Development and implementation of a training program to facilitate community partnerships in the Indigenous Cultural Understandings of Alzheimer’s Disease and Related Dementias – Research and Engagement (ICARE) project
Bibliographic record
Abstract
Abstract Background Indigenous Cultural‐understandings of Alzheimer’s – Research and Engagement (ICARE) is a program of research investigating the lived experiences of family and professional care providers for Indigenous people with dementia involving three diverse sites in Canada and the United States. We employ a community‐based participatory research (CBPR) approach that includes hiring Indigenous community‐based researchers to assist with community engagement, subject recruitment, data collection, analysis, and dissemination. This poster describes the development and deployment of a training program designed to build capacity and support community participation in the ICARE project. Method The goal was to design culturally safe training that would support community participation in the study, build research capacity in local community members, and improve standardization of protocols across the sites. The training objectives were to teach the basics of CBPR, administrative tasks, basics of qualitative research, protocols of the study, including research ethics and compliance. To accomplish this, we used a Two‐Eyed seeing approach and cultural safety lens. The training encompasses four modules, with online active and reflective learning, mandatory readings, and videotaped interviews. Five community researchers completed the training. Post‐training debriefing interviews and written review of lessons learned were conducted four months after the training was completed. Result At completion of the training, community researchers could define the key tenets and methodological procedures used in CBPR, including the unique ethical considerations for completing research related to dementia within Indigenous communities, the administrative duties required to produce reliable data, and demonstrate key qualitative research. Trainees reported the videotaped interviews conducted with a senior community were the most important to their learning, as the videos gave concrete examples of what to expect in conducting research within their own communities. They wished we had more content and videos on accessing and using the technology associated with the administrative tasks. Conclusion Hiring and training community‐based researchers is considered best practice in Indigenous Health research, yet there are few guidelines on how to develop local capacity to fill these roles. The ICARE training provided community‐based researchers with critical skills to facilitate community involvement in the research process and grounding in academic protocols and methods.
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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 | 0.028 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".