A Systematic Review: Effectiveness of Interventions to De-escalate Workplace Violence against Nurses in Healthcare Settings
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
Workplace violence (WPV) is an increasing cause of concern around the globe, and healthcare organizations are no exception. Nurses may be subject to all kinds of workplace violence due to their frontline position in healthcare settings. The purpose of this systematic review is to identify and consider different interventions that aim to decrease the magnitude/prevalence of workplace violence against nurses. The standard method by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA, 2009) has been used to collect data and assess methodological quality. Altogether, twenty-six studies are included in the review. The intervention procedures they report on can be grouped into three categories: stand-alone trainings designed to educate nurses; more structured education programs, which are broader in scope and often include opportunities to practice skills learned during the program; multicomponent interventions, which often include organizational changes, such as the introduction of workplace violence reporting systems, in addition to workplace violence training for nurses. By comparing the findings, a clear picture emerges; while standalone training and structured education programs can have a positive impact, the impact is unfortunately limited. In order to effectively combat workplace violence against nurses, healthcare organizations must implement multicomponent interventions, ideally involving all stakeholders.
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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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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