Telemedicine in the primary care of older adults: a systematic mixed studies review
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Bibliographic record
Abstract
BACKGROUND: Family physicians had to deliver care remotely during the COVID-19 pandemic. Their efforts highlighted the importance of developing a primary care telemedicine (TM) model. TM has the potential to provide a high-quality option for primary care delivery. However, it poses unique challenges for older adults. Our aim was therefore to explore the effects of TM and the determinants of its use in primary care for older adults. METHODS: In this systematic mixed studies review, MEDLINE, PsycINFO, EMBASE, CINHAL, AgeLine, DARE, Cochrane Library, and clinical trials research registers were searched for articles in English, French or Russian. Two reviewers performed study selection, data extraction and assessment of study quality. TM's effects were reported through the tabulation of key variables. TM use determinants were interpreted using thematic analysis based on Chang's framework. All data were integrated using a joint display matrix. RESULTS: From 3,328 references identified, 20 studies were included. They used either phone (n = 8), videoconference (n = 9) or both (n = 3). Among studies reporting positive outcomes in TM experience, 'user habit or preferences' was the most cited barrier and 'location and travel time' was the most cited facilitator. Only one study reported negative outcomes in TM experience and reported 'comfort with patient communication' and 'user interface, intended use or usability' as barriers, and 'technology skills and knowledge' and 'location and travel time' as facilitators. Among studies reporting positive outcomes in service use and usability, no barrier or facilitator was cited more than once. Only one study reported a positive outcome in health-related and behavioural outcomes. CONCLUSIONS: TM in older adults' primary care generally led to positive experiences, high satisfaction and generated an interest towards alternative healthcare delivery model. Future research should explore its efficacy on clinical, health-related and healthcare services use.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it