Organizational culture and nurse’s turnover: A systematic literature review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Nurses turnover is a current and international problem which is closely related to the organizational culture. Despite being widely discussed, the evidence available in the literature is dispersed and most studies only concern specific health contexts and sectors. The aim of this study is to identify scientific evidence on the factors of organizational culture associated with nurses turnover.Methods: A systematic literature review was carried out between January 2014 and December 2018. The methodological quality of the articles was assessed through the Joanna Briggs Institute and Registered Nurses Association of Ontario guidelines.Results: Nurses’ turnover in healthcare organizations is complex and multifactorial. The evidence shows individual and organizational factors that influence nurses’ turnover. Some retention strategies to reduce this phenomenon were also identified in literature.Conclusions: Nursing managers should seriously consider the problem of nurses’ turnover, as it affects the productivity and quality of care provided in health organizations. By working the factors associated with organizational culture, organizational climate and leadership, it will be possible to reduce nurses’ turnover rates in different healthcare contexts. In the development of public policies, decision-makers should take into account two fundamental aspects: the needs and expectations of the population; and the stability of professional groups. It is suggested to investigate this issue in Portugal.
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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 | 0.000 |
| 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 | 0.000 |
| 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 it