Assessment of Executive and Cognitive Functions in Children with Restless Sleep Disorder: A Pilot Study
Bibliographic record
Abstract
Restless sleep disorder affects children and is characterized by frequent nocturnal movements, iron deficiency, and daytime symptoms such as poor school performance or behavioral problems. Although sleep parameters have been thoroughly studied and daytime sleepiness has been previously assessed, neurocognitive and executive functions have not. In this study, we evaluated neurocognitive functions in a group of 13 children diagnosed with restless sleep disorder using the National Institute of Health Toolbox (NIH toolbox). The mean age was 10.62 (S.D. 2.785). Among them, seven were male and six were female. The fully corrected T-scores (adjusted for demographic variables: age, ethnicity, and education level) showed the lowest values for the Flanker test (selective attention) and dimensional change card sorting test (cognitive flexibility and inhibitory control), with a very large effect size vs. the corresponding expected frequencies. For all the other tests, the average scores were 50; however, individual children scored low on pattern recognition and two composite scores (fluid and total). In conclusion, these data support the fact that cognitive functions are affected in children with restless sleep disorder, especially selective attention. Clinicians must recognize sleep disorders and daytime impairment in order to promptly intervene and prevent cognitive impairments.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".