A Dashboard for Managing an Ecosystem and People With Dementia: Protocol for a Healthy Ageing Ecosystem for People With Dementia (HAAL) International Feasibility Pilot Study
Bibliographic record
Abstract
BACKGROUND: Dementia is a syndrome characterized by a wide spectrum of symptoms and needs. There is no cure for this syndrome, which represents a major challenge to society in terms of quality of life for those affected and in terms of workload and stress burden for those who take care of them. OBJECTIVE: The Healthy Ageing Ecosystem for People With Dementia (HAAL) aimed to improve the quality of life of both people with dementia and their formal caregivers (FCs) and informal caregivers (ICs) by providing a personalized set of devices to the person with dementia, along with a dashboard designed for caregivers to monitor and manage the older person. METHODS: The HAAL platform comprises a dashboard that integrates, aggregates, and analyzes heterogeneous data gathered from an ecosystem of devices designed for and tested with people with dementia. The study was designed as a technical feasibility pilot to test the HAAL ecosystem in 3 countries: Italy, Taiwan, and the Netherlands, where older people with initial, moderate, and severe dementia were enrolled, respectively. The study was run in 2 stages: the alpha and beta pilot studies aimed to test the second and third prototypes of the platform, respectively. RESULTS: The alpha test was conducted from March to May 2023, involving 41 end users, of which 13 were people with dementia, 13 were ICs, and 15 were FCs. The beta test was conducted from September 2023 to February 2024, involving 83 end users, of which 26 were people with dementia, 20 were ICs, and 37 were FCs. The results have been elaborated and are supposed to be published by 2026. CONCLUSIONS: The HAAL pilot study was an innovative feasibility study whose primary objectives were to assess reduction in care load for FCs, stress relief for FCs and ICs, and improvement in the perceived quality of life for ICs and people with dementia. The study also evaluated the usability and the acceptance of the platform. Preliminary analyses of the results showed that the HAAL platform partially relieved caregivers' stress and that the quality of life of people with dementia did not worsen over the test period. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/59860.
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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 | 0.037 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.031 | 0.007 |
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".