A study on work engagement among nurses in Japan: the relationship to job-demands, job-resources, and nursing competence
Bibliographic record
Abstract
Objective: This study reviewed the state of work engagement among nurses in Japan, and the relationship to job demands and job resources. Additionally, our research attempted to clarify the role of work engagement on the effects that job-resources have on nursing competence. Methods: A questionnaire composed of the Utrecht Work-Engagement Scale the Brief Scales for Job Stress-Nurse and the Clinical Nursing Competence Self-Assessment Scale was distributed to 917 nurses working in hospitals in Japan. Results: A negative correlation, although slight, was found between job-demands and work engagement. There was a positive correlation between job-resources and work engagement, however, work engagement was only found to be significantly affected by job fulfillment. Work engagement seems to mediate the relationship between job-resources and job-demands however the results from the path analysis did not fully support this model. Conclusions: Our study did not sufficiently explain the relationships between variables. It can be suggested that the correlations between job-resources, job-demands, and work engagement are bidirectional or circulatory, rather than unidirectional.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".