Wilderness Adventure Program May Help Combat Perceptions of Stigma Among Veterans
Bibliographic record
Abstract
Operational stress injuries (OSIs) are an increasing concern for military personnel, particularly those returning from conflict zones. Over the last decade, the Canadian Armed Forces (CAF) has seen a sharp increase in the number of soldiers returning from Afghanistan who are reporting OSIs. Efforts have been made by the CAF and other agencies to help this population get the help they need through specialized programming. However, some are still not seeking treatment, in part due to the perceived stigma associated with mental illness. One novel approach to improving mental well-being is the Outward Bound Canada Veterans (OBCV) program. These adventure-based wilderness education courses are shown to have a positive impact on well-being among the veteran population. This study explores how the Outward Bound program facilitates a stigma-free environment which allows participants to more fully benefit from the therapeutic wilderness setting. This exploratory mixed-methods study used a pre-, post-, concurrent-nested mixed-methods design. This small-scale study evaluated the experience of participants (n = 20) in the 2016 program. The Endorsed and Anticipated Stigma Inventory was administered at three times followed by a single semi-structured interview (n = 6) covering themes related to the OBCV program and perceptions of self-stigma and public stigma. This study found that the process of the OBCV program facilitated an environment that was perceived by participants to be stigma-free. Evidence from interviews suggests aspects of self-stigma, such as gaining a sense of personal empowerment, may be positively influenced by participation in wilderness or adventure programs.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".