Effect of Home-based Telerehabilitation on Balance, Functional Mobility, and Quality of Life in Persons with Parkinson’s Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Persons with Parkinson's disease (PwPD) require ongoing rehabilitation to maintain independence, but traditional center-based and unsupervised home programs have limitations in accessibility and adherence. Home-based telerehabilitation (TR) offers a promising alternative by enabling remote delivery of exercise interventions. Objective: To evaluate the effect of home-based TR on balance, functional mobility, and quality of life in PwPD. Methods: A comprehensive electronic search was conducted across PubMed, CINAHL, Embase, OvidSP, ProQuest, Scopus, Web of Science, Cochrane CENTRAL, and PEDro databases. Interventional studies on exercise-centric home-based TR for PwPD with either balance, functional mobility, or quality of life as outcomes were included. Results: A total of 37 studies were included in this systematic review, of which 13 were eligible for meta-analysis. The meta-analysis revealed small but significant improvements in balance (SMD = 0.25; 95% CI: 0.04 to 0.45; p = 0.02). and functional mobility (SMD = -0.28; 95% CI: -0.52 to -0.05; p = 0.02). However, no significant effect was observed for quality of life (SMD = -0.08; 95% CI: -0.25 to 0.09; p = 0.35). Conclusion: Home-based TR is effective for improving balance and functional mobility in PwPD, although, its effect on quality of life is unclear which warrants further research.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.032 |
| 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".