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Relationships between preclinical course grades and standardized exam performance.
- Source :
-
Advances in health sciences education : theory and practice [Adv Health Sci Educ Theory Pract] 2016 May; Vol. 21 (2), pp. 389-99. Date of Electronic Publication: 2015 Sep 12. - Publication Year :
- 2016
-
Abstract
- Success in residency matching is largely contingent upon standardized exam scores. Identifying predictors of standardized exam performance could promote primary intervention and lead to design insights for preclinical courses. We hypothesized that clinically relevant courses with an emphasis on higher-order cognitive understanding are most strongly associated with performance on United States Medical Licensing Examination Step exams and National Board of Medical Examiners clinical subject exams. Academic data from students between 2007 and 2012 were collected. Preclinical course scores and standardized exam scores were used for statistical modeling with multiple linear regression. Preclinical courses were categorized as having either a basic science or a clinical knowledge focus. Medical College Admissions Test scores were included as an additional predictive variable. The study sample comprised 795 graduating medical students. Median score on Step 1 was 234 (interquartile range 219-245.5), and 10.2 % (81/795) scored lower than one standard deviation below the national average (205). Pathology course score was the strongest predictor of performance on all clinical subject exams and Step exams, outperforming the Medical College Admissions Test in strength of association. Using Pathology score <75 as a screening metric for Step 1 score <205 results in sensitivity and specificity of 37 and 97 %, respectively, and a likelihood ratio of 11.9. Performance in Pathology, a clinically relevant course with case-based learning, is significantly related to subsequent performance on standardized exams. Multiple linear regression is useful for identifying courses that have potential as risk stratifiers.
- Subjects :
- Achievement
Female
Humans
Male
Models, Statistical
Retrospective Studies
College Admission Test statistics & numerical data
Education, Medical, Undergraduate statistics & numerical data
Educational Measurement statistics & numerical data
Licensure, Medical statistics & numerical data
Students, Medical statistics & numerical data
Subjects
Details
- Language :
- English
- ISSN :
- 1573-1677
- Volume :
- 21
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Advances in health sciences education : theory and practice
- Publication Type :
- Academic Journal
- Accession number :
- 26363626
- Full Text :
- https://doi.org/10.1007/s10459-015-9637-6