Evaluating real-time voice AI–based virtual patients for authentic communication training.

Introduction: Effective communication is essential in clinical training, yet opportunities for realistic and interactionally authentic practice remain limited. Standardized patients (SPs) provide realism but are resource-intensive, whereas virtual patients (VPs) offer scalability but have limited capacity to reproduce responsive, interactionally authentic dialogue. Recent advances in generative artificial intelligence (AI), particularly real-time voice models, have opened new possibilities for natural and synchronous dialogue in virtual simulations. To evaluate whether a real-time voice–based virtual patient (RT-VP) can achieve communication performance, perceived realism, and self-efficacy outcomes comparable to SP training, thereby addressing the global challenge of scalable, authentic communication training. Methods: The RT-VP was developed on the Doubao real-time voice generative AI platform, which supports synchronous, bidirectional spoken interaction. In a randomized controlled study, 134 residents were assigned to RT-VP, standardized-patient (SP), or peer role-play (PR) groups. All groups received identical SPIKES-based instruction and practiced in their assigned simulation modality. Outcomes included communication performance, self-efficacy, and perceived realism. Results: Post-training SPIKES scores were highest for SP (26.6 ± 3.0), followed by RT-VP (24.9 ± 2.9) and PR (20.4 ± 4.3) (p <.001). Both SP and RT-VP outperformed PR (p <.001), and the difference between SP and RT-VP did not reach statistical significance (p =.06). Perceived realism generally followed an SP > RT-VP > PR pattern, with RT-VP demonstrating comparable linguistic realism to SP, while SP remained superior in contextual, emotional, and engagement realism. Discussion: This study represents, to our knowledge, the first controlled comparison of real-time voice generative AI–based VPs and SP encounters in communication training. RT-VP simulation approximated SP-level communication performance and perceived authenticity while offering scalability and consistency. Real-time voice simulation offers a scalable means to expand access to emotionally authentic communication training worldwide.