Nursing students’ experiences of bullying in clinical practice
Bibliographic record
Abstract
Bullying is a major concern in the nursing profession because of its implications for patients’ safety, the health of nurses and nursing students, as well as on the workforce in the healthcare system. The purpose of the study was to explain the incidence and state of bullying experienced by nursing students in the undergraduate nursing program during clinical practice. Fifty-five undergraduate nursing students participated in the mixed methods research conducted in a tertiary institution in Western Canada. Participants completed an online survey and an individual interview. Survey data were analyzed using descriptive statistics while thematic analysis was employed for the open-ended questions on the survey and individual interviews. The findings from the study showed that a small number of students four (7.7%) frequently experienced bullying in the clinical setting with clinical instructors and practicing nurses being the main perpetrators. Students reported anxiety connected with going for clinical practice however a unique finding from this study was that the affected students continued to go for clinical practice and decided to remain in the program because of their goal to become registered nurses. Peers from the program were one of the key support systems for the students when they experienced the negative behavior. Irrespective of the low incidence of bullying at the research site, the impact of the behavior aligns with the literature. The findings from this study has the potential to inform clinical practices and policies in undergraduate nursing programs.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".