Providing medical assistance in dying: Practice perspectives.
Bibliographic record
Abstract
OBJECTIVE: To explore the experiences of the first cohort of physicians to offer medical assistance in dying (MAID) in British Columbia. DESIGN: Qualitative study using semistructured, one-on-one interviews. SETTING: British Columbia. PARTICIPANTS: Eight physicians who offered MAID in British Columbia in 2016. METHODS: The physicians were interviewed by telephone or by e-mail between 4 and 6 months after MAID was made legal in Canada, with follow-up in January 2017. Interviews were audiorecorded, transcribed, and analyzed through qualitative thematic analysis. MAIN FINDINGS: Participants believed that MAID was rewarding and satisfying work. They explained that some of the structural and emotional challenges related to providing MAID included the following: the refusal of faith-based institutions to provide information about MAID to patients, as well as their refusal to allow assessments or deaths to occur on site; having to deny MAID to patients who did not qualify for it; disagreements with colleagues who did not support the provision of MAID; dealing with the grief of family and friends who were present at the death; and feeling like they were always on call. While a few participants thought that the legislative restrictions of Bill C-14 were appropriate in the beginning when MAID was first available in Canada, most would like to see changes to the legislation to make it more aligned with the intent of the Carter decision, including broadening the eligibility criteria to include mature minors and people with advanced psychiatric diagnoses, having the ability to honour advance directives, and removing the requirement of death being in the reasonably foreseeable future for patients with grievous and irremediable conditions. CONCLUSION: Physicians in this study explained that providing MAID is rewarding work; however, there are many challenges that complicate their ability to offer MAID to patients. The current MAID legislation in Canada should be updated to better serve the needs of 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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".