian Paediatric Society guideline recommends no more than 2 hours of screen time per day. More than a third of children exceed this limit on school days, and this may have important implications for children’s sleep and behavior 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".