“How to Say It”: Women's Descriptions of Pelvic Pain
Bibliographic record
Abstract
The present research aimed to compare women's descriptions of chronic pelvic pain, when talking about their pain in narrative mode, with the descriptors used in a common pain assessment tool, the McGill Pain Questionnaire (MPQ). Our intention was to see what we could learn about the relationship between words used in these kinds of assessment tools and meanings of pain experience evident in narratives. This New Zealand-based qualitative study used open-ended interviewing to generate women's experiential narratives of pelvic pain. Forty women of European descent were recruited via a randomly selected national prevalence survey on chronic pelvic pain: 33 had chronic pelvic pain that was not associated with dysmenorrhoea or dyspareunia (CPP); 38 had dysmenorrhoea; 29 had dyspareunia; 24 had all three. The study group was aged between 22 and 51 years. The differences that emerged between the words used by women and those used in the MPQ vocabulary are described. Two main findings emerged: a difference in the relative emphasis placed on sensory descriptors and the absence in women's narratives of affective words used in the MPQ. However, a predominance of an affective dimension of pain was evident in women's narratives, which is described. Given the narrative specificity of the experience of pelvic pain, we conclude that assessment tools using the words and phrases evident in narratives of pain would potentially be more useful, and that such a pain assessment tool would ideally be used in association with narrative techniques incorporated into the clinician's interview with women who present with chronic pelvic pain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".