Even one star at A level could be "too little, too late" for medical student selection.

BACKGROUND: More and more medical school applicants in England and Wales are gaining the maximum grade at A level of AAA, and the UK Government has now agreed to pilot the introduction of a new A* grade. This study assessed the likely utility of additional grades of A* or of A**. METHODS: Statistical analysis of university selection data collected by the Universities and Colleges Admissions Service (UCAS), consisting of data from 1,484,650 applicants to UCAS for the years 2003, 2004 and 2005, of whom 23,628 were medical school applicants, and of these 14,510 were medical school entrants from the UK, aged under 21, and with three or four A level results. The main outcome measure was the number of points scored by applicants in their best three A level subjects. RESULTS: Censored normal distributions showed a good fit to the data using maximum likelihood modelling. If it were the case that A* grades had already been introduced, then at present about 11% of medical school applicants and 18% of entrants would achieve the maximum score of 3 A*s. Projections for the years 2010, 2015 and 2020 suggest that about 26%, 35% and 46% of medical school entrants would have 3 A* grades. CONCLUSION: Although A* grades at A level will help in medical student selection, within a decade, a third of medical students will gain maximum grades. While revising the A level system there is a strong argument, as proposed in the Tomlinson Report, for introducing an A** grade.

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.

'It gives you an understanding you can't get from any book.' The relationship between medical students' and doctors' personal illness experiences and their performance: a qualitative and quantitative study.

BACKGROUND: Anecdotes abound about doctors' personal illness experiences and the effect they have on their empathy and care of patients. We formally investigated the relationship between doctors' and medical students' personal illness experiences, their examination results, preparedness for clinical practice, learning and professional attitudes and behaviour towards patients. METHODS: Newly-qualified UK doctors in 2005 (n = 2062/4784), and two cohorts of students at one London medical school (n = 640/749) participated in the quantitative arm of the study. 37 Consultants, 1 Specialist Registrar, 2 Clinical Skills Tutors and 25 newly-qualified doctors participated in the qualitative arm. Newly-qualified doctors and medical students reported their personal illness experiences in a questionnaire. Doctors' experiences were correlated with self-reported preparedness for their new clinical jobs. Students' experiences were correlated with their examination results, and self-reported anxiety and depression. Interviews with clinical teachers, newly-qualified doctors and senior doctors qualitatively investigated how personal illness experiences affect learning, professional attitudes, and behaviour. RESULTS: 85.5% of newly-qualified doctors and 54.4% of medical students reported personal illness experiences. Newly-qualified doctors who had been ill felt less prepared for starting work (p < 0.001), but those who had only experienced illness in a relative or friend felt more prepared (p = 0.02). Clinical medical students who had been ill were more anxious (p = 0.01) and had lower examination scores (p = 0.006). Doctors felt their personal illness experiences helped them empathise and communicate with patients. Medical students with more life experience were perceived as more mature, empathetic, and better learners; but illness at medical school was recognised to impede learning. CONCLUSION: The majority of the medical students and newly qualified doctors we studied reported personal illness experiences, and these experiences were associated with lower undergraduate examination results, higher anxiety, and lower preparedness. However reflection on such experiences may have improved professional attitudes such as empathy and compassion for patients. Future research is warranted in this area.

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 under-perform 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.

Femoral neck trabecular patterns predict osteoporotic fractures.

In this paper we show that texture analysis of femoral neck trabecular patterns can be used to predict osteoporotic fractures. The study is based on a sample of 123 women aged 44-66 years with and without fractures. We analyzed trabecular patterns using the Co-occurrence Matrix texture analysis algorithm and compared the predictive utility of the textural data with densitometry. Logistic regression was used to estimate the predictive utility, exp(B), of clinical and textural data per standard deviation. Reproducibility was also demonstrated using paired films at 1-year intervals (CoV=4.5%). Bone mass estimated by DEXA measurements of the spine and hip were the most predictive of fractures giving a two-fold increase in fractures per s.d. bone mass loss (95% CI: 1.2-3.1, p<0.005). Age was also highly predictive with fracture risk increasing by 1.07-fold per year (95% CI: 1.01-1.14, p<0.02). Trabecular texture was found to give a lower, but significant, prediction of fracture of 1.5-fold per s.d. trabecular pattern loss (95% CI: 0.96-2.31, p<0.05). Combining age, weight, and trabecular texture increased the fracture prediction to 1.78-fold per s.d. (95% CI: 1.19-2.67). Combining trabecular texture with densitometry increased the predictive ability to 2.06-fold per s.d. (95% CI: 1.32-3.22) and combined with age and weight as well increased exp(B) to 2.1-fold per s.d. (95% CI: 1.32-3.35). This shows that osteoporotic trabecular texture changes can be "measured." Moreover, the combination of age, weight, and trabecular texture is more predictive than either alone. We propose therefore that this trabecular texture analysis is both reproducible and clinically meaningful. The application of such methods could be used to improve the estimation of fracture risk in conjunction with other clinical data, or where densitometry data cannot be obtained (e.g., in retrospective studies).