Examining the Relationship of Transformational Leadership and New Graduate Nurse Turnover Intention During the COVID-19 Pandemic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: The nursing shortage in the Canadian healthcare system presents challenges in meeting the healthcare needs of the population and addressing the growing demand for health services. There is strong evidence emphasizing the pivotal role leaders play in fostering retention through positive practices. As new graduate nurses are crucial to the healthcare team, targeted strategies by nursing leaders and managers are needed to enhance nurse retention. Purpose: The purpose of this study was to examine the relationship between transformational leadership and new graduate nurses’ turnover intention, and organizational commitment. Methods: The study included 106 registered nurses who passed the NCLEX-RN between March 2020 and February 2023. Data was collected through the Multifactor Leadership Questionnaire-5X, Turnover Intention Scale-6 and Three-Component Model Employee Commitment Survey. A descriptive correlational design was used to conduct this study with descriptive statistics and Kendall tau-b correlation. Results: A significant negative correlation was found between transformational leadership and turnover intention among new graduate nurses (τb = -.352, p < .001). Conclusion: Nursing leaders must possess the necessary leadership skills rooted in the nursing model to promote transformational leadership and foster an intention to stay among new graduate nurses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| 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 it