Treatment-Seeking Behaviors of Persons With Rheumatoid Arthritis
Bibliographic record
Abstract
PURPOSE: Describe perceptions of patients with rheumatoid arthritis (RA) regarding disease-related pain, tendency to tell others about their pain, and treatments used since diagnosis. DESIGN: Cross sectional, exploratory. METHOD: A total of 63 participants responded to telephone interview about their treatments and tendency to tell others about their RA pain. They also responded to McGill Pain Questionnaire and Health Assessment Questionnaire (HAQ) items. Participants marked pain location on mailed body outlines. FINDINGS: RA diagnosis occurred an average of 11 years prior. Mean HAQ Standard Disability Index score was 1.26. Previous week symptoms were joint pain (97%), joint swelling (83%), decreased movement/function (83%), fatigue (70%), muscle weakness (65%). Mean morning stiffness duration was 120 ± 137 minutes. Mean pain intensity was 1.15 ± 0.6 at its least and 3.8 ± 1.1 at its worst. 65% were not satisfied with pain levels. 57% stated a tendency not to tell others about their pain; 43% tended to tell. 78% used medications and alternative therapies, none solely used alternative therapies, and 22% only used medications. CONCLUSIONS: RA patients reported high rates of alternative therapy use. Dissatisfaction with pain levels indicates need for improved pain management. Not talking about pain lends insights into the importance of teaching patients to communicate their pain to others.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".