Qigong and Fibromyalgia: Randomized Controlled Trials and Beyond
Bibliographic record
Abstract
Introduction. Qigong is currently considered as meditative movement, mindful exercise, or complementary exercise and is being explored for relief of symptoms in fibromyalgia. Aim. This narrative review summarizes randomized controlled trials, as well as additional studies, of qigong published to the end of 2013 and discusses relevant methodological issues. Results. Controlled trials indicate regular qigong practice (daily, 6-8 weeks) produces improvements in core domains for fibromyalgia (pain, sleep, impact, and physical and mental function) that are maintained at 4-6 months compared to wait-list subjects or baselines. Comparisons with active controls show little difference, but compared to baseline there are significant and comparable effects in both groups. Open-label studies provide information that supports benefit but remain exploratory. An extension trial and case studies involving extended practice (daily, 6-12 months) indicate marked benefits but are limited by the number of participants. Benefit appears to be related to amount of practice. Conclusions. There is considerable potential for qigong to be a useful complementary practice for the management of fibromyalgia. However, there are unique methodological challenges, and exploration of its clinical potential will need to focus on pragmatic issues and consider a spectrum of trial designs. Mechanistic considerations need to consider both system-wide and more specific effects.
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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 | 0.015 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.005 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".