Health-related technology use by older adults in rural and small town communities
Bibliographic record
Abstract
This chapter explores how older adults living in rural and small town communities use technology for health-related purposes to remain healthy and live independently. Specifically, it explores if, and how, this population uses technology for health-related education, social support, health reminders, health alerts and health parameter monitoring. The study is foundational to addressing questions related to effective use of technology for improving health self-care self-efficacy and maintenance of ability to independently perform activities of daily living in older adults. Data gathered include ways older adults use technology for health-related purposes, access they have to health-related technology and ways older adults consider health-related technology helpful in assisting them to remain independent and community-dwelling. A review of background literature, description of the research methods used, study findings and a discussion including recommendations for enhancing the use of health-related technology by older adults is included. The chapter concludes with recommendations for further research.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".