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Predictive validity of the Dundee multiple mini‐interview
Author(s) -
Husbands Adrian,
Dowell Jonathan
Publication year - 2013
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/medu.12193
Subject(s) - context (archaeology) , test (biology) , predictive validity , aptitude , psychology , regression analysis , linear regression , clinical psychology , medicine , developmental psychology , statistics , mathematics , paleontology , biology
Context The multiple mini‐interview ( MMI ) is the primary admissions tool used to assess non‐cognitive skills at Dundee Medical School. Although the MMI shows promise, more research is required to demonstrate its transferability and predictive validity, for instance, relative to other UK pre‐admissions measures. Methods Applicants were selected for interview based on a combination of measures derived from the Universities and Colleges Admissions Service ( UCAS ) form (academic achievement, medical experience, non‐academic achievement and references) and the UK Clinical Aptitude Test ( UKCAT ) in 2009 and 2010. Candidates were selected into medical school according to a weighted combination of the UKCAT , the UCAS form and MMI scores. Examination scores were matched for 140 and 128 first‐ and second‐year students, respectively, who took the 2009 MMI s, and 150 first‐year students who took the 2010 MMI s. Pearson's correlations were used to test the relationships between pre‐admission variables, examination scores and demographic variables, namely gender and age. Statistically significant correlations were adjusted for range restrictions and were used to select variables for multiple linear regression analysis to predict examination scores. Results Statistically significant correlations ranged from 0.18 to 0.34 and 0.23 to 0.50 unrestricted. Multiple regression confirmed that MMI s remained the most consistent predictor of medical school assessments. No scores derived from the UCAS form correlated significantly with examination scores. Conclusions This study reports positive findings from the largest undergraduate sample to date. The MMI was the most consistent predictor of success in early years at medical school across two separate cohorts. UKCAT and UCAS forms showed minimal or no predictive ability. Further research in this area appears worthwhile, with longitudinal studies, replication of results from other medical schools and more detailed analysis of knowledge, skills and attitudinal outcome markers.