Prevalence and associated factor of verbal abuse against nurses: A systematic review
Bibliographic record
Abstract
BACKGROUND: Nurses who experience verbal abuse often report negative emotions, which can affect their work status and nurse-patient relationship. However, to the best of our knowledge, no study has summarized the prevalence of verbal abuse among nurses by different perpetrators and related risk factors. AIM: This review aimed to synthesize the prevalence of verbal abuse among nurses and identify the most common sources and related risk factors. METHODS: PubMed, Web of Science, Embase, and the Cochrane Library electronic databases were searched from inception to 15 October 2024, and observational studies reporting the prevalence of verbal abuse among nurses were selected. In this systematic review, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Methodological quality was appraised using a revised version of the Newcastle-Ottawa Quality Assessment Scale, and the STATA software was used for meta-analysis; PROSPERO registration number: CRD42022385401. RESULTS: The search identified 458 records, of which 45 met the inclusion criteria. The overall prevalence of verbal abuse was estimated at 67% (95% CI: 61-72). Verbally abused nurses reported patients' relatives, friends (48%, 95% CI: 42-55), and physicians (39%, 95% CI: 20-58) as the main perpetrators of verbal abuse. Personal factors, work area, and work characteristics were the main factors related to verbal abuse among nurses. CONCLUSIONS: The overall prevalence of verbal abuse among nurses was more than 65%, especially in the emergency department, and South or Southeast Asian countries had a significantly lower prevalence of verbal abuse than other countries. Physicians and patients' relatives were the main sources of verbal abuse. Hospital administrators should prevent various effects of verbal abuse on nurses' physical and mental health. IMPLICATIONS FOR NURSING AND HEALTH POLICY: Developing safe workplaces and effective interventions to protect nurses is essential. Supervisors and institutions should thoroughly monitor verbal abuse. Additionally, organizations need to focus on preventive measures and provide the necessary administrative, legal, and psychological support to nurses who are exposed to verbal abuse to ensure nursing care sustainability.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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".