What Factors Influence Canadian Nurse Practitioners’ Willingness to Act as Assessors and Providers for Medical Assistance in Dying (MAID)?
Bibliographic record
Abstract
In passing legislation in 2016 to allow medical assistance in dying (MAID), Canada became the world's first jurisdiction to allow nurse practitioners (NPs) to act as MAID assessors and providers. Health Canada's annual report shows that the demand for MAID in Canada increases each year, as does the proportion of MAID cases that NPs provide. The purpose of this study was to better understand factors that motivate or deter nurse practitioners from becoming MAID assessors and providers. The study design was a secondary analysis of a large qualitative dataset guided by interpretive description methodology. Primary data collection took place from 2018 to 2023 via semi-structured interviews with nurses and NPs. Secondary analysis of transcripts of all of the NPs interviewed for the primary study allowed for identifying significant motivational and deterring themes in their accounts. The analysis yielded two categories of motivating factors (philosophical perspectives; experiences with death and dying) and three deterring factors (moral complexity; health system barriers; professional and social considerations), and further generated insights around supports and practices that make NP MAID work viable. As the first study that explicitly sought to understand what explains Canadian NPs' willingness to participate in MAID, these findings fill a gap in the available knowledge.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".