Co-Design with Caregivers: East Toronto's Caregiver Advisory Group
Bibliographic record
Abstract
Background: As a leading Ontario Health Team (OHT), East Toronto Health Partners (ETHP) have undertaken various initiatives to include patients, community members, and caregivers in program design, planning, and service development. ETHP's Caregiver Advisory Group (CAG) exemplifies true co-design, working on projects and initiatives for caregivers, by caregivers.We are targeting integrated care researchers, policy-makers, OHTs, and organizations working with (or wanting to work with) caregivers as partners.A key focus for us is developing supports for caregivers from ethno-culturally diverse communities. Approach: We recognize the importance of caregiver engagement and co-design in doing this successfully. Many of the caregivers in East Toronto come from immigrant and refugee families, with limited social networks and knowledge of existing healthcare services. ETHP's CAG is compromised of 0-5 members from East Toronto's diverse neighborhoods. Their lived experience and insight is integral to identifying caregiver needs, gaps in services, prioritize solutions, and identify the best ways to share and promote resources.Often, the biggest issue is the language barrier, making it difficult for caregivers who don't speak English, or speak English as a second language, to find the information they need.CAG spearheaded several initiatives aimed at developing resources for caregivers from ethno-culturally diverse communities.Each year focusing on a different project: 202's NICE Fund, 2022's Caregiver Support Initiative, and 2023's Caregiver Navigation Guide. Results: The NICE Fund was able to fund urgent interventions such as medical equipment, homecare services, and medications to low-income caregivers and their care recipients. The CSI developed online and print materials in various languages for accessing resources such as Toronto Seniors Helpline, 2, and Ontario Caregiver Helpline. The Caregiver Navigation Guide was a series of 20 YouTube videos helping caregivers to navigate the healthcare system, later translated into various languages. Implications: Despite best intentions, we often see public engagement initiatives that struggle to draw participants who truly represent the communities they serve, or engage advisors in a way that is both meaningful and impactful. ETHP successfully leverages the individual strengths (caregivers have knowledge, networks, and are experienced system-users) in co-design from project inception through completion.The CAG continues to be active, meeting on a monthly basis, and has recently submitted a proposal to target high-rise seniors building with door-to-door outreach.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".