Enabling Rural Telehealth for Older Adults in Underserved Rural Communities: Focus Group Study
Bibliographic record
Abstract
BACKGROUND: Telehealth is often suggested to improve access to health care and has had significant publicity worldwide during the COVID-19 pandemic. However, limited studies have examined the telehealth needs of underserved populations such as rural communities. OBJECTIVE: This study aims to investigate enablers for telehealth use in underserved rural populations to improve access to health care for rural older adults. METHODS: In total, 7 focus group discussions and 13 individual interviews were held across 4 diverse underserved rural communities. A total of 98 adults aged ≥55 years participated. The participants were asked whether they had used telehealth, how they saw their community's health service needs evolving, how telehealth might help provide these services, and how they perceived barriers to and enablers of telehealth for older adults in rural communities. Focus group transcripts were thematically analyzed. RESULTS: The term telehealth was not initially understood by many participants and required an explanation. Those who had used telehealth reported positive experiences (time and cost savings) and were likely to use telehealth again. A total of 2 main themes were identified through an equity lens. The first theme was trust, with 3 subthemes-trust in the telehealth technology, trust in the user (consumer and health provider), and trust in the health system. Having access to reliable and affordable internet connectivity and digital devices was a key enabler for telehealth use. Most rural areas had intermittent and unreliable internet connectivity. Another key enabler is easy access to user support. Trust in the health system focused on waiting times, lack of and/or delayed communication and coordination, and cost. The second theme was choice, with 3 subthemes-health service access, consultation type, and telehealth deployment. Access to health services through telehealth needs to be culturally appropriate and enable access to currently limited or absent services such as mental health and specialist services. Accessing specialist care through telehealth was extremely popular, although some participants preferred to be seen in person. A major enabler for telehealth was telehealth deployment by a fixed community hub or on a mobile bus, with support available, particularly when combined with non-health-related services such as internet banking. CONCLUSIONS: Overall, participants were keen on the idea of telehealth. Several barriers and enablers were identified, particularly trust and choice. The term telehealth is not well understood. The unreliable and expensive connectivity options available to rural communities have limited telehealth experience to phone or patient portal use for those with connectivity. Having the opportunity to try telehealth, particularly by using video, would increase the understanding and acceptance of telehealth. This study highlights that local rural communities need to be involved in designing telehealth services within their communities.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".