Association between sleep and problematic behaviours in gifted children: a polysomnographic study
Bibliographic record
Abstract
Neurological uniqueness, maladaptive behaviours, as well as atypical sleep patterns are reported to be defining characteristics of giftedness, but this has received little empirical support. We studied the polysomnography recorded sleep of gifted and typically-developing children together with features of maladaptive behaviours. The association of sleep macrostructure and sleep instability with maladaptive behaviours was also investigated in gifted children. In all, 19 gifted children (74% boys) and 17 typically-developing children (76% boys) aged 6-12 years were studied. Giftedness was identified using Renzulli's three-factor definition. The microarousal index, number of awakenings, and number of Stage shifts between sleep stages throughout the night were computed as sleep instability parameters. Maladaptive behaviours were assessed using the Child Behaviour Checklist. We found significantly more Stage N1 and less Stage N3 in gifted children compared to typically-developing children. More Stage N1 sleep was correlated with more externalising problems and less Stage N3 sleep was correlated with more internalising problems. Gifted children also displayed more rapid eye movement (REM) sleep, but this was not significantly correlated with behavioural scales. Gifted children displayed two opposing trends of sleep instability: more instability involving N1 sleep and less instability involving N2, N3 and REM sleep. More total Stage shifts were correlated with more internalising and externalising problems. The results of this study provide initial evidence of polysomnography-based characteristics of giftedness. Further studies are needed to explore common pathways linking sleep alterations and maladaptive behaviours in children with giftedness.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".