“What Is Right for Me, Is Not Necessarily Right for You”: The Endogenous Factors Influencing Nonparticipation in Medical Assistance in Dying
Bibliographic record
Abstract
Access to medical assistance in dying (MAID) is influenced by legislation, health care providers (HCPs), the number of patient requests, and the patients’ locations. This research explored the factors that influenced HCPs’ nonparticipation in formal MAID processes and their needs to support this emerging practice area. Using an interpretive description methodology, we interviewed 17 physicians and 18 nurse practitioners who identified as non-participators in formal MAID processes. Nonparticipation was influenced by their (a) previous personal and professional experiences, (b) comfort with death, (c) conceptualization of duty, (d) preferred end-of-life care approaches, (e) faith or spirituality beliefs, (f) self-accountability, (g) consideration of emotional labor, and (h) future emotional impact. They identified a need for clear care pathways and safe passage. Two separate yet overlapping concepts were identified, conscientious objection to and nonparticipation in MAID, and we discussed options to support the social contract of care between HCPs and patients.
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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 | 0.017 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".