Patient–Physician Alignment in Satisfaction With Psoriatic Arthritis Treatment: Analysis From a Cross-Sectional Survey in the United States and Europe
Bibliographic record
Abstract
Background: There is evidence that patients and physicians are frequently misaligned in their perspectives on psoriatic arthritis (PsA) treatment priorities, which may be associated with increased disease activity, greater disability, and poorer health-related quality of life of PsA patients. Objective: To identify factors associated with patient–physician misalignment in satisfaction with PsA disease control. Methods: In a cross-sectional survey of physicians and their patients with PsA from the United States and Europe, satisfaction with disease control was examined and classified as satisfied, neutral, or dissatisfied. Bivariate and multivariate regression analyses explored alignment in satisfaction between physicians and patients. Results: There were 656 PsA patient–physician pairs included in the analysis. Misalignment occurred in 20.6% of cases. Greater disease impact, worse physician-reported disease severity, and lower patient-reported involvement in treatment decisions were associated with misalignment. Conclusion: Greater patient–physician engagement may improve satisfaction, alignment, and outcomes in PsA disease control.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".