YOGA IN SEDENTARY ADULTS ARTHRITIS: EFFECTS OF A RANDOMIZED CONTROLLED PRAGMATIC TRIAL
Bibliographic record
Abstract
Objective—To evaluate the impact of Integral-based hatha yoga in sedentary people with arthritis.Methods—75 sedentary adults aged 18+ with rheumatoid arthritis (RA) or knee osteoarthritis (OA) were randomly assigned to 8 weeks of yoga (2 60 min classes and 1 home practice/wk) or waitlist. Poses were modified for individual needs. The primary endpoint was physical health (SF36 Physical Component Summary [PCS]) adjusted for baseline; exploratory adjusted outcomes included fitness, mood, stress, self-efficacy, SF36 health-related quality of life (HRQL) and RA disease activity. In everyone completing yoga, we explored long-term effects at 9 months.Results—Participants were mostly female (96%), white (55%), and college-educated (51%), with a mean (SD) age of 52 (12). Average disease duration was 9 (9) yrs. and 49% had RA. At 8 weeks, yoga was associated with significantly higher PCS (6.5; 95% CI: 2.0,10.7), walking capacity (125 m; 95% CI:15,235), positive affect (5.2; 95% CI:1.4,8.9) and lower CES-D (−3.0; 95% CI: −4.8,−1.3). Significant (p<.05) improvements were evident in SF36 Role Physical, Pain, General Health, Vitality and Mental Health scales. Balance, grip strength, and flexibility were similar between groups. 22/28 on waitlist completed yoga. Among all yoga participants, significant (p<.05) improvements were observed in mean PCS, flexibility, 6-min walk, all psychological and most HRQL domains at 8 weeks with most still evident 9 months later. Of seven adverse events, none were associated with yoga.Conclusions—Preliminary evidence suggests yoga classes may help sedentary individuals with arthritis safely increase physical activity and improve physical and psychological health, and HRQL.Key Indexing
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".