The Contribution of Hospital Nursing Leadership Styles to 30-day Patient Mortality
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Bibliographic record
Abstract
BACKGROUND: Nursing work environment characteristics, in particular nurse and physician staffing, have been linked to patient outcomes (adverse events and patient mortality). Researchers have stressed the need for nursing leadership to advance change in healthcare organizations to create safer practice environments for patients. The relationship between styles of nursing leadership in hospitals and patient outcomes has not been well examined. OBJECTIVE: The purpose of this study was to examine the contribution of hospital nursing leadership styles to 30-day mortality after controlling for patient demographics, comorbidities, and hospital factors. METHODS: Ninety acute care hospitals in Alberta, Canada, were categorized into five styles of nursing leadership: high resonant, moderately resonant, mixed, moderately dissonant, and high dissonant. In the secondary analysis, existing data from three sources (nurses, patients, and institutions) were used to test a hypothesis that the styles of nursing leadership at the hospital level contribute to patient mortality rates. RESULTS: Thirty-day mortality was 7.8% in the study sample of 21,570 medical patients; rates varied across hospital categories: high resonant (5.2%), moderately resonant (7.4%), mixed (8.1%), moderately dissonant (8.8%), and high dissonant (4.3%). After controlling for patient demographics, comorbidities, and institutional and hospital nursing characteristics, nursing leadership styles explained 5.1% of 72.2% of total variance in mortality across hospitals, and high-resonant leadership was related significantly to lower mortality. CONCLUSIONS: Hospital nursing leadership styles may contribute to 30-day mortality of patients. This relationship may be moderated by homogeneity of leadership styles, clarity of communication among leaders and healthcare providers, and work environment characteristics.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it