Short Nighttime Sleep-Duration and Hyperactivity Trajectories in Early Childhood
Bibliographic record
Abstract
OBJECTIVES: Our objectives were to investigate the developmental trajectories of nighttime sleep duration and hyperactivity over the preschool years and to identify the risk factors associated with short nighttime sleep duration and high hyperactivity scores. DESIGN, SETTING, AND PARTICIPANTS: Nighttime sleep duration and hyperactivity were measured yearly by questionnaires administered to mothers of 2057 children from age 1.5 to 5 years. Developmental trajectories of nighttime sleep duration and hyperactivity throughout early childhood were analyzed to determine interassociations. A multinomial logistic regression was performed to determine which factors among selected child, maternal, and family characteristics and parental practices surrounding sleep periods in early childhood were associated with short nighttime sleep duration and high hyperactivity scores. RESULTS: The trajectories of nighttime sleep duration and hyperactivity were significantly associated. The odds ratio (OR) of reporting short nighttime sleep duration was 5.1 for highly hyperactive children (confidence interval [CI]: 3.2-7.9), whereas the OR of reporting high hyperactivity scores was 4.2 for persistently short sleepers (CI: 2.7-6.6). The risk factors for reporting short nighttime sleep duration and high hyperactivity scores were (1) being a boy, (2) having insufficient household income, (3) having a mother with a low education, and (4) being comforted outside the bed after a nocturnal awakening at 1.5 years of age. CONCLUSIONS: The risk of short nighttime sleep duration in highly hyperactive children is greater than the risk of high hyperactivity scores in short sleepers. Preventive interventions that target boys living in adverse familial conditions could be used to address these concomitant behavioral problems.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| 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".