Nurses’ ethical conflict with hospitals: A longitudinal study of outcomes
Bibliographic record
Abstract
This study examined the association of nurses' ethical conflict with hospitals with organizational commitment, stress, turnover intention, absence and turnover. Participants were 410 nurses working at four different Canadian hospitals. A longitudinal design was used where nurses completed a questionnaire to capture ethical conflict, stress and organizational commitment, and one year later, measures of turnover intention, absence and actual turnover were obtained for the same sample. We found three aspects of nurses' ethical conflict with hospitals: patient care values, value of nurses, and staffing policy values. Our findings showed that all three aspects of nurses' ethical conflict are associated with stress and patient care values is associated with actual turnover. We also found that staffing policy values is predictive of turnover intention, and that patient care values is predictive of absenteeism. Thus, our findings show the multidimensionality of nurses' ethical conflict with hospitals. Further implications of our findings for practice and theory are discussed.
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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 | 0.017 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.031 |
| 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; both teacher heads agree on what is shown here.
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".