<p>Treatment Mode Preferences in Rheumatoid Arthritis: Moving Toward Shared Decision-Making</p>
Bibliographic record
Abstract
PURPOSE: Current knowledge of the reasons for patients' preference for rheumatoid arthritis (RA) treatment modes is limited. This study was designed to identify preferences for four treatment modes, and to obtain in-depth information on the reasons for these preferences. PATIENTS AND METHODS: In this multi-national, cross-sectional, qualitative study, in-depth interviews were conducted with adult patients with RA in the United States, France, Germany, Italy, Spain, Switzerland, the United Kingdom, and Brazil. Patients' strength of preference was evaluated using a 100-point allocation task (0-100; 100=strongest) across four treatment modes: oral, self-injection, clinic-injection, and infusion. Qualitative descriptive analysis methods were used to identify, characterize, and summarize patterns found in the interview data relating to reasons for these preferences. RESULTS: 100 patients were interviewed (female, 75.0%; mean age, 53.9 years; mean 11.6 years since diagnosis). Among the four treatment modes, oral administration was allocated the highest mean (standard deviation) preference points (47.3 [33.1]) and was ranked first choice by the greatest percentage of patients (57.0%), followed by self-injection (29.7 [27.7]; 29.0%), infusion (15.4 [24.6]; 16.0%), and clinic-injection (7.5 [14.1]; 2.0%). Overall, 56.0% of patients had a "strong" first-choice preference (ie, point allocation ≥70); most of these patients chose oral (62.5%) vs self-injection (23.2%), infusion (10.7%), or clinic-injection (3.6%). Speed and/or ease of administration were the most commonly reported reasons for patients choosing oral (52.6%) or self-injection (55.2%). The most common reasons for patients not choosing oral or self-injection were not wanting to take another pill (37.2%) and avoiding pain due to needles (46.5%), respectively. CONCLUSION: These data report factors important to patients regarding preferences for RA treatment modes. Patients may benefit from discussions with their healthcare professionals and/or patient support groups, regarding RA treatment modes, to facilitate shared decision-making.
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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 | 0.040 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".