Relations between post-deployment divorce/separation and deployment and post-deployment stressors, social support, and symptomatology in Veterans with combat-related PTSD symptoms
Bibliographic record
Abstract
Introduction: Post-traumatic stress disorder (PTSD) is a highly prevalent diagnosis in combat Veterans. In addition to reduced quality of life in various domains of functioning, PTSD also is associated with poorer relationships and social support, including marital dissatisfaction and divorce. Although post-deployment divorce/separation was noted as problematic in past conflicts, little is known about divorce/separation following modern conflicts, such as Operations Enduring/Iraqi Freedom (OEF/OIF). The present study investigated the relations between post-deployment divorce/separation and post-deployment stressors, social support, and psychiatric symptomatology in OEF/OIF Veterans seeking treatment for PTSD. Methods: We recruited 98 United States (US) male Veterans from OEF/OIF to participate in the study. Marital status of once-married was required for participation. All participants completed consent documentation and a series of diagnostic interviews and self-report measures. Participants were separated into two groups based on their post-deployment marital status (still married vs. divorced/separated). Results: One-third of the sample indicated they divorced/separated following OEF/OIF. Participants that endorsed a post-deployment divorce/separation demonstrated heightened stress during and after deployment as well as significantly less social support compared to participants who remained married. Discussion: The rates of divorce/separation reported in the sample were comparable to samples of the general American population, despite the elevated risk factors in the Veteran sample (e.g., psychiatric diagnosis). Also, Veterans reporting post-deployment divorce/separation endorsed heightened stress and poorer social support, two factors associated with poorer treatment outcome for PTSD. Together, these findings highlight potential factors associated with post-deployment divorce/separation in OEF/OIF Veterans with PTSD.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".