Occupational stress, quality of working life and turnover intention amongst nurses
Bibliographic record
Abstract
BACKGROUND: Turnover intention is a frequent event in almost all institutions and is associated with unfavourable consequences for employees. AIM: The aim of this study was to examine the relationship between occupational stress, quality of working life and turnover intention amongst nurses working in critical care units in Iran. DESIGN: A cross-sectional survey design was used. METHOD: The study was conducted in the critical care units of 10 hospitals in Tabriz, Iran, between July and November 2017 using a sample of 203 nurses. Data were obtained using a self-administered questionnaire, and multiple logistic regression analysis was performed to determine the factors impacting turnover intention. RESULTS: Overall, 64% of nurses had an intention to leave their job; 82·8% of respondents reported their job to be highly stressful, and 81·2% reported their quality of working life to be low. Binary logistic regression analysis indicated that age (p = 0·006), clinical experience (p = 0·005), duty stressors (p = 0·040), interpersonal relations stressors, (p = 0·029) communication (p = 0·007), motivation (p = 0·006), job security (p = 0·040) and job pride (p = 0·011) were factors affecting turnover intention. CONCLUSION: Occupational stress and quality of working life are associated with turnover intention amongst nurses working in critical care units. Further research is needed to determine the generalizability of these results to other settings and countries and to identify interventions that could reduce occupational stress and improve the quality of working life so that turnover intention might be reduced. RELEVANCE TO CLINICAL PRACTICE: The findings of this research suggest that lower perceived occupational stress and higher quality of working life will result in less reported turnover intention in critical care unit nurses.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 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".