Insomnia and emotion dysregulation: a meta-analytical perspective integrating regulatory strategies and dispositional difficulties
Bibliographic record
Abstract
Insomnia and emotion dysregulation are intricately related, yet their aggregate association across different domains of emotion dysregulation and the effect of moderating factors including health-related status, age, and gender remain unclear. This systematic review and meta-analysis synthesized data from 57 studies, pooling 119 effect sizes from correlational and 55 effect sizes from group comparison studies. By separate analyses, we assessed both the strength of the association and whether clinically significant insomnia symptoms exacerbate difficulty in regulating emotion. Correlational analyses revealed a significant association between insomnia symptoms and emotion dysregulation, primarily in individuals with serious health-related conditions (Fisher Z no-serious condition = 0.22, Fisher Z serious-conditions = 0.37, p < 0.00001). Group comparison analyses indicated that clinically significant insomnia symptoms worsen emotion dysregulation regardless of health-related status (Hedges’ g = 0.99, p = 0.01). The reliance on maladaptive emotion regulation strategies and difficulties in dispositional domains of emotion regulation, particularly impulsivity, were more strongly associated with insomnia than challenges related to adaptive strategies. Age and gender did not impact these associations in either type of study. These findings underscore a robust link between insomnia and emotion dysregulation, suggesting the potential benefits of integrating emotion regulation skills into insomnia management to improve therapeutic outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".