MAiD (Medical Assistance in Dying) and Meaning: An Exploration of the Experience and Ability to Make Meaning through Involvement in a MAiD-Specific Bereavement Group, the Synergistic potential of COVID-19 and MAiD, and the Impact of Healthcare Providers Relationships from the Perspective of Relational Ethics on the Legacy of MAiD-Involved Families into their Bereavement
Bibliographic record
Abstract
MAiD became legally accessible to Canadians with a grievous and irremediable illness in June of 2016. As I write in 2023, MAiD has been expanded to include patients who do not have a foreseeable death, with anticipated inclusion of those with mental illness as a sole underlying medical condition (MI-SUMC) in 2024. As MAiD now accounts for over 3% of all deaths annually in Canada, there is a growing impetus to explore ways by which MAiD practice can be improved and care can be extended to the family members following the death of a patient.\nA hospital in southwestern Ontario created a curriculum for a MAiD specific bereavement group, to support this unique community of loss and further the Canadian initiative for excellence in palliative care (2019) – which extends to the entire network of those involved in supporting a dying patient. It was imperative that this be evaluated to determine if the promises made to this inaugural bereavement group were upheld, and how MAiD practice can be improved to meet this important initiative. In this process, three groups of findings emerged pertaining to: Assessing and determining the impact and efficacy of the MAiD bereavement group using a mixed methods approach The synergistic impact of COVID-19 public health measures on those bereaved by MAiD during the pandemic The relationship between healthcare providers and MAiD-involved families, and the impacts of this relationship into their bereavement through a relational ethics framework \nFindings suggest that a bereavement group can support families and help generate communities with shared experiences. Additionally, through secondary analysis, findings suggest that COVID-19 adversely impacted this group through additional isolation, most particularly for those who were already experiencing social isolation and stigma due to the nature of their significant person’s death which was further supported by their involvement in a bereavement group. Finally, the relationship between the health care provider and the MAiD family can have a positive or negative impact on their bereavement narrative, depending on their level of engagement, support of the family before and after the death, and facilitation of access for the patient to MAiD.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.034 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.002 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 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".