Bibliographic record
Abstract
Background: The 2016 legalization of Medical Assistance in Dying (MAID) was a landmark event in Canada. For the first time in our country’s history, healthcare providers are legally permitted to play a role in assisting patient death. Existing legislation includes registered nurses (RNs) as core members of the interprofessional MAID team, and nurse practitioners (RN/NPs) as assessors and providers of MAID. This constitutes a significant change in practice. Therefore, the purpose of this study was to understand the reported experiences of nurses who have participated in an assisted death. Research Design: A modified systematic review and narrative synthesis of international research and grey literature on RNs’ reported experiences with assisted death. Findings: From a literature sample of 20 international sources, six major themes were identified. These themes included: RNs’ reported experiences with receiving and navigating a request for assisted death; their ways of being during the practice; the intensity of their experiences; how assisted death caused significant moral conflict and uncertainty; the relationship between teamwork and assisted death and how RNs experienced the practice; and their personal and professional development over and time. Discussion: Findings indicated that RNs experienced assisted death as complex, nuanced and challenging. RNs served as advocates for patient autonomy, beneficence and truth telling, which assisted in the development of relative freedom and equality between providers and patients. However, RNs often existed “in between” their own values and patient suffering and were required to examine the relationship between their subjective moral agency, the moral ontology of nursing, and decision-making. Finally, assisted death influenced RNs’ experiences with interprofessional teamwork, wherein the nuanced aspects of collaboration, interprofessional relationships and team-based engagement were influenced by the challenging landscape of actualizing teamwork in the face of assisted death. Ultimately, these experiences highlighted the exceptionally challenging nature of assisted death-related care.
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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 | 0.026 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".