Turning the tide : registered nurses' job withdrawal intentions in a Finnish university hospital : original research
Bibliographic record
Abstract
Orientation : Given the global shortage of registered nurses, it is important to investigate the intentions for job withdrawal of nurses, and resolve these, in order to retain nurses in the field. Research purpose : The objective was to examine the intentions for job withdrawal of ageing and younger nurses, and the antecedents of these intentions, with special reference to job control and perceived development opportunities. The age of 45 was adopted as a starting point when referring to ageing employees. Motivation for the study : Different forms of job withdrawal have rarely been studied together and associated. Research design, approach and method : A quantitative study was applied with logistic regression analyses. Respondents were registered nurses working in a university hospital in Finland. The response rate was 46.1% (N = 343). Main findings : A quarter (25%) of the nurses had frequently thought about leaving the profession and 19% of the nurses had thought about taking early retirement. Factors that increased the likelihood of intentions for occupational turnover were young age, low job satisfaction, low organisational commitment, low work ability and skills in balance with or above present work demands. The intention to take early retirement was increased with older age, being male, working shifts, low work ability, low job satisfaction and poor job control. Practical/managerial implications : A nurse's job satisfaction and work ability should be regularly monitored and opportunities should be offered them, to apply their skills and to control their work, in order to retain them. Contribution/value-added : The article added information about the factors that contribute to a nurse's intentions for job withdrawal.
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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 | 0.002 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".