Deteriorated External Work Environment, Heavy Workload and Nurses' Job Satisfaction and Turnover Intention
Bibliographic record
Abstract
Health system reform experienced in Canada since the 1990s profoundly affected health-care workplaces and workers' attitudes. In this paper we examine associations between deteriorated external work environment, heavy workload and nurses' job satisfaction and turnover intention. Data are from our 2002 survey responses of 1,396 nurses employed in three teaching hospitals in southern Ontario. Data are analyzed first for all nurses and then separately for full-time, part-time, and casual nurses. External work environment refers to nurses' perceptions of important decisions being made outside the hospital, limited resources, and budget cuts. Results show that when nurses perceive a deteriorated external work environment and consider their workload to be heavy, they also report low job satisfaction. Low job satisfaction and heavy workload, in turn, are associated with nurses' turnover intention. However, when nurses perceive a deteriorated external work environment they are more inclined to stay. When data are examined separately for each employment status group, the effect of external work environment and workload are different on turnover intentions for full-time, part-time, and casual nurses. We suggest managers and policymakers pay attention to the impact of deteriorated external work environment and heavy workload in developing strategies for nurses' job satisfaction and retention. More importantly, the different impact of these factors according to employment contracts should be considered in developing human resources policies for nurses' job satisfaction and retention.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".