Comparing face-to-face and internet-based basic body awareness therapy for fibromyalgia: a randomized controlled trial
Bibliographic record
Abstract
Purpose This study aimed to investigate and compare the effecs of face-to-face and internet-based Basic Body Awareness Therapy (BBAT), in patients with fibromyalgia (FM).Materials and methods FM-diagnosed patients were randomly allocated to one of three groups: face-to-face BBAT (F2F-BBAT), internet-based BBAT (I-BBAT), or a waiting list control group (CG). The F2F-BBAT group underwent individual 8-week BBAT sessions (2 sessions per week). The I-BBAT group received an equivalent dosage of BBAT via online video conferencing software. The primary outcome was the Fibromyalgia Impact Questionnaire Revised (FIQR). Secondary outcomes included the pressure pain threshold (PPT) via algometer, the PostureScreen Mobile® (PSM) application, the Short Form McGill Pain Questionnaire (SF-MPQ), the Short Form 36 Health Survey (SF-36), and plasma fibrinogen and haptoglobin levels.Results A total of 41 patients completed the study. Both the F2F-BBAT (n = 14) and I-BBAT (n = 13) groups showed significant improvements in all outcome measures (p < 0.05) with no significant difference between them (p > 0.05). Conversely, the CG (n = 14) demonstrated no substantial improvements in the outcome measures (p > 0.05). Compared to the CG, both the F2F-BBAT and I-BBAT groups exhibited superior results in FIQR, PPT, PSM, SF-MPQ, and multiple SF-36 sub-parameters (p < 0.05).Conclusion This study showed that BBAT delivered via internet-based telerehabilitation can have comparable effective results on clinical parameters with conventional face-to face BBAT in patients with FM.Trial registration ClinicalTrials.gov: NCT04981132.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".