Toward interventions to address moral distress
Bibliographic record
Abstract
BACKGROUND: The concept of moral distress has been the subject of nursing research for the past 30 years. Recently, there has been a call to move from developing an understanding of the concept to developing interventions to help ameliorate the experience. At the same time, the use of the term moral distress has been critiqued for a lack of clarity about the concepts that underpin the experience. DISCUSSION: Some researchers suggest that a closer examination of how socio-political structures influence healthcare delivery will move moral distress from being seen as located in the individual to an experience that is also located in broader healthcare structures. Informed by new thinking in relational ethics, we draw on research findings from neuroscience and attachment literature to examine the reciprocal relationship between structures and agents and frame the experience of moral distress. CONCLUSION: We posit moral distress as a form of relational trauma and subsequently point to the need to better understand how nurses as moral agents are influenced by-and influence-the complex socio-political structures they inhabit. In so doing, we identify this reciprocity as a framework for interventions.
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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 | 0.017 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".