Redesigning a Telehealth Diabetes Management Program for a Digital Divide Seniors Population
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent advances in health information technologies promise to significantly improve the quality of care and quality of life for individuals who are chronically ill. However, significant challenges exist in targeting Digital Divide populations who are likely to be older, less educated, and novice computer users. This article presents a framework for understanding and reducing barriers for older adults to effectively use health information systems designed for disease management. The research is illustrated in the context of the IDEATel project, a large-scale telemedicine diabetes management and education program. The framework has three interdependent foci: hardware and software systems, tasks supported by the system, and user profiles. These foci are addressed in the context of usability and training studies. The studies document the challenges faced in facilitating patients’ access to Web resources supporting disease management. The article discusses system design changes that are intended to increase participants’ productive use of system resources.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it