The role of pubertal status and sleep satisfaction in emotion reactivity and regulation in children and adolescents
Bibliographic record
Abstract
Study Objectives: This study investigated the role of pubertal status and hormones in the association between sleep satisfaction and self-reported emotion functioning in 256 children and adolescents aged 8-15. Methods: Self-report data was provided on sleep duration, sleep satisfaction, and emotion reactivity and regulation, and a saliva sample was obtained for hormone measures. A subset of children also wore an Actigraph watch to measure sleep for a week. Results: Latent-class analysis revealed three classes of sleepers: Satisfied, Moderately Satisfied, and Dissatisfied. Dissatisfied sleepers reported more difficulties with emotion regulation and greater emotion reactivity than Satisfied sleepers. High difficulties with emotion regulation was associated with shorter objective sleep duration, and high emotion reactivity was associated with lower sleep efficiency. For girls, Dissatisfied sleepers reported being further through pubertal development than Satisfied sleepers. There were also significant correlations between pubertal development and shorter sleep duration and longer sleep latency in girls, and shorter and more irregular sleep in boys. Finally, pubertal development in girls was a significant moderator in the relationship between sleep satisfaction and difficulties with emotion regulation in Dissatisfied sleepers, such that being further through puberty and having unsatisfactory sleep resulted in the highest emotion regulation difficulties. Conclusions: This study expands on previous literature by considering the role of sleep satisfaction and the interaction with puberty development on emotion function. Specifically, a role for pubertal development was identified in the association between unsatisfactory sleep and emotion regulation in girls.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".