Using a Proactive Telecare System to Support Independence, Health, and Well-Being in Older Adults: Feasibility Randomized Controlled Trial
Bibliographic record
Abstract
Background: Proactive telecare offers services designed to reduce the occurrence of emergency situations by delivering proactive outbound calls and follow-ups and providing information and advice. By engaging regularly with users, proactive telecare may foster social connections with older adults and enable the detection of changes in needs. Telecare systems that promote active participation among older adults may also foster feelings of autonomy and self-management. Objective: This study aimed to (1) explore the acceptability and feasibility of delivering and evaluating a proactive telecare intervention to community-dwelling older adults prior to a potential effectiveness trial and (2) evaluate the proposed eligibility criteria and estimate the potential effect size of the impact of the intervention on health and well-being outcomes to inform sample size calculations for a future trial. Methods: An 8-week randomized pre-post feasibility study was conducted. Using a mixed methods approach, questionnaires and semistructured interviews were used to explore the feasibility and acceptability of the study. The proactive telecare system encouraged users to press an OK button once a day to confirm their well-being. If they did not respond, participants received a well-being check, and emergency contacts were notified if required. Outcomes associated with independence, health, and well-being were measured using standardized questionnaires, including health-related quality of life, mental health, and loneliness. Results: Thirty older adults were recruited, with 13 randomized into the intervention group and 17 into the control group. The mean (SD) age of the participants was 75.4 (5.2) years; 66.7% (20/30) of the participants recruited had more than one health condition. This study achieved high retention rates (30/33, 90.9%); however, the expression of interest rate was low (52/295, 17.6%), indicating that changes to recruitment strategies are required. Effect sizes for all quantitative outcomes were small (approximately 0.2). Participants demonstrated high acceptance of the intervention, with the primary benefit cited as providing reassurance and promoting autonomy. Proactive engagement encouraged self-regulation and allowed users to control the level of support received. Those who were socially isolated reported feeling less lonely because of having additional social contact. Most participants felt the intervention would be particularly beneficial if they were experiencing poor health that significantly affected their daily activities, suggesting it may be more suited to those with limited independence. Some participants expressed anxiety about using the technology, primarily due to a lack of understanding and uncertainty in their perceived need for the device. Conclusions: This proactive telecare system is feasible to deliver within a cohort of older adults living in the community. However, changes to recruitment approaches and implementation are needed to ensure acceptability and target numbers are achieved in a future effectiveness trial.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".