Nurse turnover: the mediating role of burnout
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
AIM: This study tested whether the mediation model of burnout could predict nurses' turnover intentions. BACKGROUND: A better understanding of what factors support a commitment to a nursing career could inform both policies and workplace practices. The mediation model of burnout provides a way of linking the quality of a nurse's worklife to various outcomes, such as turnover. METHOD: Data on areas of worklife, burnout, and turnover intentions were collected by surveying 667 Canadian nurses in the Atlantic Provinces. RESULTS: The findings supported the mediation model of burnout, in which areas of worklife predicted burnout, which in turn predicted turnover intentions. Cynicism was the key burnout dimension for turnover, and the most critical areas of worklife were value conflicts and inadequate rewards. CONCLUSIONS: The results of this study provide some new insights into how the intention of nurses to leave their job is related to particular aspects of their worklife and to burnout. IMPLICATIONS FOR NURSING MANAGEMENT: These results suggest what may be the most appropriate areas to target for interventions to reduce the risk of nurses exiting early from their chosen career.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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