Development of an Implementation Strategy for Patient Decision Aids in Rheumatoid Arthritis Through Application of the Behavior Change Wheel
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Decision aids are being developed to support guideline-based rheumatology care in Canada. The study objective was to identify barriers to decision aid use in rheumatoid arthritis (RA) within a behavior change model to inform an implementation strategy. METHODS: Perspectives from Canadian health care providers (HCPs) and patients living with RA were obtained on an early RA decision aid and on perceived facilitators and barriers to decision aid implementation. Data were collected through semistructured interviews, transcribed, and then analyzed by inductive thematic analysis. The lessons learned were then mapped to the behavior change wheel COM-B system (C = capability, O = opportunity, and M = motivation interact to influence B = behavior) to inform key elements of a national implementation strategy. RESULTS: Fifteen HCPs and fifteen patients participated. The analysis resulted in five lessons learned: 1) paternalistic decision-making is a dominant practice in early RA, 2) patients need emotional support and access to educational tools to facilitate participation in shared decision-making (SDM), 3) there are many logistical barriers to decision aid implementation in current care models, 4) flexibility is necessary for successful implementation, and 5) HCPs have limited interest in further training opportunities about decision aids. Implementation recommendations included the following: 1) making the decision aids directly available to patients (O) and providing SDM education (C/M), 2) creating an SDM rheumatology curriculum (C/O/M), 3) using "decision coaches" or patient partners as peer support (C/O/M), 4) linking decision aids to "living" rheumatology guidelines (M), and 5) designing trials of patient decision aid/SDM interventions to evaluate patient-important outcomes (O/M). CONCLUSION: A multifaceted strategy is suggested to improve uptake of decision aids.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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