The Discourse of Medical Assistance in Dying and Its Relationship With Hospice Palliative Care in Canada: An Integrative Literature Review
Bibliographic record
Abstract
AIM: To explore how the legalisation of medical assistance in dying (MAiD) has shaped the discourse of MAiD and its relationship with hospice palliative care (HPC) in Canada. BACKGROUND: There is perceived tension in the discourse between the goals of MAiD and HPC, but little literature examines this relationship and the effect it has on healthcare providers such as nurses. DESIGN: Integrative review following Whittemore and Knafl's and Toronto and Remington's methodology. REVIEW METHODS: A search was conducted to identify literature discussing MAiD and HPC in Canada. Articles were critically appraised for methodological quality. Data from each article were abstracted, thematically analysed, and synthesised. DATA SOURCES: Initial searches were conducted in CINAHL, PubMed, and professional association and government websites in September 2018 and updated in May 2023. RESULTS: A total of 457 records were screened for inclusion, and 83 articles were included. Articles included healthcare provider, patient, public, and institutional perspectives. Three themes identified from the data were the relationship between MAiD and HPC, suffering in the context of MAiD, and moral distress and moral uncertainty in providing or not providing MAiD. CONCLUSIONS: The discourse around the relationship between MAiD and HPC is complex and contextual. Personal and professional understandings of end-of-life care differ and influence perspectives on how and whether MAiD and hospice palliative care can be reconciled. More exploration of this topic is recommended, given the changing legislation and beliefs around MAiD. IMPACT: Findings consider how the concepts of end of life, MAiD, HPC, suffering, and moral distress influence and are influenced by the discourse of dying. This review provides direction for healthcare professionals working in end-of-life care and future ethical and moral areas for consideration. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution was necessary for this literature review.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".