Predictors of Long-Term Treatment Outcome in Combat and Peacekeeping Veterans With Military-Related PTSD
Bibliographic record
Abstract
OBJECTIVE: Posttraumatic stress disorder (PTSD) is a significant psychiatric condition that may result from exposure to combat; it has been associated with severe psychosocial dysfunction. This study examined the predictors of long-term treatment outcomes in a group of veterans with military-related PTSD. METHOD: The study consisted of a retrospective chart review of 151 consecutive veterans treated at an outpatient clinic for veterans with psychiatric disorders resulting from their military operations between January 2002 and May 2012. The diagnosis of PTSD was made using the Clinician-Administered PTSD Scale. As part of treatment as usual, all patients completed the PTSD Checklist-Military version and Beck Depression Inventory (BDI-II) at intake and at each follow-up appointment, the Short-Form Health Survey (SF-36) at intake, and either the SF-36 or the 12-item Short-Form Health Survey at follow-up. All patients received psychoeducation about PTSD and combined pharmacotherapy and psychotherapy. RESULTS: Analyses demonstrated a significant and progressive improvement in PTSD severity over the 2-year period ([n = 117] Yuan-Bentler χ²40 = 221.25, P < .001). We found that comorbid depressive symptom severity acted as a significant predictor of PTSD symptom decline (β = -.44, SE = .15, P = .004). However, neither alcohol misuse severity nor the number of years with PTSD symptoms (chronicity) was a significant predictor of treatment response. CONCLUSIONS: This study highlights the importance of treating comorbid symptoms of depression aggressively in veterans with military-related PTSD. It also demonstrates that significant symptom reduction, including loss of probable PTSD diagnosis, is possible in an outpatient setting for veterans with chronic military-related PTSD.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".