Association Between Physical Activity, Screen Time and Sleep, and School Readiness in Canadian Children Aged 4 to 6 Years
Bibliographic record
Abstract
OBJECTIVE: School readiness is strongly associated with a child's future school success and well-being. The primary objective of this study was to determine whether meeting 24-hour movement guidelines (national physical activity, sedentary behaviors, and sleep recommendations) was associated with school readiness measured with mean scores in each of the 5 developmental domains of the Early Development Instrument (EDI) in Canadian children aged 4 to 6 years. Secondary objectives include examining the following: (1) the association between meeting 24-hour movement guidelines and overall vulnerability in school readiness and (2) the association between meeting individual physical activity, screen use and sleep recommendations, and overall school readiness. METHODS: A prospective cohort study was performed using data from children (aged 4-6 years) who participated in a large-scale primary care practice-based research network. RESULTS: Of the 739 participants (aged 5.9 + 0.12 years) in this prospective cohort study, 18.2% met the 24-Hour Movement Guidelines. Linear regression models (adjusted for child/family demographic characteristics, number of siblings, immigration status, and annual household income) revealed no evidence of an association between meeting all 24-hour movement guidelines and any of the 5 domains of the EDI (p > 0.05). Adjusted linear regression models revealed evidence of an association between meeting screen use guidelines and the "language and cognitive development" (β = 0.16, p = 0.004) domain, and for the sleep guideline, there was a statistically significant association with the "physical health and well-being" (β = 0.23, p = 0.001), the "language and cognitive development" (β = 0.10, p = 0.003), and the "communication skills and general knowledge" (β = 0.18, p < 0.001) domain. CONCLUSION: Early lifestyle interventions targeting screen use and sleep may be beneficial for improving a child's readiness for school.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".