Abstract
This article was migrated. The article was marked as recommended. Content: There remains much debate over the 'best' method for selecting students in to medicine. This study aimed to assess the predictive validity of four different selection tools with academic performance outcomes in first-year undergraduate medical students. Methods: Regression analyses were conducted between admission scores on previous academic performance - the Australian Tertiary Admission Rank (ATAR), the Undergraduate Medicine and Health Sciences Admission Test (UMAT), Multiple-Mini Interview (MMI) and the Personal Qualities Assessment (PQA) with student performance in first-year assessments of Multiple Choice Questions, Short Answer Questions, Objective Structured Clinical Examinations (OSCE) and Problem-Based Learning (PBL) Tutor ratings in four cohorts of students (N = 604, 90%). Results: All four selection tools were found to have significant predictive associations with one or more measures of student performance in Year One of undergraduate medicine. UMAT, ATAR and MMI scores consistently predicted first year performance on a number of outcomes. ATAR was the only selection tool to predict the likelihood of making satisfactory progress overall. Conclusions: All four selection tools play a contributing role in predicting academic performance in first year medical students. Further research is required to assess the validity of selection tools in predicting performance in the later years of medicine.
Highlights
The most appropriate methods for selecting undergraduate medical students continues to generate debate in Australia (Wilson 2012) and overseas (Ferguson 2002)
Regression analyses were conducted between admission scores on previous academic performance – the Australian Tertiary Admission Rank (ATAR), the Undergraduate Medicine and Health Sciences Admission Test (UMAT), Multiple-Mini Interview (MMI) and the Personal Qualities Assessment (PQA) with student performance in first-year assessments of Multiple Choice Questions, Short Answer Questions, Objective Structured Clinical Examinations (OSCE) and Problem-Based Learning (PBL) Tutor ratings in four cohorts of students (N = 604, 90%)
Higher scores on Short-Answer Question (SAQ) were predicted by higher ATAR (p
Summary
The most appropriate methods for selecting undergraduate medical students continues to generate debate in Australia (Wilson 2012) and overseas (Ferguson 2002). In order to increase transparency in the selection process and reduce potential sources of bias, many university medical programs utilise a range of selection tools These include interview panels or multiple mini-interviews (MMIs) (Eva et al 2004), personality questionnaires (e.g., the Personal Qualities Assessment [PQA]) (Powis et al 2005) and verbal and non-verbal logic tests (e.g., Undergraduate Medicine and Health Sciences Admission Test, UMAT). The implementation of these types of selection processes imposes significant time and resources costs for both medical schools and applicants, yet robust and consistent evidence regarding the validity of these selection tools in predicting first-year medical undergraduate performance is limited. There is a vital need to for more research on the predictive validity of these selection tools to ensure evidence-based, time- and cost-effective identification of appropriate students into undergraduate medical degrees
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