[TD‐P‐012]: ACTO DEMENTIA: IMPLEMENTING ACCESSIBILITY OPTIONS FOR DEMENTIA IN EXISTING TOUCHSCREEN APPS
Bibliographic record
Abstract
Enabling independent activity can be beneficial for people living with dementia to promote autonomy, reduce boredom and to avoid dependence on caregivers. There is growing evidence that people living with dementia are able to successfully use touchscreen tablet devices, and this technology is increasingly available and affordable. In an earlier study, two existing touchscreen applications (apps) were tested with people living with dementia. It was established that these apps were enjoyable and that people were able to use them, but design issues were identified for this population. The developers of the apps were approached and accessibility options were implemented in collaboration with the researchers. In order to compare the original apps with the ‘dementia-friendly’ versions, a new study was conducted repeating the design of the original study. A new cohort of thirty older adults living with dementia were recruited from local care services and assigned to play either game one (Solitaire) or game two (Bubble Explode). Each participant played the same game on three separate occasions within one week. Performance on the games were compared with the results of the original study. Preliminary results suggest that the amended version of Solitaire was more accessible for people living with dementia, evidence by a reduction in the number of errors, an increased response to the prompt feature and an increase to the number of participants able to progress through the game. In contrast, participants’ performance on the amended version of Bubble Explode was comparable with the original app, suggesting a ceiling effect. This study highlights the potential in working collaboratively with service users, researchers and app developers to make everyday technology more accessible for people living with dementia.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.052 | 0.016 |
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".