Longitudinal comparison of the academic performances of Asian-American and white medical students

Acad Med. 1993 Jan;68(1):82-6. doi: 10.1097/00001888-199301000-00013.


Purpose: To compare the academic performances of Asian-American medical students--before, during, and after medical school--with those of white students.

Method: The 140 Asian-American graduates and 2,269 white graduates from the classes of 1981-1992 at Jefferson Medical College were studied prospectively: data on academic performance, indebtedness, and delayed graduation were analyzed and compared for all the graduates. F-tests, chi-square tests, and regression models were used.

Results: The Asian-Americans had statistically significantly higher scores on the SAT (Scholastic Aptitude Test) quantitative subtest and on the MCAT (Medical College Admission Test) chemistry, physics, and science problems subtests; the whites had significantly higher scores on the MCAT reading subtest; third-year grade-point averages for required clerkships; and scores on National Board of Medical Examiners Part I, II, and III examinations (NBME I, II, and III). No significant difference was found in the other performance measures, including ratings in the first year of residency. Regression analysis showed that the MCAT reading score was the major predictor of Asian-Americans' performances on the NBME I and II.

Conclusion: Because the MCAT reading score is the major predictor of later performance for Asian-American students, schools should consider employing different criteria in predicting and monitoring these students' performances.

Publication types

  • Comparative Study

MeSH terms

  • Achievement*
  • Adult
  • Asian / statistics & numerical data*
  • Clinical Competence / statistics & numerical data
  • Education, Medical, Undergraduate
  • Education, Premedical
  • Educational Measurement* / methods
  • Female
  • Humans
  • Internship and Residency
  • Longitudinal Studies
  • Male
  • Philadelphia
  • Prospective Studies
  • Students, Medical / statistics & numerical data*
  • White People / statistics & numerical data*