Advances in Health Sciences Education

, Volume 14, Issue 3, pp 355–366 | Cite as

Aptitude, achievement and competence in medicine: a latent variable path model

Original Paper

Abstract

To develop and test a latent variable path model of general achievement, aptitude for medicine and competence in medicine employing data from the Medical College Admission Test (MCAT), pre-medical undergraduate grade point average (UGPA) and demographic characteristics for competence in pre-clinical and measures of competence (United States Licensure Examination {USMLE} Steps 1, 2, and 3). Data were gathered on 839,710 participants from 1991 to 2000 on demographic and school variables, UGPA, MCAT subtest scores and Steps 1, 2, and 3 of the United Stated Licensure Examination (USMLE). However, subsets of the total 839,710 participants included in the database were used for various analyses and the testing of a latent variable path model (LVPA). A number of preliminary descriptive and inferential techniques were used to confirm previous hypotheses and stated relationships amongst the variables of interest to the present study. Through development and testing of a latent variable path model, three latent variables measured by UGPA (general achievement), subscales of the MCAT (aptitude for medicine), and Steps 1, 2, and 3 of the USMLE (competence in medicine) were identified which resulted in a comparative fit index = .932 of the model to a large sample (n = 20,714). In a confirmatory latent variable path model we were able to identify theoretical constructs, aptitude for medicine, general achievement, and competence in medicine and their interrelationships. These are distinct but interrelated latent variables.

Keywords

Medical school performance MCAT Predicative validity Latent variable path analyses 

References

  1. Accreditation Council for Graduate Medical Education. (2001). Graduate medical education directory 2001–2002. Chicago, IL: AMA.Google Scholar
  2. Albanese, M. A., Snow, M. H., Skochelak, S. E., Huggett, K. N., & Farrell, P. M. (2003). Assessing personal qualities in medical school admissions. Academic Medicine, 78, 313–321. doi:10.1097/00001888-200303000-00016.CrossRefGoogle Scholar
  3. Association of American Medical Colleges. (1991). Use of MCAT data in admissions: A guide for medical school admissions officers and faculty. Washington, DC: AAMC.Google Scholar
  4. Basco, W., Way, D., Gilbert, G., & Hudson, A. (2002). Undergraduate institutional MCAT scores as predictors of USMLE step 1 performance. Academic Medicine, 77, s13–s15.Google Scholar
  5. Bentler, P. M. (1982). Linear systems with multiple levels and types of latent variable. In K. G. Jöreskog & H. Wold (Eds.), Systems under indirect observation—causality—structure—prediction (pp. 1–18; 102–130). New York: North-Holland Publishers.Google Scholar
  6. Bollen, K. A. (1989). Structural equations with latent variables (pp. 1–80; 226–236). New York: Wiley.Google Scholar
  7. Cohen, J. (2001). Facing the future. President’s Address. In 112th Annual Meeting of the Association of American Medical Colleges. Washington, DC, November 4, 2001.Google Scholar
  8. Crowder, D. G. (1959). Prediction of first-year grades in a medical college. Educational and Psychological Measurement, 19, 637–639. doi:10.1177/001316445901900418.CrossRefGoogle Scholar
  9. Dawson-Sauders, B., Paiva, R. E. A., & Doolen, D. R. (1986). Using ACT scores and grade point averages to predict students’ MCAT scores. Journal of Medical Education, 61, 681–683.Google Scholar
  10. Donnon, T., Oddone, E., & Violato, C. (2007). The predictive validity of the MCAT on medical school performance and medical board licensing examinations: A meta-analysis of the published research. Academic Medicine (in press).Google Scholar
  11. Donnon, T., & Violato, C. (2006). Medical students’ clinical reasoning skills as a function of basic science achievement and clinical competency measures. Academic Medicine, 81, S12–S15. doi:10.1097/01.ACM.0000236543.88782.b6.CrossRefGoogle Scholar
  12. Feil, D., Kristian, M., & Mitchell, N. (1998). Older medical students’ performances at McGill University. Academic Medicine, 73, 98–100. doi:10.1097/00001888-199801000-00020.CrossRefGoogle Scholar
  13. Gilbert, G. E., Basco, W. T., Jr., Blue, A. V., & O’Sullivan, P. S. (2002). Predictive validity of the Medical College Admissions Test writing sample for the United States Medical Licensing Examination Step 1 and 2. Advances in Health Science Education, 7, 191–200. doi:10.1023/A:1021110132214.CrossRefGoogle Scholar
  14. Hojat, M., Erdmann, J. B., Veloski, J. J., et al. (2000). A validity study of the writing sample section of the Medical College Admission Test. Academic Medicine, 75, S25–S27. doi:10.1097/00001888-200010001-00008.CrossRefGoogle Scholar
  15. Huff, K. L., Koenig, J. A., Treptau, M. M., & Sireci, S. G. (1999). Validity of MCAT scores for predicting clerkship performance of medical students grouped by sex and ethnicity. Academic Medicine, 74, S41–S44.Google Scholar
  16. Jones, R. F., & Thomae-Forgues, M. (1984). Validity of the MCAT in predicting performance in the first two years of medical school. Journal of Medical Education, 59, 455–464.Google Scholar
  17. Jöreskog, K. G. (1982). The LISREL approach to causal model-building in the social sciences. In K. G. Jöreskog & H. Wold (Eds.), Systems under indirect observation–causality–structure–prediction (pp. 1–18; 81–100). New York: North-Holland Publishers.Google Scholar
  18. Koenig, J., Sireci, S., & Wiley, A. (1998). Evaluating the predictive validity of MCAT scores across diverse applicant groups. Academic Medicine, 73, 1095–1106. doi:10.1097/00001888-199810000-00021.CrossRefGoogle Scholar
  19. Mitchell, K., Haynes, R., & Koenig, J. A. (1994). Assessing the validity of the updated Medical College Admission Test. Academic Medicine, 69, 394–401.Google Scholar
  20. Myung, I. J. (2003). Tutorial on maximum likelihood estimation. Journal of Mathematical Psychology, 47, 90–100. doi:10.1016/S0022-2496(02) 00028-7.CrossRefGoogle Scholar
  21. Parlow, J., & Rothman, A. I. (1974). Personality traits of first year medical students: trends over a six year period. British Journal of Medical Education, 54, 759–765.Google Scholar
  22. Raykov, T. (2000). On sensitivity if structural equation modeling to latent relation misspecifications. SEM, 7, 596–607.Google Scholar
  23. Societal Needs Working Group. (1996). CanMEDS 2000 project. Skills for the new millennium. Annals of the Royal College of Physicians and Surgeons of Canada, 29, 206–216.Google Scholar
  24. Swanson, D. B., Case, S. M., Koenig, J. A., & Killian, C. D. (1996). Preliminary study of the accuracies of the old and new Medical College Admission Tests for predicting performance on USMLE Step 1. Academic Medicine, 71, S25–S30.Google Scholar
  25. Tekian, T., Mrtek, R., Syftestad, P., Foley, R., & Sandlow, L. (1996). Baseline longitudinal data of undergraduate medical students at risk. Academic Medicine, 71, s86–s87. doi:10.1097/00001888-199610000-00053.CrossRefGoogle Scholar
  26. The Medical School Objectives Writing Group. (1999). Learning objectives for medical student education–guidelines for medical schools: Report I of the medical school objectives project. Academic Medicine, 74, 13–18.CrossRefGoogle Scholar
  27. United States Medical Licensing Examination. (2008). Scoring and score reporting. Philadelphia, PA: NBME.Google Scholar
  28. Veloski, J. J., Callahan, C. A., Xu, G., Hojat, M., & Nash, D. B. (2000). Prediction of students’ performances on licensing examinations using age, race, sex, undergraduate GPA, and MCAT scores. Academic Medicine, 75, S28–S30. doi:10.1097/00001888-200010001-00009.CrossRefGoogle Scholar
  29. Violato, C., & Donnon, T. (2005). Does the Medical College Admission Test predict clinical reasoning skills? A longitudinal study employing the Medical Council of Canada Clinical Reasoning Examination. Academic Medicine, 80, S76–S78. doi:10.1097/00001888-200510001-00007.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • V. Terri Collin
    • 1
  • Claudio Violato
    • 2
  • Kent Hecker
    • 3
  1. 1.Department of SurgeryUniversity of Pittsburgh Medical CenterPittsburghUSA
  2. 2.Medical Education and Research Unit, Faculty of MedicineUniversity of CalgaryCalgaryCanada
  3. 3.Faculty of Veterinary MedicineUniversity of CalgaryCalgaryCanada

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