Predicting medical students' academic performances by their cognitive abilities and personality characteristics

Purpose. To utilize multiple regression analyses with both linear and quadratic models to explore and confirm the relationships among students' cognitive abilities, personality traits, and medical school performances at the University of Los Angeles, California, UCLA School of Medicine. Method. Ninety-seven ''not-disadvantaged'' students' premedical grade-point averages (GPAs), Medical College Admission Test (MCAT) scores, and personality traits as measured by the Comrey Personality Scales (administered at their application to medical school in 1985) were used to predict their medical school performances according to several criteria. ''Disadvantaged'' students were excluded from the study because their poor performances' on all criteria would confound the relationships of personality, cognitive ability, and performance. Results. The MCAT score was a strong predictor of medical school performances, particularly those criteria measured by medical school GPAs and the National Board of Medical Examiners examination scores, but its predictive power dropped sharply when clinical performance and personal suitability were part of the performance evaluation. Specific personality traits not only strengthened the predictive power of cognitive and personality variables jointly, they became the primary predictors of clinical performance and personal suitability. A single personality-profile index failed to show any power of prediction. As expected, quadratic relationships were found between some personality traits and some medical school performance measures. Conclusion. According to these data it is not realistic to use one or two personality traits to predict personal suitability on all medical performance measures. The multiple regression analysis results indicate that different personality characteristics are incorporated in different types of medical performances, which is perhaps why the overall personality-profile score failed to predict any of the studied criteria. Because of the study's relatively small sample size, however, cross-validation studies are necessary to confirm these findings.