Use of UKCAT scores in student selection by UK medical schools, 2006-2010

<p>Abstract</p> <p>Background</p> <p>The United Kingdom Clinical Aptitude Test (UKCAT) is a set of cognitive tests introduced in 2006, taken annually before application to medical school. The UKCAT is a test of aptitude and not acquired knowledge and as such the results give medical schools a standardised and objective tool that all schools could use to assist their decision making in selection, and so provide a fairer means of choosing future medical students.</p> <p>Selection of students for UK medical schools is usually in three stages: assessment of academic qualifications, assessment of further qualities from the application form submitted via UCAS (Universities and Colleges Admissions Service) leading to invitation to interview, and then selection for offer of a place. Medical schools were informed of the psychometric qualities of the UKCAT subtests and given some guidance regarding the interpretation of results. Each school then decided how to use the results within its own selection system.</p> <p>Methods</p> <p>Annual retrospective key informant telephone interviews were conducted with every UKCAT Consortium medical school, using a pre-circulated structured questionnaire. The key points of the interview were transcribed, 'member checked' and a content analysis was undertaken.</p> <p>Results</p> <p>Four equally popular ways of using the test results have emerged, described as Borderline, Factor, Threshold and Rescue methods. Many schools use more than one method, at different stages in their selection process. Schools have used the scores in ways that have sought to improve the fairness of selection and support widening participation. Initially great care was taken not to exclude any applicant on the basis of low UKCAT scores alone but it has been used more as confidence has grown.</p> <p>Conclusions</p> <p>There is considerable variation in how medical schools use UKCAT, so it is important that they clearly inform applicants how the test will be used so they can make best use of their limited number of applications.</p

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

Background: Measures 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. Methods: Construct-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. Results: Meta-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. Conclusions: Educational 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

Predictive validity of the UK clinical aptitude test in the final years of medical school:a prospective cohort study

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Free text adversity statements as part of a contextualised admissions process:a qualitative analysis

Abstract Background Medical schools globally are encouraged to widen access and participation for students from less privileged backgrounds. Many strategies have been implemented to address this inequality, but much still needs to be done to ensure fair access for all. In the literature, adverse circumstances include financial issues, poor educational experience and lack of professional-status parents. In order to take account of adverse circumstances faced by applicants, The University of Dundee School of Medicine offers applicants the opportunity to report circumstances which may have resulted in disadvantage. Applicants do this by completing a free text statement, known as an ‘adversity statement’, in addition to the other application information. This study analysed adversity statements submitted by applicants during two admissions cycles. Analysis of content and theme was done to identify the information applicants wished to be taken into consideration, and what range of adverse circumstances individuals reported. Methods This study used a qualitative approach with thematic analysis to categorise the adversity statements. The data was initially analysed to create a coding framework which was then applied to the whole data set. Each coded segment was then analysed for heterogeneity and homogeneity, segments merged into generated themes, or to create sub-themes. Results The data set comprised a total of 384 adversity statements. These showed a wide range of detail involving family, personal health, education and living circumstances. Some circumstances, such as geographical location, have been identified and explored in previous research, while others, such as long term health conditions, have had less attention in the literature. The degree of impact, the length of statement and degree of detail, demonstrated wide variation between submissions. Conclusions This study adds to the debate on best practice in contextual admissions and raises awareness of the range of circumstances and impact applicants wish to be considered. The themes which emerged from the data included family, school, personal health, and geographical location issues. Descriptions of the degree of impact that an adverse circumstance had on educational or other attainment was found to vary substantially from statements indicating minor, impact through to circumstances stated as causing major impact

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

Most 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

Predictors of Fitness to Practise Declarations in UK Medical Undergraduates

Background: Misconduct during medical school predicts subsequent fitness to practise (FtP) events in doctors, but relatively little is known about which factors are associated with such issues during undergraduate education. This study exploits the newly created UK medical education database (UKMED), with the aim of identifying predictors of conduct or health-related issues that could potentially impair FtP. The findings would have implications for policies related to both the selection and support of medical students. Methods: Data were available for 14,379 students obtaining provisional registration with the General Medical Council who started medical school in 2007 and 2008. FtP declarations made by students were available, as were various educational and demographic predictor variables, including self-report ‘personality measures’ for students who participated in UK Clinical Aptitude Test (UKCAT) pilot studies. Univariable and multivariable logistic regression models were developed to evaluate the predictors of FtP declarations. Results: Significant univariable predictors (p < 0.05) for conduct-related declarations included male gender, white ethnicity and a non-professional parental background. Male gender (OR 3.07) and higher ‘self-esteem’ (OR 1.45) were independently associated with an increased risk of a conduct issue. Female gender, a non-professional background, and lower self-reported ‘confidence’ were, among others, associated with increased odds of a health-related declaration. Only ‘confidence’ was a significant independent predictor of a health declaration (OR 0.69). Female gender, higher UKCAT score, a non-professional background and lower ‘confidence’ scores were significant predictors of reported depression, and the latter two variables were independent predictors of declared depression. Conclusions: White ethnicity and UK nationality were associated with increased odds of both conduct and health-related declarations, as were certain personality traits. Students from non-professional backgrounds may be at increased risk of depression and therefore could benefit from targeted support. The small effect sizes observed for the ‘personality measures’ suggest they would offer little potential benefit for selection, over and above those measures already in use