Cannabis use preferences in women with myofascial pelvic pain: A cross-sectional study
Bibliographic record
Abstract
Objective: Myofascial tenderness is present in most chronic pelvic pain conditions and causes significant distress to patients. Treatment is challenging and often not curative. Cannabis is often used for self-management of chronic pelvic pain. However, we do not know which concentrations and routes of administration are most acceptable to users. We aimed to investigate patterns and willingness of cannabis product use among both habitual users and non-users with myofascial pelvic pain (MPP), to inform therapeutic development. Study design: We conducted a cross-sectional study of questionnaire responses from female patients with MPP from two tertiary pelvic pain centers. We aimed for a convenience sample of 100 responses with representation from both centers. Inclusion criteria were age over 18 with pelvic floor muscle tenderness on standard gynecologic examination. We collected information on demographics, pelvic pain history, cannabis use status, cannabis use preferences, validated opioid misuse risk assessment, and interest in using gynecologic cannabis products and used descriptive analyses. Results: 77/135 (57 %) questionnaire respondents were cannabis users and 58 (43 %) were non-users. Most users consume cannabis daily, (48.1 %) orally (66.2 %) or by smoking (60.7 %), and rated cannabis as effective at relieving pelvic pain. 37/58 (63.8 %) non-cannabis users responded that they would be willing to use cannabis for pelvic pain. Lack of information and potential adverse effects were the most common reasons for unwillingness to use. Approximately 3 of 4 respondents were willing to try vaginal or vulvar application of cannabis products for pelvic pain. Conclusions: This cross-sectional study describes cannabis use patterns in MPP patients. Topical vulvar and vaginal cannabis products are of strong interest to both cannabis users and non-users and warrant further research.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".