The Impact of Leader-Member Exchange Quality, Empowerment, and Core Self-evaluation on Nurse Manager's Job Satisfaction
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study is to test a theoretical model linking nurse managers' perceptions of the quality of the relationship with their supervisors, and empowerment to job satisfaction, and to examine the effect of a personal dispositional variable, core self-evaluation, on the relationships among these variables. BACKGROUND DATA: Nursing leadership roles have been transformed as a result of dramatic changes within healthcare in the past decade, yet research on the nature of nurse manager work life in current work environments is limited. METHODS: A nonexperimental, predictive design was used in a sample of 141 hospital-based nurse managers obtained from a provincial registry. RESULTS: Approximately 40.4% of the variance in job satisfaction was explained by leader-member exchange quality (LMX), empowerment, and core self-evaluation. CONCLUSION: Higher quality relationships with their immediate supervisor were associated with greater manager structural and psychological empowerment and, consequently, greater job satisfaction. Core self-evaluation played a strong significant role, affecting all components of the model. The results suggest that both situational and personal factors are important determinants of satisfying work environments for nurse managers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.011 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".