5,615 research outputs found
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
Recommended from our members
Flood- and Weather-Damaged Homes and Mental Health: An Analysis Using England's Mental Health Survey
There is increasing evidence that exposure to weather-related hazards like storms and floods adversely affects mental health. However, evidence of treated and untreated mental disorders based on diagnostic criteria for the general population is limited. We analysed the Adult Psychiatric Morbidity Survey, a large probability sample survey of adults in England (n = 7525), that provides the only national data on the prevalence of mental disorders assessed to diagnostic criteria. The most recent survey (2014–2015) asked participants if they had experienced damage to their home (due to wind, rain, snow or flood) in the six months prior to interview, a period that included months of unprecedented population exposure to flooding, particularly in Southern England. One in twenty (4.5%) reported living in a storm- or flood-damaged home in the previous six months. Social advantage (home ownership, higher household income) increased the odds of exposure to storm or flood damage. Exposure predicted having a common mental disorder over and above the effects of other known predictors of poor mental health. With climate change increasing the frequency and severity of storms and flooding, improving community resilience and disaster preparedness is a priority. Evidence on the mental health of exposed populations is key to building this capacity
Recommended from our members
Problem gambling and suicidality in England: secondary analysis of a representative cross-sectional survey
Objectives: Problem gamblers in treatment are known to be at high risk for suicidality, but few studies have examined if this is evident in community samples. Evidence is mixed on the extent to which an association between problem gambling and suicidality may be explained by psychiatric comorbidity. We tested whether they are associated after adjustment for co-occurring mental disorders and other factors. Study design: Secondary analysis of the Adult Psychiatric Morbidity Survey 2007, a cross-sectional na- tional probability sample survey of 7403 adults living in households in England.
Methods: Rates of suicidality in problem gamblers and the rest of the population were compared. A series of logistic regression models assessed the impact of adjustment on the relationship between problem gambling and suicidality.
Results: Past year suicidality was reported in 19.2% of problem gamblers, compared with 4.4% in the rest of the population. Their unadjusted odds ratios (OR) of suicidality were 5.3 times higher. Odds attenuated but remained significant when depression and anxiety disorders, substance dependences, attention- deficit/hyperactivity disorder, and other factors were accounted for (adjusted OR 1⁄4 2.9, 95% confi- dence interval 1⁄4 1. 1, 8.1 P 1⁄4 0.023).
Conclusions: Problem gamblers are a high-risk group for suicidality. This should be recognised in indi- vidual suicide prevention plans and local and national suicide prevention strategies. While some of this relationship is explained by other factors, a significant and substantial association between problem gambling and suicidality remains
Graduates of different UK medical schools show substantial differences in performance on MRCP(UK) Part 1, Part 2 and PACES examinations
Background: The UK General Medical Council has emphasized the lack of evidence on whether graduates from different UK medical schools perform differently in their clinical careers. Here we assess the performance of UK graduates who have taken MRCP( UK) Part 1 and Part 2, which are multiple-choice assessments, and PACES, an assessment using real and simulated patients of clinical examination skills and communication skills, and we explore the reasons for the differences between medical schools. Method: We perform a retrospective analysis of the performance of 5827 doctors graduating in UK medical schools taking the Part 1, Part 2 or PACES for the first time between 2003/2 and 2005/3, and 22453 candidates taking Part 1 from 1989/1 to 2005/3. Results: Graduates of UK medical schools performed differently in the MRCP( UK) examination between 2003/2 and 2005/3. Part 1 and 2 performance of Oxford, Cambridge and Newcastle-upon-Tyne graduates was significantly better than average, and the performance of Liverpool, Dundee, Belfast and Aberdeen graduates was significantly worse than average. In the PACES ( clinical) examination, Oxford graduates performed significantly above average, and Dundee, Liverpool and London graduates significantly below average. About 60% of medical school variance was explained by differences in pre-admission qualifications, although the remaining variance was still significant, with graduates from Leicester, Oxford, Birmingham, Newcastle-upon-Tyne and London overperforming at Part 1, and graduates from Southampton, Dundee, Aberdeen, Liverpool and Belfast underperforming relative to pre-admission qualifications. The ranking of schools at Part 1 in 2003/2 to 2005/3 correlated 0.723, 0.654, 0.618 and 0.493 with performance in 1999-2001, 1996-1998, 1993-1995 and 1989-1992, respectively. Conclusion: Candidates from different UK medical schools perform differently in all three parts of the MRCP( UK) examination, with the ordering consistent across the parts of the exam and with the differences in Part 1 performance being consistent from 1989 to 2005. Although pre-admission qualifications explained some of the medical school variance, the remaining differences do not seem to result from career preference or other selection biases, and are presumed to result from unmeasured differences in ability at entry to the medical school or to differences between medical schools in teaching focus, content and approaches. Exploration of causal mechanisms would be enhanced by results from a national medical qualifying examination
A hazard model of the probability of medical school dropout in the United Kingdom
From individual level longitudinal data for two entire cohorts of medical students in UK universities, we use multilevel models to analyse the probability that an individual student will drop out of medical school. We find that academic preparedness—both in terms of previous subjects studied and levels of attainment therein—is the major influence on withdrawal by medical students. Additionally, males and more mature students are more likely to withdraw than females or younger students respectively. We find evidence that the factors influencing the decision to transfer course differ from those affecting the decision to drop out for other reasons
- …