The mental health experience of treatment-seeking military members and public safety personnel: a qualitative investigation of trauma and non-trauma-related concerns
Bibliographic record
Abstract
INTRODUCTION: Paramedics, firefighters, police officers and other public safety personnel (PSP) as well as Canadian Armed Forces (CAF) members are frequently exposed to stressors and demanding work environments. Although their specific work-related tasks may vary, a commonality between these occupations is the significant likelihood of repeated exposure to potentially psychologically traumatic events (PPTE) over the course of their careers. Due in part to these repeated exposures, CAF members and PSP are at an elevated risk of mental health concerns including posttraumatic stress disorder. The purpose of this study was to obtain a more in-depth understanding of the trauma- and non-trauma-related experiences of active or retired PSP and CAF members that may be implicated in mental health issues and resultant treatment and recovery. METHODS: Study participants were recruited during inpatient treatment at a private mental health and addictions inpatient hospital in Canada. We conducted and audiotaped semistructured focus groups and transcribed the discussions. Interpretive phenomenological analysis and thematic coding generated a coding scheme from which to identify concepts and linkages in the data. RESULTS: Analysis generated four primary themes: interpersonal relationships, personal identity, mental health toll and potential moral injury. A variety of subthemes were identified, including family dynamics, inability to trust, feelings of professional/personal betrayal, stigma within the CAF/PSP culture, increased negative emotions about self/others, and a reliance on comradery within the service. CONCLUSION: The information gathered is critical to understanding the perspectives of PSP and military members as the career stressors and related exposure to PPTE of these occupations are unique.
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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".