How to minimize adverse effects of physical workplace violence on health sector workers: A preliminary study
Bibliographic record
Abstract
Purpose: This paper is an exploratory study to investigate possible remedial measures accounting for a relatively favorable prognosis of health sector workers who have experienced physical WPV in Zhejiang province, China. Methods: Following a proportionate stratified sampling strategy, five tertiary hospitals (in the developed capital city of Hangzhou and other prefecture-level cities), eight secondary hospitals (in counties), and thirty-two primary care facilities (16 urban community health centers and 16 rural township health centers) were conveniently selected. Among 4,862 valid respondents out of 6,089 self-conducted questionnaires, 224 health sector workers who have been directly exposed to physical WPV in the past year were included in the present study. Results: The present study has three major findings: (1) Victims' satisfaction with the resolution of the physical WPV conflict was directly associated with the favorable prognosis. (2) Taking days off from work after the violence can promote victims' satisfaction with the resolution of the physical WPV conflict. (3) Knowing that relevant departments investigated the case can promote victims' satisfaction with the resolution of the physical WPV conflict. Conclusion: We propose a combined gesture of "offering adequate days off work after physical WPV" and "every physical violence must be investigated" that should be taken by all medical institutions in China. Health sector workers who get involved in physical WPV incidents should prioritize their safety and avoid any behavior that may intensify the conflicts.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".