Furthering Our Understanding of Post-Traumatic Mental Health Conditions and Intimate Relationship Outcomes in Veterans of the Wars in Afghanistan and Iraq
Bibliographic record
Abstract
OBJECTIVE: Although there has been substantial research on post-traumatic stress disorder and its commonly comorbid conditions, the unique associations among these mental health symptoms and relationship adjustment have not been investigated. The purpose of this paper is to extend understanding of the associations among PTSD and relationship adjustment for female and male veterans, as well as to account for the impact of comorbid symptoms of depression and problematic alcohol use in a large sample. METHOD: = 1122 men and 1203 women) veterans of the wars in Iraq and Afghanistan from a larger study exploring wartime experiences and post-deployment adjustment. Chi-square analyses and regressions tested the associations among mental health symptoms (PTSD symptom severity, depressive symptoms, and problematic alcohol use) and relationship status and adjustment. RESULTS: For both men and women, those with probable PTSD were less likely to be in an intimate relationship than those without probable PTSD, and those in intimate relationships had lower PTSD symptom severity compared with those not in intimate relationships. However, when accounting for PTSD, depression, and problematic alcohol use simultaneously, only depression emerged as a significant negative predictor of relationship adjustment. CONCLUSIONS: Shared variance among these common post-traumatic mental health conditions comorbidities may be most responsible for PTSD's negative association with relationship adjustment. Unique remaining variance of depression is also negatively associated with relationship adjustment. Treatment implications of these findings for individual and couple therapy post-trauma are provided.
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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) | 0.000 | 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) | 0.000 | 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".