Cinematic Clinical Narratives: Utilizing A Multimodal AI Approach in Medical Education (Preprint)

Abstract

<sec> <title>BACKGROUND</title> Medical students often struggle to engage with and retain complex pharmacology topics during their preclinical education. Traditional teaching methods can lead to passive learning and poor long-term retention of critical concepts. </sec> <sec> <title>OBJECTIVE</title> To enhance the teaching of clinical pharmacology in medical school by employing a multimodal generative artificial intelligence (AI) approach to create compelling cinematic clinical narratives (CCNs). </sec> <sec> <title>METHODS</title> We transformed a standard clinical case into an engaging, interactive multimedia experience called "Shattered Slippers." This CCN utilized various AI tools for content creation: GPT-4 for developing the storyline, Leonardo.ai and Stable Diffusion for generating images, Eleven Labs for creating audio narrations, and Suno for composing a theme song. The CCN integrated narrative styles and pop culture references to enhance student engagement. It was applied in teaching first-year medical students about immune system pharmacology. Student responses were assessed through the Situational Interest Survey for Multimedia (SIS-M) and examination performance. The target audience comprised 40 first-year medical students, with 18 responding to the SIS-M survey (n=18). </sec> <sec> <title>RESULTS</title> The study revealed a marked preference for the AI-enhanced CCNs over traditional teaching methods. Key findings include a high percentage of surveyed students preferring the CCN over traditional clinical cases, as well as high average scores for triggered situational interest, maintained interest, maintained-feeling interest, and maintained-value interest. Students achieved an average score of 88% on exam questions related to the CCN material, indicating successful learning and retention. Qualitative feedback highlighted increased engagement, improved recall, and appreciation for the narrative style and pop culture references. </sec> <sec> <title>CONCLUSIONS</title> This study demonstrates the potential of utilizing a multimodal AI-driven approach to create CCNs in medical education. The "Shattered Slippers" case effectively enhanced student engagement and promoted knowledge retention in complex pharmacological topics. This innovative method suggests a novel direction for curriculum development that could improve learning outcomes and student satisfaction in medical education. Future research should explore the long-term retention of knowledge and the applicability of learned material in clinical settings, as well as the potential for broader implementation of this approach across various medical education contexts. </sec>

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