Investigating the role of substance use in coping with genito-pelvic pain/penetration disorder
Bibliographic record
Abstract
Genito-pelvic pain/penetration disorder (GPPPD) is a common health issue among women and individuals, characterized by pain upon vaginal penetration. Despite its prevalence, GPPPD remains a significantly underdiagnosed and undertreated disorder. As a result, many individuals with this condition struggle to obtain proper medical care and may turn to substances to cope with their pain and distress. However, research on self-medication in the context of GPPPD is currently sparse—a critical oversight, given the long-term health risks associated with heightened substance use. This study aimed to investigate whether individuals with GPPPD use alcohol and cannabis to cope with the symptoms of this condition. The study employed a cross-sectional design, using data collected from an online survey. The survey yielded 166 responses. Path analysis was conducted to examine the associations between GPPPD pain severity, sexual distress, and the use of alcohol and cannabis to cope with emotional and physical pain. Analysis revealed that GPPPD pain severity was significantly associated with higher levels of sexual distress, and this in turn was associated with a significantly greater likelihood of using alcohol and cannabis to cope with emotional pain (i.e., embarrassment, stress, relationship strain, hopelessness). The results demonstrate the critical need for improved recognition and treatment of GPPPD, with particular focus on addressing the psychological impacts of the condition. In a broader context, this study aims to draw attention to the urgent need for increased education addressing sexual health stigmas and the dismissal of women’s and individuals’ vulvar pain within the healthcare landscape.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".