Getting Beyond Pros and Cons: Results of a Stakeholder Needs Assessment on Physician Assisted Dying in the Hospital Setting
Bibliographic record
Abstract
This study assessed the attitudes and needs of physicians and health professional staff at a tertiary care hospital in Canada regarding the introduction of physician assisted dying (PAD) during 2015-16. This research aimed to develop an understanding of the wishes, concerns and hopes of stakeholders related to handling requests for PAD; to determine what supports/structures/resources health care professionals (HCP) require in order to ensure high quality and compassionate care for patients requesting PAD, and a supportive environment for all healthcare providers across the moral spectrum. This study constituted a mixed methods design with a qualitative descriptive approach for the study's qualitative component. A total of 303 HCPs working in a tertiary care hospital completed an online survey and 64 HCPs working in hospital units with high mortality rates participated in 8 focus group discussions. Both focus group and survey data coalesced around several themes to support the implementation of PAD following the decriminalization of this practice: the importance of high quality care; honoring moral diversity; supporting values (such as autonomy, privacy, beneficence); and developing resources, including collaboration with palliative care, education, policies and a specialized team. This study provided the foundational evidence to support the development of the PAD program described in other papers in this collection, and can be a model for gathering evidence from stakeholders to inform the implementation of PAD in any healthcare organization.
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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 | 0.030 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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 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".