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...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-01-01
|
| Series: | BMC Medical Education |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12909-025-06652-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832594616198627328 |
|---|---|
| author | 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 |
| author_facet | 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 |
| author_sort | Jie Sun |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-48de88d7f6d84da880f64d8bc337ba27 |
| institution | Kabale University |
| issn | 1472-6920 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Education |
| spelling | doaj-art-48de88d7f6d84da880f64d8bc337ba272025-01-19T12:27:29ZengBMCBMC Medical Education1472-69202025-01-0125111010.1186/s12909-025-06652-7Nonacademic predictors of China medical licensing examinationJie Sun0Yingying Xie1Ningnannan Zhang2Jingliang Cheng3Meiyun Wang4Bing Zhang5Wenzhen Zhu6Hui Zhang7Shijun Qiu8Xiaojun Xu9Yongqiang Yu10Tong Han11Zuojun Geng12Weihua Liao13Bo Gao14Wen Qin15Feng Liu16Meng Liang17Qiang Xu18Jilian Fu19Jiayuan Xu20Mengge Liu21Peng Zhang22Wei Li23Dapeng Shi24Caihong Wang25Xi-Nian Zuo26Quan Zhang27Feng Chen28Jiance Li29Zhihan Yan30Wen Shen31Yanwei Miao32Junfang Xian33Longjiang Zhang34Kai Xu35Zhaoxiang Ye36Jing Zhang37Guangbin Cui38Chunshui Yu39for the CHIMGEN ConsortiumDepartment of Radiology and Tianjin Key Lab of Functional Imaging and Tianjin Institute of Radiology and State Key Laboratory of Experimental Hematology, Tianjin Medical University General HospitalDepartment of Radiology, The First Affiliated Hospital of Fujian Medical UniversityDepartment of Radiology and Tianjin Key Lab of Functional Imaging and Tianjin Institute of Radiology and State Key Laboratory of Experimental Hematology, Tianjin Medical University General HospitalDepartment of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou UniversityDepartment of Radiology, Henan Provincial People’s Hospital and Zhengzhou University People’s HospitalDepartment of Radiology, Drum Tower Hospital, Medical School of Nanjing UniversityDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Radiology, The First Hospital of Shanxi Medical UniversityDepartment of Medical Imaging, the First Affiliated Hospital of Guangzhou University of Traditional Chinese MedicineDepartment of Radiology, The Second Affiliated Hospital of Zhejiang University, School of MedicineDepartment of Radiology, The First Affiliated Hospital of Anhui Medical UniversityDepartment of Radiology, Tianjin Huanhu HospitalDepartment of Medical Imaging, The Second Hospital of Hebei Medical UniversityDepartment of Radiology, Xiangya Hospital, Central South UniversityDepartment of Radiology, The Affiliated Hospital of Guizhou Medical UniversityDepartment of Radiology and Tianjin Key Lab of Functional Imaging and Tianjin Institute of Radiology and State Key Laboratory of Experimental Hematology, Tianjin Medical University General HospitalDepartment of Radiology and Tianjin Key Lab of Functional Imaging and Tianjin Institute of Radiology and State Key Laboratory of Experimental Hematology, Tianjin Medical University General HospitalSchool of Medical Imaging, Tianjin Medical UniversityDepartment of Radiology and Tianjin Key Lab of Functional Imaging and Tianjin Institute of Radiology and State Key Laboratory of Experimental Hematology, Tianjin Medical University General HospitalDepartment of Radiology and Tianjin Key Lab of Functional Imaging and Tianjin Institute of Radiology and State Key Laboratory of Experimental Hematology, Tianjin Medical University General HospitalDepartment of Radiology and Tianjin Key Lab of Functional Imaging and Tianjin Institute of Radiology and State Key Laboratory of Experimental Hematology, Tianjin Medical University General HospitalDepartment of Radiology and Tianjin Key Lab of Functional Imaging and Tianjin Institute of Radiology and State Key Laboratory of Experimental Hematology, Tianjin Medical University General HospitalDepartment of Radiology, Tianjin Medical University Cancer Institute and HospitalDepartment of Radiology, Tianjin Medical University Cancer Institute and HospitalDepartment of Radiology, Henan Provincial People’s Hospital and Zhengzhou University People’s HospitalDepartment of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou UniversityIDG/McGovern Institute for Brain Research, Beijing Normal UniversityDepartment of Radiology, Characteristic Medical Center of Chinese People’s Armed Police ForceDepartment of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University)Department of Radiology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Radiology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical UniversityDepartment of Radiology, Tianjin First Center HospitalDepartment of Radiology, The First Affiliated Hospital of Dalian Medical UniversityDepartment of Radiology, Beijing Tongren Hospital, Capital Medical UniversityDepartment of Medical Imaging, Jinling Hospital, Medical School of Nanjing UniversityDepartment of Radiology, The Affiliated Hospital of Xuzhou Medical UniversityDepartment of Radiology, Tianjin Medical University Cancer Institute and HospitalDepartment of Magnetic Resonance, Lanzhou University Second HospitalFunctional and Molecular Imaging Key Lab of Shaanxi Province and Department of Radiology, Tangdu Hospital, Air Force Medical UniversityDepartment of Radiology and Tianjin Key Lab of Functional Imaging and Tianjin Institute of Radiology and State Key Laboratory of Experimental Hematology, Tianjin Medical University General HospitalAbstract 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.https://doi.org/10.1186/s12909-025-06652-7National medical licensing examinationGeneral medical knowledge testMedical studentsPredictors |
| spellingShingle | 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 Nonacademic predictors of China medical licensing examination BMC Medical Education National medical licensing examination General medical knowledge test Medical students Predictors |
| title | Nonacademic predictors of China medical licensing examination |
| title_full | Nonacademic predictors of China medical licensing examination |
| title_fullStr | Nonacademic predictors of China medical licensing examination |
| title_full_unstemmed | Nonacademic predictors of China medical licensing examination |
| title_short | Nonacademic predictors of China medical licensing examination |
| title_sort | nonacademic predictors of china medical licensing examination |
| topic | National medical licensing examination General medical knowledge test Medical students Predictors |
| url | https://doi.org/10.1186/s12909-025-06652-7 |
| work_keys_str_mv | AT jiesun nonacademicpredictorsofchinamedicallicensingexamination AT yingyingxie nonacademicpredictorsofchinamedicallicensingexamination AT ningnannanzhang nonacademicpredictorsofchinamedicallicensingexamination AT jingliangcheng nonacademicpredictorsofchinamedicallicensingexamination AT meiyunwang nonacademicpredictorsofchinamedicallicensingexamination AT bingzhang nonacademicpredictorsofchinamedicallicensingexamination AT wenzhenzhu nonacademicpredictorsofchinamedicallicensingexamination AT huizhang nonacademicpredictorsofchinamedicallicensingexamination AT shijunqiu nonacademicpredictorsofchinamedicallicensingexamination AT xiaojunxu nonacademicpredictorsofchinamedicallicensingexamination AT yongqiangyu nonacademicpredictorsofchinamedicallicensingexamination AT tonghan nonacademicpredictorsofchinamedicallicensingexamination AT zuojungeng nonacademicpredictorsofchinamedicallicensingexamination AT weihualiao nonacademicpredictorsofchinamedicallicensingexamination AT bogao nonacademicpredictorsofchinamedicallicensingexamination AT wenqin nonacademicpredictorsofchinamedicallicensingexamination AT fengliu nonacademicpredictorsofchinamedicallicensingexamination AT mengliang nonacademicpredictorsofchinamedicallicensingexamination AT qiangxu nonacademicpredictorsofchinamedicallicensingexamination AT jilianfu nonacademicpredictorsofchinamedicallicensingexamination AT jiayuanxu nonacademicpredictorsofchinamedicallicensingexamination AT menggeliu nonacademicpredictorsofchinamedicallicensingexamination AT pengzhang nonacademicpredictorsofchinamedicallicensingexamination AT weili nonacademicpredictorsofchinamedicallicensingexamination AT dapengshi nonacademicpredictorsofchinamedicallicensingexamination AT caihongwang nonacademicpredictorsofchinamedicallicensingexamination AT xinianzuo nonacademicpredictorsofchinamedicallicensingexamination AT quanzhang nonacademicpredictorsofchinamedicallicensingexamination AT fengchen nonacademicpredictorsofchinamedicallicensingexamination AT jianceli nonacademicpredictorsofchinamedicallicensingexamination AT zhihanyan nonacademicpredictorsofchinamedicallicensingexamination AT wenshen nonacademicpredictorsofchinamedicallicensingexamination AT yanweimiao nonacademicpredictorsofchinamedicallicensingexamination AT junfangxian nonacademicpredictorsofchinamedicallicensingexamination AT longjiangzhang nonacademicpredictorsofchinamedicallicensingexamination AT kaixu nonacademicpredictorsofchinamedicallicensingexamination AT zhaoxiangye nonacademicpredictorsofchinamedicallicensingexamination AT jingzhang nonacademicpredictorsofchinamedicallicensingexamination AT guangbincui nonacademicpredictorsofchinamedicallicensingexamination AT chunshuiyu nonacademicpredictorsofchinamedicallicensingexamination AT forthechimgenconsortium nonacademicpredictorsofchinamedicallicensingexamination |