THE INFLUENCE OF PERCEIVED FAIRNESS AND RELATIONAL LEADERSHIP ON NURSING SAFETY CLIMATE AND WORK ENVIRONMENT
Bibliographic record
Abstract
Canadian statistics on patient safety in acute care hospitals are alarming. Hospital safety concerns are not isolated to patient safety. Occupational safety is also important. With increasing shortages of nurses, stress in the work place is growing. Nurses report high levels of absenteeism of 14.5 days per year. The importance of a just and fair culture and the role of nurse leaders have been emphasized in safety literature. Although deemed important, studies of nurse leaders and patient outcomes are limited. The influence of interactional justice in the workplace on nurse and patient safety has not been studied. \nThe purpose of this study was to test and refine a model developed from the literature which explains the impact of perceived interactional justice, relational leadership, and quality of nurse manager – clinical nurse relationships on the nursing work environment and ultimately patient and nurse safety outcomes. \nThe model was tested on a random sample of 266 Ontario acute care registered nurses. Findings indicated the model reasonably fit the observed data, however could benefit from further refinement. The addition of 2 pathways (span of control to nurses’ intent to leave and number of medication errors to nurse emotional exhaustion) and trimming of the insignificant paths improved the overall model fit. \nThe resulting model indicates that resonant leadership style and interactional justice improves the quality of nurse leader-nurse relationships which in turn improves quality of the nurses’ work environment and safety climate. A positive safety climate led to a decrease in the number medication errors and nurses’ intentions to leave their unit. A higher quality work environment predicted lower nurse emotional exhaustion. Additionally, higher numbers of medication errors led to an increase in nurse emotional exhaustion. This suggests that distress may be associated with making a medication error or fear of consequences. As well, larger manager spans were associated with less nurse intent to leave. As the span increased, the number of support personnel also increased. Contrary to other research findings, this result suggests that supportive personnel may mitigate the effect of large manager spans of control on nurses’ intent to leave their units.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".