Medical assistance in dying and the meaning of care: Perspectives of nurses, pharmacists, and social workers
Bibliographic record
Abstract
Medical Assistance in Dying (MAiD) was legalized in Canada in 2016. While it has generated significant academic interest, the experiences of healthcare workers other than physicians remain understudied. This paper reports on a qualitative study of interprofessional Healthcare Providers (HCPs) involved in the provision of MAiD in order to: (1) characterize providers' views about the care they offer in general; (2) examine whether or not they consider MAiD a form of care; and (3) explore their reasons for viewing or not viewing MAiD as care. Semi-structured qualitative interviews were conducted with ten nurses, eight social workers, and three pharmacists with firsthand experience delivering MAiD at an academic hospital in Toronto, Canada. The study was approved by the hospital's REB. Written informed consent was obtained prior to participation. Codebook thematic analysis and template analysis generated four themes: (1) care as advocacy, (2) care as easing suffering, (3) care as psychosocial, and (4) care as relational. Every participant viewed MAiD as a form of care and drew on these four themes to authenticate MAiD as care. Participants consider MAiD a form of care for patients, families, other healthcare workers, and even themselves. In alternating and composite fashion, they describe MAiD in terms of autonomy, easing suffering, and a kind death for the dying (and those entrusted with their care)-a complex choreography of social discourses and moral logics that refuse to settle into a simple dichotomy of "choice versus care." Participants depict MAiD in many of the same terms and imagery they use to describe the care they offer in general. In light of ongoing social controversies surrounding MAiD, HCPs utilize a range of logics strategically to repel negative attention and enable their participation in what they see as a caring end for their patients.
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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 | 0.016 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.025 | 0.029 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.004 | 0.009 |
| 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".