Using a community-based participatory research approach to meaningfully engage those with lived experience of diabetes and homelessness
Bibliographic record
Abstract
INTRODUCTION: Participatory research is a study method that engages patients in research programs, ideally from study design through to dissemination. It is not commonly used in diabetes health services research. Our objectives were to describe the process and challenges of conducting a participatory research project and to highlight the experiences of both patient co-researchers and academic researchers. RESEARCH DESIGN AND METHODS: We recruited people with lived experience of homelessness (PWLEH) and diabetes in Toronto, Canada to become patient co-researchers. They were asked to commit to attending biweekly meetings. We undertook two major research projects: concept mapping to choose a research focus; and photovoice to explore accessing healthy food while homeless. We used a convergent mixed-methods design to evaluate their experience. RESULTS: A diverse group of eight PWLEH had an average attendance of 82% over 21 meetings-despite this success, we encountered a number of challenges of conducting this research: funding, ethics approval and recruitment were particularly difficult. Group members reported that participation improved their ability to self-advocate in their diabetes care and provided them with tangible skills and social benefits. Group members stated that they valued being involved in all aspects of the research, in particular knowledge translation activities, including advocating for nutritious food at shelters; presenting to stakeholders; and meeting with policymakers. CONCLUSIONS: The use of participatory research methods enables academic researchers to support community members in pursuing research that is pertinent to them and which has a positive impact. In our study, co-researchers contributed in meaningful ways and also valued the experience.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".