An intensive outpatient program with prolonged exposure for veterans with posttraumatic stress disorder: Retention, predictors, and patterns of change.
Bibliographic record
Abstract
High rates of drop-out from treatment of PTSD have challenged implementation. Care models that integrate PTSD focused psychotherapy and complementary interventions may provide benefit in retention and outcome. The first 80 veterans with chronic PTSD enrolled in a 2-week intensive outpatient program combining Prolonged Exposure (PE) and complementary interventions completed symptom and biological measures at baseline and posttreatment. We examined trajectories of symptom change, mediating and moderating effects of a range of patient characteristics. Of the 80 veterans, 77 completed (96.3%) treatment and pre- and posttreatment measures. Self-reported PTSD (p < .001), depression (p < .001) and neurological symptoms (p < .001) showed large reductions with treatment. For PTSD, 77% (n = 59) showed clinically significant reductions. Satisfaction with social function (p < .001) significantly increased. Black veterans and those with a primary military sexual trauma (MST) reported higher baseline severity than white or primary combat trauma veterans respectively but did not differ in their trajectories of treatment change. Greater cortisol response to the trauma potentiated startle paradigm at baseline predicted smaller reductions in PTSD over treatment while greater reductions in this response from baseline to post were associated with better outcomes. Intensive outpatient prolonged exposure combined with complementary interventions shows excellent retention and large, clinically significant reduction in PTSD and related symptoms in two weeks. This model of care is robust to complex presentations of patients with varying demographics and symptom presentations at baseline. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".