Socio-economic predictors of performance in the Undergraduate Medicine and Health Sciences Admission Test (UMAT)
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- 作者：Ian B Puddey (1)
Annette Mercer (1) - 刊名：BMC Medical Education
- 出版年：2013
- 出版时间：December 2013
- 年：2013
- 卷：13
- 期：1
- 全文大小：289 KB
- 参考文献：1. Hunt M, Pywell S, Le L, Lay D: / UMAT2012. Report on the 2012 Undergraduate Medicine and Health Sciences Admission Test. Australian: Australian Council for Education Research; 2012.
2. Nicholson S: The benefits of aptitude testing for selecting medical students. / BMJ 2005, 331:559-60. CrossRef
3. Wilson IG, Flynn E, Roberts C, Crotty B, Griffin B: Only the best: medical student selection in Australia. / MJA 2012, 196:357-57.
4. Tiffin PA, Dowell JS, McLachlan JC: Widening access to medical education for under-represented socioeconomic groups: modelling the impact of the UKCAT in the 2009 cohort. / BMJ 2012, 344:e1805. CrossRef
5. Puddey IB, Mercer A, Carr SE, Louden W: Potential influence of selection criteria on the demographic composition of students in an Australian medical school. / BMC Med Educ 2011, 11:97. CrossRef
6. BMA, Equality and Diversity Committee: Equality and diversity in UK medical schools. 2009.
7. Mitchell CJ, Shulruf B, Poole PJ: Relationship between decile score of secondary school, the size of town of origin and career intentions of New Zealand medical students. / J Primary Health Care 2010, 2:183-89.
8. Ferguson E, James D, Yates J, Lawrence C: Predicting who applies to study medicine: implication for diversity in UK medical schools. / Med Teach 2012, 34:382-1. CrossRef
9. Powis D, Hamilton J, McManus IC: Widening access by changing the criteria for selecting medical students. / Teach Teach Ed 2007, 23:1235-5. CrossRef
10. Powis D, Hamilton J, Gordon J: Are graduate entry programmes the answer to recruiting and selecting tomorrow’s doctors? / Med Educ 2004, 38:1147-3. CrossRef
11. O’Neill L, Vonsild MC, Wallstedt B, Dornan T: Admission criteria and diversity in medical school. / Med Educ 2013, 47:557-1. CrossRef
12. Reiter HI, Lockyer J, Ziola B, Courneya CA, Eva K: Should efforts in favour of medical student diversity be focused during admissions or further upstream? / Acad Med 2012, 87:443-. CrossRef
13. James D, Yates J, Nicholson S: Comparison of A level and UKCAT performance in students applying to UK medical and dental schools in 2006: cohort study. / BMJ 2010, 349:c478. CrossRef
14. Griffin B, Carless S, Wilson I: The effect of commercial coaching on selection test performance. / Med Teach 2013, 35:295-00. CrossRef
15. Edwards D, Friedman T, Coates H: / Establishing the criterion validity of UMAT: A multi-cohort study of Australian medical students. Australian: For the UMAT Consortium; 2011.
16. Australian Bureau of Statistics: 2039.0 - Information paper: an Introduction to Socio-Economic Indexes for Areas (SEIFA). 2006. http://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/2039.0Main+Features12006?OpenDocument
17. ABS series 1267.0 - Australian Standard Classification of Languages (ASCL) 2011. http://www.abs.gov.au/ausstats/abs@.nsf/mf/1267.0
18. Measuring Remoteness: Accessibility/Remoteness Index of Australia (ARIA) revised edition. Occasional papers: new series number 14 2001. http://www.health.gov.au/internet/main/publishing.nsf/Content/healthhistoricpubs-hfsocc-ocpanew14a.htm
19. Mercer A, Chiavaroli N, UMAT: / A validity study. A review of the underlying constructs and an analysis of the content of the undergraduate medicine and health sciences admission test. Australian: A report prepared for the UMAT Consortium; 2006.
20. Powis D, James D, Ferguson E: Demographic and socio-economic associations with academic attainment (UCAS tariff scores) in applicants to medical school. / Med Educ 2007, 41:242-. CrossRef
21. Mathers J, Sitch A, Marsh JL, Parry J: Widening access to medical education for under-represented socioeconomic groups: population based cross sectional analysis of UK data, 2002-. / BMJ 2011, 342:d918. CrossRef
22. Seyan K, Greenhalgh T, Dorling D: The standardised admissions ratio for measuring widening participation in medical schools: analysis of UK medical school admissions by ethnicity, socioeconomic status, and sex. / BMJ 2004, 328:1545-. CrossRef
23. Poole PJ, Moriarty HJ, Wearn AM, Wilkinson TJ, Weir JM: Medical student selection in New Zealand: looking to the future. / NZ Med J 2009, 122:88-00.
24. McGaghie WC, Downing SM, Kubilius R: What is the impact of commercial test preparation courses on medical examination performance. / Teach Learn Med 2004, 16:202-11. CrossRef
25. Wilkinson TM, Wilkinson TJ: Preparation courses for a medical admissions test: effectiveness contrasts with opinion. / Med Educ 2013, 47:417-24. CrossRef
26. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1472-6920/13/155/prepub - 作者单位：Ian B Puddey (1)
Annette Mercer (1)
1. Faculty of Medicine, Dentistry and Health Sciences, University of Western Australia, 35 Stirling Hwy, Crawley, WA, 6009, Australia - ISSN：1472-6920
文摘
Background Entry from secondary school to Australian and New Zealand undergraduate medical schools has since the late 1990’s increasingly relied on the Undergraduate Medicine and Health Sciences Admission Test (UMAT) as one of the selection factors. The UMAT consists of 3 sections -logical reasoning and problem solving (UMAT-1), understanding people (UMAT-2) and non-verbal reasoning (UMAT-3). One of the goals of using this test has been to enhance equity in the selection of students with the anticipation of an increase in the socioeconomic diversity in student cohorts. However there has been limited assessment as to whether UMAT performance itself might be influenced by socioeconomic background. Methods Between 2000 and 2012, 158,909 UMAT assessments were completed. From these, 118,085 cases have been identified where an Australian candidate was sitting for the first time during that period. Predictors of the total UMAT score, UMAT-1, UMAT-2 and UMAT-3 scores were entered into regression models and included gender, age, school type, language used at home, deciles for the Index of Relative Socioeconomic Advantage and Disadvantage score, the Accessibility/Remoteness Index of Australia (ARIA), self-identification as being of Aboriginal or Torres Strait Islander origin (ATSI) and current Australian state or territory of abode. Results A lower UMAT score was predicted by living in an area of relatively higher social disadvantage and lower social advantage. Other socioeconomic indicators were consistent with this observation with lower scores in those who self-identified as being of ATSI origin and higher scores evident in those from fee-paying independent school backgrounds compared to government schools. Lower scores were seen with increasing age, female gender and speaking any language other than English at home. Divergent effects of rurality were observed, with increased scores for UMAT-1 and UMAT-2, but decreasing UMAT-3 scores with increasing ARIA score. Significant state-based differences largely reflected substantial socio-demographic differences across Australian states and territories. Conclusions Better performance by Australian candidates in the UMAT is linked to an increase in socio-economic advantage and reduced disadvantage.This observation provides a firm foundation for selection processes at medical schools in Australia that have incorporated affirmative action pathways to quarantine places for students from areas of socio-economic disadvantage.