Latent class analysis identified three distinct groups of Korean medical students based on pre-admission characteristics, with the regular admission-male retaker group showing significantly higher internet over-dependency, lower academic performance, and higher grade repetition rates than the other groups.
Key Findings
Results
Latent class analysis identified three distinct student groups based on pre-admission characteristics among 314 Korean medical students.
Total sample was 314 medical students who matriculated from 2015–2018 at a single Korean medical school.
Classification variables included gender, region of origin, admission type, and gap years (periods for retaking the college entrance examination).
The three classes were: rolling admission-regional talent group (25.0% of total sample), regular admission-male retaker group (57.3%), and non-local female group (17.7%).
LCA was used rather than traditional categorical grouping to identify naturally occurring subgroups.
Results
The regular admission-male retaker group showed significantly higher internet over-dependency levels compared to the other latent classes.
Internet addiction/over-dependency was measured using the K-Scale (Korean Internet Addiction Scale).
The difference in internet over-dependency across groups was statistically significant at p<0.001.
This group comprised 57.3% of the total sample, making it the largest of the three latent classes.
The group was characterized by male gender, regular admission pathway, and having taken gap years to retake the college entrance exam.
Results
The regular admission-male retaker group had significantly lower academic performance than the other latent classes.
Differences in academic performance across latent classes were statistically significant at p<0.001.
Academic outcomes were compared across latent classes through analysis of variance and regression analyses.
The regular admission-male retaker group also showed higher grade repetition rates, significant at p<0.05.
Mental health was assessed using BDI-II (Beck Depression Inventory-II) and SSI-Beck (Scale for Suicidal Ideation-Beck) in addition to academic outcome measures.
Results
The rolling admission-regional talent group had the highest proportion of students working at their alma mater-affiliated hospitals after graduation.
The difference in the proportion working at alma mater-affiliated hospitals across groups was statistically significant at p<0.05.
This group comprised 25.0% of the total sample.
The rolling admission-regional talent group was characterized by regional talent admission type and regional origin.
Career path differences were compared across latent classes through analysis of variance and regression analyses.
Conclusions
The study suggests that specific policies and student support systems should be tailored to admission-type-based student subgroups for improved academic achievement and career transition.
The authors note 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."
The study analyzed mental health status, academic performance, and career paths simultaneously based on admission types.
The findings are described as having "practical implications to the medical school systems."
The study was conducted at a single Korean medical school, which may limit generalizability.
What This Means
This research suggests that Korean medical students can be meaningfully grouped into three distinct categories based on characteristics they had before entering medical school: how they were admitted, where they came from, their gender, and whether they took time off to retake entrance exams. The largest group (about 57%) consisted of male students admitted through the regular process who had taken gap years to retake entrance exams. This group fared worse in several ways — they had lower grades, were more likely to have to repeat academic years, and showed higher levels of problematic internet use compared to the other two groups. Meanwhile, students admitted through a regional talent program were most likely to end up working at hospitals affiliated with the school where they trained.
The study used a statistical method called latent class analysis, which identifies naturally occurring subgroups within a population rather than simply dividing students by a single characteristic like admission type. This approach revealed that combinations of factors — not just one variable in isolation — define meaningfully different student experiences and outcomes. The research also measured mental health using standardized tools for depression, suicidal ideation, and internet addiction, connecting these measures to academic and career outcomes.
This research suggests that medical schools in Korea may benefit from recognizing these distinct student subgroups and designing targeted support programs for each. For example, students who took gap years for exam retakes may need specific academic or mental health support. The finding that regionally admitted students tend to stay local for their careers also has implications for healthcare workforce planning, particularly for addressing physician shortages in regional areas.
Kim S, Hwang I, Han C. (2026). Latent class analysis of medical students by admission type in Korea: effects on academic performance and career paths.. Korean journal of medical education. https://doi.org/10.3946/kjme.2025.093