Screen-time is associated with inattention problems in preschoolers: Results from the CHILD birth cohort study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Pre-school children spend an average of two-hours daily using screens. We examined associations between screen-time on pre-school behavior using data from the Canadian Healthy Infant Longitudinal Development (CHILD) study. METHODS: CHILD participant parents completed the Child Behavior Checklist (CBCL) at five-years of age. Parents reported their child's total screen-time including gaming and mobile devices. Screen-time was categorized using the recommended threshold of two-hours/day for five-years or one-hour/day for three-years. Multiple linear regression examined associations between screen-time and externalizing behavior (e.g. inattention and aggression). Multiple logistic regression identified characteristics of children at risk for clinically significant externalizing problems (CBCL T-score≥65). RESULTS: Screen-time was available for over 95% of children (2,322/2,427) with CBCL data. Mean screen-time was 1·4 hours/day (95%CI 1·4, 1·5) at five-years and 1·5 hours/day (95%CI: 1·5, 1·6) at three-years. Compared to children with less than 30-minutes/day screen-time, those watching more than two-hours/day (13·7%) had a 2·2-point increase in externalizing T-score (95%CI: 0·9, 3·5, p≤0·001); a five-fold increased odd for reporting clinically significant externalizing problems (95%CI: 1·0, 25·0, p = 0·05); and were 5·9 times more likely to report clinically significant inattention problems (95%CI: 1·6, 21·5, p = 0·01). Children with a DSM-5 ADHD T-score above the 65 clinical cut-off were considered to have significant ADHD type symptoms (n = 24). Children with more than 2-hours of screen-time/day had a 7·7-fold increased risk of meeting criteria for ADHD (95%CI: 1·6, 38·1, p = 0·01). There was no significant association between screen-time and aggressive behaviors (p>0.05). CONCLUSION: Increased screen-time in pre-school is associated with worse inattention problems.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it