“Putting Down and Letting Go”: An Exploration of a Community-Based Trauma-Oriented Retreat Program for Military Personnel, Veterans, and RCMP
Bibliographic record
Abstract
(1) Background: Current military members, veterans, and Royal Canadian Mounted Police (RCMP) experience higher rates of posttraumatic stress disorder (PTSD) and moral injury (MI). Trauma-oriented retreats have been offered as a means of addressing these concerns. This article aims to explore the impact of a non-evidence-based trauma-oriented retreat for the above populations experiencing PTSD or MI; (2) Methods: This qualitative study, nested within the larger mixed-methods pre/post longitudinal follow-up study, examined the experiences of 124 military members, veterans, and RCMP who participated in the retreat. Data were collected from semi-structured interviews and first-hand observations of the organization. Analysis was conducted using thematic analysis while being informed by realist evaluation principles; (3) Results: The results showed that important contextual elements were related to participants being ready, having multiple comorbidities and using the program as a first or last resort. Effectual mechanisms included a home-like setting; immersion; credibility of facilitators; experiential learning; an holistic approach; letting go, and reconnecting to self. Outcomes included: re-finding self, symptom management, social connection, and hope for a meaningful life. The gendered analysis suggested less favorable results; (4) Conclusions: Care is warranted as the evidence-base and effectiveness of trauma-oriented retreats yet needs to be established prior to broad use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".