Advancing Indigenous-Centred Dementia Care: A Qualitative Study
Bibliographic record
Abstract
Indigenous populations in Canada are experiencing increased rates of dementia compared to non-Indigenous populations, yet there remains a lack of culturally safe, Indigenous-centred dementia care. The current dementia care system is ineffective and does not address the care and treatment needs of Indigenous people living with dementia and their care partners. The aims of this project were to gain an understanding of the experiences of dementia for Indigenous people living with dementia, their care partners, families, and communities and to determine the foundational principles of culturally safe approaches to Indigenous-centred dementia care. This work is framed within an Indigenous worldview and informed by Indigenous paradigms of relationality. This research used a Métis methodological approach, Keeoukaywin (The Visiting Way) and qualitative semi-structured interviews to collect in-depth data with 12 participants throughout Alberta. Participants included Indigenous people living with dementia, care partners, and community members and used thematic analysis to create a framework to improve culturally safe dementia care. The framework includes three domains that inform Indigenous-centred dementia care including relationality, being well, and safety. Each of these three domains include subdomains including social, cultural, and physical characteristics informed by participant experiences. This framework provides a foundation that can be integrated into the creation of an Indigenous-centred dementia care approach.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.025 | 0.013 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.007 |
| 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".