Public safety communications employment and mental health: contributing factors and desired changes from those on the front lines
Bibliographic record
Abstract
Purpose Public safety communicators (PSCs) provide an essential connection to public safety and health resources. Organizational stressors (job context) and operational stressors (job content) accompany the PSC occupation. The resultant occupational strain creates risk for adverse mental health outcomes, a challenge among PSC who already demonstrate high prevalence of mental health disorders. However, paucity in research on occupational experiences and mental health of PSC remains. Design/methodology/approach We surveyed Canadian PSC (n = 381) with opened ended questions about the effects their employment has on their mental health and workplace modifications they feel could support PSC mental health. Qualitative analysis revealed emerging themes using a constructed approach. Findings Findings reveal education, awareness, as well as organizational and operational factors that have affected our respondents' mental health and influenced considerations for how to make their workspace healthier based on their frontline experiences. Originality/value PSC provides an essential public safety service to our communities, but they lack recognition within research. Their contributions to society are accompanied by potential detriments to their occupational health subsequently affecting mental health. Lessons learned directly from self-reported experiences of PSC can be harnessed to improve working conditions, mental health and well-being for those in communications employment. Such work can also help to provide a foundation for future research to delve deeper into the occupational experiences of PSC, further shedding light on PSC who are behind the frontline providing a lifeline in and for the public safety ecosystem.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.001 | 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".