Feasibility of a 3-week intensive treatment program for service members and veterans with PTSD.
Bibliographic record
Abstract
OBJECTIVE: The purpose of the present study was to detail the patient flow and establish the feasibility of a brief 3-week intensive treatment program (ITP) for veterans with posttraumatic stress disorder (PTSD). METHOD: The present study examined data from 648 veterans referred to a non-Veterans Affairs ITP for PTSD from January 2016 to February 2018 to determine the flow of patients into and through the ITP and evaluate individuals' satisfaction with treatment. RESULTS: On average, 25.9 individuals contacted the ITP each month expressing interest in the program. A large proportion of individuals who completed an intake evaluation were accepted (72.2%) into the ITP. Of those accepted, 70.6% ultimately attended the ITP, and the vast majority of veterans who attended the ITP completed treatment (91.6%). Logistic regression results suggested that among veterans who were accepted to the program, those who were legally separated or divorced had significantly greater odds of attending the program compared to single veterans. Veterans were highly satisfied with the 3-week ITP and rated cognitive processing therapy components as the most helpful part of the program. CONCLUSIONS: The present study demonstrates that ITP formats for PTSD are of interest and acceptable to veterans, and this format allows individuals to receive high doses of evidence-based treatments in a short amount of time. (PsycInfo Database Record (c) 2020 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".