106 Online Pelvic Floor Physical Therapy Group Program for Women with Persistent Genital Arousal Disorder: A Descriptive Feasibility Study
Bibliographic record
Abstract
Persistent genital arousal disorder (PGAD) is a highly distressing, and poorly understood condition characterized by physiological genital arousal (i.e., genital sensitivity and/or vascongestion) in the absence of subjective sexual desire. Currently there are no empirically-informed treatment options available to this population, despite the significant negative impact of the condition (Jackowich, Pink, Gordon, Poirier & Pukall, 2018). Few healthcare providers are knowledgeable about PGAD, making it challenging for individuals with PGAD to receive information and care. To determine the feasibility of an adapted physical therapy group educational program for vulvar pain conditions, to the specific needs of women with PGAD, in an online group format. Ethical approval was provided by [MASKED] University. A descriptive approach was undertaken to evaluate the feasibility of this group. A total of 12 women participated in the study (average age = 43.4 years, SD = 18.3, Range = 18-71). Phone screenings were conducted to confirm that individuals experienced PGAD (defined by its clinical presentation: Leiblum & Nathan, 2001). Women completed questionnaires prior to, immediately following, and 6-months following the group sessions. Participants also completed an anonymous feedback form. The group sessions were run by a registered physical therapist specializing in pain and pelvic floor health.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".