Elders Living with Dementia: Nuu-Chah-Nulth First Nations Family Perspectives on Elder Healthcare
Bibliographic record
Abstract
In Canada, the literature regarding First Nations people’s experiences with dementia is sparse, as is the literature relating to the health and wellness of Indigenous dementia caregivers. Colonization has imposed physical, psychological and structural disadvantages on Indigenous communities that impact the family’s ability to provide informal dementia care. The First Nations senior population is growing rapidly and there is a pressing need to gather knowledge about the unique needs of First Nations informal dementia caregivers. This doctoral research seeks to contribute to the growing body of literature on this vitally important topic. This thesis reports the findings from my PhD research study, which was conducted in collaboration with the Nuu-Chah-Nulth Tribal Council, and with generous support from the Nuu-Chah-Nulth community. Using an Indigenous storytelling research method, the study explored the following questions: What are the experiences of Nuu-Chah-Nulth First Nations dementia caregivers? What support services do caregivers access and what services do they perceive are lacking? Nine Nuu-Chah-Nulth caregivers shared their experiences providing support and care to a family member with memory loss, and their perspectives on memory care resources. Interviews were conducted in various locations within the Nuu-Chah-Nulth territories to gather the caregiver’s knowledge. The author’s story as an informal dementia caregiver is also interwoven throughout the dissertation. The Nuu-Chah-Nulth caregivers narratives revealed diverse and complex experiences with the following central themes and sub-themes: trauma over the life-cycle (residential school, family violence, grief and loss); pressures of care-giving (managing the symptoms of dementia, health and family dynamics); and finally, participants’ perceptions of community resources. The findings from this research reveal that Nuu-Chah-Nulth dementia caregivers and the family members they supported were still healing from the various traumas that were inflicted on their mind, body and spirit through residential school experiences. Most of the caregivers reported that they prefer to care for their family member at home but community supports are limited.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.033 | 0.010 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".