Trial reportObesity surgery2026
The VALUE of AI-Guided Communication: Enhancing Shared Decision-Making in Metabolic Bariatric Surgery Consultations Through a Metacognitive Framework.
Trial report in Obesity surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
Funding
Abstract
backgroundEffective communication in metabolic bariatric surgery (MBS) is essential for patient engagement and adherence, yet surgical residents often lack structured training. Artificial intelligence offers a novel approach to scaffold communication skills.
objectiveTo evaluate the impact of an AI-Guided metacognitive framework VALUE (Validate, Align & Reframe, Link & Educate, Unite in a plan) on shared decision-making (SDM) and communication outcomes in MBS consultations compared to self-directed learning.
methodsForty surgical residents were randomized into two groups: AI-Guided (using the VALUE framework) and self-learning. The AI-Guided group used a structured prompt to interact with a large language model (DeepSeek-V3.2) to generate personalized consultation plans. Each conducted simulated consultations with standardized patients from a case library. Outcomes were measured using the Shared Decision-Making Questionnaire-9 (SDM-Q-9), Decision Conflict Scale (DCS), Four Habits Coding Scheme (4HCS), Surgeon Self-Efficacy scale (SSI-BS), Communication Outline Quality Scale (CQS), and AI Interaction Quality (AIIQ). The trial was registered on the Open Science Framework (Registration DOI: https://doi.org/10.17605/OSF.IO/BAQH6 ).
resultsThe AI-Guided group scored significantly higher on SDM-Q-9 (84.7 vs. 71.3, p < 0.01) and 4HCS (17.5 vs. 14.8, p < 0.01), and lower on DCS (19.5 vs. 32.1, p < 0.01). Communication outlines were also of higher quality (13.8 vs. 7.5, p < 0.01). Residents reported greater self-efficacy gains in information provision, values integration, decision facilitation, and emotional support. All secondary analyses remained significant after Benjamini-Hochberg correction for multiple comparisons.
conclusionAn AI-Guided metacognitive communication framework significantly improves shared decision-making, reduces decisional conflict, and enhances communication quality and self-efficacy in MBS consultations, suggesting a promising approach that requires further validation in larger, multi-site trials.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.