Investigating the enabling factors influencing occupational therapists’ adoption of assisted living technology
Bibliographic record
Abstract
IntroductionResearch into technology adoption has focused on older adults’ motivations, with less exploration of the perspective of healthcare providers, including occupational therapists, who are often described as the gatekeepers to assisted living technology. MethodThis qualitative study utilized semi-structured interviews and focus groups with 20 occupational therapists in England and Scotland. The goal was to identify those enabling factors necessary for occupational therapists to adopt assisted living technology. ResultsFive themes emerged regarding the enablers needed to support the adoption of assisted living technology by occupational therapists, including: (1) a positive client–therapist relationship; (2) affordability; (3) time; (4) increased awareness, education, and training; and (5) usability features of the assisted living technology. ConclusionWith an aging population and the increasing role that technology is playing globally in older adults’ lives, it has never been more important for occupational therapists to harness the potential of new, developing, and existing technologies to support people to live and age as well as possible. To accomplish this, however, requires that occupational therapists are equipped with the time, training, and education necessary to offer their clients assisted living technologies that are client-centered, usable, and affordable.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".