Lower pain thresholds in women with chronic pelvic pain: recognizing the role of anxiety and depression as part of person-centered approaches to treatment
Bibliographic record
Abstract
Aims and objectives: The interdisciplinary approach for managing chronic pelvic pain is based on the foundation that pain perception is not only linked to peripheral nociceptive stimuli, but also strongly influenced by a combination of modulating factors. We performed a cross-sectional study to compare pain thresholds in women with chronic pelvic pain versus healthy controls, analyzing the influence of anxiety and depression in the thresholds. Methods: A total of 43 women with chronic pelvic pain and 20 healthy female volunteers were evaluated using transcutaneous electrical nerve stimulation. The intensity of clinical pain was measured by the visual analogue scale and the McGill pain questionnaire and the presence of anxiety and depression was verified by the Hospital Anxiety and Depression Scale. Results: The median for the pain thresholds in the study and control groups was 11,66 and 13,3 (p = 0.0009). There was a significant correlation between the visual analogue scale and pain response (r = -0.42, p = 0.005). There was also a significant correlation between pain threshold and anxiety (r = -0.49, p = 0.001) and between depression and pain threshold (r = - 0,46 p = 0.001). Conclusion: Our findings suggest that women with chronic pelvic pain have lower experimental pain thresholds, and this may be influenced by anxiety and depression. We therefore contend that assessments of anxiety and depression should form part of the person-centered approach to the management of chronic pelvic pain.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".