Addressing Weight Bias in Clinical Practice: An Educational Proposal Based on Clinical Scenarios and Artificial Intelligence

Abstract

This article presents the development of an educational tool based on artificial intelligence and clinical simulation to address weight bias in medical practice. The platform allows health professionals to interact with simulated clinical scenarios in which their decision making is evaluated in front of overweight or obese patients. Through clinical vignettes and questionnaires, the tool seeks to promote self-awareness and critical reflection in users, with the aim of reducing implicit biases and improving the quality of care. Preliminary results indicate that a significant portion of professionals still associate patient weight with unrelated health problems, highlighting the need for educational interventions in this area. In addition, the platform generates valuable data for future research on the effectiveness of simulation-based educational approaches to reduce bias in clinical care. This proposal offers a replicable model for continuing health education, enhancing a more inclusive and equitable medical practice.