Telehealth Use for Enhancing the Health of Rural Older Adults: A Systematic Mixed Studies Review
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Telehealth holds potential for inclusive and cost-saving health care; however, a better understanding of the use and acceptance of telehealth for health promotion among rural older adults is needed. This systematic review aimed to synthesize evidence for telehealth use among rural-living older adults and to explore cost-effectiveness for health systems and patients. RESEARCH DESIGN AND METHODS: This systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Study designs reporting health promotion telehealth interventions with rural-living adults aged 55 and older were eligible for review. Following screening and inclusion, articles were quality-rated and ranked by level of evidence. Data extraction was guided by the Technology Acceptance Model and organized into outcomes related to ease of use, usefulness, intention to use, and usage behavior along with cost-effectiveness. RESULTS: Of 2,247 articles screened, 42 were included. Positive findings for the usefulness of telehealth for promoting rural older adults' health were reported in 37 studies. Evidence for ease of use and usage behavior was mixed. Five studies examined intention to continue to use telehealth and in 4 of these, patients preferred telehealth. Telehealth was cost-effective for health care delivery (as a process) compared to face to face. However, findings were mixed for cost-effectiveness with both reports of savings (e.g., reduced travel) and increased costs (e.g., insurance). DISCUSSION AND IMPLICATIONS: Telehealth was useful for promoting health among rural-living older adults. Technological supports are needed to improve telehealth ease of use and adherence. Cost-effectiveness of telehealth needs more study, particularly targeting 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 | 0.014 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".