Practising brain health through traditional teachings and arts: A project funded by the Centre for Aging and Brain Health Innovation
Bibliographic record
Abstract
Abstract Background The loss of Indigenous culture in Canada through colonial interventions such as Residential Schools and the 60’s Scoop have left Indigenous Peoples and communities with deep‐rooted trauma. This type of trauma, in addition to the social isolation of living in remote communities, places Indigenous populations at risk for developing dementia. There is a need to increase opportunities for aging Indigenous populations to engage in social interaction that is culturally‐relevant and based in Traditional ways and culture. Method Morning Star Lodge, an Indigenous Health Research lab, has developed workshops for aging Indigenous adults who are at risk for developing dementia and their caregiver(s) to engage in traditional activities such as: games, arts and crafts, prayer (smudging). Research circles were conducted with Indigenous community members aging in place along with their caregiver(s) to discuss their perceived impacts on social functioning and cognitive health. Result The community members engaged in social interaction through Indigenous languages and story‐sharing. Traditional Knowledges and teachings were also weaved into the project design as many aging individuals expressed a feeling of isolation from cultural events and ceremonies due to immobility or lack of assistance with transportation, other needs, and the COVID‐19 pandemic. Through the data collected via an Indigenous, community‐led qualitative data analysis method the research team was able to identify central themes regarding practising Traditional arts and the cognitive health benefits that caregivers would like integrated in their communities. Conclusion Further research is needed to evaluate the long‐term benefits of health outcomes for Indigenous Peoples living with dementia and the effects on caregiver stress. Indigenous caregivers have expressed a desire for Traditional arts and teachings in their communities to alleviate stressors caused by dementia.
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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 | 0.014 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".