Violence Against Nurses Working in US Emergency Departments
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
OBJECTIVE: The objective of this study was to investigate emergency nurses' experiences and perceptions of violence from patients and visitors in US emergency departments (EDs). BACKGROUND: The ED is a particularly vulnerable setting for workplace violence, and because of a lack of standardized measurement and reporting mechanisms for violence in healthcare settings, data are scarce. METHODS: Registered nurse members (n = 3,465) of the Emergency Nurses Association participated in this cross-sectional study by completing a 69-item survey. RESULTS: Approximately 25% of respondents reported experiencing physical violence more than 20 times in the past 3 years, and almost 20% reported experiencing verbal abuse more than 200 times during the same period. Respondents who experienced frequent physical violence and/or frequent verbal abuse indicated fear of retaliation and lack of support from hospital administration and ED management as barriers to reporting workplace violence. CONCLUSION: Violence against ED nurses is highly prevalent. Precipitating factors to violent incidents identified by respondents is consistent with the research literature; however, there is considerable potential to mitigate these factors. Commitment from hospital administrators, ED managers, and hospital security is necessary to facilitate improvement and ensure a safer workplace for ED nurses.
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.
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 | 0.000 |
| 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 it