The role of vulnerability in stress‐related insomnia, social support and coping styles on incidence and persistence of insomnia
Bibliographic record
Abstract
Individuals who are more prone to experience situational insomnia under stressful conditions may also be at greater risk to develop subsequent insomnia. While cross-sectional data exist on the link between sleep reactivity (heightened vulnerability to stress-related insomnia) and insomnia, limited data exist on its predictive value. The aim of the study was to evaluate prospectively whether sleep reactivity was associated with increased risk of incident and persistent insomnia in a population-based sample of good sleepers. Social support and coping styles were also investigated as potential moderators. Participants were 1449 adults (Mage = 47.4 years, standard deviation = 15.1; 41.2% male) without insomnia at baseline and evaluated four times over 3 years. Sleep reactivity was measured using the Ford Insomnia Response to Stress Test (FIRST). Additional measures included depressive symptoms, the frequency and perceived impact of stressful life events, social support and coping styles. After controlling for prior sleep history, depressive symptoms, arousal predisposition, stressful life events and perceived impact, individuals with higher sleep reactivity had an odds ratio (OR) of 1.56 [95% confidence interval (CI): 1.13-2.16], 1.41 (95% CI: 0.87-2.30) and 2.02 (95% CI: 1.30-3.15) of developing insomnia symptoms, syndrome and persistent insomnia, respectively. Social support and coping styles did not moderate these associations. Results suggest that heightened vulnerability to insomnia is associated with an increased risk of developing new-onset subsyndromal and persistent insomnia in good sleepers. Knowledge of premorbid differences is important to identify at-risk individuals, as this may help to develop more targeted prevention and intervention strategies for insomnia.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".