Applications of yoga in Parkinson's disease: a systematic literature review
Bibliographic record
Abstract
Background: Yoga may be applicable to persons with Parkinson's disease (PD). The adaptability of yoga to suit varying abilities is of significance to the PD population with its progressive mobility problems. The additional psychosocial benefits of yoga are important to the quality of life. This systematic review presents scientific evidence pertaining to the impact of yoga on physical function and psychological well-being in PD. Methods: A literature search was conducted for randomized controlled trials (n=1), pretest–post-test design (n=3), and case studies (n=3) with the terms “yoga” and “Parkinson disease”. The study quality was assessed with a modified version of the Downs and Black Checklist and ranged from 8 to 16. The study outcomes included functional mobility (n=6), flexibility (n=4), balance (n=4), strength (n=4), depression (n=2), sleep (n=1), and quality of life (n=1). Results: The preliminary data suggested that yoga resulted in modest improvements in functional mobility, balance, and lower-limb strength in persons with PD. This has implications for gait, postural stability, balance confidence, and functional declines related to inactivity. An improved upper- and lower-body flexibility following yoga in persons with PD is applicable to rigidity, shuffling gait, and flexed posture. The presented evidence also showed positive outcomes for mood and sleep, demonstrating yoga's benefit for self-efficacy and social support. Conclusion: This review suggests that yoga provided an alternative method for addressing some of the reversible factors that impact motor function in PD, as well as contributing to an improved psychosocial well-being. However, limitations to the design of the studies necessitate further research to validate yoga as a therapy for PD. Keywords: alternative therapy, adaptable, mobility, mood, quality of life, neurological disorders
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".