EXPLORING END-OF-LIFE DEMENTIA CARE IN RESIDENTIAL CARE SETTINGS: TOWARD A RELATIONAL MODEL
Bibliographic record
Abstract
Abstract With the biomedicalization of death in Canada, and the stigma associated with both dementia and death, people living with dementia (PLwD) in Canada suffer painful and undignified end-of-life (EOL) experiences. There is growing evidence that relational approaches, which value relationships as complex and dynamic connections including broader social, cultural, political, and environmental forces, can reduce stigma and improve quality of care. Yet, these approaches have not been explored or implemented in EOL care. Further, despite that EOL care is a priority in a number of national dementia strategies, EOL research in Canada remains limited and has largely neglected the inclusion of PLwD. To address these limitations, we conducted arts-based research conversations with PLwD in residential care settings in Ontario, Canada. These sessions were guided by Liberation Arts (i.e., using the arts to challenge oppressive attitudes, policies and practices), co-facilitated by community artists and researchers, and focused on what compassionate, relational EOL care looks like from the perspectives and experiences of PLwD. Transcripts of the audio-recorded conversations and the art created with PLwD were analyzed using the participatory Critical and Creative Hermeneutic Analysis Framework. Our analysis highlights EOL as relational (i.e., a communal rather than an individual process), as demonstrated by prioritizing relationships (e.g., human, pets, biographical objects, place/space), honoring PLwD (e.g., cultural/religious traditions, contributions to life), and supporting living life until the end. Our analysis contributes to the nascent EOL research that is inclusive of PLwD and will importantly inform a new model of EOL care grounded in relational caring.
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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 | 0.020 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.024 | 0.057 |
| Scholarly communication | 0.019 | 0.012 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".