• 1.

    Albanese, MA, MH Snow, SE Skochelak, et al. :Assessing personal qualities in medical school admissions. .Acad Med 78::313. ,2003. .

  • 2.

    Tekian, A . :Cognitive factors, attrition rates and under-represented minority students: the problem of predicting future performance. .Acad Med 73::S38. ,1998. .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3.

    Julian, ER . :Validity of the Medical College Admission Test for predicting medical school performance. .Acad Med 80::910. ,2005. .

  • 4.

    Petek, JM and WF Todd. :Predictive validity of the new MCAT relative to other preadmission predictors in podiatric school. .Acad Med 66::425. ,1991. .

  • 5.

    Salvatori, P . :Reliability and validity of admissions tools used to select students for health professions. .Adv Health Sci Educ Theory Pract 6::159. ,2001. .

  • 6.

    Evans, P and FK Wen. :Does the medical college admissions test predict global academic performance in osteopathic medical school. .J Am Osteopath Assoc 107::157. ,2007. .

    • Search Google Scholar
    • Export Citation
  • 7.

    McGaghie, W . :Perspective on medical school admission. .Acad Med 65::136. ,1990. .

  • 8.

    Steinbrook, R . :Medical student debt: is there a limit? N Engl J Med 359::2629. ,2008. .

    • Crossref
    • Web of Science
    • Search Google Scholar
    • Export Citation
  • 9.

    Association of American Medical Colleges :AAMC Statement on the Physician Workforce. ,Association of American Medical Colleges. ,Washington, DC. ,June 2006. .

    • Search Google Scholar
    • Export Citation
  • 10.

    Kassebaum, DG and PL Szenas. :The longer road to medical school graduation. .Acad Med 69::856. ,1994. .

  • 11.

    Huff, KL and D Fang. :When are students most at risk of encountering academic difficulty? a study of the 1992 matriculants to US medical schools. .Acad Med 74::454. ,1999. .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12.

    Yates, J and D James. :Predicting the “strugglers”: a case control study of students at Nottingham University Medical School. .BMJ 332::1009. ,2006. .

  • 13.

    Kleshinski, J, SA Khuder, JI Shapiro, et al. :Impact of preadmission variables on USMLE step 1 and 2 performance. .Acad Med 14::69. ,2009. .

    • Search Google Scholar
    • Export Citation
  • 14.

    Steinecke, A, J Beaudreau, RB Bletzinger, et al. :Race-neutral admission approaches: challenges and opportunities for medical schools. .Acad Med 82::117. ,2007. .

    • Crossref
    • PubMed
    • Web of Science
    • Search Google Scholar
    • Export Citation
  • 15.

    Blue, AV, GE Gilbert, CL Elam, et al. :Does institutional selectivity aid in the prediction of medical school performance? Acad Med 75::31. ,2000. .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16.

    Urlings-Strop, LC, T Stijnen, AP Themmen, et al. :Selection of medical students: a controlled experiment. .Med Educ 43::175. ,2009. .

    • Crossref
    • PubMed
    • Web of Science
    • Search Google Scholar
    • Export Citation
  • 17.

    Cariaga-Lo, L, C Enarson, S Crandall, et al. :Cognitive and noncognitive predictors of academic difficulty and attrition. .Acad Med 72::S69. ,1997. .

  • 18.

    Johnson, CW, R Johnson, JC McKee, et al. :Using the personal background preparation survey to identify health science professions students at risk for adverse academic events. .Adv Health Sci Educ Theory Pract 14::739. ,2009. .

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Mertler, CA and R Vannatta. :Advanced and Multivariate Statistical Methods. ,Pyrczak Publishing. ,Los Angeles. ,2002. .

  • 20.

    Morton, RF, JR Hebel, and RJ McCarter. :A Study Guide to Epidemiology and Biostatistics, ,5th Ed. ,An Aspen Publication. ,Gaithersburg, MD. ,2001. .

    • Search Google Scholar
    • Export Citation
  • 21.

    Wiley, A and JA Koenig. :The validity of the Medical College Admission Test for predicting performance in the first two years of medical school. .Acad Med 71::S83. ,1996. .

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Hoffman, RM, FD Gilliland, M Adams-Cameron, et al. :Prostate-specific antigen testing accuracy in community practice. .BMC Fam Pract 3::19. ,2002. .

  • 23.

    Payne, JL, CM Nowacki, JY Girotti, et al. :Increasing the graduation rates of minority students. .J Med Educ 61::353. ,1986. .

  • 24.

    Segal, SS, B Giordani, LH Gillum, et al. :The Academic Support Program at the University of Michigan School of Medicine. .Acad Med 74::383. ,1999. .

    • Crossref
    • Search Google Scholar
    • Export Citation

Can We Predict 4-year Graduation in Podiatric Medical School Using Admission Data?

Sanjay Sesodia Barry University School of Podiatric Medicine, Miami Shores, FL.

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David Molnar Barry University School of Podiatric Medicine, Miami Shores, FL.

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Graham P. Shaw Barry University School of Podiatric Medicine, Miami Shores, FL.

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Background:

This study examined the predictive ability of educational background and demographic variables, available at the admission stage, to identify applicants who will graduate in 4 years from podiatric medical school.

Methods:

A logistic regression model was used to identify two predictors of 4-year graduation: age at matriculation and total Medical College Admission Test score. The model was cross-validated using a second independent sample from the same population. Cross-validation gives greater confidence that the results could be more generally applied.

Results:

Total Medical College Admission Test score was the strongest predictor of 4-year graduation, with age at matriculation being a statistically significant but weaker predictor.

Conclusions:

Despite the model’s capacity to predict 4-year graduation better than random assignment, a sufficient amount of error in prediction remained, suggesting that important predictors are missing from the model. Furthermore, the high rate of false-positives makes it inappropriate to use age and Medical College Admission Test score as admission screens in an attempt to eliminate attrition by not accepting at-risk students. (J Am Podiatr Med Assoc 102(6): 463–470, 2012)

Corresponding author: Sanjay Sesodia, PhD, Barry University School of Podiatric Medicine, 11300 NE 2nd Ave, Miami Shores, FL 33161. (E-mail: ssesodia@mail.barry.edu)