Inclusive dementia research: A guidebook to support researchers engaging with people living with dementia from ethno‐racial communities
Bibliographic record
Abstract
BACKGROUND: Despite the growing ethno-racial diversity of people living with dementia globally and nationally, individuals who participate in dementia research often do not reflect this diversity. An environmental scan of resources that address the intersection of dementia, diversity and research failed to identify resources to support researchers interested in working in this area. A lack of guidance for researchers could result in tokenism, insensitive research practices, and further harm to ethno-racial communities. The objective of this presentation is to describe the "Inclusive Research Guidebook: Partnering with People Living with Dementia from Ethno-racial Communities", a new resource that was co-designed for researchers and research teams to support them in conducting research with ethno-racial communities. METHOD: A diverse Steering Committee that included people living with dementia, family/friend care partners, providers working with people living with dementia and/or people who are part of ethno-racial communities, and researchers was assembled. Over a 1.5-year period, the group worked together to co-design the Inclusive Research Guidebook. Development of the Guidebook included: a rapid review of the literature; monthly meetings with the Steering Committee to develop and review draft content for the Guidebook; an in-person symposium involving a group of 35 people living with dementia, care partners, providers and researchers to review and provide feedback on the Guidebook using a World Café process; and incorporation of the feedback and further engagement with the literature. RESULT: The Guidebook provides information, reflective questions, and resources to support researchers and research teams in considering: (1) individual biases, assumptions, and privileges; (2) how to learn about the community the researchers want to work with, including the community's identity, history, and trauma; (3) building relationships and trust with communities; and (4) considerations for the research team and research processes. The presentation will highlight insights into the co-design process and the key concepts addressed in the Guidebook. CONCLUSION: It is anticipated that the Guidebook will help to promote safe and inclusive research with ethno-racial communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 0.014 |
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".