Using Parental Report to Identify Children at Risk for Poor Sleep and Daytime Problems
Bibliographic record
Abstract
OBJECTIVE: To examine objective sleep patterns and the daytime behavioral, emotional and academic functioning of school-age children above and below the clinical cutoff score for the Child Sleep Habits Questionnaire (CSHQ), which is a parental-report-based measure of sleep disturbances. PARTICIPANTS: 48 boys and 74 girls aged 7-11 years. METHODS: Participants' sleep was assessed in their home environment using a miniature actigraph (AW-64 series; Mini-Mitter, Sunriver, OR, USA) for five consecutive weeknights. The parents provided their child's report card and completed a battery of questionnaires that included the CSHQ, the Child Behavior Checklist, a demographic questionnaire and a health questionnaire. RESULTS: Children that were above the cutoff score of the CSHQ had later objectively measured sleep schedule, were less likely to obtain the recommended amount of sleep for their age, had higher levels of internalizing and externalizing symptoms and a higher prevalence of clinical levels of externalizing and internalizing problems, had lower grades in English and French as a Second Language, and were more likely to fail these subjects. Discriminant analysis revealed that information from the objective sleep and emotional/behavioral and academic measures could significantly discriminate between those with or without parent-reported sleep disturbance. CONCLUSION: Parental reports of sleep disturbances can be used to identify children at increased risk for sleep, emotional, behavioral and academic problems. Such questionnaires should be incorporated into clinical practice and school-based evaluations with the goal of identifying undiagnosed children who might be at risk for poor adjustment related to night- and daytime difficulties.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".