How well do selection tools predict performance later in a medical programme?

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dc.contributor.author Shulruf, Boaz en
dc.contributor.author Poole, P en
dc.contributor.author Wang, GY en
dc.contributor.author Rudland, J en
dc.contributor.author Wilkinson, T en
dc.date.accessioned 2012-02-23T02:16:10Z en
dc.date.issued 2011 en
dc.identifier.citation Advances in Health Sciences Education 1-12 2011 en
dc.identifier.issn 1382-4996 en
dc.identifier.uri http://hdl.handle.net/2292/11820 en
dc.description.abstract The choice of tools with which to select medical students is complex and controversial. This study aimed to identify the extent to which scores on each of three admission tools (Admission GPA, UMAT and structured interview) predicted the outcomes of the first major clinical year (Y4) of a 6 year medical programme. Data from three student cohorts (n = 324) were analysed using regression analyses. The Admission GPA was the best predictor of academic achievement in years 2 and 3 with regression coefficients (B) of 1.31 and 0.9 respectively (each P\0.001). Furthermore, Admission GPA predicted whether or not a student was likely to earn ‘Distinction’ rather than ‘Pass’ in year 4. In comparison, UMAT and interview showed low predictive ability for any outcomes. Interview scores correlated negatively with those on the other tools. None of the tools predicted failure to complete year 4 on time, but only 3% of students fell into this category. Prior academic achievement remains the best measure of subsequent student achievement within a medical programme. Interview scores have little predictive value. Future directions include longer term studies of what UMAT predicts, and of novel ways to combine selection tools to achieve the optimum student cohort. en
dc.publisher Springer en
dc.relation.ispartofseries Advances in Health Sciences Education en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. Details obtained from: http://www.sherpa.ac.uk/romeo/issn/1382-4996/ en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.title How well do selection tools predict performance later in a medical programme? en
dc.type Journal Article en
dc.identifier.doi 10.1007/s10459-011-9324-1 en
pubs.begin-page 1 en
dc.rights.holder Copyright: Springer en
pubs.end-page 12 en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.subtype Article en
pubs.elements-id 228331 en
dc.identifier.eissn 1573-1677 en
pubs.record-created-at-source-date 2012-02-21 en


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