Organizational levers supporting police officers’ psychological health in the workplace after exposure to a potentially psychologically traumatic event
Bibliographic record
Abstract
One in two police officers report having experienced a potentially psychologically traumatic event (PPTE) in the course of their career that has had an impact on their professional or personal life. In addition, daily exposure to PPTEs results in major adverse effects that affect all aspects of health: psychological, emotional, and physical. However, it is not necessarily PPTEs as such that cause psychological distress at work; rather, the determining factor seems to be the organization’s response to police officers’ exposure to PPTEs. The purpose of this study is therefore to identify the organizational factors that explain psychological health at work for police officers who have experienced a PPTE in the line of duty. The results show that the quality of relationships with the superior and colleagues, the availability of support such as advice, job demand, and job decision latitude are factors that partially explain the psychological distress that police officers experience at work after a PPTE [R2 = .38, p<.05; F(1,451) = 55.99, p<.001]. Conversely, quality relationships with co-workers, job demand, and job decision latitude partially account for the workplace psychological well-being experienced by officers after a PPTE [R2=.42, p<.05; F(1,457) = 109.55, p<.001]. This study highlights the importance for police organizations to promote good relationships between police officers and, above all, to encourage managers to invest in their relational skills and counseling-type social support. The study limitations and new avenues for research are also discussed.
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 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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".