Equine Programs for Military Veterans and RCMP Officers with Occupational Stress Injuries: A Qualitative Analysis
Bibliographic record
Abstract
Alternative approaches to mental health and support programming for military veterans and for officers of the Royal Canadian Mounted Police (RCMP) with occupational stress injuries have recently received attention in the field of post-traumatic stress. The purpose of this study was to evaluate the experiences of military veterans and actively serving RCMP officers with occupational stress injuries who participated in an exploratory study using an equine-assisted learning program. Using a focus group research design, 20 veterans and five RCMP officers were interviewed about their experiences in a 4-week equine-assisted learning program. A thematic content analysis, following Braun and Clarke’s (2006) method, revealed five main themes: (1) appreciation for the value of learning new skills, (2) connection with the horse in terms of the human–animal bond, (3) self-regulation and learning to “speak horse,” (4) sense of accomplishment and competence, and (5) transferable skills to everyday life. The qualitative findings of this study provide support for the use of equine-assisted learning programming with military veterans and RCMP members and demonstrate potential as an alternative therapeutic intervention for occupational stress injuries in these populations.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".