Latent class analysis of medical students by admission type in Korea: effects on academic performance and career...

This study employed latent class analysis (LCA) to classify medical students based on their pre-admission characteristics and examine differences in academic performance, mental health, and post-graduation career paths.

A total of 314 medical students who matriculated from 2015-2018 at a Korean medical school participated for this study. LCA was performed with their gender, region of origin, admission type, and gap years (i.e., a period for retaking the college entrance examination) as classification variables. Mental health was assessed using BDI-II (Beck Depression Inventory-II), SSI-Beck (Scale for Suicidal Ideation-Beck), and K-Scale (Korean Internet Addiction Scale). Academic outcomes and career paths were compared across latent classes through analysis of variance and regression analyses.

Three distinct latent classes were identified in the total sample (n=314): the rolling admission-regional talent group (25.0% of the total sample), the regular admission-male retaker group (57.3%), and the non-local female group (17.7%). The regular admission-male retaker group showed significantly higher internet over- dependency levels (p<0.001), lower academic performance (p<0.001), and higher grade repetition rates (p<0.05) than the others. The rolling admission-regional talent group had the highest proportion of students working at their alma mater-affiliated hospitals (p<0.05).

The research findings could present practical implications to the medical school systems because this research analyzed the mental health status, academic performance, and career paths based on the admission types of medical school students. Furthermore, the results imply that a specific policy and/or a student support system should be required for medical students' achievement and their successful transition to career.