Job and career satisfaction and turnover intentions of newly graduated nurses
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: To describe new graduate nurses' worklife experiences in Ontario hospital settings in the first 2 years of practice and to examine predictors of job and career satisfaction and turnover intentions. BACKGROUND: With a large cohort of nurses approaching retirement, every effort must be made to ensure that the work environments of new graduate nurses are positive, promoting job satisfaction and commitment to the profession to address the nursing workforce shortage. METHOD: A cross-sectional analysis of data from a mail survey of new graduate nurses (n=342) in their first and second year of experience was used to address the research objectives. RESULTS: Overall, new graduate nurses were positive about their working conditions and there were few differences between nurses in their first and second years of practice. Structural and personal factors explained significant amounts of variance (31-68%) in both job and career satisfaction and turnover intentions. Empowerment, work engagement and burnout were important significant predictors. CONCLUSIONS: Modifiable workplace factors play an important role in influencing new graduates' job and career satisfaction and turnover intentions. IMPLICATIONS FOR NURSING MANAGEMENT: Managers can employ strategies to enhance quality work environments that promote retention of new graduates and lessen the nursing workforce shortage.
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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 | 0.000 | 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 it