EXPLORING ASSISTIVE TECHNOLOGY ACCESS AND USE AMONG OLDER ADULTS THROUGH SELF-DIRECTED HOME TOURS
Bibliographic record
Abstract
Abstract Assistive technology (AT) and home modifications play a crucial role in enhancing independence and quality of life for individuals with disabilities. Our aim was to explore access and use of AT for older adults through an innovative research methodology, virtual self-directed home tours. These interviews were held across three groups of participants (A) first-generation Chinese-speaking immigrants to Canada, (B) second and subsequent generations of Chinese-speaking immigrants, and (C) native-born English-speaking Canadian citizens of European descent. A total of 17 interviews were conducted (Group A=8, Group B=3, and Group C=6) through Zoom Video Communications. Participants were demographically diverse adults with disabilities living in Metro Vancouver, British Columbia (Age= 59 ± 15 years; 11 female and 6 male). Most participants had assistance from their caregivers to complete the interview. Three main themes were identified. (1) Enabling Participation described the transformative role of AT in optimizing participants’ ability to engage in activities that are meaningful to them independently. (2) User-Driven Do-It-Yourself Adaptations explored how participants developed cost effective alternatives by creatively adding their own modifications to existing AT. (3) Navigating Complexities and Hurdles encompassed the challenges with accessing and incorporating AT in their homes due to lack of adequate knowledge transfer from healthcare professionals, financial circumstances, and other systemic barriers that further delayed the implementation of home modifications. Chinese-speaking immigrants faced compound challenges due to language barriers. The insights gained from this study may inform strategies for improving the experiences of older adults accessing and using AT and home modifications.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".