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Using latent class growth analysis to detect group developmental trajectories in preclinical medical education

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Abstract

Medical educators and programs are deeply interested in understanding and projecting 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 study explored students’ developmental trajectories and detected group differences based on their coursework performance in Anatomy within the two years of preclinical education in one medical school. Four subgroups were identified with various intercepts and slopes. There were significant group differences between these subgroups and their standardized scores in MCAT and UCMLE Step 1. The study provides evidence about the heterogeneity of the student population and points out future research directions.

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Both authors wrote the main manuscript text and were involved in research design and analyses. All authors reviewed the manuscript.

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Correspondence to Xiaomei Song.

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Song, X., Jia, Y. Using latent class growth analysis to detect group developmental trajectories in preclinical medical education. Adv in Health Sci Educ (2023). https://doi.org/10.1007/s10459-023-10279-y

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