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Nomograms for Predicting Medical Students' Perceptions of the Learning Environment: Multicenter Evidence From Medical Schools in China

Medical students' perceptions of the medical school learning environment (MSLE) have an important impact on their professional development, and physical and mental health. Few studies reported potential factors that influenced medical students' perceptions of MSLE. Thus, the main goal of t...

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Detalles Bibliográficos
Autores principales: Zhou, Zhitong, Huang, Runzhi, Zhang, Guoyang, Gong, Meiqiong, Xian, Shuyuan, Yin, Huabin, Meng, Tong, Wang, Xiaonan, Wang, Yue, Chen, Wenfang, Zhang, Chongyou, Du, Erbin, Lin, Min, Liu, Xin, Lin, Qing, Ji, Shizhao, Wu, Hongbin, Huang, Zongqiang, Zhang, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099049/
https://www.ncbi.nlm.nih.gov/pubmed/35570958
http://dx.doi.org/10.3389/fpubh.2022.825279
Descripción
Sumario:Medical students' perceptions of the medical school learning environment (MSLE) have an important impact on their professional development, and physical and mental health. Few studies reported potential factors that influenced medical students' perceptions of MSLE. Thus, the main goal of this study was to identify influencing factors for medical students' perception levels of MSLE. The perception levels of MSLE were assessed by the Johns Hopkins Learning Environment Scale. The univariate and multivariate logistic regression analyses were performed to identify significant predictors for the perceptions of MSLE. The nomograms were established to predict medical students' perception levels of MSLE. In the multivariate logistic regression model, gender, university category, grade, mother education level, learning environment of schools, interests in medicine, and Kolb learning experience were significantly associated with medical students' perceptions of MSLE. Correspondently, the nomograms were built based on significant variables identified by the univariate logistic regression analysis. The validation of the nomograms showed that the model had promising predictive accuracy, discrimination, and accordance (area under the curve (AUC) = 0.751). This study identified influencing factors of medical students' perceptions of MSLE. It is essential to implement corresponding interventions to improve medical students' perceptions.