The academic backbone: longitudinal continuities in educational achievement from secondary school and medical school to MRCP(UK) and the specialist register in UK medical students and doctors

Background: Selection of medical students in the UK is still largely based on prior academic achievement, although doubts have been expressed as to whether performance in earlier life is predictive of outcomes later in medical school or post-graduate education. This study analyses data from five longitudinal studies of UK medical students and doctors from the early 1970s until the early 2000s. Two of the studies used the AH5, a group test of general intelligence (that is, intellectual aptitude). Sex and ethnic differences were also analyzed in light of the changing demographics of medical students over the past decades. Methods: Data from five cohort studies were available: the Westminster Study (began clinical studies from 1975 to 1982), the 1980, 1985, and 1990 cohort studies (entered medical school in 1981, 1986, and 1991), and the University College London Medical School (UCLMS) Cohort Study (entered clinical studies in 2005 and 2006). Different studies had different outcome measures, but most had performance on basic medical sciences and clinical examinations at medical school, performance in Membership of the Royal Colleges of Physicians (MRCP(UK)) examinations, and being on the General Medical Council Specialist Register. Results: Correlation matrices and path analyses are presented. There were robust correlations across different years at medical school, and medical school performance also predicted MRCP(UK) performance and being on the GMC Specialist Register. A-levels correlated somewhat less with undergraduate and post-graduate performance, but there was restriction of range in entrants. General Certificate of Secondary Education (GCSE)/O-level results also predicted undergraduate and post-graduate outcomes, but less so than did A-level results, but there may be incremental validity for clinical and post-graduate performance. The AH5 had some significant correlations with outcome, but they were inconsistent. Sex and ethnicity also had predictive effects on measures of educational attainment, undergraduate, and post-graduate performance. Women performed better in assessments but were less likely to be on the Specialist Register. Non-white participants generally underperformed in undergraduate and post-graduate assessments, but were equally likely to be on the Specialist Register. There was a suggestion of smaller ethnicity effects in earlier studies. Conclusions: The existence of the Academic Backbone concept is strongly supported, with attainment at secondary school predicting performance in undergraduate and post-graduate medical assessments, and the effects spanning many years. The Academic Backbone is conceptualized in terms of the development of more sophisticated underlying structures of knowledge ('cognitive capital’ and 'medical capital’). The Academic Backbone provides strong support for using measures of educational attainment, particularly A-levels, in student selection

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

A systematic review of lesbian, gay, bisexual and transgender health in the West Midlands region of the UK compared to published UK research

It is estimated that approximately 3-8% of the UK population identify as lesbian, gay, bisexual or trans (LGBT). Until now, most health research on gay and bisexual men has been around HIV, AIDS and sexually transmitted diseases and for trans people has been on the transitioning process only. However, it has been apparent to the LGBT community that that there are a wide variety of other physical and mental health issues that are also important and that the proportion of gay and bisexual men who have HIV/AIDS is relatively small. Very little general LGBT health research has been published so far and there are very few health services that specifically address the general health concerns of the LGBT community. This systematic review presents all available research conducted in the West Midlands on LGBT health since 2000. Local health research is compared to UK national, peer reviewed and published LGBT health research in order to determine whether the local results are unusual compared to national LGBT data, and to routinely collected data on the UK population, where appropriate, in order to determine whether and where the LGBT population differ from the general population. Only UK research has been included because there was no previous UK specific systematic review so it was unclear how generalisable foreign research would be to the UK

A model balancing cooperation and competition explains our right-handed world and the dominance of left-handed athletes

An overwhelming majority of humans are right-handed. Numerous explanations for individual handedness have been proposed, but this population-level handedness remains puzzling. Here we use a minimal mathematical model to explain this population-level hand preference as an evolved balance between cooperative and competitive pressures in human evolutionary history. We use selection of elite athletes as a test-bed for our evolutionary model and account for the surprising distribution of handedness in many professional sports. Our model predicts strong lateralization in social species with limited combative interaction, and elucidates the rarity of compelling evidence for "pawedness" in the animal world.Comment: 5 pages of text and 3 figures in manuscript, 8 pages of text and two figures in supplementary materia

Is any but a tiny fraction of handedness variance likely to be due to the external environment?

Non-shared environmental variance (NSEV) accounts for 76% of variance in genetic modelling of handedness. However, it is very misleading to suggest that NSEV, “highlights the importance of non-genetic factors for the ontogenesis of hemispheric asymmetries”. NSEV is poorly named, is calculated only by subtraction, and provides no direct evidence for environmental effects in the sense of the external environment. Miller suggested that it would be better named as “residual effect”. Mitchell has suggested that much or indeed most of NSEV is “developmental variance” and should be included under the heading of nature rather than nurture, and in handedness, “largely reflect[s] the outcome of randomness in brain development”. Overall only a very small proportion of NSEV in handedness is likely to be related to external environmental factors in the usual sense of the term

Performance in the MRCP(UK) Examination 2003-4: analysis of pass rates of UK graduates in relation to self-declared ethnicity and gender

Background: Male students and students from ethnic minorities have been reported to underperform in undergraduate medical examinations. We examined the effects of ethnicity and gender on pass rates in UK medical graduates sitting the Membership of the Royal Colleges of Physicians in the United Kingdom [MRCP( UK)] Examination in 2003-4. Methods: Pass rates for each part of the examination were analysed for differences between graduate groupings based on self- declared ethnicity and gender.Results: All candidates declared their gender, and 84 - 90% declared their ethnicity. In all three parts of the examination, white candidates performed better than other ethnic groups (P < 0.001). In the MRCP(UK) Part 1 and Part 2 Written Examinations, there was no significant difference in pass rate between male and female graduates, nor was there any interaction between gender and ethnicity. In the Part 2 Clinical Examination (Practical Assessment of Clinical Examination Skills, PACES), women performed better than did men (P < 0.001). Non-white men performed more poorly than expected, relative to white men or non-white women. Analysis of individual station marks showed significant interaction between candidate and examiner ethnicity for performance on communication skills (P = 0.011), but not on clinical skills (P = 0.176). Analysis of overall average marks showed no interaction between candidate gender and the number of assessments made by female examiners (P = 0.151).Conclusion: The cause of these differences is most likely to be multifactorial, but cannot be readily explained in terms of previous educational experience or differential performance on particular parts of the examination. Potential examiner prejudice, significant only in the cases where there were two non- white examiners and the candidate was non- white, might indicate different cultural interpretations of the judgements being made