Healthcare Top Management’s Transformational Leadership Behaviors and Nurses’ Occupational and Organizational Turnover Intention: On the Role of Work Engagement and Autonomous Motivation
Bibliographic record
Abstract
Aims: This study examines the contribution of top management’s transformational leadership behaviors on two targets of nurses’ turnover intention (organization and occupation) by focusing on the indirect (through vigor and dedication) and conditional indirect associations (involving autonomous motivation as a moderator). Background: Although the issue of nurse turnover has received growing scientific attention, the research is currently silent about the specific targets of turnover intention and more importantly, the potential pathways through which top management’s transformational leadership behaviors relate to each target. Method: Cross‐sectional data from a sample of 426 French–Canadian nurses and structural equation modeling were used to test the proposed model. Results: Top management’s transformational leadership behaviors distinctly predicted organizational and occupational turnover intention through specific nurses’ states of engagement. While perceived transformational leadership positively predicted vigor, its indirect associations (via dedication) with organizational and occupational turnover intention depend on nurses’ level of autonomous motivation at work. Conclusion: In times of nurse shortage, the present findings provide insights into how and when top management’s transformational leadership behaviors relate to nurses’ organizational and occupational turnover intention. Implications for Nursing Management: Healthcare organizations are advised to foster top management transformational leadership behaviors and autonomous motivation to sustain the nursing workforce.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".