0957 The Association Between Sleep and Sustained Attention Differs in Children vs. Adolescents With ADHD
Bibliographic record
Abstract
Abstract Introduction Sleep disturbance in children with attention-deficit/hyperactivity disorder (ADHD) is frequent, and lead to shorter sleep duration which has been associated with lower performance on sustained attention tasks. However, no study has investigated this association in adolescents with ADHD. We sought to explore whether the association between sleep and sustained attention performance of children with ADHD is similar in adolescents with ADHD given that sleep patterns are different. Methods Parents of 32 children (mean age = 8.0; SD = 1.3) and 10 adolescents (mean = 15.2; SD = 1.3) with ADHD completed a developmental questionnaire including sleep questions. Children and adolescents were medication free and underwent a comprehensive neuropsychological evaluation. Three sleep variables were extracted from the questionnaire, namely the duration of the sleep period during week nights and weekends as well as the difference between the two (“weekend shift”). The Continuous Performance Test was used to measure sustained attention (omission, commission, hit reaction time). Pearson correlations between sleep variables and sustained attention measures were calculated. Results Children showed a positive correlation between hit reaction time and the duration of the sleep period during week nights (r = 0.37; p =0.04), weekends (r = 0.51; p = 0.004) and the weekend shift (r = 0.37; p =0.04). No significant correlations were found in the adolescent group. Conclusion The fact that no significant associations were found in the adolescent group suggest an improvement of the arousal system through brain development in ADHD, or that other mechanisms could be involved in the etiology of ADHD in adolescents. Support Centre d’apprentissage aux 1001 astuces; Fonds de recherche du Québec - Santé
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".