Differential Outcomes of Sleep Problems in Children with and Without Special Health Care Needs
Bibliographic record
Abstract
OBJECTIVE: In a nationally representative sample of Australian children at ages 4 to 5, 6 to 7, 8 to 9, 10 to 11, and 12 to 13 years, we aim to examine the (1) prevalence of sleep problems in children with and without special health care needs (SHCN); (2) association of sleep problems with child behavior, health-related quality of life, learning and parent mental health outcomes; and (3) whether associations between sleep problems and outcomes among children with SHCN are larger in magnitude than among children without SHCN. METHOD: Biennial data from 5 waves of the Growing Up in Australia Study. EXPOSURES: Child SHCN as defined by the Children Special Health Care Needs Screener and parent report of child sleep problem. OUTCOMES: Child: parent-reported health-related quality of life; parent-reported and teacher-reported behavior; nonverbal and verbal cognition and teacher-reported learning. Parent: self-report mental health. ANALYSIS: Logistic and linear regression, adjusted for family socioeconomic position. RESULTS: Children with SHCN were more likely to have sleep problems, odds ranging from 2.0 (95% confidence interval [CI], 1.6-2.5) at 4 to 5 years to 3.9 (95% CI, 3.0-5.2) at 8 to 9 years. Compared with children who had neither condition, those with either sleep problems or SHCN had similarly poor child and maternal outcomes. Children with both SHCN and sleep problems had the poorest outcomes at every age (all p < .001). Tests of interaction found sleep problems are more strongly associated with poorer behavior and health-related quality of life among children with SHCN than those without during the preschool and early school years. CONCLUSION: Sleep problems in children with SHCN are common and are associated with poorer child and maternal outcomes. These associations are stronger for poorer behavior and health-related quality of life among children with SHCN than those without during the preschool and early school years.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".