Actigraphy and Parental Ratings of Sleep in Children with Attention-Deficit/Hyperactivity Disorder (ADHD)
Bibliographic record
Abstract
STUDY OBJECTIVES: To assess various sleep parameters in latency-aged children with ADHD and their normally developing peers through the use of multiple sleep measures. DESIGN: Six sleep parameters were evaluated for two groups of children, ADHD and normal comparison. Each group consisted of 25 children (20 males, 5 females) who ranged in age from 7 to 11 years. All children underwent rigorous diagnostic procedures and the ADHD subjects were selected only if they displayed pervasiveness in their symptomatology and were medication naive. Parents completed a retrospective questionnaire which evaluated sleep problems over the past six months. Additionally, each child wore an actigraph for seven consecutive nights, and the child's parents completed a sleep diary during this time period. SETTING: N/A. PATIENTS OR PARTICIPANTS: N/A. INTERVENTIONS: N/A. RESULTS: Based on the findings from the questionnaire, parents of children with ADHD reported significantly more sleep problems than parents of normally developing children. However, the majority of these sleep differences were not verified through actigraphy or sleep diary data, with the exception of longer sleep duration for children with ADHD and parent reports that describe increased bedtime resistence. It was also found that child-parent interactions during bedtime routines were more challenging in the ADHD group. CONCLUSIONS: Despite the possibility of intrinsic sleep problems such as longer sleep duration, results indicate that many of the sleep problems of children with ADHD may be due to challenging behaviours during bedtime routines. The reason for discrepancies among sleep studies employing objective measures as well as between retrospective and prospective measures are discussed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".