Nurses' participation in personal knowledge transfer: the role of leader-member exchange (LMX) and structural empowerment
Bibliographic record
Abstract
AIM: The purpose of this study was to test Kanter's theory by examining relationships among structural empowerment, leader-member exchange (LMX) quality and nurses' participation in personal knowledge transfer activities. BACKGROUND: Despite the current emphasis on evidence-based practice in health care, research suggests that implementation of research findings in everyday clinical practice is unsystematic at best with mixed outcomes. METHODS: This study was a secondary analysis of data collected using a non-experimental, predictive mailed survey design. A random sample of 400 registered nurses who worked in urban tertiary care hospitals in Ontario yielded a final sample of 234 for a 58.5% response rate. RESULTS: Hierarchical multiple linear regression analysis revealed that the combination of LMX and structural empowerment accounted for 9.1% of the variance in personal knowledge transfer but only total empowerment was a significant independent predictor of knowledge transfer (β=0.291, t=4.012, P<0.001). CONCLUSIONS: Consistent with Kanter's Theory, higher levels of empowerment and leader-member exchange quality resulted in increased participation in personal knowledge transfer in practice. IMPLICATIONS FOR NURSING MANAGEMENT: The results reinforce the pivotal role of nurse managers in supporting empowering work environments that are conducive to transfer of knowledge in practice to provide evidence-based care.
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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 | 0.000 | 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) | 0.000 | 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".