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Medical school dropout ‐ testing at admission versus selection by highest grades as predictors
Author(s) -
O’Neill Lotte,
Hartvigsen Jan,
Wallstedt Birgitta,
Korsholm Lars,
Eika Berit
Publication year - 2011
Publication title -
medical education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.776
H-Index - 138
eISSN - 1365-2923
pISSN - 0308-0110
DOI - 10.1111/j.1365-2923.2011.04057.x
Subject(s) - dropout (neural networks) , logistic regression , confidence interval , odds ratio , entrance exam , test (biology) , medicine , odds , cohort , demography , multivariate analysis , psychology , predictive validity , clinical psychology , paleontology , machine learning , sociology , computer science , biology
Medical Education 2011: 45 : 1111–1120 Context Very few studies have reported on the effect of admission tests on medical school dropout. The main aim of this study was to evaluate the predictive validity of non‐grade‐based admission testing versus grade‐based admission relative to subsequent dropout. Methods This prospective cohort study followed six cohorts of medical students admitted to the medical school at the University of Southern Denmark during 2002–2007 ( n = 1544). Half of the students were admitted based on their prior achievement of highest grades (Strategy 1) and the other half took a composite non‐grade‐based admission test (Strategy 2). Educational as well as social predictor variables (doctor‐parent, origin, parenthood, parents living together, parent on benefit, university‐educated parents) were also examined. The outcome of interest was students’ dropout status at 2 years after admission. Multivariate logistic regression analysis was used to model dropout. Results Strategy 2 (admission test) students had a lower relative risk for dropping out of medical school within 2 years of admission (odds ratio 0.56, 95% confidence interval 0.39–0.80). Only the admission strategy, the type of qualifying examination and the priority given to the programme on the national application forms contributed significantly to the dropout model. Social variables did not predict dropout and neither did Strategy 2 admission test scores. Conclusions Selection by admission testing appeared to have an independent, protective effect on dropout in this setting.