Advances in Health Sciences Education

, Volume 14, Issue 5, pp 739–752 | Cite as

Using the personal background preparation survey to identify health science professions students at risk for adverse academic events

  • Craig W. Johnson
  • Ronald Johnson
  • John C. McKee
  • Mira Kim


In the first predictive validity study of a diagnostic and prescriptive instrument for averting adverse academic status events (AASE) among multiple populations of diverse health science professions students, entering matriculates’ personal background and preparation survey (PBPS) scores consistently significantly predicted 1st- or 2nd-year AASE. During 1st-year orientations, 441 entering matriculates in four southwestern schools from dental, medical, and nursing disciplines completed the 2004 PBPS. The following year during 1st-year orientations, 526 entering matriculates in five schools from dental, medical, nursing, and biomedical science disciplines completed the 2005 PBPS. The PBPS identifies and quantifies a student’s noncognitive and cognitive academic performance risks. One standard deviation increments in PBPS risks consistently multiplied 1st- or 2nd-year AASE odds by approximately 140% (p < .05), controlling for underrepresented minority student (URMS) status and school affiliation. Odds of 2nd-year AASE for URMS one standard deviation above the 2004 PBPS mean reached 494% of odds for nonURMS at the mean. PBPS total risks, school affiliation, and URMS status together provided 70–76% correct predictions of 1st- or 2nd-year AASE. PBPS predictive validity did not differ significantly among dental, medical, nursing, or biomedical science schools, or URMS/nonURMS. PBPS sensitivity and specificity approached those for FDA-approved screening mammograms for breast cancer and PSA tests for prostate cancer. PBPS positive predictive values of 42–60% exceeded those for both. The diagnostic and prescriptive PBPS can facilitate proactive targeting of corrective interventions aimed at reducing AASE and attrition among health science education students at risk for academic difficulties.


Health sciences professions students Underrepresented minority students Student retention Student attrition Health sciences graduate education Instrumentation Measurement Student advising Student persistence 


  1. AAMC. (2007). Medical school graduation and attrition rates. Analysis in Brief, 7(2). Retrieved 22 February 2008, from
  2. Abdur-Rahman, V., & Gaines, C. (1999). Retaining ethnic minority nursing students (REMNS): A multidimensional approach. ABNF Journal, 10(2), 33–36. March-April.Google Scholar
  3. Abernethy, A. D. (1999). A mentoring program for underrepresented-minority students at the University of Rochester School of Medicine. Academic Medicine, 74(4), 356–359.CrossRefGoogle Scholar
  4. ACT. (2001–2008). National collegiate retention and persistence to degree rates. Retrieved 20 October 2008, from through
  5. Allen, W. R. (1988). Improving black student access and achievement in higher education. Review of Higher Education, 11(4), 403–416.Google Scholar
  6. AMA. (2004). Health professions education data book 2004–2005. Chicago, IL: American Medical Association.Google Scholar
  7. Braxton, J. M., Brier, E. M., & Hossler, D. (1988). The influence of student problems on student withdrawal decisions: An autopsy on ‘autopsy’ studies. Research in Higher Education, 28, 241–253.CrossRefGoogle Scholar
  8. Cariaga-Lo, L., Enarson, C. E., Crandell, S., Zaccaro, D. J., & Richards, B. F. (1997). Cognitive and non-cognitive predictors of academic difficulty and attrition. Academic Medicine, 72, s69–s71.CrossRefGoogle Scholar
  9. Childs, G., Jones, R., Nugent, K. E., Cook, P. (2004). Retention of African-American students in baccalaureate nursing programs: Are we doing enough? Journal of Professional Nursing, 20, 129–133.CrossRefGoogle Scholar
  10. Clewell, B. C., de Cohen, C. C., Tsui, L., Forcier, L., Gao, E., Young, N., et al. (2005). Evaluation of the National Science Foundation Louis Stokes Alliances for Minority Participation Program. Retrieved 1 February 2007, from
  11. Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.Google Scholar
  12. Fitzpatrick, K. M., & Wright, M. P. (1995). Gender differences in medical school attrition rates, 1973–1992. Journal of American Medical Womens Association, 50, 204–206.Google Scholar
  13. Giordani, B., Edwards, A. S., Segal, S. S., Gillum, L. H., Lindsay, A., & Johnson, N. (2001). Effectiveness of a formal post-baccalaureate pre-medicine program for underrepresented minority students. Academic Medicine, 76, 844–848.CrossRefGoogle Scholar
  14. Gupta, G. C. (1991). Student attrition. A challenge for allied health education programs. Journal of the American Medical Association, 266, 963–967.CrossRefGoogle Scholar
  15. Habley, W. (2004). The status of academic advising: Final report from the ACT sixth national survey. Manhattan, KS: National Academic Advising Association. NACADA monograph #10.Google Scholar
  16. Habley, W. R., & McClanahan, R. (2004). What works in student retention—Four-year public colleges. ACT, Inc. Retrieved 18 February 2008, from
  17. Hesser, A., Pond, E., Lewis, L., & Abbott, B. (1996). Evaluation of a supplementary retention program for African–American baccalaureate nursing students. Journal of Nursing Education, 35, 304–309.Google Scholar
  18. Huff, K. L., & Fang, D. (1999). When are students most at risk of encountering academic difficulty? A study of the 1992 matriculants to US medical schools. Academic Medicine, 74, 454–460.CrossRefGoogle Scholar
  19. Humphrey, L. L., Helfand, M., Chan, B. K. S. Woolf, S. H. (2002). Annals Internal Medicine. 137(5 Part 1):347–360.Google Scholar
  20. Institute for Higher Education Policy (1998). Reaping the benefits: Defining the public and private value of going to college. Retrieved 19 February 2008 from
  21. Jaccard, J. (2001). Interaction effects in logistic regression. Thousand Oaks, CA: Sage.Google Scholar
  22. Jeffreys, M. R. (1998). Predicting nontraditional student retention and academic achievement. Nurse Educator, 23, 42–48.CrossRefGoogle Scholar
  23. Jeffreys, M. R. (2001). Evaluating enrichment program study groups: Academic outcomes, psychological outcomes, and variables influencing retention. Nurse Educator, 26, 142–149.CrossRefGoogle Scholar
  24. Johnson, C. W., Johnson, R., Mckee, J. C. (2009a). Underrepresented minority student retention: Risk differentials in health professional and graduate schools (Manuscript submitted for publication).Google Scholar
  25. Johnson, C. W., Johnson, R., Mckee, J. C., Kim, M. (2009b). Personal background preparation survey early identifies nursing students at risk for attrition. Journal of Nursing Education (in press).Google Scholar
  26. Kornitzer, B., Ronan, E., & Rifkin, M. R. (2005). Improving the adjustment of educationally disadvantaged students to medical school: The summer enrichment program. The Mount Sinai Journal of Medicine, 72, 317–321.Google Scholar
  27. Loo, C. M., & Rolison, G. (1986). Alienation of ethnic minority students at a predominantly white university. Journal of Higher Education, 57(1), 58–77.CrossRefGoogle Scholar
  28. Metzner, B. S. (1989). Perceived quality of academic advising: The effect on freshman attrition. American Educational Research Journal, 26, 422–442.Google Scholar
  29. Metzner, B. S., & Bean, J. P. (1987). The estimation of a conceptual model of nontraditional undergraduate student attrition. Research in Higher Education, 27, 15–38.CrossRefGoogle Scholar
  30. Penick, B. E., & Morning, C. (1983). The retention of minority engineering students. Report on the 1981–1982 NACME retention research program [Abstract] (ERIC Document Reproduction Service No.ED247325).Google Scholar
  31. Pounds, A. W. (1987). Black students’ needs on predominantly white campuses. In D. J. Wright (Ed.), New directions for student services, no. 38 (pp. 23–38). San Francisco: Jossey-Bass.Google Scholar
  32. Price, C. R., & Balogh, J. (2001). Using alumni to mentor nursing students at risk. Nurse Educator, 26, 209–211.CrossRefGoogle Scholar
  33. Richardson, R. C. (2000). The role of state and institutional policies and practices. In G. Campbell, R. Denes, & C. Morrison (Eds.), Access denied: Race, ethnicity, and the scientific enterprise (pp. 207–215). New York: Oxford University Press.Google Scholar
  34. Seidman, A. (1996). Retention revisited: RET = E Id + (E + I + C)Iv. College and University, 71(4), 18–20.Google Scholar
  35. Seidman, A. (Ed.). (2005). College student retention: Formula for student success. Westport, CT: ACE/Praeger.Google Scholar
  36. Smedley, B. D., Myers, H. F., & Harrell, S. P. (1993). Minority-status stresses and the college adjustment of ethnic minority freshmen. Journal of Higher Education, 64, 434–452.CrossRefGoogle Scholar
  37. Tekian, A. (1998). Attrition rates of underrepresented minority students at the University of Illinois at Chicago college of medicine, 1993–1997. Academic Medicine, 73, 336–338.Google Scholar
  38. Tekian, A., & Hruska, L. (2004). A review of medical school records to investigate the effectiveness of enrichment programs for “at risk” students. Teaching and Learning in Medicine, 16, 28–33.CrossRefGoogle Scholar
  39. Tracey, T. J., & Sedlacek, W. E. (1984). Non-Cognitive variables in predicting academic success by race. Measurement and Evaluation in Guidance, 16, 171–178.Google Scholar
  40. Tracey, T. J., & Sedlacek, W. E. (1987). A comparison of white and black student academic success using noncognitive variables: A LISREL analysis. Research in Higher Education, 27, 333–348.CrossRefGoogle Scholar
  41. U.S. Preventive Services Task Force. (2008). Screening for prostate cancer: US preventive services task force recommendation statement. Annals Internal Medicine, 149, 185–191.Google Scholar
  42. Wells, M. I. (2003). An epidemiologic approach to addressing student attrition in nursing programs. Journal of Professional Nursing, 19, 230–236.CrossRefGoogle Scholar
  43. Wells, M. I. (2006–2007). Dreams deferred but not deferred: A qualitative study on undergraduate nursing student attrition. Journal of College Student Retention Research, Theory & Practice, 8, 439–456.CrossRefGoogle Scholar
  44. Wilson, J. E., & Murphy, L. (1999). Premedical and predental enrichment program for minority students, 1969–1996, at Meharry Medical College. Academic Medicine, 74, 400–407.CrossRefGoogle Scholar
  45. Woolf, S. H. (2001). The accuracy and effectiveness of routine population screening with mammography, prostate-specific antigen, and prenatal ultrasound: A review of published scientific evidence. International Journal of Technology Assessment in Health Care, 17, 275–304.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Craig W. Johnson
    • 1
  • Ronald Johnson
    • 2
  • John C. McKee
    • 3
  • Mira Kim
    • 2
  1. 1.The University of Texas School of Health Information Sciences at HoustonHoustonUSA
  2. 2.Office of Cultural and Institutional DiversityThe University of Texas Health Science Center at HoustonHoustonUSA
  3. 3.Office of Outcomes AssessmentThe University of Texas Health Science Center at HoustonHoustonUSA

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