“It gets your foot in the door”: An examination of the Healthy Apples Self-Care Program at Durham Regional Police Service
Bibliographic record
Abstract
The psychological strain inherent to the policing profession and the effect of psychological strain on sworn and civilian members are increasingly recognized. The effects of stress can be wide-ranging, including an increased risk for occupational or posttraumatic stress injuries. Police services have implemented a variety of wellness programs; however, little is known about the benefits and challenges of these programs. In the current study, we examine one such program, the Healthy Apples Self-Care Program, which entails mental and physical health ‘check-ins’. Semi-structured interviews with 76 police members, sworn and civilian, from January 2024 through April 2024 were completed. In total, 44 men and 32 women were interviewed for this study – 75 % of whom reported using the Healthy Apples Program. Interviews analyzed using a semi-grounded thematic approach. Responses indicated overwhelming support for the program with several benefits identified such as learning about themselves and new psychological skills, facilitating more engagement with mental health resources, and building a culture of wellness. Challenges were also noted such as the lack of time or difficulty with scheduling program activities, lack of access to care providers (i.e., medical doctors), administrative burden of participating, and lack of knowledge about the process. Results provide rich descriptions of aspects of the wellness program and offering strong support for police organizations to provides the program yet highlight pitfalls for organizations to avoid or address. •We studied the Healthy Apples Self-Care Program at a police service. •Program users learned about their health (physical and mental health) by participating in the program. •The program reduced the mystique of and provided comfort when seeing a clinician for mental health. •The program resulted in some participants seeking regular psychological care. •Incentivized health programs support the mental health of civilian and sworn police employees.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".