Preparation courses for a medical admissions test: effectiveness contrasts with opinion

Med Educ. 2013 Apr;47(4):417-24. doi: 10.1111/medu.12124.

Abstract

Objectives: The Undergraduate Medicine and Health Sciences Admissions Test (UMAT) is used to rank applicants for admission to many medical schools. This study aimed to determine the effects of preparation courses on UMAT performance and on students' perceptions of their performance.

Methods: We asked students who sat the UMAT twice across two consecutive years to complete an online survey. The survey was administered in 2010 and 2011 to gather information on preparation activities, costs of preparation activities and students' opinions regarding their expected performance. Survey responses were compared with student scores on the second taking of the UMAT, adjusted for prior UMAT scores and university performance.

Results: The study (cohort: n = 263) was sufficiently powered to investigate two forms of preparation: courses offered by MedEntry (a UMAT preparation provider), and tutoring offered by the students' halls of residence. Neither was found to significantly affect UMAT score (p = 0.09 for MedEntry courses; p = 0.50 for halls of residence tutoring). There was no relationship between total time or money spent preparing and UMAT performance. However, students taking MedEntry courses and students spending more money on UMAT preparation were more likely to predict an improved score (p < 0.001 for both). A total of 85% of students improved their score on the second sitting, irrespective of preparation.

Conclusions: The use of either of two common forms of UMAT preparation does not translate to an improvement in UMAT score. However, in accordance with confirmation bias theory, the association between money spent on preparatory courses and self-assessed predicted score suggests that students' belief in the effectiveness of such courses may be confounded by their financial outlay.

MeSH terms

  • Cohort Studies
  • College Admission Test / statistics & numerical data*
  • Cost-Benefit Analysis / statistics & numerical data*
  • Education, Medical, Undergraduate*
  • Humans
  • Schools, Medical
  • Students / psychology*