Impact and determinants of nurse turnover: a pan-Canadian study
Why this work is in the frame
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Bibliographic record
Abstract
AIM: As part of a large study of nursing turnover in Canadian hospitals, the present study focuses on the impact and key determinants of nurse turnover and implications for management strategies in nursing units. BACKGROUND: Nursing turnover is an issue of ever-increasing priority as work-related stress and job dissatisfaction are influencing nurses' intention to leave their positions. METHODS: Data sources included the nurse survey, unit managers, medical records and human resources databases. A broad sample of hospitals was represented with nine different types of nursing units included. RESULTS: Nurses turnover is a major problem in Canadian hospitals with a mean turnover rate of 19.9%. Higher levels of role ambiguity and role conflict were associated with higher turnover rates. Increased role conflict and higher turnover rates were associated with deteriorated mental health. Higher turnover rates were associated with lower job satisfaction. Higher turnover rate and higher level of role ambiguity were associated with an increased likelihood of medical error. CONCLUSION: Managing turnover within nursing units is critical to high-quality patient care. A supportive practice setting in which role responsibilities are understood by all members of the caregiver team would promote nurse retention. IMPLICATIONS FOR NURSING MANAGEMENT: Stable nurse staffing and adequate managerial support are essential to promote job satisfaction and high-quality patient care.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 it