0845 The Contributions of Sleep and Circadian Parameters to Adolescents ADHD Symptoms
Bibliographic record
Abstract
Abstract Introduction Attention-deficit/hyperactivity disorder (ADHD) is a chronic and debilitating disorder that negatively impacts adolescents’ academic achievements and interpersonal relationships. Individuals with ADHD are two to three times more likely to experience sleep problems. It has been proposed that untreated sleep problems exacerbate ADHD. However, empirical evidence regarding the relative contributions of specific sleep issues to the daytime manifestation of ADHD symptoms among adolescents is limited. The objective of this study was to determine the relative contributions of sleep and circadian parameters to adolescents' ADHD symptoms. Methods A sample of 40 unmedicated adolescents (26 girls, 18 boys) between the ages of 12 to 15 years (M= 13.9; SD = 0.95) with no psychiatric or medical comorbidities participated in the study. Sleep EEG was recorded using a single night of ambulatory sleep EEG (Sleep Profiler) monitoring with frontal derivations during the school week in the child’s home. Automated sleep/wake scoring was performed using the system followed by visual scoring and analysis by an experienced pediatric sleep specialist. In addition, adolescents were asked to complete questionnaires regarding insomnia and circadian problems and ADHD symptoms. Parents were asked to provide demographic information and complete questionnaires regarding their child’s ADHD symptoms, sleep, and daytime behavior. Results Linear regression analysis revealed that PSG-based sleep duration, adolescents’ reported insomnia symptoms, and parents' reported Restless Leg Syndrome symptoms contributed to the manifestation of adolescents’ ADHD symptoms above and beyond gender or SES. No other effects were significant. Conclusion Adolescents’ ADHD symptoms were related to different sleep problems requiring different interventional strategies. These findings provide compelling motivation for the development of interventions that use sleep as a means to improve the daytime functioning of adolescents with ADHD. Clinical Implications Given the negative impact of unhealthy sleep on adolescents’ mental, cognitive, and physical health, it is essential that clinicians integrate sleep assessments and interventions into their screening, diagnosis and ongoing care for adolescents, particularly when caring for adolescents with behavioral and functional difficulties. Support (if any) CIHR Grant 418638 to Dr. Reut Gruber
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".