ASSESSING INNOVATIVE ASSISTIVE TECHNOLOGIES FOR OLDER ADULTS; A KNOWLEDGE AND TECH DEVELOPER'S PERSPECTIVES
Bibliographic record
Abstract
Abstract Objective Can Assist is a University of Victoria organization that has been developing assistive technologies (ATs) for almost two decades aimed at developing client-centred broad-impact solutions that address unmet need and help people improve their independence and quality of life. CanAssist’s interest and involvement in this study is predicated on our belief that their approach to technology development align with the criteria needed for determining better tools for evaluating assistive technologies need to be developed and implemented. This is critical to our goal of providing successful customized technology solutions to sustain our clients’ independence and autonomy. Methods From the beginning of the project, as a Research User Co-Lead, CanAssist has actively participated in regular advisory committee and expert panel meetings along with several other research activities to co-create all dimensions of the study. Results The results from the Rapid Realist Review and preliminary analyses of the interview data with older adults and caregivers have validated the need for more appropriate assessment/evaluation tools to address the varied AT needs of older adults and their caregivers. In particular, the study has provided opportunities for our staff and clients to examine and discuss important factors/processes for successful AT development and implementation. Conclusions As a key partner on this implementation science team, CanAssist will use the study’s findings to provide information to our development and management teams on how to appropriately scale-up, spread, and sustain the use of ATs in the health and social care system.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".