Developing practice standards for engaging people living with dementia in product design, testing, and commercialization – a case study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To successfully create assistive technologies for persons with dementia, product developers must understand the capacity of people with dementia to use these technologies. Capacity assessment is typically done through user experience research. However, the published literature is bereft of guidelines to conduct optimal user experience research in samples of persons with dementia. We recruited persons with dementia from community-based organizations and private partners to participate in user experience research for an assistive technology platform. After a testing session, we used semi-structured interviews to ask participants about their involvement in the user experience process. We employed an inductive thematic approach to analyze the interview transcripts and draft guidelines to meaningfully engage persons with dementia in user experience research in the future. Ten participants with mild to moderate dementia (6 females, 4 males) participated in the study. Nine participants had previous experience with mobile devices. Thematic analysis yielded three overarching themes: 1) the techniques, approaches and attributes of the interviewer; 2) participants' views on being part of the user experience research process; and 3) specific items to optimize the research process. Resulting guidelines were divided into recommendations for the interviewer specifically, and for the broader research process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it