‘I feel more part of the world’: Participatory action research to develop post-diagnostic dementia support
Bibliographic record
Abstract
Many people living with dementia are 'on the margins', not accessing services and support, despite policy and care advancements. The COVID-19 pandemic exacerbated this, with the closure of face-to-face support during lockdowns in the UK and globally. The aim of the 'Beyond the Margins' project was to develop, implement, and evaluate a face-face programme of support with, by and for people with direct experience of dementia who are on the margins of existing services and support. In March 2020 the project was interrupted by the outbreak of the COVID-19 pandemic and it changed to an online format. The three-phase participatory action research project included 40 people living with dementia, 26 care partners and 31 health and social care practitioners. A seven-week online personal development programme called Getting On with Life (GO) was developed, delivered, and evaluated. This paper focuses on the participatory approaches used to develop and implement the GO programme, and the resulting aspects of its approach to facilitation and content. Key features include the GO Programme's principles of providing a safe and a respectful space, and the programme's values of: Everyone who comes already knows things, can learn things and can teach things; Doing things 'with' each other, rather than 'for' or 'to' each other; Personalised goals-led by the needs of participants rather than an imposed agenda. A key finding was the importance of developing post-diagnostic programmes as a 'sandwich', providing a safe space for learning that is preceded by understanding pathways to access the programme and followed by explicit consideration of the next steps in increasing social engagement.
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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 | 0.197 | 0.125 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.017 | 0.034 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.006 | 0.026 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".