Disorders of Arousal in Children and Associated Emotional–Behavioural Problems: Results From a Non‐Clinical Longitudinal Cohort
Bibliographic record
Abstract
This study aimed to assess the associations between the frequency of episodes of disorders of arousal (sleepwalking and sleep terrors) and emotional-behavioural problems in a longitudinal cohort of healthy children aged 4 and 5 years. Mother-child dyads (N = 345) were recruited during pregnancy for a longitudinal cohort study. Mothers completed validated questionnaires when children were 4 and 5 years old. Linear regressions assessed (1) the concurrent association between the frequency of disorders of arousal episodes (i.e., sleepwalking and sleep terrors) and emotional-behavioural problems in children at 4 and 5; and (2) the association between the frequency of disorders of arousal episodes at 4 and emotional-behavioural problems at 5. Models included the following covariates: child's sex, child's nighttime sleep duration, socioeconomic status and maternal depressive symptoms. More frequent episodes of disorders of arousal at age 4 were significantly associated with more concurrent internalising (B = 2.659, p = 0.001), and externalising problems (B = 2.740, p = 0.006). At age 5, the frequency of episodes was not associated with concurrent internalising and externalising problems (p > 0.05). More frequent episodes at age 4 were associated with more externalising problems at 5 (B = 2.462, p = 0.039). Although sleep terrors and sleepwalking are often benign, our results show that even in a non-clinical cohort, these sleep phenomena can be associated with emotional-behavioural problems in children as young as 4. While the mere presence of sleep terrors or sleepwalking is not alarming, screening for emotional-behavioural problems seems appropriate for children with frequent episodes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".