Evaluating real-time voice AI–based virtual patients for authentic communication training
收藏NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Evaluating_real-time_voice_AI_based_virtual_patients_for_authentic_communication_training/31812912
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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.
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.
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.
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.
创建时间:
2026-03-19



