Palliative care providers’ roles in medical assistance in dying decision-making triads with patients and families: A qualitative analysis
Bibliographic record
Abstract
OBJECTIVES: Research on medical assistance in dying (MAiD) decision-making indicates that family members and close friends are often involved in making decisions with patients and their care providers. This decision-making model comprising patients, family members, and palliative care providers (PCPs) has been described as a triad. The objective of this study is to understand PCPs' experiences engaging in MAiD-related decision-making triads with patients and their families in Canada. METHODS: Semi-structured qualitative interviews were analyzed using interpretive description. RESULTS: We interviewed 48 specialist PCPs in Vancouver (26) and Toronto (22). Interviews were audio-recorded, professionally transcribed, and coded using a coding framework. PCPs take on 5 notable roles in their work with family members around MAiD. They provide emotional support and counseling, balance confidentiality between patients and families, provide education, coordinate support, and mediate family dynamics. SIGNIFICANCE OF RESULTS: PCPs take on multiple roles in working with patients and families to make decisions about MAiD. As patients and families may require different forms of support throughout the MAiD pathway, PCPs can benefit from institutional and interprofessional resources to enhance their ability to support patients and families in decision-making and bereavement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".