This study aimed to explore the application of a clinical reasoning training system based on digital patient simulation technology in undergraduate neurology education. We designed multidimensional interactive clinical cases integrating key knowledge points and constructed a clinical reasoning training system simulating the entire diagnostic and therapeutic process using virtual simulation technology. From March to May 2023, the model was implemented in neurology theory and clinical clerkship courses for 38 fourth-year clinical medicine students (enrolled in the 5+3 integrated program) at Capital Medical University. Through interactions with virtual patients, 34 students (89.5%) reported enhanced depth of understanding in neurology, 35 students (92.1%) acknowledged increased learning motivation, and 37 students (97.4%) supported broader implementation of this training system. Compared with the initial training, students′ post-course assessments demonstrated a 9.3% improvement in the rate of key information retrieval during history-taking and physical examination, along with a 9.6% increase in the accuracy of localization and etiological diagnosis The model received high approval from students and teachers, and demonstrated promising educational potential, offering novel insights for neurology pedagogical innovation.
Mei Shanshan
,
Han Yan
,
Lei Yuan
,
Zhang Bo
,
Zhao Nan
,
Fang Lirui
,
Hao Junwei
. Application of a clinical reasoning training system with digital patient simulation technology in undergraduate neurology teaching[J]. Chinese Journal of Medical Education, 2026
, 46(2)
: 107
-111
.
DOI: 10.3760/cma.j.cn115259-20240327-00320
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