BackgroundStudent selection at Hamburg medical school is based on the combination of a natural science knowledge test (HAM-Nat) and pre-university educational attainment.MethodOf the 1565 medical students enrolled in Hamburg from 2012 to 2015 about half were admitted by an entrance test, half by quotas. First, we analysed sociodemographic determinants of entrance test performance. Then, we used regression analysis to describe the interplay of variables in the prediction of study outcome, the role of sociodemographic factors, and differences in the calibration of educational attainment specific to German federal states.ResultsBetter performance in the entrance test was associated with age over 21, male gender, German nationality, first language German and both parents holding an academic degree – effect sizes were small. No differences were found for the birthplaces of parents (a proxy for migration background). Study outcome differed considerably among admission paths: Students admitted by entrance test or the quota for excellent pre-university educational attainment performed markedly better during the first 3 terms than students admitted by the waiting list quota and the quota for foreign students. Gender differences in study outcome were slight with better performance by males. The relation of pre-university educational attainment to study outcome was moderated by the federal state in which secondary schooling took place. Methods for the equating of state-specific grades are explored. The predictive validity of the HAM-Nat after correction for range restriction was r = .31. The relatively low value of this coefficient may be attributed to 3 factors: 1. self-selection of applicants which leads to a validity-enhancing effect that is not revealed by the predictor-outcome correlation, 2. reduction of variance due to a high selection ratio, and 3. high test difficulty, exceeding the demands of the medical curriculum.ConclusionThe HAM-Nat achieves a small amount of incremental validity over pre-university educational attainment. This effect, obtained from correlational analysis, underestimates the validity of the test, because it does not reflect the role of self-selection and other validity enhancing features of the selection process.
Background Sociodemographic subgroup differences in multiple mini-interview (MMI) performance have been extensively studied within the MMI research literature, but heterogeneous findings demand a closer look at how specific aspects of MMI design (such as station type) affect these differences. So far, it has not been investigated whether sociodemographic subgroup differences imply that an MMI is biased , particularly in terms of its predictive validity. Methods Between 2010 and 2017, the University Medical Centre Hamburg-Eppendorf (UKE) tested 1438 candidates in an MMI who also provided sociodemographic data and agreed to participate in this study. Out of these, 400 candidates were admitted and underwent a first objective structured clinical examination (OSCE) after one and a half years, including one station assessing communication skills. First, we analyzed the relationship between gender, age, native language and medical family background and MMI station performance including interaction terms with MMI station type (simulation, interview, and group) in a hierarchical linear model. Second, we tested whether the prediction of OSCE overall and communication station performance in particular differed depending on sociodemographic background by adding interaction terms between MMI performance and gender, age and medical family background in a linear regression model. Results Young female candidates performed better than young male candidates both at interview and simulation stations. The gender difference was smaller (simulation) or non-significant (interview) in older candidates. There were no gender or age effects in MMI group station performance. All effects were very small, with the overall model explaining only 0.6% of the variance. MMI performance was not related to OSCE overall performance but significantly predicted OSCE communication station performance with no differences in the prediction for sociodemographic subgroups. Conclusions The Hamburg MMI is fair in its prediction of OSCE communication scores. Differences in MMI station performance for gender and age and their interaction with MMI station type can be related to the dimensions assessed at different station types and thus support the validity of the MMI. Rather than being threats to fairness, these differences could be useful for decisions relating to the design and use of an MMI.
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