Moral distress: Does this impact on intent to stay among adult critical care nurses?
Bibliographic record
Abstract
BACKGROUND: Moral distress is recognized as an international problem that contributes to decreased work productivity, job dissatisfaction and intent to leave for adult Critical Care nurses. AIM: To explore Critical Care nurses moral distress levels using the Moral Distress Scale Revised (MDS-R) and its relationship with intention to stay. The study reported in this paper was part of a larger study that also investigated Critical Care nurses' work environment in Canada and the Midlands region of the UK. STUDY DESIGN: During January to August 2017 a cross-sectional survey was distributed to adult Critical Care nurses in the Midlands region of the UK. METHODS: Surveys were distributed to adult Critical Care Registered Nurses in the Midlands region of the UK examining moral distress levels and intention to stay in Critical Care, the organization (NHS Trust) and in the nursing profession. RESULTS: Two hundred sixty-six number of a potential sample of 1066 Critical Care nurses completed the survey (25% response rate). Age and moral distress were significantly positively correlated with intention to stay on their current unit (r = 0.16, P = .05), indicating older nurses were more likely to stay in the critical care unit. Moral distress was negatively correlated with intent to stay scores, showing critical care nurses with higher levels of moral distress were less likely to stay on their unit (r = -0.20, P = .02). Moral distress was also significantly negatively correlated with intention to stay with their current employer (r = -0.28, P < .001). Nurses that stated they had high rates of moral distress were more likely to consider leaving their current employer. CONCLUSION: Moral distress appears to be an issue among adult Critical Care nurses requiring further exploration and development of effective strategies to reduce this phenomenon and stabilize the workforce by reducing turnover. RELEVANCE TO CLINICAL PRACTICE: By identifying the top causes of moral distress, tools and strategies can be developed to allow the Critical Care nurse to work within an ethically safe clinical environment and reduce the turnover of experienced adult Critical Care nurses.
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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 | 0.002 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".