The relation between common sleep problems and emotional and behavioral problems among 2‐ and 3‐year‐olds in the context of known risk factors for psychopathology
Bibliographic record
Abstract
The contribution of sleep problems to emotional and behavioral problems among young children within the context of known risk factors for psychopathology was examined. Data on 2- and 3-year-olds, representative of Canadian children without a chronic illness, from three cross-sectional cohorts of the Canadian National Longitudinal Study of Child and Youth were analysed (n = 2996, 2822, and 3050). The person most knowledgeable (PMK), usually the mother, provided information about her child, herself, and her family. Predictors included: child health status and temperament; parenting and PMK depressive symptomatology; family demographics (e.g., marital status, income) and functioning. Child sleep problems included night waking and bedtime resistance. Both internalizing/emotional (i.e., anxiety) and externalizing/behavioral problems (i.e., hyperactivity, aggression) were examined. Adjusting for other known risk factors, child sleep problems accounted for a small, but significant, independent proportion of the variance in internalizing and externalizing problems. Structural equation models examining the pathways linking risk factors to sleep problems and emotional and behavioral problems were a good fit of the data. Results were replicated on two additional cross-sectional samples. The relation between sleep problems and emotional and behavioral problems is independent of other commonly identified risk factors. Among young children, sleep problems are as strong a correlate of child emotional and behavioral problems as PMK depressive symptomatology, a well-established risk factor for child psychopathology. Adverse parenting and PMK symptomatology, along with difficult temperament all contribute to both sleep problems and emotional and behavioral problems. Children's sleep problems appear to exacerbate emotional and 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".