Predictors of Nurse Managers' Health in Canadian Restructured Healthcare Settings
Bibliographic record
Abstract
Although nursing leadership roles have been greatly transformed as a result of dramatic changes within healthcare over the past decade, there is little research on the nature of nurse manager work life in current work environments. The purpose of this study was to test a theoretical model derived from Kanter's theory of organizational empowerment: linking nurse managers' perceptions of structural and psychological empowerment to burnout, job satisfaction and physical and mental health. A descriptive, correlational design was used in a sample of 286 first-line (n=202) and middle-level (n=84) hospital-based nurse managers obtained from a provincial registry. Ironically, managers reported high levels of burnout, but good mental and physical health. Middle managers were more empowered and satisfied with their jobs than first-line managers. In both groups, approximately 45% of the variance in job satisfaction and 18-52% of the variance in physical and mental health was explained by empowerment and burnout. Empowered work environments were associated with lower nurse manager burnout and better physical and mental health. The results suggest that creating work environments that provide access to empowerment structures may be a fruitful strategy for creating healthy work environments for nurse managers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".