“Functioning better is doing better”: older adults’ priorities for the evaluation of assistive technology
Bibliographic record
Abstract
Despite the benefits of assistive technology (AT), barriers to technology adoption still exist and are uniquely affecting older populations. Improving technology adoption can be achieved by involving end-users in the development and evaluation process. However, existing AT evaluation tools rarely take into account older adults’ experiences. The goal of this study was to fill this gap by determining which AT evaluation criteria are important for older adults. We conducted 4 nominal group meetings with 21 participants aged 50+ in Vancouver, Canada. In the meetings, participants generated AT evaluation criteria and organized them in the order of importance. The content from the meetings was analyzed using qualitative content analysis. Final rankings were collated to reveal which criteria were the most important across the groups. We found that promotion of independence, affordability, ease of use and ethics are the most important AT evaluation criteria for older adults. Some aspects of ATs that older adults value, such as reliability, are not featured in AT evaluation tools. This study provides insight into older adults’ priorities for AT evaluation criteria, and concerns that older adults have about AT use. The findings are supplemented with a comprehensive analysis of the group discussions that contextualizes the criteria.
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.
How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.102 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".