Undergraduate Medicine And Health Sciences Admission Test Research Articles

The efficacy of medical student selection tools in Australia and New Zealand.

To estimate the efficacy of selection tools employed by medical schools for predicting the binary outcomes of completing or not completing medical training and passing or failing a key examination; to investigate the potential usefulness of selection algorithms that do not allow low scores on one tool to be compensated by higher scores on other tools. Data from four consecutive cohorts of students (3378 students, enrolled 2007-2010) in five undergraduate medical schools in Australia and New Zealand were analysed. Predictor variables were student scores on selection tools: prior academic achievement, Undergraduate Medicine and Health Sciences Admission Test (UMAT), and selection interview. Outcome variables were graduation from the program in a timely fashion, or passing the final clinical skills assessment at the first attempt. Optimal selection cut-scores determined by discriminant function analysis for each selection tool at each school; efficacy of different selection algorithms for predicting student outcomes. For both outcomes, the cut-scores for prior academic achievement had the greatest predictive value, with medium to very large effect sizes (0.44-1.22) at all five schools. UMAT scores and selection interviews had smaller effect sizes (0.00-0.60). Meeting one or more cut-scores was associated with a significantly greater likelihood of timely graduation in some schools but not in others. An optimal cut-score can be estimated for a selection tool used for predicting an important program outcome. A "sufficient evidence" selection algorithm, founded on a non-compensatory model, is feasible, and may be useful for some schools.

The relative predictive value of undergraduate versus graduate selection tools in two Australian medical schools

Context: Monash University and the University of Western Australia admit both school-leavers and graduates into their Bachelor of Medicine and Bachelor of Surgery (MBBS) courses. The Undergraduate Medicine and Health Sciences Admission Test (UMAT) and the Graduate Medical Schools Admissions Test (GAMSAT) are used for selection, along with an academic score and an interview score. The aim of this study was to compare the relative predictive validity of the selected components in the two entry streams, particularly UMAT versus GAMSAT.Methods: Aggregated scores for course outcomes were calculated in the categories of knowledge, clinical and total scores, at four-time points. A path analysis was conducted based on multivariate regressions with model constraint parameters defined across the outcome variables to investigate change over time.Results: Academic scores were the strongest predictors of knowledge scores and end of course results. Interview scores had a small positive increasing effect, being stronger for clinical than knowledge outcomes. The effect size for GAMSAT was greater than for UMAT.Conclusions: Aptitude tests and interview scores added small but significant incremental predictive value to previous academic achievement. GAMSAT showed larger predictive value on outcomes than UMAT, for which one section (UMAT 3) had a negative effect.

Have we got the selection process right? The validity of selection tools for predicting academic performance in the first year of undergraduate medicine.

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.

On the validity of repeated assessments in the UMAT, a high-stakes admissions test.

The possibility that the validity of assessment is compromised by repeated sittings of highly competitive and high profile selection tests has been documented and is of concern to stake-holders. An illustrative example is the Undergraduate Medicine and Health Sciences Admission Test (UMAT) used by some medical and dental courses in Australia and New Zealand. The proficiencies of all applicants who sat the UMAT from one to four sittings between 2006 and 2012 were estimated on the same metric using the probabilistic Rasch model. A fit index characterising each profile's degree of conformity to the model was also calculated. Confirming expectations, mean proficiencies increased with repeated sittings on all three UMAT scales with the greatest difference (which was nevertheless relatively small) between the first two sittings. The fit index showed that the increases in proficiency estimates arose from additional easier items being answered correctly on repeated sittings rather than additional more difficult ones, suggesting that improvements are not on the substantive construct of the variable of assessment but in skills in answering the questions. Although strategies for dealing with the increase in proficiency estimates on repeated sittings could be canvassed, these results suggest that the validity of results on repeated sittings was not compromised. Accordingly, it might be concluded that although particular individuals might improve substantially between sittings, any validity is not likely to be compromised with the possibility that for some applicants, the second sitting might be the most valid.

Medical student selection criteria as predictors of intended rural practice following graduation.

BackgroundRecruiting medical students from a rural background, together with offering them opportunities for prolonged immersion in rural clinical training environments, both lead to increased participation in the rural workforce after graduation. We have now assessed the extent to which medical students’ intentions to practice rurally may also be predicted by either medical school selection criteria and/or student socio-demographic profiles.MethodsThe study cohort included 538 secondary school-leaver entrants to The University of Western Australia Medical School from 2006 to 2011. On entry they completed a questionnaire indicating intention for either urban or rural practice following graduation. Selection factors (standardised interview score, percentile score from the Undergraduate Medicine and Health Sciences Admission Test (UMAT) and prior academic performance (Australian Tertiary Admissions Rank), together with socio-demographic factors (age, gender, decile for the Index of Relative Socioeconomic Advantage and Disadvantage (IRSAD) and an index of rurality) were examined in relation to intended rural or urban destination of practice.ResultsIn multivariate logistic regression, students from a rural background had a nearly 8-fold increase in the odds of intention to practice rurally after graduation compared to those from urban backgrounds (OR 7.84, 95% CI 4.10, 14.99, P < 0.001). Those intending to be generalists rather than specialists had a more than 4-fold increase in the odds of intention to practice rurally (OR 4.36, 95% CI 1.69, 11.22, P < 0.001). After controlling for these 2 factors, those with rural intent had significantly lower academic entry scores (P = 0.002) and marginally lower interview scores (P = 0.045). UMAT percentile scores were no different. Those intending to work in a rural location were also more likely to be female (OR 1.93, 95% CI 1.08, 3.48, P = 0.027), to come from the lower eight IRSAD deciles (OR 2.52, 95% CI 1.47, 4.32, P = 0.001) and to come from Government vs independent schools (OR 2.02, 95% CI 1.15, 3.55, P = 0.015).ConclusionsVery high academic scores generally required for medical school entry may have the unintended consequence of selecting fewer graduates interested in a rural practice destination. Increased efforts to recruit students from lower socioeconomic backgrounds may be beneficial in terms of an ultimate intended rural practice destination.Electronic supplementary materialThe online version of this article (doi:10.1186/1472-6920-14-218) contains supplementary material, which is available to authorized users.

Predictive validity of a new integrated selection process for medical school admission.

BackgroundThis 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.MethodAdmission 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.ResultsUAI 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.ConclusionResults 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.

Practice effects in medical school entrance testing with the undergraduate medicine and health sciences admission test (UMAT)

BackgroundThe UMAT is widely used for selection into undergraduate medical and dental courses in Australia and New Zealand (NZ). It tests aptitudes thought to be especially relevant to medical studies and consists of 3 sections – logical reasoning and problem solving (UMAT-1), understanding people (UMAT-2) and non-verbal reasoning (UMAT-3). A substantial proportion of all candidates re-sit the UMAT. Re-sitting raises the issue as to what might be the precise magnitude and determinants of any practice effects on the UMAT and their implications for equity in subsequent selection processes.MethodsBetween 2000 and 2012, 158,909 UMAT assessments were completed. From these, 135,833 cases were identified where a candidate had sat once or more during that period with 117,505 cases (86.5%) having sat once, 14,739 having sat twice (10.9%), 2,752 thrice (2%) and 837, 4 or more times (0.6%). Subsequent analyses determined predictors of multiple re-sits as well as the magnitude and socio-demographic determinants of any practice effects.ResultsIncreased likelihood of re-sitting the UMAT twice or more was predicted by being male, of younger age, being from a non-English language speaking background and being from NZ and for Australian candidates, being urban rather than rurally based. For those who sat at least twice, the total UMAT score between a first and second attempt improved by 10.7 ± 0.2 percentiles, UMAT-1 by 8.3 ± 0.2 percentiles, UMAT-2 by 8.3 ± 0.2 percentiles and UMAT-3 by 7.7 ± 0.2 percentiles. An increase in total UMAT percentile score on re-testing was predicted by a lower initial score and being a candidate from NZ rather than from Australia while a decrease was related to increased length of time since initially sitting the test, older age and non-English language background.ConclusionsRe-sitting the UMAT augments performance in each of its components together with the total UMAT percentile score. Whether this increase represents just an improvement in performance or an improvement in understanding of the variables and therefore competence needs to be further defined. If only the former, then practice effects may be introducing inequity in student selection for medical or dental schools in Australia or NZ.

The impact of preparatory activities on medical school selection outcomes: a cross-sectional survey of applicants to the university of Adelaide medical school in 2007

BackgroundSelection into medical school is highly competitive with more applicants than places. Little is known about the preparation that applicants undertake for this high stakes process. The study aims to determine what preparatory activities applicants undertake and what difficulties they encounter for each stage of the application process to medical school and in particular what impact these have on the outcome.MethodsA cross-sectional survey of 1097 applicants who applied for a place in the University of Adelaide Medical School in 2007 and participated in the UMAT (Undergraduate Medicine and Health Sciences Admission Test) and oral assessment components of the selection process. The main outcome measures were an offer of an interview and offer of a place in the medical school and were analysed using logistic regression.ResultsThe odds of a successful outcome increased with each additional preparatory activity undertaken for the UMAT (odds ratio 1.22, 95% confidence interval 1.11 to 1.33; P < 0.001) and the oral assessment (1.36, 1.19 to 1.55; P < 0.001) stage of selection. The UMAT preparatory activities associated with the offer of an interview were attendance of a training course by a private organisation (1.75, 1.35 to 2.27: P < 0.001), use of online services of a private organisation (1.58, 1.23 to 2.04; P < 0.001), and familiarising oneself with the process (1.52, 1.15 to 2.00; p = 0.021). The oral assessment activities associated with an offer of a place included refining and learning a personal resume (9.73, 2.97 to 31.88; P < 0.001) and learning about the course structure (2.05, 1.29 to 3.26; P = 0.022).For the UMAT, applicants who found difficulties with learning for this type of test (0.47, 0.35 to 0.63: P < 0.001), with the timing of UMAT in terms of school exams (0.48, 0.5 to 0.66; P < 0.001) and with the inability to convey personal skills with the UMAT (0.67, 0.52 to 0.86; P = 0.026) were significantly less likely to be offered an interview.ConclusionsMedical schools make an enormous effort to undertake a selection process that is fair and equitable and which selects students most appropriate for medical school and the course they provide. Our results indicate that performance in the selection processes can be improved by training. However, if these preparatory activities may be limited to those who can access them, the playing field is not even and increasing equity of access to medical schools will not be achieved.

Socio-economic predictors of performance in the Undergraduate Medicine and Health Sciences Admission Test (UMAT)

BackgroundEntry 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.MethodsBetween 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.ResultsA 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.ConclusionsBetter 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.

Shaping the future medical workforce: take care with selection tools

Medical school selection is a first step in developing a general practice workforce. To determine the relationship between medical school selection scores and intention to pursue a career in general practice. A longitudinal cohort study of students selected in 2006 and 2007 for The University of Auckland medical programme, who completed an exit survey on career intentions. Students are ranked for selection into year 2 of a six-year programme by combining grade point average from prior university achievement (60%), interview (25%) and Undergraduate Medicine and Health Sciences Admission Test (UMAT) scores (15%). The main outcome measure was level of interest in general practice at exit. Logistic regression assessed whether any demographic variables or admission scores predicted a 'strong' interest in general practice. None of interview scores, grade point average, age, gender, or entry pathway predicted a 'strong' interest in general practice. Only UMAT scores differentiated between those with a 'strong' interest versus those with 'some' or 'no' interest, but in an inverse fashion. The best predictor of a 'strong' interest in general practice was a low UMAT score of between 45 and 55 on all three UMAT sections (OR 3.37, p=0.020). Yet, the academic scores at entry of students with these UMAT scores were not lower than those of their classmates. Setting inappropriately high cut-points for medical school selection may exclude applicants with a propensity for general practice. These findings support the use of a wider lens through which to view medical school selection tools.

Comparison of UMAT scores and GPA in prediction of performance in medical school: a national study

Medical schools continue to seek robust ways to select students with the greatest aptitude for medical education, training and practice. Tests of general cognition are used in combination with markers of prior academic achievement and other tools, although their predictive validity is unknown. This study compared the predictive validity of the Undergraduate Medicine and Health Sciences Admission Test (UMAT), the admission grade point average (GPA), and a combination of both, on outcomes in all years of two medical programmes. Subjects were students (n = 1346) selected since 2003 using UMAT scores and attending either of New Zealand's two medical schools. Regression models incorporated demographic data, UMAT scores, admission GPA and performance on routine assessments. Despite the different weightings of UMAT used in selection at the two institutions and minor variations in student demographics and programmes, results across institutions were similar. The net predictive power of admission GPA was highest for outcomes in Years 2 and 5 of the 6-year programme, accounting for 17-35% of the variance; UMAT score accounted for < 10%. The highest predictive power of the UMAT score was 9.9% for a Year 5 written examination. Combining UMAT score with admission GPA improved predictive power slightly across all outcomes. Neither UMAT score nor admission GPA predicted outcomes in the final trainee intern year well, although grading bands for this year were broad and numbers smaller. The ability of the general cognitive test UMAT to predict outcomes in major assessments within medical programmes is relatively minor in comparison with that of the admission GPA, but the UMAT score adds a small amount of predictive power when it is used in combination with the GPA. However, UMAT scores may predict outcomes not studied here, which underscores the need for further validation studies in a range of settings.

Does performance in selection processes predict performance as a dental student?

This study investigated associations between the performance of dental students in each of the three components of the selection procedure [academic average, Undergraduate Medicine and Health Sciences Admission Test (UMAT) and structured interview], socio-demographic characteristics and their academic success in an undergraduate dental surgery programme. Longitudinal review of admissions data relating to students entering dental education at the University of Otago, New Zealand, between 2004 and 2009 was compared with academic performance throughout the dental programme. After controlling for variables, pre-admission academic average, UMAT scores and interview performance did not predict performance as a dental student. Class place in second year, however, was a strong predictor of class place in final year. Multivariate analysis demonstrated that the best predictors of higher class placement in the final year were New Zealand European ethnicity and domestic (rather than international) student status. Other socio-demographic characteristics were not associated with performance. These interim findings provide a sound base for the ongoing study. The study found important socio-demographic differences in pre-admission test scores, but those scores did not predict performance in the dental programme, whether measured in second year or in final year.

Predictive validity of the Undergraduate Medicine and Health Sciences Admission Test for medical students’ academic performance

To determine the predictive validity of the Undergraduate Medicine and Health Sciences Admission Test (UMAT) for academic performance at university. We studied all 339 students who entered medical study at the School of Medicine, University of Queensland, directly from high school, between 2005 and 2009. UMAT scores before entry compared with grade point averages (GPAs) during university study. Mean overall UMAT score at entry was 60/100 and mean GPA during university study was 6.1 (range, 1-7), with a correlation coefficient of 0.15 (P = 0.005). This relationship existed only in the first year of university study. For UMAT Section 1 score, the correlation coefficient was 0.14 (P = 0.01); for UMAT Section 2, the correlation coefficient was 0.06 (P = 0.29); and for UMAT Section 3, the correlation coefficient was 0.09 (P = 0.11). UMAT overall score for men (60.2) and women (59.8), and GPA for men (6.1) and women (6.2) were similar. However, men performed better in Section 1 (mean score 61.6 v 61; P = 0.05) and Section 3 (63.2 v 60.7; P < 0.001), whereas women performed better in Section 2 (58.5 v 55.8; P = 0.009). In multivariate analysis, only correlation between GPA and UMAT Section 1 score remained significant but was weak and lasted for 1 year of university study. Our findings suggest that UMAT has limited predictive validity for academic performance.

Emotional intelligence in medical students: does it correlate with selection measures?

Much attention and emphasis are placed on the selection of medical students. Although selection measures have been validated in the literature, it is not yet known whether high scores at selection are indicative of high levels of interpersonal aptitude. Emotional intelligence (EI) is reported to be a predictor of the interpersonal and communications skills medical schools are looking for in applicants. This study describes EI scores in medical students and explores correlations between EI and selection scores at the University of Western Australia. Senior medical students from a 6-year undergraduate curriculum completed the online MSCEIT (Mayer-Salovey-Caruso Emotional Intelligence Test) survey. Scores for EI were described and correlations between EI and Undergraduate Medicine and Health Sciences Admission Test (UMAT), Interview and Tertiary Entrance Rank (TER) scores were analysed. Mean scores of the 177 respondents (58%) reflected the normal distribution of scores (mean 98, standard deviation [SD] 15.0) in the general population. Males had higher EI scores than females and Asian students demonstrated higher EI Total and branch scores than White students. The highest and lowest EI scores were obtained for the branches Understanding Emotions (mean 110, SD 19.0) and Perceiving Emotions (mean 94, SD 15.6), respectively. No significant correlations were found between EI Total or EI branch scores and any of the selection scores (UMAT, TER and Interview). This study offers information that can be used to compare the EI scores of medical students with those of other health professionals. No relationship was identified between cognition (measured by the UMAT) and skill (measured by the MSCEIT) in the interpersonal domain and EI. Further studies are required to explore whether UMAT Section 2 is measuring EI, if there are associations between EI and academic performance and if EI can be used to predict the performance of junior doctors.

Does practice make perfect? The effect of coaching and retesting on selection tests used for admission to an Australian medical school

To assess the practice effects from coaching on the Undergraduate Medicine and Health Sciences Admission Test (UMAT), and the effect of both coaching and repeat testing on the Multiple Mini Interview (MMI). Observational study based on a self-report survey of a cohort of 287 applicants for entry in 2008 to the new School of Medicine at the University of Western Sydney. Participants were asked about whether they had attended UMAT coaching or previous medical school interviews, and about their perceptions of the relative value of UMAT coaching, attending other interviews or having a "practice run" with an MMI question. UMAT and MMI results for participants were compared with respect to earlier attempts at the test, the degree of similarity between questions from one year to the next, and prior coaching. Effect of coaching on UMAT and MMI scores; effect of repeat testing on MMI scores; candidates' perceptions of the usefulness of coaching, previous interview experience and a practice run on the MMI. 51.4% of interviewees had attended coaching. Coached candidates had slightly higher UMAT scores on one of three sections of the test (non-verbal reasoning), but this difference was not significant after controlling for Universities Admission Index, sex and age. Coaching was ineffective in improving MMI scores, with coached candidates actually having a significantly lower score on one of the nine interview tasks ("stations"). Candidates who repeated the MMI in 2007 (having been unsuccessful at their 2006 entry attempt) did not improve their score on stations that had new content, but showed a small increase in scores on stations that were either the same as or similar to previous stations. A substantial number of Australian medical school applicants attend coaching before undertaking entry selection tests, but our study shows that coaching does not assist and may even hinder their performance on an MMI. Nevertheless, as practice on similar MMI tasks does improve scores, tasks should be rotated each year. Further research is required on the predictive validity of the UMAT, given that coaching appeared to have a small positive effect on the non-verbal reasoning component of the test.