A systematic review of interventions for supporting partners of military Veterans with PTSD
Bibliographic record
Abstract
Introduction: Partners of military Veterans with post-traumatic stress disorder (PTSD) and other mental health difficulties can themselves develop difficulties with stress, well-being, and secondary trauma. Various interventions exist which involve partners of military personnel, but very few with an explicit focus on the partners’ well-being. This article aims to conduct a systematic review of these interventions and outline the range of interventions and the outcomes measured. Methods: We conducted a systematic literature search, from which 25 papers were reviewed. Papers were included if they described any form of intervention in which a partner was involved, where the Veteran was described as having PTSD, and where the aim of the intervention was aimed at least partly at improving the well-being of partners. Results: We found various types of interventions, such as group-based interventions, residential retreats, couples therapies, Internet-based interventions, and family-based interventions. Of the 25 studies reviewed, 21 reported on well-being outcomes, either via randomized controlled trials (RCTs), evaluations, or case studies. In most cases, interventions reported improvements in the well-being of partners, although there were very few controlled studies. Only a small number of interventions were aimed solely at partners. The most common feature of interventions was psychoeducation on topics such as communication, problem solving, and emotion regulation. Many papers described the advantages of group processes such as social support and normalization, gained from partners sharing experiences with one another. Discussion: A wide range of formats exist of interventions for improving the well-being of military partners. The literature would benefit from more robust experimental research into their effectiveness, and exploration of interventions aimed directly at the well-being of partners.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".