Application of latent class analysis in assessing the competency of physicians in China

Abstract Background The physicians’ competency is an important public health issue around the world. Several international organizations have taken the lead in examining the competencies required to be a physician. The purpose of this study is to identify subgroups of physicians’ competency based up...

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Main Authors: Zhuang Liu, Yue Zhang, Lei Tian, Baozhi Sun, Qing Chang, Yuhong Zhao
Format: Article
Language:English
Published: BMC 2017-11-01
Series:BMC Medical Education
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12909-017-1039-4
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author Zhuang Liu
Yue Zhang
Lei Tian
Baozhi Sun
Qing Chang
Yuhong Zhao
author_facet Zhuang Liu
Yue Zhang
Lei Tian
Baozhi Sun
Qing Chang
Yuhong Zhao
author_sort Zhuang Liu
collection DOAJ
description Abstract Background The physicians’ competency is an important public health issue around the world. Several international organizations have taken the lead in examining the competencies required to be a physician. The purpose of this study is to identify subgroups of physicians’ competency based upon the importance results of competency evaluation and provide a scientific basis for the qualitative research of the competency of physicians. Methods A cross-sectional study was conducted on a large population-based sample in 31 provinces, autonomous regions and municipalities directly under the central government in China. The latent class analysis was performed to identify patterns of physicians’ competency using M-plus software. Results In this study, the latent class analysis was adopted to identify the appropriate number of distinct latent classes of physicians’ competency based on eight competency dimensions, and a four-class model best fit the data, which are excellent competency group, lack of professionalism competency group, individual competency driven group, and lack of competency cognitive group. Therefore, 6247 physicians can be divided into four latent classes based on the importance results of competency evaluation, and the number of each class is 5684, 284, 215 and 64, respectively. Conclusion These findings suggested that latent class analysis can be used to study the competency of physicians, and four distinct subgroups were identified. Therefore, we can effectively understand the patterns of physicians’ competency, and the health administrative departments could utilize more specific measures according to their different competency subgroups, and providing individualized training schemes in the future training and management of physicians.
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spelling doaj.art-675743ecb0674fecb740adeec09996c32022-12-21T23:07:32ZengBMCBMC Medical Education1472-69202017-11-011711810.1186/s12909-017-1039-4Application of latent class analysis in assessing the competency of physicians in ChinaZhuang Liu0Yue Zhang1Lei Tian2Baozhi Sun3Qing Chang4Yuhong Zhao5School of Public Health, China Medical UniversitySchool of Public Health, China Medical UniversityResearch Center for Medical Education, China Medical UniversityResearch Center for Medical Education, China Medical UniversityDepartment of Clinical Epidemiology, Shengjing Hospital, China Medical UniversityDepartment of Clinical Epidemiology, Shengjing Hospital, China Medical UniversityAbstract Background The physicians’ competency is an important public health issue around the world. Several international organizations have taken the lead in examining the competencies required to be a physician. The purpose of this study is to identify subgroups of physicians’ competency based upon the importance results of competency evaluation and provide a scientific basis for the qualitative research of the competency of physicians. Methods A cross-sectional study was conducted on a large population-based sample in 31 provinces, autonomous regions and municipalities directly under the central government in China. The latent class analysis was performed to identify patterns of physicians’ competency using M-plus software. Results In this study, the latent class analysis was adopted to identify the appropriate number of distinct latent classes of physicians’ competency based on eight competency dimensions, and a four-class model best fit the data, which are excellent competency group, lack of professionalism competency group, individual competency driven group, and lack of competency cognitive group. Therefore, 6247 physicians can be divided into four latent classes based on the importance results of competency evaluation, and the number of each class is 5684, 284, 215 and 64, respectively. Conclusion These findings suggested that latent class analysis can be used to study the competency of physicians, and four distinct subgroups were identified. Therefore, we can effectively understand the patterns of physicians’ competency, and the health administrative departments could utilize more specific measures according to their different competency subgroups, and providing individualized training schemes in the future training and management of physicians.http://link.springer.com/article/10.1186/s12909-017-1039-4PhysiciansCompetencyLatent class analysis
spellingShingle Zhuang Liu
Yue Zhang
Lei Tian
Baozhi Sun
Qing Chang
Yuhong Zhao
Application of latent class analysis in assessing the competency of physicians in China
BMC Medical Education
Physicians
Competency
Latent class analysis
title Application of latent class analysis in assessing the competency of physicians in China
title_full Application of latent class analysis in assessing the competency of physicians in China
title_fullStr Application of latent class analysis in assessing the competency of physicians in China
title_full_unstemmed Application of latent class analysis in assessing the competency of physicians in China
title_short Application of latent class analysis in assessing the competency of physicians in China
title_sort application of latent class analysis in assessing the competency of physicians in china
topic Physicians
Competency
Latent class analysis
url http://link.springer.com/article/10.1186/s12909-017-1039-4
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