Development and Pilot Testing of Decision Aid for Shared Decision Making in Barrett’s Esophagus With Low-Grade Dysplasia
Bibliographic record
Abstract
GOALS: To develop an encounter decision aid [Barrett's esophagus Choice (BE-Choice)] for patients and clinicians to engage in shared decision making (SDM) for management of BE with low-grade dysplasia (BE-LGD) and assess its impact on patient-important outcomes. BACKGROUND: Currently, there are 2 strategies for management of BE-LGD-endoscopic surveillance and ablation. SDM can help patients decide on their preferred management option. STUDY: Phase-I: Patients and clinicians were engaged in a user-centered design approach to develop BE-Choice. Phase-I included review of evidence on BE-LGD management, observation of usual care (UC), creation, field-testing, and iterative development of BE-Choice in clinical settings. Phase-II: Impact of BE-Choice on patient-important outcomes (patient knowledge, decisional conflict, and patient involvement in decision making) was assessed using a controlled before-after study design (UC vs. BE-Choice). RESULTS: Phase-I: Initial prototype was designed with observation of 8 clinical encounters. With field-testing, 3 successive iterations were made before finalizing BE-Choice. BE-Choice was paper based and fulfilled the qualifying criteria of International patient decision aid standards. Phase II: 29 patients were enrolled, 8 to UC and 21 to BE-Choice. Compared with UC, use of BE-Choice improved patient knowledge (90.4% vs. 70.5%; P=0.03), decisional comfort (89.6 vs. 71.9; P=0.01), and patient involvement (OPTION score: 27.1 vs. 19.2; P=0.01). CONCLUSIONS: BE-Choice is a feasible and effective decision aid to promote SDM in the management of BE-LGD. On pilot testing, BE-Choice had promising impact on patient-important outcomes. A larger multicenter trial is needed to confirm our results and promote widespread use of BE-Choice.
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How this classification was reachedexpand
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 | 0.002 | 0.010 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".