The relationship of gender to pain, pain behavior, and disability in osteoarthritis patients: the role of catastrophizing
Bibliographic record
Abstract
One hundred and sixty-eight patients with osteoarthritis (OA) of the knees participated in this study. Of the participants, 72 were men and 96 were women. All participants completed the Arthritis Impact Measurement Scales (AIMS), underwent a 10 min standardized observation session to assess their pain behavior, and completed the Catastrophizing Scale of the Coping Strategies Questionnaire (CSQ) and the Depression Scale of the Symptom Checklist 90 Revised (SCL-90R). The study found that there were significant differences in pain, pain behavior, and physical disability in men and women having OA. Women had significantly higher levels of pain and physical disability, and exhibited more pain behavior during an observation session than men. Further analyses revealed that catastrophizing mediated the relationship between gender and pain-related outcomes. Once catastrophizing was entered into the analyses, the previously significant effects of gender were no longer found. Interestingly, catastrophizing still mediated the gender-pain relationship even after controlling for depression. These findings underscore the importance of both gender and catastrophizing in understanding the OA pain experience and may have important implications for pain assessment and treatment.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".