The incidence and management of workplace violence among medical professionals in the United States: A methodological pilot study
Bibliographic record
Abstract
This study aimed to investigate workplace violence (WPV) experienced by medical professionals in the United States as well as individual and managerial actions following violent episodes and further, predict estimators of WPV. A modified version of the Workplace Violence in the Health Sector: Country Case Studies Research Instruments Survey Questionnaire was used to assess the incidence and management of workplace violence experienced by healthcare workers. Medical personnel from two social aggregation websites were recruited to participate in an online survey. 226 valid questionnaires were received. 48.5\% and 76.1\% of respondents, respectively, experienced physical and psychological violence in the past year. Risk factors for violence included occupation, patient population, ethnicity, and higher levels of anxiety regarding violence in hospitals. Overall, 17.7\% of reported incidents were investigated, 52.4\% of cases saw no consequences meted out to perpetrators and 51.7\% of victims suffered from negative emotions or aftereffects following a violent episode. Only 30.1\% of victims formally reported their experience with violence. The prevalence of violence was high and medical professionals were negatively affected by violence; however, formal reporting of episodes was low and measures combating violence were inadequate. Harsher penalties for perpetrators of violence are needed and hospitals need to implement guidelines that track the management of violence.
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 | 0.009 | 0.001 |
| 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) | 0.000 | 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".