Sleep, internalizing symptoms, and health-related quality of life in children with neurodevelopmental disorders: a cross-sectional analysis of cohort data from three research programs in Canada
Bibliographic record
Abstract
Objective: The objectives of this study were to determine rates of sleep disturbances in children with neurodevelopmental disorders (NDDs) within and across disorders and compared to typically developing (TD) children and to describe differences above and below the clinical cut-off for sleep disturbances. In addition, we explored the associations between demographic variables, severity of disorder, sleep disturbances, internalizing symptoms, and health-related quality of life (HRQOL) in children with NDDs. Method: We conducted cross-sectional data analyses of an existing database with community-dwelling children with NDDs (n = 1438) and TD children (n = 140) aged 4–12 years. Parent-reported measures on sleep disturbances using the Children's Sleep Habits Questionnaire (CSHQ), internalizing symptoms using the Revised Children's Anxiety and Depression Scale, and HRQOL using the KINDL-R were assessed. Hierarchical linear regression examined the associations between demographic variables, severity of disorder, sleep disturbances, internalizing symptoms, and HRQOL in children with NDDs. Results: Children with NDDs (8.5 ± 2.1 years, 69.9% M) had significantly greater total sleep disturbance index (TSDI) than TD children [(8.6 ± 2.3 years, 60.0% M) (mean difference = 6.88 [95% CI 5.37, 8.40]; p < 0.001) (n = 838 NDDs (58.3%); n = 120 TD (86.7%)]. Children with severe NDDs reported significantly greater TSDI above the clinical cut-off (i.e., ≥41; CSHQ) than those with less severe NDDs (p < 0.001). Internalizing symptoms (β = −0.082 [95% CI −0.144, −0.019]; p = 0.011) and TSDI (β = −0.226 [95% CI −0.380, −0.073]; p = 0.004) were significantly associated with HRQOL in children with NDDs. Conclusion: Surveillance and management of sleep and internalizing symptoms are needed to improve HRQOL in children with NDDs. Commonalities in sleep disturbances for children with NDDs support transdiagnostic interventions to treat sleep.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".