{"title":"综合基础科学考试临床前学业成绩的预测效度：伊朗医学生全国队列研究","authors":"Farhang Rashidi, Reza Sattarpour, Alipasha Meysamie","doi":"10.2147/AMEP.S552380","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Medical education directly impacts patient care, yet the predictive validity of pre-clinical academic performance for licensure exam outcomes remains debated. This national, multi-institutional study (2019-2021) assessed the relationship between university course grades, cumulative grade point average (GPA), and Comprehensive Basic Science Examination (CBSE) scores in Iranian medical students.</p><p><strong>Methods: </strong>Course grades and GPAs of 23 medical schools were linked to CBSE outcomes of 51 medical schools across five consecutive exam periods via student national ID. Pearson's correlation, paired t-tests, ANOVA, and chi-square assessed trends. Hierarchical cluster analysis (dendrogram) examined course grade correlations. Independent CBSE total score predictors were found using multiple linear regression.</p><p><strong>Results: </strong>Of the 25,757 individual records, 9,359 (45.2% female) had complete academic and CBSE data, making them eligible for primary analyses (84.5% passed CBSE on the first attempt). The GPA was 15.11±1.74, and the CBSE score was 101.68±24.61. All course grades correlated significantly with CBSE subtests (r=0.055-0.544, P<0.001). A significant moderate association (r=0.492, P<0.001) exists between overall GPA and CBSE. Repeat examinees had considerably lower GPAs and CBSE scores (P<0.001). GPA (β=0.318), Anatomy (β=0.158), Physiology (β=0.135), Epidemiology (β=0.043), and Virology (β=0.043) were the most significant predictors in regression modeling (R²=0.426). Cluster analysis showed that academic grades in anatomy, physiology, and biochemistry were strongly correlated with CBSE subtests.</p><p><strong>Conclusion: </strong>This study represents the first large-scale national dataset in Iran pertaining to medical education. Pre-clinical GPA and course grades exhibit overall and subject-specific, notable predictive validity for CBSE performance. To enhance medical education and licensure results, it is advisable to implement standardized, cross-institutional comparisons alongside dynamic curriculum reviews. The regression model and clustering insights provide a framework for targeted educational interventions.</p>","PeriodicalId":47404,"journal":{"name":"Advances in Medical Education and Practice","volume":"16 ","pages":"1747-1759"},"PeriodicalIF":1.7000,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12493098/pdf/","citationCount":"0","resultStr":"{\"title\":\"Predictive Validity of Pre-Clinical Academic Achievements in Comprehensive Basic Science Examination: A Nationwide Cohort of Iranian Medical Students.\",\"authors\":\"Farhang Rashidi, Reza Sattarpour, Alipasha Meysamie\",\"doi\":\"10.2147/AMEP.S552380\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Medical education directly impacts patient care, yet the predictive validity of pre-clinical academic performance for licensure exam outcomes remains debated. This national, multi-institutional study (2019-2021) assessed the relationship between university course grades, cumulative grade point average (GPA), and Comprehensive Basic Science Examination (CBSE) scores in Iranian medical students.</p><p><strong>Methods: </strong>Course grades and GPAs of 23 medical schools were linked to CBSE outcomes of 51 medical schools across five consecutive exam periods via student national ID. Pearson's correlation, paired t-tests, ANOVA, and chi-square assessed trends. Hierarchical cluster analysis (dendrogram) examined course grade correlations. Independent CBSE total score predictors were found using multiple linear regression.</p><p><strong>Results: </strong>Of the 25,757 individual records, 9,359 (45.2% female) had complete academic and CBSE data, making them eligible for primary analyses (84.5% passed CBSE on the first attempt). The GPA was 15.11±1.74, and the CBSE score was 101.68±24.61. All course grades correlated significantly with CBSE subtests (r=0.055-0.544, P<0.001). A significant moderate association (r=0.492, P<0.001) exists between overall GPA and CBSE. Repeat examinees had considerably lower GPAs and CBSE scores (P<0.001). GPA (β=0.318), Anatomy (β=0.158), Physiology (β=0.135), Epidemiology (β=0.043), and Virology (β=0.043) were the most significant predictors in regression modeling (R²=0.426). Cluster analysis showed that academic grades in anatomy, physiology, and biochemistry were strongly correlated with CBSE subtests.</p><p><strong>Conclusion: </strong>This study represents the first large-scale national dataset in Iran pertaining to medical education. Pre-clinical GPA and course grades exhibit overall and subject-specific, notable predictive validity for CBSE performance. To enhance medical education and licensure results, it is advisable to implement standardized, cross-institutional comparisons alongside dynamic curriculum reviews. The regression model and clustering insights provide a framework for targeted educational interventions.</p>\",\"PeriodicalId\":47404,\"journal\":{\"name\":\"Advances in Medical Education and Practice\",\"volume\":\"16 \",\"pages\":\"1747-1759\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2025-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12493098/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Medical Education and Practice\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2147/AMEP.S552380\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"EDUCATION, SCIENTIFIC DISCIPLINES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Medical Education and Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2147/AMEP.S552380","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
Predictive Validity of Pre-Clinical Academic Achievements in Comprehensive Basic Science Examination: A Nationwide Cohort of Iranian Medical Students.
Background: Medical education directly impacts patient care, yet the predictive validity of pre-clinical academic performance for licensure exam outcomes remains debated. This national, multi-institutional study (2019-2021) assessed the relationship between university course grades, cumulative grade point average (GPA), and Comprehensive Basic Science Examination (CBSE) scores in Iranian medical students.
Methods: Course grades and GPAs of 23 medical schools were linked to CBSE outcomes of 51 medical schools across five consecutive exam periods via student national ID. Pearson's correlation, paired t-tests, ANOVA, and chi-square assessed trends. Hierarchical cluster analysis (dendrogram) examined course grade correlations. Independent CBSE total score predictors were found using multiple linear regression.
Results: Of the 25,757 individual records, 9,359 (45.2% female) had complete academic and CBSE data, making them eligible for primary analyses (84.5% passed CBSE on the first attempt). The GPA was 15.11±1.74, and the CBSE score was 101.68±24.61. All course grades correlated significantly with CBSE subtests (r=0.055-0.544, P<0.001). A significant moderate association (r=0.492, P<0.001) exists between overall GPA and CBSE. Repeat examinees had considerably lower GPAs and CBSE scores (P<0.001). GPA (β=0.318), Anatomy (β=0.158), Physiology (β=0.135), Epidemiology (β=0.043), and Virology (β=0.043) were the most significant predictors in regression modeling (R²=0.426). Cluster analysis showed that academic grades in anatomy, physiology, and biochemistry were strongly correlated with CBSE subtests.
Conclusion: This study represents the first large-scale national dataset in Iran pertaining to medical education. Pre-clinical GPA and course grades exhibit overall and subject-specific, notable predictive validity for CBSE performance. To enhance medical education and licensure results, it is advisable to implement standardized, cross-institutional comparisons alongside dynamic curriculum reviews. The regression model and clustering insights provide a framework for targeted educational interventions.
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