JMIR Publications

ABSTRACT

Medical education and healthcare systems are inherently people-centered, yet high-stress clinical environments can foster implicit biases and microaggressions that disproportionally affect underrepresented minorities. Microaffirmations are small, intentional acts of expanding opportunities, gestures of inclusion, and graceful acts of listening, that may help to reduce these behaviors and improve psychological safety. This tutorial introduces an approach grounded in Universal Design Learning (UDL) theory to provide tailored, contextualized-driven resources, and human-centered training to integrate microaffirmations into undergraduate and graduate medical education and the clinical setting using generative artificial intelligence (AI) as a time-saving and efficient method of delivery. These AI methods, using effective prompt writing, generate visual aids that can be leveraged by clinicians to improve patient communication. The approach’s efficacy can be measured through future patient and family surveys, participation rates, and the potential reduction of workplace violence. While AI offers innovative solutions for improving peer and clinician patient experiences in medicine, this approach acknowledges essential limitations.