Examining the Efficacy and Feasibility of a Residential Retreat Program for First Responders and Veterans with Posttraumatic Stress Disorder: A Pilot Study
Bibliographic record
Abstract
Background: Veterans and first responders suffering from posttraumatic stress disorder (PTSD) often report having difficulties with treatment adherence and exhibit high rates of dropout. To address these issues, previous studies have implemented the use of residential retreat programs, in the populations of interest. However, previous studies have mostly utilized trauma-centered therapy methods, which are accompanied by their challenges and trade-offs. To rectify this, the Learn to Live residential retreat program was formulated, which incorporates non-trauma-centered methods to improve PTSD symptom manifestation and management. Methods: Twenty-one participants registered for the five-day residential retreat program and attended the first day of the program. The primary objective of the pilot trial was to determine the feasibility of the protocol in terms of retention rates and subjective efficacy of the program. Secondarily, the authors sought to examine the potential impact of the program on PTSD symptom manifestation measured by the PTSD Checklist for DSM-5. Results: Of the 21 participants attending the first day of the program, 19 completed all five days. Eighteen participants who finished the program reported finding the program helpful and being willing to recommend the program to others. Similarly, symptoms of PTSD showed statistically significant improvements at a one-month follow-up ( V (17) = 152, P < 0.001), with 12 of the 18 participants exhibiting clinically significant improvements. Conclusion: This pilot trial provided preliminary evidence for the feasibility and efficacy of the program. This provides the groundwork for future randomized controlled trials to establish the effectiveness of similar programs for improving PTSD symptoms in veterans and first responders.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".