A qualitative exploration of the mental health challenges and therapeutic needs of Canadian correctional workers
Bibliographic record
Abstract
Purpose Correctional work is described as a high-stress environment associated with increased prevalence of mental health disorders in employees. Identifying appropriate healthcare services necessitates investigating the mental health challenges and needs of correctional workers (CWs). Methods Individual interviews (n = 9; 5 M and 4 W) and a mixed gender focus group (n = 6; 3 M and 3 W) were conducted to gather a general sense of the mental health landscape. Data were analyzed to develop a targeted and comprehensive question guide for gender-specific focus groups (n = 14 unique participants; 6 M and 8 W). Results Eight themes emerged from the gender-specific focus groups. Themes focusing on work culture described the negative repercussions of job stress and the inability to discuss challenges openly due to confidentiality concerns and feelings of seclusion associated with the CW profession. Men were more likely to be subjected to physical violence and women to emotional and sexual harassment from staff and inmates. Themes related to mental health care described the benefits and limitations of the current services and digital mental healthcare. Stigma and accessibility were notable treatment barriers. Lastly, sector-specific therapy was seen as an important component in enhancing engagement and therapist interaction. Conclusion The study demonstrates the interconnection between work culture and CW mental health that needs to be acknowledged when addressing mental health care.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.028 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".