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Using latent class growth analysis to detect group developmental trajectories in preclinical medical education.
Song, Xiaomei; Jia, Yuane.
Afiliação
  • Song X; School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106-7504, USA. Xiaomei.song@case.edu.
  • Jia Y; Rutgers, The State University of New Jersey, Newark, NJ, USA.
Article em En | MEDLINE | ID: mdl-37679596
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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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Adv Health Sci Educ Theory Pract Assunto da revista: EDUCACAO / SAUDE PUBLICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Adv Health Sci Educ Theory Pract Assunto da revista: EDUCACAO / SAUDE PUBLICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos