New Graduate Nurses’ Incivility Experiences: The Roles of Workplace Empowerment, Nursing Leadership and Areas of Worklife
Bibliographic record
Abstract
AIMS: To determine what extent are workplace empowerment, New Graduate Nurses' (NGN) perceptions of nurse leaders, trust in management, and areas of worklife predict coworker incivility experiences? BACKGROUND: NGNs' perceptions of nursing leaderships' control over workload contribute to coworker incivility experiences were tested. The relationship between workplace empowerment, authentic leadership, and areas of work life (workload control and fair resource allocation) to coworker incivility experiences were examined. DESIGN: Secondary analysis of Starting Out, national survey, Time 1 dataset. Select factors of workplace empowerment, authentic leadership, areas of worklife, trust in management and NGNs' co- worker incivility experiences were situated within an ecological approach. Multiple linear regression was used to test whether a negative relationship of workplace empowerment, areas of worklife and authentic leadership to NGNs co-worker incivility experiences and important new findings were discovered. RESULTS: First, NGNs' perceptions of workplace empowerment predict coworker incivility experiences when controlling for authentic leadership and trust in management. Second, NGNs' perceptions of areas of worklife predict coworker incivility experiences when controlling for authentic leadership, trust in management, and workplace empowerment. Third, NGNs' perceptions of authentic leadership do not predict coworker incivility experiences when controlling for workplace empowerment and trust in management. Finally, NGNs' perceptions of authentic leadership do predict coworker incivility experiences when trust in management and workplace empowerment are not controlled. CONCLUSIONS: NGNs' perceptions of authentic leadership would benefit from workplace empowerment of the nurse leader in workplace environments to mitigate coworker incivility experiences.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".