Nonacademic predictors of China medical licensing examination

Nonacademic predictors of China medical licensing examination

Abstract Background National Medical Licensing Examination (NMLE) is the entrance exam for medical practice in China, and its general medical knowledge test (GMKT) evaluates abilities of medical students to comprehensively apply medical knowledge to clinical practice. This study aimed to identify no...

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Main Authors: Jie Sun, Yingying Xie, Ningnannan Zhang, Jingliang Cheng, Meiyun Wang, Bing Zhang, Wenzhen Zhu, Hui Zhang, Shijun Qiu, Xiaojun Xu, Yongqiang Yu, Tong Han, Zuojun Geng, Weihua Liao, Bo Gao, Wen Qin, Feng Liu, Meng Liang, Qiang Xu, Jilian Fu, Jiayuan Xu, Mengge Liu, Peng Zhang, Wei Li, Dapeng Shi, Caihong Wang, Xi-Nian Zuo, Quan Zhang, Feng Chen, Jiance Li, Zhihan Yan, Wen Shen, Yanwei Miao, Junfang Xian, Longjiang Zhang, Kai Xu, Zhaoxiang Ye, Jing Zhang, Guangbin Cui, Chunshui Yu, for the CHIMGEN Consortium
Format: Article
Language:English
Published: BMC 2025-01-01
Series:BMC Medical Education
Subjects:
National medical licensing examination
General medical knowledge test
Medical students
Predictors
Online Access:https://doi.org/10.1186/s12909-025-06652-7
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Summary:Abstract Background National Medical Licensing Examination (NMLE) is the entrance exam for medical practice in China, and its general medical knowledge test (GMKT) evaluates abilities of medical students to comprehensively apply medical knowledge to clinical practice. This study aimed to identify nonacademic predictors of GMKT performance, which would benefit medical schools in designing appropriate strategies and techniques to facilitate the transition from medical students to qualified medical practitioners. Methods In 1202 medical students, we conducted the deletion-substitution-addition (DSA) and structural equation model (SEM) analyses to identify nonacademic predictors of GMKT performance from 98 candidate variables including early life events, physical conditions, psychological and personality assessments, cognitive abilities, and socioeconomic conditions. The candidate variables were assessed using psychometrically or cognitively validated and accepted instruments. Results We identified seven nonacademic predictors for GMKT performance. Body mass index (BMI) and working memory reaction time showed direct negative effects on GMKT performance. Psychological and personality features (conscientiousness, state anxiety, and openness to experience) indirectly affected GMKT performance via BMI, while socioeconomic conditions (father’s education and mother’s occupation) indirectly affected GMKT performance by influencing psychological and personality features and further BMI. Conclusion The identified nonacademic predictors for GMKT performance and their pathways may be useful for improving medical education by strengthening favorable and weakening, rectifying, or compensating unfavorable factors that are modifiable.
ISSN:1472-6920

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