Development and Feasibility of a Group-Based Therapeutic Yoga Program for Women with Chronic Pelvic Pain
Bibliographic record
Abstract
OBJECTIVE: To develop a group-based therapeutic yoga program for women with chronic pelvic pain (CPP) and explore the effects of this program on pain severity, sexual function, and well-being. METHODS: A yoga therapy program for CPP was developed by a multidisciplinary panel of clinicians, researchers, and yoga consultants. Women reporting moderate to severe pelvic pain for at least six months were recruited into a single-arm trial. Participants attended twice weekly group classes focusing on Iyengar-based yoga techniques and were instructed to practice yoga at home an hour a week for six weeks. Participants self-rated the severity of their pelvic pain using daily logs. The impact of participants' pain on everyday activities, emotional well-being, and sexual function was assessed using an Impact of Pelvic Pain (IPP) questionnaire. Sexual function was further assessed using the Sexual Health Outcomes in Women Questionnaire (SHOW-Q). RESULTS: Among the 16 participants (age range = 31-64 years), average ratings of the severity of pain "at its worst," "at its best," and "on average" decreased by 29%, 32%, and 34%, respectively, from start to six weeks (P < 0.05 for all). Women demonstrated improvements in scores on IPP subscales for daily activities (1.8 ± 0.7 to 0.9 ± 0.7, P < 0.001), emotional well-being (1.7 ± 0.9 to 0.9 ± 0.7, P = 0.005), and sexual function (1.9 ± 1.1 to 1.0 ± 0.9, P = 0.04). Scores on the SHOW-Q "pelvic problem interference" scale also improved over six weeks (53 ± 23 to 27 ± 23, P = 0.002). CONCLUSIONS: Findings provide preliminary evidence of the feasibility of teaching women with CPP to practice yoga to self-manage pain and improve quality of life and sexual function.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".