Linking Nurses’ Perceptions of Patient Care Quality to Job Satisfaction
Bibliographic record
Abstract
OBJECTIVES: A model linking authentic leadership, structural empowerment, and supportive professional practice environments to nurses' perceptions of patient care quality and job satisfaction was tested. BACKGROUND: Positive work environment characteristics are important for nurses' perceptions of patient care quality and job satisfaction (significant factors for retention). Few studies have examined the mechanism by which these characteristics operate to influence perceptions of patient care quality or job satisfaction. METHODS: A cross-sectional provincial survey of 723 Canadian nurses was used to test the hypothesized models using structural equation modeling. RESULTS: The model was an acceptable fit and all paths were significant. Authentic leadership had a positive effect on structural empowerment, which had a positive effect on perceived support for professional practice and a negative effect on nurses' perceptions that inadequate unit staffing prevented them from providing high-quality patient care. These workplace conditions predicted job satisfaction. CONCLUSION: Authentic leaders play an important role in creating empowering professional practice environments that foster high-quality care and job satisfaction.
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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 | 0.004 | 0.016 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".