The role of veterans' PTSD symptoms in veteran couples' insomnia
Bibliographic record
Abstract
Insomnia contributes to individual mental and physical health and relationship well-being. Veterans' PTSD symptoms are associated with their own insomnia. However, research has not explored whether and how veterans' PTSD symptoms are associated with their partners' insomnia. The present study examined the association between veterans' PTSD symptom severity and veterans' and partners' insomnia. Veterans (n = 192) and their partners (n = 192; total N = 384) completed baseline assessments in a PTSD treatment study for veterans with PTSD and their partners. Path analysis was used to examine the relation between veterans' PTSD symptom severity, as measured by the PTSD symptom checklist-5 (PCL-5) and veterans' and partners' insomnia, as measured by the Insomnia Severity Index (ISI). Veterans' full-scale PCL-5 was positively related to veterans' and partners' insomnia. For veterans, intrusion and arousal symptoms were positively related to their own insomnia severity, while veterans' negative alterations in cognition and mood were associated with partners' insomnia severity. In exploratory analyses, partners' depressive symptoms fully mediated the relation between veterans' negative cognitions and mood and partners' insomnia. PTSD symptoms impact both veterans' and partners' insomnia. However, different PTSD symptom clusters were related to insomnia for each partner, and the link for partners was explained by their own depression symptoms. PTSD, insomnia, and integrated treatments should consider strategies for including partners in treatment to address these interconnected problems.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".