Predictive validity of a new integrated selection process for medical school admission
1 Faculty of Medicine, University of New South Wales, Sydney, Australia
2 School of Public Health & Community Medicine, Faculty of Medicine, University of New South Wales, Sydney, Australia
3 School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia
4 South Western Sydney Clinical School, Faculty of Medicine, University of New South Wales, Sydney, Australia
5 Department of Rheumatology, Liverpool Hospital, Locked Bag 7103, Liverpool BC NSW 1871, Australia
BMC Medical Education 2014, 14:86 doi:10.1186/1472-6920-14-86Published: 23 April 2014
This paper is an evaluation of an integrated selection process utilising previous academic achievement [Universities Admission Index (UAI)], a skills test [Undergraduate Medicine and Health Sciences Admission Test (UMAT)], and a structured interview, introduced (in its entirety) in 2004 as part of curriculum reform of the undergraduate Medicine Program at the University of New South Wales (UNSW), Australia. Demographic measures of gender, country of birth, educational background and rurality are considered.
Admission scores and program outcomes of 318 students enrolled in 2004 and 2005 were studied. Regression analyses were undertaken to determine whether selection scores predicted overall, knowledge-based and clinical-based learning outcomes after controlling for demographics.
UAI attained the highest values in predicting overall and knowledge-based outcomes. The communication dimension of the interview achieved similar predictive values as UAI for clinical-based outcomes, although predictive values were relatively low. The UMAT did not predict any performance outcome. Female gender, European/European-derived country of birth and non-rurality were significant predictors independent of UAI scores.
Results indicate promising validity for an integrated selection process introduced for the Medicine Program at UNSW, with UAI and interview predictive of learning outcomes. Although not predictive, UMAT may have other useful roles in an integrated selection process. Further longitudinal research is proposed to monitor and improve the validity of the integrated student selection process.