Chronic prostatitis/chronic pelvic pain syndrome-related pain symptoms and their impact on sexual functioning
Bibliographic record
Abstract
INTRODUCTION: The present study sought to examine a new model to evaluate the mechanistic pathways between pain and sexual dysfunction in men with chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS), incorporating cognitive and emotional factors. METHODS: =44.22, standard deviation 11.25) were recruited through social media, support groups, and urology clinics and completed an online questionnaire of demographic, pain, cognitive, psychological, and sexual variables. Descriptive statistics, correlation analysis, and serial mediation analyses assessed variable associations. RESULTS: Almost half of participants reported mild to severe erectile dysfunction (47.4%). Sexual dysfunction was associated with greater pain symptom severity and pain catastrophizing, as well as depressive symptoms (p<0.01 for all). While pain did not independently predict levels of sexual dysfunction, the addition of pain catastrophizing and depressive symptoms into the pathway explained the association between increased pain symptoms and decreased sexual functioning (p<0.01). CONCLUSIONS: Beyond generally poor sexual functioning in the current sample, it appears as if cognitive and emotional factors play a role in the association between pain symptoms and sexual functioning in these men with CP/CPPS. The findings of how pain catastrophizing and depression impact the association of pain severity and decreased sexual functioning is important for improving patient care.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".