Simulating the Clinical Encounter: Using AI Personas for Risk-Free Mental Health Assessment Practice

Abstract

Mental health assessment requires students to navigate complex conversations involving depression, anxiety, mania, psychosis, suicide risk, and other sensitive clinical situations. Yet opportunities to repeatedly practice these conversations in a safe, low-stakes environment can be limited. This session demonstrates an innovative approach to using generative artificial intelligence as an interactive patient simulation tool in nursing education. Rather than using AI simply to generate written assignments or answer questions, students interact with AI-generated patient personas designed to exhibit specific psychiatric symptoms and communication patterns. Through spoken or conversational interactions, students practice conducting mental health assessments, asking therapeutic follow-up questions, recognizing clinical cues, and adapting their communication as an encounter unfolds. During this interactive session, participants will see a live demonstration of an AI-simulated mental health encounter and experience how thoughtfully constructed prompts can transform generative AI into a repeatable practice environment. Practical examples will illustrate how faculty can design patient personas representing conditions such as depression, mania, anxiety, and psychosis while incorporating appropriate educational guardrails. The session will also address the role of faculty oversight, limitations of AI-generated responses, and the importance of positioning AI simulation as preparation for, rather than a replacement for, authentic human clinical experiences. Participants will leave with a practical framework for creating AI patient personas and ideas for incorporating low-risk, repeatable conversational practice into their own nursing courses.