Oncologists and Medical Assistance in Dying: Where Do We Stand? Results of a National Survey of Canadian Oncologists
Bibliographic record
Abstract
Background: In June 2016, when the Parliament of Canada passed Bill C-14, the country joined the small number of jurisdictions that have legalized medical assistance in dying (maid). Since legalization, nearly 7000 Canadians have received maid, most of whom (65%) had an underlying diagnosis of cancer. Although Bill C-14 specifies the need for government oversight and monitoring of maid, the government-collected data to date have tracked patient characteristics, rather than clinician encounters and beliefs. We aimed to understand the views of Canadian oncologists 2 years after the legalization of maid. Methods: We developed and administered an online survey to medical and radiation oncologists to understand their exposure to maid, self-perceived knowledge, willingness to participate, and perception of the role of oncologists in introducing maid as an end-of-life care option. We used complete sampling through the Canadian Association of Medical Oncologists and the Canadian Association of Radiation Oncology membership e-mail lists. The survey was sent to 691 physicians: 366 radiation oncologists and 325 medical oncologists. Data were collected during March-June 2018. Results are presented using descriptive statistics and univariate or multivariate analysis. Results: The survey attracted 224 responses (response rate: 32.4%). Of the responding oncologists, 70% have been approached by patients requesting maid. Oncologists were of mixed confidence in their knowledge of the eligibility criteria. Oncologists were most willing to engage in maid with an assessment for eligibility, and yet most refer to specialized teams for assessments. In terms of introducing maid as an end-of-life option, slightly more than half the responding physicians (52.8%) would initiate a conversation about maid with a patient under certain circumstances, most commonly the absence of viable therapeutic options, coupled with unmanageable patient distress. Conclusions: In this first national survey of Canadian oncologists about maid, we found that most respondents encounter patient requests for maid, are confident in their knowledge about eligibility, and are willing to act as assessors of eligibility. Many oncologists believe that, under some circumstances, it is appropriate to present maid as a therapeutic option at the end of life. That finding warrants further deliberation by national or regional bodies for the development of consensus guidelines to ensure equitable access to maid for patients who wish to pursue it.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".