Influence of organizational stress on reported depressive symptoms among police
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: There is a growing body of research on operational stress injuries (OSIs) among police officers and first responders. Most studies focus on operational stressors' contribution to OSI and the development of post-traumatic stress disorder. However, preliminary research shows that organizational stressors may uniquely contribute to OSI and depression, and thus should be examined more closely. AIMS: This study explored the influence of organizational stress on symptoms of depression in a sample of police officers from a large urban region. METHODS: Front-line (n = 109) police officers completed questionnaires measuring police organizational and operational stress, depression, anxiety, hostility, rumination, perceived social support and social desirability. Using negative binomial regression (NBR), a best subset model of self-reported depression symptoms was derived from the full model (a function of gender, age, police experience (years), organizational stress, operational stress, anxiety, anger, rumination and social support), based on Akaike Information Criterion (AIC) goodness of fit. RESULTS: Organizational stress and anxiety were positively associated with self-reported depression symptoms. A paired t-test revealed no significant difference between reported organizational and operational stress levels. CONCLUSIONS: Organizational stress may uniquely contribute to OSI and depressive symptoms and should be examined in future research. Findings support prior literature suggesting that initiatives to treat OSI among police should address workplace environment and organizational stressors. Addressing organizational issues in police culture and developing long-lasting initiatives is key in the future of OSI prevention and treatment for police officers.
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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 it