What Matters from Admissions? Identifying Success and Risk Among Canadian Dental Students

The aims of this study were to determine whether different student profiles would emerge in terms of high and low GPA performance in each year of dental school and to investigate the utility of preadmissions variables in predicting performance and performance stability throughout each year of dental school. Data from 11 graduating cohorts (2004–14) at the Schulich School of Medicine & Dentistry, University of Western Ontario, Canada, were collected and analyzed using bivariate correlations, latent profile analysis, and hierarchical generalized linear models (HGLMs). The data analyzed were for 616 students in total (332 males and 284 females). Four models were developed to predict adequate and poor performance throughout each of four dental school years. An additional model was developed to predict student performance stability across time. Two separate student profiles reflecting high and low GPA performance across each year of dental school were identified, and scores on cognitive preadmissions variables differentially predicted the probability of grouping into high and low performance profiles. Students with higher pre‐dental GPAs and DAT chemistry were most likely to remain stable in a high‐performance group across each year of dental school. Overall, the findings suggest that selection committees should consider pre‐dental GPA and DAT chemistry scores as important tools for predicting dental school performance and stability across time. This research is important in determining how to better predict success and failure in various areas of preclinical dentistry courses and to provide low‐performing students with adequate academic assistance.