Developing interdisciplinary participatory practices to disrupt the status quo in dementia research
Bibliographic record
Abstract
Abstract Background In dementia research, there is a growing emphasis on generating meaningful research collaborations with people with lived experiences (PWLE). This brings attention to different participatory methods that have the ability to shift perspectives in research and deepen engagement with both PWLE and researchers. However, how participatory methods are realized in practice across the research process requires further investigation; as such, the purpose of this study was to: 1) Explore existing interdisciplinary practices, tools and strategies that promote partnership with PWLE to amplify lived experiences and foster inclusivity; and 2) Identify gaps and opportunity spaces to further develop person‐centred and collaborative research tools and practices. Method The Alzheimer Society of B.C., Emily Carr University’s Health Design Lab and researchers from the University of Victoria and the University of British Columbia partnered at the 2021 Dementia Lab conference to conduct two virtual participatory workshops. The workshops gathered 38 participants including researchers, interdisciplinary creatives, designers and PWLE. Participants were invited to share their experiences in dementia research and their vision of how to foster best‐practices. Design methods such as envisioning, imagining, visualizing and drawing were adopted to facilitate dialogue and bring out tacit knowledge held by participants. Results Inductive analysis of workshop data revealed that interdisciplinary practices are adopted in different dementia‐related projects to foster collaboration with PWLE, which contributes to levelling out epistemological hierarchies. The following four overlapping themes emerged from the analysis: 1) Relationships of reciprocity: Translating research findings into community support and ensuring participants are invited to participate in knowledge making and sharing. 2) Pace: Developing research strategies, objectives and methods that allow for a slower pace to afford generative and person‐centred outcomes. 3) Power dynamics: Shifting hierarchical power relations in research activities. 4) Generative and continuous practices: Embedding continuity of knowledge and ongoing relationships into research projects to ensure that acquired knowledge can be continually nourished, adopted and updated. Conclusion By centring perspectives of people with lived experiences of dementia and fostering interdisciplinary collaborations, generative and person‐centred research practices can propel a shift in the status quo of dementia research, while empowering people living with 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 | 0.373 | 0.253 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.026 | 0.094 |
| Scholarly communication | 0.026 | 0.031 |
| Open science | 0.007 | 0.052 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".