School of Medicine Publications and Presentations
Document Type
Poster
Publication Date
2025
Abstract
Motivational Interviewing (MI) is an evidence-based system for talking to patients about behavioral change that has proven effective in multiple use cases such as promoting positive outcomes in patients with Substance Use Disorder and those managing chronic illness. Those who learn motivational interviewing through observed practice with correctional guidance from an expert practitioner demonstrate higher proficiency than those who learn via self-study, group seminars, or the classroom setting. Having one-on-one guidance for every interested learner may be possible through technological advancements, chiefly Artificial Intelligence. In this work, we present one possible path toward a digital platform that leverages this technology as well as insights in evidence-based learning strategies. The incorporation of the latter is facilitated through the creation of a Knowledge Graph, whose application to MI is presented in this work and is a novel contribution to research in this space. Furthermore, we demonstrate a proof-of-concept for using ChatGPT-40 to develop one MI skill—offering Simple Affirmations—illustrating an approach that can be generalized to other MI component skills.
Recommended Citation
Srinivasan, Sridhar B. and Martinez, Eric M., "Initial Design and Development of a Novel Framework for Motivational Interviewing Training Through Knowledge Graphs, AI, and Evidence-Based Learning" (2025). School of Medicine Publications and Presentations. 1916.
https://scholarworks.utrgv.edu/som_pub/1916
Academic Level
medical student
