Differential Prediction of Medical School Selection Factors for Rural and Non-Rural Populations

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Virginia Tech

Differential predictive validity in assessing academic performance in institutions of higher education has been assessed for a number of years. Historically, this body of research focused on gender and ethnicity. This study extends that research to geographic region (e.g., rural and non-rural populations). Specifically, this study predicted relationships between preadmission variables of incoming grade point average (GPA) and medical college admissions test (MCAT) and output variables of medical school GPA and comprehensive osteopathic medical licensing exam (COMLEX). Results indicate incoming GPA and MCAT are good variables to use to predict academic performance in medical school and score on the licensing board exam. Further, rural populations presented similar scores on preadmission variables and, thus, are not at a disadvantage in the admission process. A second goal of this study was to explore differential prediction of medical school GPA and COMLEX Level 1 score for the MCAT for rural and non-rural populations. Results provide some evidence of differential prediction of COMLEX score for the physical and biological sciences MCAT sub-tests such that rural populations' performance on the COMLEX Level 1 exam was underpredicted. Hence, when rural and non-rural populations present the same physical sciences and biological sciences MCAT sub-test score, the rural sub-group is predicted to obtain a lower COMLEX score and non-rural sub-group is predicted to obtain a higher COMLEX score. Further, when the two sub-groups present different MCAT scores for the physical and biological sciences sub-test, they are likely to obtain similar scores on the COMLEX. Implications and recommendations for future research are discussed.

rural, medical school, differential prediction, MCAT, admissions, COMLEX