Impact of Workplace Mistreatment on Patient Safety Risk and Nurse-Assessed Patient Outcomes
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to investigate the impact of subtle forms of workplace mistreatment (bullying and incivility) on Canadian nurses' perceptions of patient safety risk and, ultimately, nurse-assessed quality and prevalence of adverse events. BACKGROUND: Workplace mistreatment is known to have detrimental effects on job performance and in nursing may threaten patient care quality. METHODS: A total of 336 nurses from acute care settings across Ontario responded to a questionnaire that was mailed to their home address in early 2013, with a response rate of 52%. RESULTS: Bullying and incivility from nurses, physicians, and supervisors have significant direct and indirect effects on nurse-assessed adverse events (R = 0.03-0.06) and perceptions of patient care quality (R = 0.04-0.07), primarily through perceptions of increased patient safety risk. CONCLUSIONS: Bullying and workplace incivility have unfavorable effects on nurse-assessed patient quality through their effect on perceptions of patient safety risk.
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 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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".