Evidence-based treatments for PTSD symptoms resulting from military sexual trauma in women Veterans: A systematic review
Bibliographic record
Abstract
Introduction: Military sexual trauma (MST) can encompass sexual assault and harassment and has been shown to be pervasive across militaries, disproportionately affecting women. The most common psychological consequence is posttraumatic stress disorder (PTSD). This study sought to synthesize the treatments that demonstrate effectiveness in treating PTSD symptoms resulting from MST in women Veterans. Methods: A systematic review explored research into interventions that included measured outcomes of PTSD symptoms resulting from MST. An electronic search for studies published between 1992 and 2022 was conducted. Effect sizes were calculated for all interventions. Results: A total of 998 papers were initially identified, of which 12 met inclusion criteria. Seven interventions were studied, and all reported meaningful impact on PTSD symptoms. Studies with follow-up measurements post-treatment were limited in number (n = 5). Heterogeneity in study design and populations, and definition of MST were observed. Trauma-focused interventions - particularly cognitive processing therapy (CPT) - had the strongest evidence for reducing PTSD symptoms beyond treatment completion. One non-trauma-focused intervention - Trauma Center Trauma-Sensitive Yoga (TCTSY) - similarly demonstrated longitudinal PTSD symptom reductions. Higher dropout rates were reported for trauma-focused therapies compared to non-trauma-focused interventions. Discussion: CPT demonstrated the strongest published evidence base, with emerging evidence for TCTSY. Future attempts should be made to facilitate international comparisons, with a need for a consistent operationalization of MST. A focus on the sequalae resulting from MST beyond PTSD may also allow for developing targeted adjuvant interventions that may improve overall treatment response.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".