PIECES of My RELATIONSHIPS: The Cultural Adaptation of a Biographical Assessment Tool for Indigenous Older Adults in Canada
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Healthcare services are rarely designed to meet the needs of Indigenous people, resulting in culturally unsafe care and assessment tools. This paper describes a collaboration between North East Behavioural Supports Ontario (NEBSO), university researchers, and Indigenous communities to adapt a biographical assessment tool used by NEBSO to be culturally appropriate and safe for Indigenous older adults (55+) in long-term care facilities in Ontario, Canada. RESEARCH DESIGN AND METHODS: Over 36 months, this project applied an Indigenized, community-based participatory research (CBPR) and cultural safety framework to the adaptation process. Qualitative data sources include the guidance of an Indigenous Elder, an Anishinaabe Language Expert Group, and focus groups conducted along the North Shore of Lake Huron, Sudbury, and Cochrane, Ontario. RESULTS: The adapted tool shifts the focus from personhood to relationships, includes culturally relevant domains, and supports trauma-informed approaches. Five themes were identified during the adaptation process: (1) practicing a relational approach to care, (2) valuing Indigenous language, (3) understanding Indigenous trauma, (4) respecting cultural values and understandings, and (5) addressing systemic barriers to culturally safe care. DISCUSSION AND IMPLICATIONS: Themes elucidated from this research process can inform future studies adapting mainstream practice tools and developing new tools for Indigenous populations. The collaboration and approach to this adaptation process demonstrated how cultural safety at systemic and practice levels can be addressed through CPBR partnerships between universities, organizations, and Indigenous communities. Findings support the need to evaluate the cultural safety of other assessments for older Indigenous adults in health care settings.
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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 | 0.019 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".