Development of Sleep-Wake Schedules During Childhood and Relationship With Sleep Duration
Bibliographic record
Abstract
OBJECTIVES: To present a longitudinal overview of the sleep schedules during weekdays and the weekend in a large sample of children and to examine the sleep-wake schedules in relation to nocturnal sleep duration and birth season. DESIGN: Longitudinal survey design. SETTING: Data were collected by home interviews and questionnaires. PARTICIPANTS: Data for sleep schedules at the ages of 4, 5, and 6 years on weekdays were obtained for 1112 children. Data for bedtimes on the weekend were available for 1094 children, and data for wake times on the weekend were available for 1083 children. OUTCOME MEASURES: Habitual bedtimes and wake times during weekdays and the weekend were reported by the mothers at the 3 ages. Nighttime sleep duration was calculated from bedtime to wake time. Birth characteristics came from medical records. RESULTS: As children grow up, we found later bedtimes on the weekend for a given bedtime on weekdays. Interestingly, most children slept less during the weekend compared with weekdays. No significant difference (P > .10 for all) was found in the seasonal distribution of births in any of the sleep-wake schedules. CONCLUSIONS: Despite a lack of a strong preference for sleep timing during childhood, the displacement of bedtime toward later hours during the weekend starts early in life. More important, sleep-wake patterns are associated with sleep duration and later bedtimes on the weekend seem to shorten sleep duration in most children.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".