Addressing Moral Distress in Critical Care Nurses: A Systemized Literature Review of Intervention Studies
Bibliographic record
Abstract
Background: The literature on moral distress highlights the need for hospitals and healthcare organizations to improve the work environment in critical care. However, only few studies delve into the types of intervention programs and administrative processes that can be put into effect to help nurses effectively deal with moral distress. Aim: The aim of this study was to systematically synthesize evidence from published studies of interventions that address moral distress in critical care nurses. The attributes, measures, and outcomes of published interventions were described. Methods: Systemized literature review based on searches in four biomedical sciences databases (CINAHL, MEDLINE, COCHRANE, and SCOPUS). The Cochrane Collaboration's tool was employed for risk of bias. Eligibility criteria included published full-text articles exploring any type of intervention for critical care nurses' moral distress. Results: Based on the selection criteria, seven studies were included in the review (two quasi-experimental, two randomized clinical trials, three mixed method). The majority of studies exhibited high risk of bias. Only two studies had moderate risk of bias. The most common type of interventions were workshops. Conclusion: We identified a small number of overall low-quality intervention studies, which provided weak evidence on the effectiveness of workshops for moral distress. Based on the indications for potentially large effect size of workshops, more well-designed studies are needed in order to elucidate the characteristics, content, and duration of effective workshops for moral distress. The results of this review can inform future efforts to develop and test intervention strategies for moral distress among intensive care unit (ICU) 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 | 0.004 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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".