Bi-directional association between sleep and outdoor active play among 10–13 year olds
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to investigate whether there is a bi-directional relationship between sleep characteristics (time in bed, sleep duration, sleep chronology, and sleep efficiency) and time spent participating in outdoor active play among children. METHODS: Participants consisted of 433 children aged 10-13 years from Kingston, ON, Canada. Time in bed, sleep duration, sleep chronology, and sleep efficiency were measured for 8 consecutive nights using data from a sleep log and Actical accelerometer. Outdoor active play was measured for the 7 days that fell in between these 8 nights using a combination of data from accelerometers, global positioning system loggers, and geographic information systems. Generalized estimating equation models were used to assess the relationships between sleep characteristics and outdoor active play. These models accounted for the repeated measures nested within participants and adjusted for several confounders (e.g., age, sex, family income, neighborhood traffic and green space). RESULTS: Time in bed, sleep duration, sleep chronology, and sleep efficiency were not significantly associated with the following day's outdoor active play. There was a significant (p = 0.017) association between outdoor active play and the following night's time in bed, which suggested that each hour increase in outdoor active play was associated with a 4.0 min increase in time in bed. Outdoor active play was not significantly associated with sleep duration, sleep chronology, or sleep efficiency. CONCLUSIONS: None of the sleep characteristics predicted the following day's outdoor active play. Increase time spent in outdoor active play predicted a longer time in bed, but not sleep duration, sleep chronology, or sleep efficiency.
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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 | 0.001 |
| 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 | 0.000 | 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".