Effectiveness of physiotherapist-led tele-rehabilitation for older adults with chronic conditions: a systematic review and meta-analysis
Bibliographic record
Abstract
:Background Older adults live with chronic conditions worldwide. The aim of this systematic review was to determine the effectiveness of physiotherapist-led (PT-led) tele-rehabilitation on various health outcomes.Methods Six databases were searched. Eligible studies were randomized controlled trials that included older adults (≥65 years) who had ≥1 chronic condition, and evaluated tele-rehabilitation (e.g., video, telephone) that was PT-led or overseen. Screening and data extraction were performed in duplicate. Meta-analyses were performed where appropriate. Cochrane’s Risk of Bias 2.0 tool was used.Results Fifteen studies were included. A meta-analysis of studies of knee osteoarthritis demonstrated that tele-rehabilitation is more effective than usual care for functional mobility (MD= −2.72, 95% CI= −3.56, −1.88, p < 0.001), quadriceps strength (MD= 15.54, 95% CI= 10.14, 20.95, p < 0.001), pain (MD= −1.2, 95% CI= −2.09, −0.39, p = 0.004) and physical function (MD= −5.95, 95% CI= −8.32, −3.58, p < 0.001). No clear differences were found between tele-rehabilitation and usual care or comparator interventions for outcomes related to physical activity level, gait speed, mental health, and quality of life.Conclusions PT-led tele-rehabilitation appears to be comparable to traditional methods at improving outcomes in older adults with various chronic conditions. However, high-quality trials are needed so future conclusions on the effectiveness of tele-rehabilitation can be made.PROSPERO Registration ID CRD42023428048
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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 | 0.012 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".