Sandra Nicholson

How effective are selection methods in medical education? A systematic review

Selection methods used by medical schools should reliably identify whether candidates are likely to be successful in medical training and ultimately become competent clinicians. However, there is little consensus regarding methods that reliably evaluate non‐academic attributes, and longitudinal studies examining predictors of success after qualification are insufficient. This systematic review synthesises the extant research evidence on the relative strengths of various selection methods. We offer a research agenda and identify key considerations to inform policy and practice in the next 50 years.

Comparison of A level and UKCAT performance in students applying to UK medical and dental schools in 2006: cohort study

Objectives To determine whether the UK Clinical Aptitude Test (UKCAT) adds value to the selection process for school leaver applicants to medical and dental school, and in particular whether UKCAT can reduce the socioeconomic bias known to affect A levels. Design Cohort study Setting Applicants to 23 UK medical and dental schools in 2006. Participants 9884 applicants who took the UKCAT in the UK and who achieved at least three passes at A level in their school leaving examinations (53% of all applicants). Main outcome measures Independent predictors of obtaining at least AAB at A level and UKCAT scores at or above the 30th centile for the cohort, for the subsections and the entire test. Results Independent predictors of obtaining at least AAB at A level were white ethnicity (odds ratio 1.58, 95% confidence interval 1.41 to 1.77), professional or managerial background (1.39, 1.22 to 1.59), and independent or grammar schooling (2.26, 2.02 to 2.52) (all P<0.001). Independent predictors of achieving UKCAT scores at or above the 30th centile for the whole test were male sex (odd ratio 1.48, 1.32 to 1.66), white ethnicity (2.17, 1.94 to 2.43), professional or managerial background (1.34, 1.17 to 1.54), and independent or grammar schooling (1.91, 1.70 to 2.14) (all P<0.001). One major limitation of the study was that socioeconomic status was not volunteered by approximately 30% of the applicants. Those who withheld socioeconomic status data were significantly different from those who provided that information, which may have caused bias in the analysis. Conclusions UKCAT was introduced with a high expectation of increasing the diversity and fairness in selection for UK medical and dental schools. This study of a major subgroup of applicants in the first year of operation suggests that it has an inherent favourable bias to men and students from a higher socioeconomic class or independent or grammar schools. However, it does provide a reasonable proxy for A levels in the selection process.

The UKCAT-12 study: educational attainment, aptitude test performance, demographic and socio-economic contextual factors as predictors of first year outcome in a cross-sectional collaborative study of 12 UK medical schools.

BackgroundMost UK medical schools use aptitude tests during student selection, but large-scale studies of predictive validity are rare. This study assesses the United Kingdom Clinical Aptitude Test (UKCAT), and its four sub-scales, along with measures of educational attainment, individual and contextual socio-economic background factors, as predictors of performance in the first year of medical school training.MethodsA prospective study of 4,811 students in 12 UK medical schools taking the UKCAT from 2006 to 2008 as a part of the medical school application, for whom first year medical school examination results were available in 2008 to 2010.ResultsUKCAT scores and educational attainment measures (General Certificate of Education (GCE): A-levels, and so on; or Scottish Qualifications Authority (SQA): Scottish Highers, and so on) were significant predictors of outcome. UKCAT predicted outcome better in female students than male students, and better in mature than non-mature students. Incremental validity of UKCAT taking educational attainment into account was significant, but small. Medical school performance was also affected by sex (male students performing less well), ethnicity (non-White students performing less well), and a contextual measure of secondary schooling, students from secondary schools with greater average attainment at A-level (irrespective of public or private sector) performing less well. Multilevel modeling showed no differences between medical schools in predictive ability of the various measures. UKCAT sub-scales predicted similarly, except that Verbal Reasoning correlated positively with performance on Theory examinations, but negatively with Skills assessments.ConclusionsThis collaborative study in 12 medical schools shows the power of large-scale studies of medical education for answering previously unanswerable but important questions about medical student selection, education and training. UKCAT has predictive validity as a predictor of medical school outcome, particularly in mature applicants to medical school. UKCAT offers small but significant incremental validity which is operationally valuable where medical schools are making selection decisions based on incomplete measures of educational attainment. The study confirms the validity of using all the existing measures of educational attainment in full at the time of selection decision-making. Contextual measures provide little additional predictive value, except that students from high attaining secondary schools perform less well, an effect previously shown for UK universities in general.

Construct-level predictive validity of educational attainment and intellectual aptitude tests in medical student selection: meta-regression of six UK longitudinal studies

BackgroundMeasures used for medical student selection should predict future performance during training. A problem for any selection study is that predictor-outcome correlations are known only in those who have been selected, whereas selectors need to know how measures would predict in the entire pool of applicants. That problem of interpretation can be solved by calculating construct-level predictive validity, an estimate of true predictor-outcome correlation across the range of applicant abilities.MethodsConstruct-level predictive validities were calculated in six cohort studies of medical student selection and training (student entry, 1972 to 2009) for a range of predictors, including A-levels, General Certificates of Secondary Education (GCSEs)/O-levels, and aptitude tests (AH5 and UK Clinical Aptitude Test (UKCAT)). Outcomes included undergraduate basic medical science and finals assessments, as well as postgraduate measures of Membership of the Royal Colleges of Physicians of the United Kingdom (MRCP(UK)) performance and entry in the Specialist Register. Construct-level predictive validity was calculated with the method of Hunter, Schmidt and Le (2006), adapted to correct for right-censorship of examination results due to grade inflation.ResultsMeta-regression analyzed 57 separate predictor-outcome correlations (POCs) and construct-level predictive validities (CLPVs). Mean CLPVs are substantially higher (.450) than mean POCs (.171). Mean CLPVs for first-year examinations, were high for A-levels (.809; CI: .501 to .935), and lower for GCSEs/O-levels (.332; CI: .024 to .583) and UKCAT (mean = .245; CI: .207 to .276). A-levels had higher CLPVs for all undergraduate and postgraduate assessments than did GCSEs/O-levels and intellectual aptitude tests. CLPVs of educational attainment measures decline somewhat during training, but continue to predict postgraduate performance. Intellectual aptitude tests have lower CLPVs than A-levels or GCSEs/O-levels.ConclusionsEducational attainment has strong CLPVs for undergraduate and postgraduate performance, accounting for perhaps 65% of true variance in first year performance. Such CLPVs justify the use of educational attainment measure in selection, but also raise a key theoretical question concerning the remaining 35% of variance (and measurement error, range restriction and right-censorship have been taken into account). Just as in astrophysics, ‘dark matter’ and ‘dark energy’ are posited to balance various theoretical equations, so medical student selection must also have its ‘dark variance’, whose nature is not yet properly characterized, but explains a third of the variation in performance during training. Some variance probably relates to factors which are unpredictable at selection, such as illness or other life events, but some is probably also associated with factors such as personality, motivation or study skills.

Taking context seriously : explaining widening access policy enactments in UK medical schools

Since the 1970s, the UK medical student body has become increasingly diverse in terms of gender, ethnicity and age, but not in socio‐economic background. This variance may be linked to large differences in how individual medical schools interpret and put into practice widening participation (WP) policy. However, attempts to theorise what happens when policy enters practice are neglected in medical education. We aimed to explore the dynamics of policy enactment to give a novel perspective on WP practices across UK medical schools.

The benefits of aptitude testing for selecting medical students

The A level is the most common tool for assessing school leavers applying for higher education, including medicine. If medical school outcome is accurately predicted by A level grades, as described by McManus et al,1 what place, if any, do aptitude tests have in the selection of medical students? Applications for medical school from appropriately highly qualified candidates have increased year on year2 until it has become increasingly difficult to discriminate between candidates with similar A level performance. Most medical schools wish to select future doctors using non-cognitive attributes alongside A levels, but procedures, such as interviewing, are time consuming and labour intensive. An urgent need is to reduce the number of …

A model for widening access into medicine and dentistry: the SAMDA-BL project

Objectives  To assess whether assistance with and/or advice on the UK Universities & Colleges Admissions Service (UCAS) application process by undergraduate medical and dental students increases the offer rate to applicants from educational institutions situated in areas of socio‐economic deprivation for medical and dental courses.

Comparison of the sensitivity of the UKCAT and A Levels to sociodemographic characteristics: a national study

BackgroundThe UK Clinical Aptitude Test (UKCAT) was introduced to facilitate widening participation in medical and dental education in the UK by providing universities with a continuous variable to aid selection; one that might be less sensitive to the sociodemographic background of candidates compared to traditional measures of educational attainment. Initial research suggested that males, candidates from more advantaged socioeconomic backgrounds and those who attended independent or grammar schools performed better on the test. The introduction of the A* grade at A level permits more detailed analysis of the relationship between UKCAT scores, secondary educational attainment and sociodemographic variables. Thus, our aim was to further assess whether the UKCAT is likely to add incremental value over A level (predicted or actual) attainment in the selection process.MethodsData relating to UKCAT and A level performance from 8,180 candidates applying to medicine in 2009 who had complete information relating to six key sociodemographic variables were analysed. A series of regression analyses were conducted in order to evaluate the ability of sociodemographic status to predict performance on two outcome measures: A level ‘best of three’ tariff score; and the UKCAT scores.ResultsIn this sample A level attainment was independently and positively predicted by four sociodemographic variables (independent/grammar schooling, White ethnicity, age and professional social class background). These variables also independently and positively predicted UKCAT scores. There was a suggestion that UKCAT scores were less sensitive to educational background compared to A level attainment. In contrast to A level attainment, UKCAT score was independently and positively predicted by having English as a first language and male sex.ConclusionsOur findings are consistent with a previous report; most of the sociodemographic factors that predict A level attainment also predict UKCAT performance. However, compared to A levels, males and those speaking English as a first language perform better on UKCAT. Our findings suggest that UKCAT scores may be more influenced by sex and less sensitive to school type compared to A levels. These factors must be considered by institutions utilising the UKCAT as a component of the medical and dental school selection process.

Reasons selectors give for accepting and rejecting medical applicants before interview.

Medical Education 2011: 45: 298–307

Widening access in selection using situational judgement tests: Evidence from the UKCAT

Widening access promotes student diversity and the appropriate representation of all demographic groups. This study aims to examine diversity‐related benefits of the use of situational judgement tests (SJTs) in the UK Clinical Aptitude Test (UKCAT) in terms of three demographic variables: (i) socio‐economic status (SES); (ii) ethnicity, and (iii) gender.