AI-based virtual patient training for clinical communication skills in dental undergraduates: A randomized controlled mixed methods study

移情 客观结构化临床检查 随机对照试验 虚拟病人 干预(咨询) 医学教育 医学 沟通技能培训 沟通技巧 心理学 德雷福斯技能获得模型 定性研究 梅德林 临床实习 临床试验 物理疗法 模拟病人 护理部 教育测量 能力(人力资源) 社交技能 定性性质 虚拟现实 反思性练习 焦点小组 牙科实习 核心竞争力 基于问题的学习 应用心理学 主动学习(机器学习) 患者满意度 非语言交际
作者
Yuanmei Zhang,Haixia Zhou,Huali Huo,Yangli Yue,Yi-Xiang Wang,Juanfang Zhu
出处
期刊:Medical Teacher [Taylor & Francis]
卷期号:: 1-12 被引量:1
标识
DOI:10.1080/0142159x.2026.2681199
摘要

Introduction Effective clinical communication is a core competency in dental education, yet traditional teaching methods often fail to provide authentic, repeatable practice with immediate feedback. Artificial intelligence (AI)-based virtual patients offer a promising alternative, but evidence in dental education remains limited. This study evaluated the effectiveness of an AI virtual patient system for developing clinical communication skills in dental undergraduates.Methods A prospective, single-blind, randomized controlled trial was conducted with 60 fourth-year dental students randomly allocated to an intervention group (n = 30) using an AI virtual patient system for 8 weeks of self-directed inquiry training or a control group (n = 30) receiving traditional peer role-play training. Outcomes included Objective Structured Clinical Examination (OSCE) assessments of inquiry completeness and communication skills, Jefferson Scale of Empathy (JSE) scores, and self-reported learning motivation and clinical confidence. Assessments were conducted at baseline, immediately post-intervention, and at 3-month follow-up. Semi-structured interviews with 12 intervention participants provided qualitative insights into learning experiences.Results The intervention group demonstrated significantly higher OSCE inquiry completeness (86.4 ± 5.2 vs. 73.8 ± 6.1, p < 0.01), communication skills (89.1 ± 4.8 vs. 76.3 ± 5.9, p < 0.01), and self-reported empathic orientation (JSE scores: 112.4 ± 8.3 vs. 103.7 ± 9.2, p < 0.05) post-intervention, with effects sustained at 3 months. Learning motivation and clinical confidence were also significantly higher in the intervention group (p < 0.05). Qualitative analysis revealed that AI training fostered deliberate practice, reduced communication anxiety, and enhanced reflective learning through immediate feedback.Conclusion An AI-mediated training package, integrating structured practice with automated feedback, effectively enhances dental students’ clinical communication skills, self-reported empathic orientation, and learning motivation, with effects sustained at 3 months. This approach, which integrates established learning theories into a scalable digital format, may help address longstanding challenges in communication training and offers particular value for competency-based curricula and resource-constrained settings.Practice pointsAI-based virtual patient training significantly improves dental students’ clinical communication skills compared to traditional peer role-play.The immediate, objective feedback from AI systems fosters deliberate practice and reflective learning.AI training enhances student self-reported empathic orientation and learning motivation, with educational gains sustained at 3-month follow-up.This scalable approach offers a practical solution for communication training, particularly in resource-constrained settings.
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