Engaging Youth in a Co‐Design Process for Development of a Young Dementia Supporter Toolkit
Bibliographic record
Abstract
Dementia-friendly communities are places where people living with dementia and their care partners are understood, respected and supported. It is an environment where they feel more confident and able to participate in all aspects of community life because community members are educated about dementia and know how to engage with and support someone living with the condition. This begins with our youth. By creating supportive and inclusive communities of young people who understand the experience of dementia and the impact of ageism and stereotypes, we can change attitudes before stigma begins and have a long-term impact on mental and social health and wellness of older adults living with dementia. The Alzheimer Society of Ontario (ASO) in partnership with the Murray Alzheimer Research and Education Program (MAREP) at the Schlegel-UW Research Institute for Aging (RIA) brought together a co-design team of youth aged 9 to 16, people living with dementia, care partners, teachers, Alzheimer Society staff and researchers to develop a Young Dementia Supporter Toolkit. The toolkit was designed over xx virtual Zoom meetings and one full-day in-person workshop. The end product was a toolkit for youth, aged 9-12 that equips young people with an understanding of dementia and practical strategies to tackle stigma and support people living with dementia in their families, local communities and beyond by becoming dementia supporters. This presentation will share the co-design process, the contents of the Young Dementia Supporter Toolkit, pilot test feedback results from youth volunteers, and evaluation of the development process including the experiences of co-design team members. Project leads and co-design team members will present the findings.
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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 | 0.022 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".