Veille Scientifique étudiante concernant la cognition partagée (SharedCognition) et la polarisation politique
Alimenté par : Claudia Dapino Ponel, Madeline Desmurs
Cette application est une plateforme collaborative de veille scientifique permettant d'importer des publications depuis PubMed, de suivre leur lecture, d'en extraire les éléments méthodologiques clés (protocole, variables, résultats), et de constituer une synthÚse structurée pour faciliter la réalisation de revues de littérature.
DerniĂšre synchronisation : 13/09/2026
Obes Surg . 2026;36 (7) :3497-3510
BACKGROUND: Effective 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.OBJECTIVE: To 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.METHODS: Forty 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 ).RESULTS: The AI-Guided group scored significantly higher on SDM-Q-9 (84.7 vs. 71.3, pâ