Enhancing Telehealth Competency: Development and Evaluation of Education Modules for Older Adults
Bibliographic record
Abstract
Despite a rapid increase in telehealth utilization, older adults disproportionately experience disparities to services. To promote telehealth accessibility among this population, there is a need for specific training to increase user perceived competency. For this sequential mixed-methods study, we designed telehealth education modules through consultation with older adults. We then evaluated their impact on older adults’ perceived telehealth competency. To solicit feedback on preliminary modules, we administered a semi-structured interview to a sample (n = 5) of older adults; then, we assessed the revised modules’ impact on perceived competency among a sample of older adults (n = 53). Participants critiqued the preliminary training materials as having limited information on telehealth privacy and advised increasing the accessibility of design. Those that completed the revised modules demonstrated significant improvements in perceived telehealth competence. Telehealth training modules may be a promising method to increase perceived telehealth competency among older adults.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".