Design, Implementation, and Evaluation of a Community-Based Phygital Telemonitoring Program for Older Adults: Multisite Retrospective Pilot Study in Singapore
Bibliographic record
Abstract
Background: Noncommunicable diseases, particularly hypertension, diabetes, hyperlipidemia, and obesity, are on the rise among older adults in Singapore, emphasizing the need for effective screening, monitoring, and educational interventions. The traditional health care model, relying on in-person visits to review patients, poses risks of underreported cases and missed opportunities for early interventions to manage complications. Community-based telemonitoring programs present promising opportunities to extend telehealth services to underserved populations, thereby mitigating the digital divide and addressing health inequalities. Objective: This study aimed to retrospectively evaluate the implementation of a community-based telemonitoring program, the Community Telehealth Service (CTS), developed to reduce digital barriers and raise awareness for regular health screening among older adults in the Singapore community. It also aimed to generate insights for scaling up similar telehealth initiatives in the community. Methods: This retrospective study used the (1) Implementation Research Logic Model, (2) Reach, Effectiveness, Adoption, Implementation, and Maintenance framework, and the Implementation Outcomes Framework to guide the design and evaluation of CTS' implementation strategies. Outcomes covered implementation outcomes (reach, adoption, feasibility, and cost), service outcomes (safety and preliminary effectiveness), and user outcomes (satisfaction). Data were collected from operational statistics and structured user feedback surveys across 3 phases of implementation at different community sites. Results: Over the course of the 3 phases, CTS has reached more than 800 older individuals and 147 health ambassadors, with the participation of community organizations, health care institutions, academic collaborators, corporate sponsors, and government agencies. Operational statistics indicated that CTS was delivered consistently across 3 sites, with improving show-up rates and stable service hours. User feedback was generally positive, citing convenience, perceived value, and appreciation for health ambassador support. However, challenges were noted in referral tracking due to differing workflows across partners and in collecting user feedback, particularly in later phases where the survey was perceived as lengthy and complex for older users. Several areas for improvement were identified, such as incorporating more health assessments, providing more health-related information, and improving the referral process. Conclusions: This early-stage retrospective study suggests that community-based telehealth programs may be a feasible and acceptable approach to delivering preventive services in community settings. While initial findings are promising, further rigorous research is needed to evaluate long-term outcomes, integration with health systems, and potential for scale-up.
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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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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 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".