Unacknowledged Pain and Disenfranchised Grief: A Narrative Analysis of Physical and Emotional Pain in Complex MAiD Bereavement Stories
Bibliographic record
Abstract
Background: Pain can influence an individual's choice to pursue medical assistance in dying (MAiD) and may also influence how family members experience that decision. Family conflict or discordance surrounding a loved one's MAiD decision can cause unique challenges affecting grief and bereavement, including disenfranchised grief. There is limited knowledge of how individuals with complex MAiD bereavement experiences describe the role of physical and emotional pain in their bereavement stories. Aims: This article explores the role of physical and emotional pain in the stories of family members with complex MAiD bereavement and identifies opportunities to improve care for individuals and families experiencing disagreement around MAiD. Methods: We conducted qualitative interviews and utilized a narrative and ethics of care approach to analyze the data. Results: = 12 narrative interviews with participants in three provinces: Ontario, British Columbia, and Alberta. Descriptions of physical pain were used to justify the morality, or immorality, of MAiD in the context of patient suffering. Emotional pain described experiences where participants' feelings about MAiD went unacknowledged by their family or friends, institutions, and sociopolitical environments. We conceptualize this unacknowledged emotional pain as disenfranchised grief and make recommendations to improve care for individuals experiencing complex MAiD bereavement. Conclusions: Experiences of physical and emotional pain leave a lasting impact on family members with complex MAiD bereavement. Health care professionals should continue to improve care for family members following MAiD, especially where there is disagreement or family conflict.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".