Co-Designing Dementia Diagnosis And Post Diagnostic Care, The Cognisance Project: Forward with Dementia (FWD)
Bibliographic record
Abstract
Despite many national guidelines for diagnosis and management of dementia, persons diagnosed with dementia and their family carer partners are often dissatisfied with the diagnostic process and receive limited post-diagnostic support. Teams from Australia, Canada, the Netherlands, the UK and Poland co-designed and delivered, in partnership with people living with dementia, family care partners and health care professionals, online packages, toolkits and campaigns to improve the dementia diagnostic process and post-diagnostic support.Our website www.forwardwithdementia.org (FWD) offers information in English, Dutch, French and Polish for people living with dementia, carers and health care practitioners developed based on published evidence, national dementia guidelines and, across five countries, from surveys focus groups and input from each target group; and refined after field testing. FWD uses engaging language and graphics to provide personal stories, tips, advice and local contacts for assistance. The FWD website, and in two countries an online tool-kit for curating the information, was promoted with social media, regionally-specific targetted campaigns, webinars, local events, television coverage and presentations to the public and to health care providers. The effectiveness of the internationally varied campaigns, evaluated using RE-AIM framework, demonstrated variable Reach and Engagement; Adoption, Implementation and Maintenance are still being assessed. In collaboration with the World Health Organisation, Alzheimer’s Disease International and Dementia Alliance International we have developed a playbook that facilitates FWD to be adapted and implemented internationally.
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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 | 0.026 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".