title: How well do selection tools predict performance later in a medical programme?
abstract: The choice of tools with which to select medical students is complex and controversial. This study aimed to identify the extent to which scores on each of three admission tools (Admission GPA, UMAT and structured interview) predicted the outcomes of the first major clinical year (Y4) of a 6 year medical programme. Data from three student cohorts (n = 324) were analysed using regression analyses. The Admission GPA was the best predictor of academic achievement in years 2 and 3 with regression coefficients (B) of 1.31 and 0.9 respectively (each P < 0.001). Furthermore, Admission GPA predicted whether or not a student was likely to earn 'Distinction' rather than 'Pass' in year 4. In comparison, UMAT and interview showed low predictive ability for any outcomes. Interview scores correlated negatively with those on the other tools. None of the tools predicted failure to complete year 4 on time, but only 3% of students fell into this category. Prior academic achievement remains the best measure of subsequent student achievement within a medical programme. Interview scores have little predictive value. Future directions include longer term studies of what UMAT predicts, and of novel ways to combine selection tools to achieve the optimum student cohort.
authors: Centre for Medical and Health Sciences Education, Faculty of Medical and Health Sciences, The University of Auckland, Auckland Mail Centre, New Zealand. b.shulruf@auckland.ac.nz
authors: Boaz
authors: B
authors: Shulruf
authors: Phillippa
authors: P
authors: Poole
authors: Grace Ying
authors: GY
authors: Wang
authors: Joy
authors: J
authors: Rudland
authors: Tim
authors: T
authors: Wilkinson
mesh_terms: D000124:Achievement; D004521:Educational Measurement; D005260:Female; D005544:Forecasting; D006801:Humans; D008297:Male; D009520:New Zealand; D012044:Regression Analysis; D012570:School Admission Criteria; D012577:Schools, Medical; D013337:Students, Medical