How Emergency Nurses Develop Resilience in the Context of Workplace Violence: A Grounded Theory Study
Bibliographic record
Abstract
PURPOSE: To understand how emergency nurses develop resilience in the context of workplace violence. DESIGN: This study employed grounded theory methodology. Thirty nurses from three hospital emergency departments in Taiwan were interviewed between August and December 2018. METHODS: Semistructured interviews were used to collect data. Interviews were audio-recorded and transcribed verbatim. FINDINGS: The process through which emergency nurses who had experienced workplace violence developed resilience took place in three stages: the release of emotions after the assault; the interpretation of conflicting thoughts and actions; and the establishment of strategies to cope with workplace violence in the future. The core theme was the motivating role of professional commitment to emergency patient care. CONCLUSIONS: The results of this study can inform the development of support systems to enhance the resilience of nurses experiencing workplace violence by alerting healthcare administrators and governing institutions to their needs. CLINICAL RELEVANCE: Emergency nurses viewed professional growth and professional commitment as an invisible motivator in the development of resilience following an encounter with workplace violence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".