An Integrative Approach for Endometriosis-Related Pain
Bibliographic record
Abstract
Background: Pain is a common, severe symptom related to endometriosis. Despite this prominent feature, there is limited literature regarding its description and use of integrative treatment methods. Objective: We aimed to describe endometriosis-related pain characteristics, severity, and association with an integrative approach encompassing pharmacological and non-pharmacological methods. Methods: A cross-sectional descriptive correlational study was conducted using convenience sampling of adult women with endometriosis-related pain. Three questionnaires were utilized: a demographic and general health questionnaire, a visual analog pain scale (VAS), and the short-form McGill pain questionnaire (SF-MPQ). Results: Participants included 93 women with a mean general pain level of 6.2/10 (SD = 2.7) on the VAS. The total mean pain score on the SF-MPQ was 26.25/45 (SD = 10.1). Sixty-four women (68.8%) reported experiencing pain at the time of completion of the questionnaire (mean: 1.6/4, SD = 1.3). All participants utilized analgesia; those who used opioids reported a higher overall mean pain score of 2.3 (SD = 1.3) than patients who did not use opioids reported a mean of 1.4 (SD = 1.2; z = 9.59; P < .001). Present pain intensity was significantly higher for women using opioids than those not using opioids. In all, 77 women (82.8%) used integrative methods to alleviate the pain symptoms. Women who utilized nutritional therapy as part of the non-pharmacological method experienced lower mean (SD) overall pain (4.4 [2.5]) compared with patients who did not utilize nutritional therapy (6.75 [2.5]; P < .01). Conclusions: More studies are needed to find evidence-based treatment options for women for integrative pain relief for endometriosis-related 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".