Using Latent Growth Mixture Modeling to Detect Group Developmental Differences in Preclinical Medical Education

• In Event: Simulation and Clinical Reasoning

Abstract

Medical educators and programs are deeply interested in understanding the longitudinal developmental trajectories of medical students after these students are matriculated into medical schools so appropriate resources and interventions can be provided to support students’ learning and progression during the process. As students have different characteristics and they do not learn and progress at the same pace, it is important to identify student subgroups and address their academic needs to create more equitable learning opportunities. Using latent class growth analysis, this project explored students’ developmental trajectory and detected group differences based on their Anatomy performance in nine courses at the preclinical education in one medical school.

Authors

• Xiaomei Song, Case Western Reserve University

• Yuane Jia, Rutgers University