ArticleBMC medical education2022
Administrative data analysis of student attrition in hungarian medical training.
Article in BMC medical education, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Medical Student Engagement and Intention to Practise Medicine Across Undergraduate Years: A Longitudinal Study.Perspectives on medical education · 2026Article
- Early detection of at-risk health sciences students: a machine learning-based predictive study using midterm grades.BMC medical education · 2025Article
- Impact of psychological wellbeing and academic readiness on early medical student attrition: educators' perspective.BMC research notes · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is numerous empirical evidence supporting that college students studying in fields with rigorous curriculum and high requirements, such as medical training, are characterized by a higher risk of attrition than their peers. Since Hungarian medical training attracts more and more international students every year, the issue of dropout can have a global impact. Our study aimed to examine attrition risks of local and international students in Hungarian medical training.
methodsIn our study, we examined the dropout behaviour of all medical students who started their studies in 2010 in Hungary (N = 2391) by analysing longitudinal administrative data of those who studied between 2010 and 2017. Doing this, we conducted descriptive statistics and uncovered the risks of dropout using binary logistic regression.
resultsOur results indicate that the danger is primarily increased by factors directly linked to or indicating poor academic performance (slow pace of credit accumulation, tuition-based forms of finance). Individual characteristics, namely gender, and citizenship, also have a moderate but significant effect on the latter.
conclusionsThus a policy proposal can be formulated consisting of making the training network less rigid, devoting more educational attention to and providing targeted mentoring for students with learning difficulties and academic hardships. Foreign medical students studying in Hungary comprise a large group that has a high attrition rate, making it a prime target for dropout-reducing programs.
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Registered trials
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