Applicants to medical school: if at first they don’t succeed, who tries again and are they successful?
- 131 Downloads
This study compared the profile of those who, after initial failure to be selected, choose to reapply to study medicine with those who did not reapply. It also evaluates the chance of a successful outcome for re-applicants. In 2013, 4007 applicants to undergraduate medical schools in the largest state in Australia were unsuccessful. Those who chose to reapply (n = 665) were compared to those who did not reapply (n = 3342). Results showed that the odds of re-applying to medicine were 55% less for those from rural areas, and 39% more for those from academically-selective schools. Those who had higher cognitive ability and high school academic performance scores in 2013 were also more likely to re-apply. Socioeconomic status was not related to re-application choice. Re-applicants’ showed significant improvements in selection test scores and had a 34% greater probability of selection than first-time applicants who were also interviewed in the same selection round. The findings of this study indicate that re-testing and re-application improves one’s chance of selection into an undergraduate medical degree, but may further reduce the diversity of medical student cohorts in terms of rural background and educational background.
KeywordsRetesting Widening participation Selection
- Andrich, D., Styles, I., Mercer, A., & Puddey, I. B. (2017). On the validity of repeated assessments in the UMAT, a high-stakes admissions test. Advances in Health Sciences Education, 22, 1245–1262.Google Scholar
- Australian Bureau of Statistics, (ABS). (2013). 2033.0.55.001—Census of population and housing: Socio-Economic indexes for areas (SEIFA), Australia, 2011. Retrieved January 15, 2018, from http://www.abs.gov.au/ausstats/abs@.nsf/DetailsPage/2033.0.55.0012011?OpenDocument.
- Barron, L. G., Randall, J. G., Trent, J. D., Johnson, J. F., & Villado, A. J. (2017). Big Five traits: Predictors of retesting propensity and score improvement. International Journal of Selection and Assessment, 25(2), 138–148.Google Scholar
- Baxter, J., Hayes, A., & Gray, M. (2011). Families in regional, rural and remote Australia. Australian Government Report accessed February 12, 2018 from https://aifs.gov.au/publications/families-regional-rural-and-remote-australia.
- Department of Health (Australia). (2017). Doctor connect. Retrieved September 1, 2017, from http://www.doctorconnect.gov.au/internet/otd/publishing.nsf/Content/ASGSRA_locator.
- Griffin, B., Bayl-Smith, P., & Hu, W. (2018). Predicting patterns of change and stability in student performance across a medical degree. Medical Education, 52(4), 438–446.Google Scholar
- Griffin, B., Carless, S., & Wilson, I. (2013). The undergraduate medical and health sciences admissions test: What is it measuring? Medical Teacher, 35, 727–730.Google Scholar
- Griffin, B., & Hu, W. (2015). The interaction of socio-economic status and gender in widening participation in medicine. Medical Education, 49, 103–113.Google Scholar
- Hausknecht, J. P. (2010). Candidate persistence and personality test practice effects: Implications for staffing system management. Personnel Psychology, 63(2), 299–324.Google Scholar
- Hausknecht, J. P., Halpert, J. A., Di Paolo, N. T., & Moriarty Gerrard, M. O. (2007). Retesting in selection: A meta-analysis of coaching and practice effects for tests of cognitive ability. Journal of Applied Psychology, 92, 373–385.Google Scholar
- Hay, M., Mercer, A. M., Lichtwark, I., Tran, S., Hodgson, W. C., Aretz, H. T., et al. (2017). Selecting for a sustainable workforce to meet the future healthcare needs of rural communities in Australia. Advances in Health Sciences Education, 22, 533–551.Google Scholar
- Ho, C. (2017). Selective schools increasingly cater to the most advantaged students. Retrieved March 9, 2017, from https://theconversation.com/selective-schools-increasingly-cater-to-the-most-advantaged-students-74151.
- Jones, M., Humphreys, J., & Prideaux, D. (2009). Predicting medical students’ intentions to take up rural practice after graduation. Medical Education, 43, 1001–1009.Google Scholar
- Koenig, J. A., & Leger, K. F. (1997). A comparison of retest performances and test-preparation methods for MCAT examinees grouped by gender and race-ethnicity. Academic Medicine, 72(10, Suppl 1), S100–S102.Google Scholar
- Lievens, F., Buyse, T., & Sackett, P. R. (2005). Retest effects in operational selection settings: Development and test of a framework. Personnel Psychology, 58, 981–1007.Google Scholar
- Lievens, F., Reeve, C. L., & Heggestad, E. D. (2007). An examination of psychometric bias due to retesting on cognitive ability tests in selection settings. Journal of Applied Psychology, 92, 1672–1682.Google Scholar
- Mercer, A., & Chiavaroli, N. (2006). UMAT: A Validity Study. A review of the underlying constructs and an analysis of the content of the Undergraduate Medicine and Health Sciences Admission Test.; a report prepared for the UMAT Consortium.Google Scholar
- Nicholson, S., & Cleland, J. (2015). Reframing research on widening participation in medical education: Using theory to inform practice. In J. Cleland & S. J. Durning (Eds.), Researching medical education (pp. 231–242). Oxford: Wiley-Blackwell.Google Scholar
- Nicholson, S., & Cleland, J. A. (2017). “It’s making contacts”: Notions of social capital and implications for widening access to medical education. Advances in Health Sciences Education, 22, 477–490.Google Scholar
- Olenick, J., Bhatia, S., & Ryan, A. M. (2016). Effects of g-loading and time lag on retesting in job selection. International Journal of Selection and Assessment, 24, 324–336.Google Scholar
- Puddey, I. B., Mercer, A., Andrich, D., & Styles, I. (2014). Practice effects in medical school entrance testing with the undergraduate medicine and health sciences admission test (UMAT). BMC Medical Education, 14, 48.Google Scholar
- Richardson, S., & Friedman, T. (2010). Australian Regional Higher Educatio: Student characteristics and experiences. Report produced by the Austtralia Council for Educational Research Ltd.Google Scholar
- Robb, N., Dunkley, L., Boynton, P., & Greenhalgh, T. (2007). Looking for a better future: Identity construction in socio-economically deprived 16-year olds considering a career in medicine. Social Science and Medicine, 65, 738–754.Google Scholar
- Schleicher, D. J., Van Iddekinge, C. H., Morgeson, F. P., & Campion, M. A. (2010). If at first you don’t succeed, try, try again: Understanding race, age, and gender differences in retesting score improvement. Journal of Applied Psychology, 95, 603–617.Google Scholar
- van Iddekinge, C. H., & Arnold, J. D. (2017). Retaking employment tests: What we know and what we still need to know. Annual Review of Organizational Psychology and Organizational Behavior, 4, 445–471.Google Scholar
- van Iddekinge, C. H., Morgeson, F. P., Schleicher, D. J., & Campion, M. A. (2011). Can I retake it? Exploring subgroup differences and criterion-related validity in promotion retesting. Journal of Applied Psychology, 96, 941–955.Google Scholar
- Watson, J., Wright, S., Hay, I., Beswick, K., Allen, J., & Cranston, N. (2016). Rural and regional students’ perceptions of schooling and factors that influence their aspirations. Australian and International Journal of Rural Education, 26(2), 4–18.Google Scholar
- Zhao, X., Oppler, S., Dunleavy, D., & Kroopnick, M. (2010). Validity of four approaches of using repeaters’ MCAT scores in medical school admissions to predict USMLE Step 1 total scores. Academic Medicine, 85(10), S64–S67.Google Scholar