Mind-body therapy for treating fibromyalgia: a systematic review
Bibliographic record
Abstract
OBJECTIVE: Fibromyalgia (FM) is a chronic and disabling condition that presents treatment challenges for both patients and healthcare providers. The objective of this review was to systematically assess the effectiveness and safety of mind-body therapies for FM. METHODS: We searched MEDLINE, EMBASE, PsycINFO, AMED, and CINAHL databases from their inception to December 2023. Eligible articles included adults diagnosed with FM participating in a mind-body therapy intervention and were published from the beginning of 2012 onwards. We assessed the quality of the studies using the Joanna Briggs Institute Critical Appraisal Checklists. RESULTS: Twenty-seven studies (1969 participants) were included, comprising 22 randomized controlled trials and 5 quasi-experimental studies. Mind-body therapies included guided imagery (n = 5), mindfulness-based stress reduction (n = 5), qi gong (n = 5), tai chi (n = 5), biofeedback (n = 3), yoga (n = 2), mindfulness awareness training (n = 1), and progressive muscle relaxation (n = 1). With the exception of mindfulness-based stress reduction, all therapies had at least 1 study showing significant improvements in pain at the end of treatment. Three or more studies on qi gong and tai chi demonstrated significant improvements in fatigue and multidimensional function, with tai chi showing the most evidence for improvement in anxiety and depression. Approximately one-third of the studies reported on adverse events. CONCLUSIONS: This systematic review found that mind-body therapies are potentially beneficial for adults with FM. Further research is necessary to determine if the positive effects observed post-intervention are sustained. STUDY REGISTRATION: Open Science Framework (https://osf.io) (September 12, 2023; https://doi.org/10.17605/osf.io/6w7ac).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".