The influence of resonant leadership on the structural empowerment and job satisfaction of registered nurses
Bibliographic record
Abstract
The demanding nature of nursing work environments signals longstanding and growing concerns about nurses' health and job satisfaction and the provision of quality care. Specifically in healthcare settings, nurse leaders play an essential role in creating supportive work environments to avert these negative trends and increase nurse job satisfaction. The purpose of this study was to examine the influence of managers' resonant leadership on nurses' structural empowerment and job satisfaction. A secondary analysis of data collected from a cross-sectional survey design of 1216 registered nurses from nine Canadian provinces was conducted. Structural empowerment partially mediated the relationship between resonant leadership and job satisfaction. Resonant leadership and structural empowerment explained a total of 36% of the variance in job satisfaction while controlling for age, education and work setting ( F (5, 1169) = 131.78, p < 0.001). Findings suggested that resonant leaders are instrumental in creating empowering environments that contribute to higher job satisfaction in nursing. Therefore, a focus on developing resonant leadership skills among nurse leaders in healthcare organisations will advance the creation of healthy work environments that promote job satisfaction and the retention of nurses.
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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 | 0.007 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".