<p>Using a Discrete-Choice Experiment in a Decision Aid to Nudge Patients Towards Value-Concordant Treatment Choices in Rheumatoid Arthritis: A Proof-of-Concept Study</p>
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Bibliographic record
Abstract
PURPOSE: To evaluate, in a proof-of-concept study, a decision aid that incorporates hypothetical choices in the form of a discrete-choice experiment (DCE), to help patients with early rheumatoid arthritis (RA) understand their values and nudge them towards a value-centric decision between methotrexate and triple therapy (a combination of methotrexate, sulphasalazine and hydroxychloroquine). PATIENTS AND METHODS: In the decision aid, patients completed a series of 6 DCE choice tasks. Based on the patient's pattern of responses, we calculated his/her probability of choosing each treatment, using data from a prior DCE. Following pilot testing, we conducted a cross-sectional study to determine the agreement between the predicted and final stated preference, as a measure of value concordance. Secondary outcomes including time to completion and usability were also evaluated. RESULTS: Pilot testing was completed with 10 patients and adjustments were made. We then recruited 29 patients to complete the survey: median age 57, 55% female. The patients were all taking treatment and had well-controlled disease. The predicted treatment agreed with the final treatment chosen by the patient 21/29 times (72%), similar to the expected agreement from the mean of the predicted probabilities (68%). Triple therapy was the predicted treatment 24/29 times (83%) and chosen 20/29 (69%) times. Half of the patients (51%) agreed that completing the choice questions helped them to understand their preferences (38% neutral, 10% disagreed). The tool took an average of 15 minutes to complete, and median usability scores were 55 (system usability scale) indicating "OK" usability. CONCLUSION: Using a DCE as a value-clarification task within a decision aid is feasible, with promising potential to help nudge patients towards a value-centric decision. Usability testing suggests further modifications are needed prior to implementation, perhaps by having the DCE exercises as an "add-on" to a simpler decision aid.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it