Winging it: a qualitative study of knowledge-acquisition experiences for early adopting providers of medical assistance in dying
Bibliographic record
Abstract
Background: Medical Assistance in Dying (MAID) was legalized in Canada without a designated period for implementation. Providers did not have access to customary alternatives for training and mentorship during the first 1-3 years after legalization. Objective: To report on how doctors prepared for their first provision of MAID in the early period after legalization in Canada. Design: Qualitative research design within an interpretive phenomenological theoretical framework. We asked participants to describe their experiences preparing for first MAID provision. Analysis of transcripts elicited themes regarding training and information desired by early adopters for provision of newly legalized MAID. Participants: Twenty-one early adopting physician-providers in five Canadian provinces were interviewed. Results: Few formal training opportunities were available. Many early-adopting providers learned about the procedure from novel sources using innovative methods. They employed a variety of strategies to meet their needs, including self-training and organizing provider education groups. They acknowledged and reflected on uncertainty and knowledge gained from unexpected experiences and missteps. Key phrases from participants indicated a desire for early training and mentorship. Limitations: This study included only the perspective of physicians who were providers of MAID. It does not address the training needs for all health practitioners who receive requests for assisted death nor report the patient/family experience. Conclusion: The Canadian experience demonstrates the importance of establishing accessible guidance and training opportunities for providers at the outset of implementation of newly legalized assisted dying.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".