Yoga in the Management of Chronic Disease
Bibliographic record
Abstract
BACKGROUND: Heart disease, stroke, and chronic obstructive pulmonary disease (COPD) are the leading causes of death and disability worldwide. Although individuals with these conditions have been reported to benefit from yoga, its effectiveness remains unclear. OBJECTIVE: To perform a systematic review of the effectiveness of yoga on exercise capacity, health related quality of life (HRQL), and psychological well-being for individuals with chronic disease and describe the structure and delivery of programs. RESEARCH DESIGN: We performed a systematic review of randomized controlled trials examining yoga programs for individuals with heart disease, stroke, and COPD compared with usual care. Quality was assessed using the Cochrane risk of bias tool. Meta-analyses were conducted using Review Manager 5.3. The protocol was registered on PROSPERO (CRD42014014589). RESULTS: Ten studies (431 individuals, mean age 56±8 y) were included and were comparable in their design and components, irrespective of the chronic disease. The standardized mean difference for the mean change in exercise capacity was 2.69 (95% confidence interval, 1.39-3.99) and for HRQL it was 1.24 (95% confidence interval, -0.37 to 2.85). Symptoms of anxiety were reduced after yoga in individuals with stroke, although this was not observed in individuals with COPD. The effect of yoga on symptoms of depression varied across studies with no significant effects compared with usual care. CONCLUSIONS: Yoga programs have similar designs and components across chronic disease populations. Compared with usual care, yoga resulted in significant improvements in exercise capacity and a mean improvement in HRQL. Yoga programs may be a useful adjunct to formal rehabilitation programs.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".