Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

BACKGROUND

Medical schools differ, particularly in their teaching, but it is unclear whether such differences matter, although influential claims are often made. The Medical School Differences (MedDifs) study brings together a wide range of measures of UK medical schools, including postgraduate performance, fitness to practise issues, specialty choice, preparedness, satisfaction, teaching styles, entry criteria and institutional factors.

METHOD

Aggregated data were collected for 50 measures across 29 UK medical schools. Data include institutional history (e.g. rate of production of hospital and GP specialists in the past), curricular influences (e.g. PBL schools, spend per student, staff-student ratio), selection measures (e.g. entry grades), teaching and assessment (e.g. traditional vs PBL, specialty teaching, self-regulated learning), student satisfaction, Foundation selection scores, Foundation satisfaction, postgraduate examination performance and fitness to practise (postgraduate progression, GMC sanctions). Six specialties (General Practice, Psychiatry, Anaesthetics, Obstetrics and Gynaecology, Internal Medicine, Surgery) were examined in more detail.

RESULTS

Medical school differences are stable across time (median alpha = 0.835). The 50 measures were highly correlated, 395 (32.2%) of 1225 correlations being significant with p < 0.05, and 201 (16.4%) reached a Tukey-adjusted criterion of p < 0.0025. Problem-based learning (PBL) schools differ on many measures, including lower performance on postgraduate assessments. While these are in part explained by lower entry grades, a surprising finding is that schools such as PBL schools which reported greater student satisfaction with feedback also showed lower performance at postgraduate examinations. More medical school teaching of psychiatry, surgery and anaesthetics did not result in more specialist trainees. Schools that taught more general practice did have more graduates entering GP training, but those graduates performed less well in MRCGP examinations, the negative correlation resulting from numbers of GP trainees and exam outcomes being affected both by non-traditional teaching and by greater historical production of GPs. Postgraduate exam outcomes were also higher in schools with more self-regulated learning, but lower in larger medical schools. A path model for 29 measures found a complex causal nexus, most measures causing or being caused by other measures. Postgraduate exam performance was influenced by earlier attainment, at entry to Foundation and entry to medical school (the so-called academic backbone), and by self-regulated learning. Foundation measures of satisfaction, including preparedness, had no subsequent influence on outcomes. Fitness to practise issues were more frequent in schools producing more male graduates and more GPs.

CONCLUSIONS

Medical schools differ in large numbers of ways that are causally interconnected. Differences between schools in postgraduate examination performance, training problems and GMC sanctions have important implications for the quality of patient care and patient safety.

National Student Survey: Reliability and prediction of overall satisfaction scores with special reference to UK Dental Schools

INTRODUCTION

The aim of this study was to assess the reliability of the UK National Student Survey (NSS) (2018) and explore the predictive values of individual questions and question domains on the overall satisfaction score.

METHODS

UK NSS result data (for 2018) were assessed for all those providers that award an undergraduate degree in dentistry. To analyse the correlation of each question item to the overall satisfaction question (question 27), a bivariate 2-tailed Pearson correlation test was conducted, where a P value of <.05 was considered statistically significant. The same test was used to assess such correlation at question domain level. Cronbach's alpha was used to assess the test reliability of the NSS data.

RESULTS

Question 5 ("My course has provided me with opportunities to explore ideas or concepts in depth") had the highest predictive value, explaining 85% of the correlation data to the overall satisfaction question. The strongest positive correlation could be seen at the "teaching on my course" and "learning opportunities" domains, whereby 84% of the data can be explained by each of these variables. The worst predictor domain was assessment and feedback, whereby only 40% of the data could be explained by the correlation line. Cronbach's alpha was 0.952-0.976.

CONCLUSIONS

The NSS is a highly reliable test, both at question and domain levels. The highest predictors of overall satisfaction are teaching, learning opportunities and academic support domains. Assessment and feedback has weak predictive value towards the overall satisfaction score. Question 5 is highly predictive of the overall outcome.