A Realist Review of Violence Prevention Education in Healthcare
Bibliographic record
Abstract
Violence from patients and visitors towards healthcare workers is an international concern affecting the safety and health of workers, quality of care, and healthcare system sustainability. Although the predominant intervention has been violence prevention (VP) education for healthcare workers, evaluating its effectiveness is challenging due to underreporting of violence and the inherent complexity of both violence and the health care environment. This review utilized a theory-driven, realist approach to synthesize and analyze a wide range of academic and grey literature to identify explanations of how and why VP education makes a difference in preventing violence and associated physical and psychological injury to workers. The review confirmed the importance of positioning VP education as part of a VP strategy, and consideration of the contexts that influence successful application of VP knowledge and skills. Synthesis and analysis of patterns of evidence across 64 documents resulted in 11 realist explanations of VP education effectiveness. Examples include education specific to clinical settings, unit-level modeling and mentoring support, and support of peers and supervisors during violent incidents. This review informs practical program and policy decisions to enhance VP education effectiveness in healthcare settings.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".