Engagement of persons with dementia: how to co‐construct research?
Bibliographic record
Abstract
Social determinants of health, such as racialization and socioeconomic status, influence both the risk of developing dementia and access to quality care. However, many dementia studies lack representation from underserved communities, resulting in gaps in understanding their unique needs and the barriers they face in accessing appropriate care. With growing awareness of and interest in addressing these gaps, sharing effective engagement strategies and inclusive research practices becomes essential. This presentation will explore some of the challenges of engaging people living with dementia from underserved communities and offer evidence-based strategies to address these challenges. We will focus on approaches that consider individual needs and socio-cultural contexts while ensuring that voices from diverse communities are included and valued. Drawing on our experiences with participatory research, we will share recommendations on how researchers and healthcare providers can meaningfully collaborate with members of underserved groups to co-design inclusive research methodologies, recruitment strategies, and interventions. These approaches are crucial for improving the representation of underserved communities in dementia research and ensuring their needs are reflected in care delivery design. As a case study, we will present our experience of co-designing an inclusive interview guide and recruitment strategy for people living with dementia and their care partners from racially and economically diverse backgrounds to gather their perspectives on electronic consultations (eConsult) as a means of accessing specialist care. This example highlights how a participatory, co-design approach can bridge the gap between research and underserved communities, fostering inclusivity and shared ownership of research processes and outcomes. This session will offer an opportunity to discuss participatory and co-design approaches as innovative methods in Alzheimer's disease and related dementias research and to foster international collaborations among researchers and patient partners to advance inclusive research practices and equity in dementia care.
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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 | 0.466 | 0.449 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.018 | 0.011 |
| Science and technology studies | 0.023 | 0.054 |
| Scholarly communication | 0.051 | 0.063 |
| Open science | 0.009 | 0.064 |
| Research integrity | 0.018 | 0.027 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".