Sociodemographic and educational characteristics of doctors applying for psychiatry training in the UK: secondary analysis of data from the UK Medical Education Database project.

Aims and methodWorkforce shortages in psychiatry are common worldwide. The international literature provides insights into factors influencing decisions to train in psychiatry but is predominately survey based. This national cohort study aimed to identify the characteristics of doctors who were most likely to apply to psychiatry training programmes. The sample comprised doctors who entered UK medical schools in 2007/8 and who made first-time specialty training applications in 2015. The association between application to psychiatry and doctors' sociodemographic and educational characteristics was examined using multivariable logistic regression. RESULTS: Those most likely to apply were White, privately educated older doctors with below average performance at medical school.Clinical implicationsTo reduce workforce shortages, psychiatry must make itself more attractive to all doctors, especially those from underrepresented groups such as state-educated Black and minority ethnic individuals. Otherwise, national policies to widen participation in the study of medicine by such groups may exacerbate the current recruitment crisis.Declaration of interestNone.

Factors associated with junior doctors' decisions to apply for general practice training programmes in the UK: secondary analysis of data from the UKMED project.

BACKGROUND: The UK, like many high-income countries, is experiencing a worsening shortfall of general practitioners (GPs) alongside an increasing demand for their services. At the same time, factors influencing junior doctors' decisions to apply for GP training are only partially understood and research in this area has been hampered by the difficulties in connecting the datasets that map the journey from student to qualified GP. The UK Medical Education Database (UKMED) has been established to ameliorate this problem by linking institutional data across the spectrum of medical education from school to specialty training. Our study aimed to use UKMED to investigate which demographic and educational factors are associated with junior doctors' decisions to apply for GP training. METHODS: Study data, provided by the UKMED Development Group and accessed remotely, contained longitudinal educational and sociodemographic information on all doctors who entered UK medical schools in the 2007/2008 academic year and who made first-time specialty training applications in 2015. We used multivariable logistic regression models to investigate two binary outcomes, namely (1) application to GP training, possibly alongside applications to other specialties, and (2) application solely to GP training. RESULTS: Of 7634 doctors in the sample, 43% applied to GP training possibly alongside other specialities and 26% applied solely to GP training. The odds of applying to GP training were associated with particular demographic factors (being female, non-white or secondary educated in the UK increased the odds of application) and educational factors (non-graduate entry, intercalation and above-median academic performance during medical school all decreased the odds of application). After adjusting for these factors, both the medical school and the foundation school attended were independently associated with the odds of applying to GP training. CONCLUSIONS: Our findings suggest that the supply and demand imbalance in UK primary care might be improved by (1) efforts to attract greater numbers of female, non-white and UK secondary-educated students into medical schools, and (2) targeting resources at medical and foundation schools that deliver doctors likely to fill significant gaps in the workforce. Further research is required to better understand inter-school differences and to develop strategies to improve recruitment of GP trainees.

Do differentials in the support and advice available at UK schools and colleges influence candidate performance in the medical school admissions interview? A survey of direct school leaver applicants to a UK medical school.

BACKGROUND: To our knowledge, nothing is known about whether differentials in support and advice during preparation for the interview influence candidate performance and thereby contribute to bias in selection for medical school. AIM: To assess if differences in advice and support with preparation for the medical school admissions interview given type of school last attended influence interview score achieved by direct school leaver applicants to study on an undergraduate UK medical degree course. METHODS: Confidential self-completed on-line questionnaire survey. RESULTS: Interview performance was positively related to whether a teacher, tutor or career advisors at the School or College last attended had advised a respondent to prepare for the interview, had advised about the various styles of medical interview used and the types of questions asked, and what resources were available to help in preparation. Respondents from Private/Independent schools were more likely than those from State schools to have received such advice and support. CONCLUSIONS: Differentials in access to advice on and support with preparation for the medical school interview may advantage some candidates over others. This inequity would likely be ameliorated by the provision of an authoritative and comprehensive guide to applying to medical school outlining admission requirements and the preparation strategy applicants should use in order to best meet those requirements. The guide could be disseminated to the Principals of all UK schools and colleges and freely available electronic versions signposted in medical school prospectuses and the course descriptor on the Universities and Colleges Admissions Service.

The UK Clinical Aptitude Test: is it a fair test for selecting medical students?

BACKGROUND: The United Kingdom Clinical Aptitude Test (UKCAT) is designed to increase diversity and fairness in selection to study medicine. AIM: The aim of this study is to determine if differences in: access to support and advice, in modes of preparation, type of school/college attended, level of achievement in mathematics, gender and age influence candidate performance in the UKCAT and thereby unfairly advantage some candidates over others. METHODS: Confidential, self-completed, on-line questionnaire of applicants to study on an undergraduate medical degree course who had taken the UKCAT in 2010. RESULTS: Differentials in access to support and advice, in modes of preparation, type of school/college attended, in level of achievement in mathematics, gender and age were found to be associated with candidate performance in the UKCAT. CONCLUSION: The findings imply that the UKCAT may disadvantage some candidate groups. This inequity would likely be improved if tutors and career advisors in schools and colleges were more informed about the UKCAT and able to offer appropriate advice on preparation for the test.

Predicting medical student performance from attributes at entry: a latent class analysis.

OBJECTIVES: The objectives of this study were two-fold. Firstly, we aimed to model 'typologies' of student examination performance by grouping students into like categories based on measures of prior academic achievement (particularly in the science subjects) and interview rating at time of entry to a medical degree course, and outcome measures of subsequent performance across the course. Secondly, we aimed to illustrate and evidence the utility of the latent class analysis (LCA) clustering technique to provide meaningful information on the effectiveness of a student selection process with respect to the likelihood of poor examination performance. METHODS: For this retrospective study, anonymised data on two sequential cohorts of students who graduated from a 5-year Bachelor of Medicine, Bachelor of Surgery degree course were analysed using LCA. In order to triangulate the findings, the same data were analysed using the more conventional approach of logistic regression. RESULTS: The LCA identified three distinct classes or typologies of student examination performance using measures of prior academic achievement and interview rating at time of course entry. Measures of prior academic achievement and score on a structured admissions interview made significant contributions to the model's ability to discriminate between typologies. Strong prior academic achievement, especially in chemistry, and high interview score were positively related to the likelihood of successful test performance. These findings were supported by the logistic regression analysis. CONCLUSIONS: The LCA clustering technique provided meaningful information on the performance of a selection process. As a complementary tool to existing methods used in this area of research, LCA has the potential to empirically inform the selection process.

What are the most important non-academic attributes of good doctors? A Delphi survey of clinicians.

BACKGROUND: Although a multiplicity of qualities and behaviours considered essential in a good doctor are identified in the profession's guidance documents, there is no consensus as to their relative importance, or indeed, agreement as to the core qualities that should be, or could be, feasibly assessed in the limited time of the typical medical school interview. AIM: The aim of the study was to identify the most important generic attributes of good doctors, which can inform the content of the undergraduate medical student selection processes. METHOD: The study used a Delphi survey to systematically gather the opinion of a panel of experts from a range of medical specialties as to the most important core attributes of good doctors. Additionally, a snapshot of opinion was obtained from the attendees of workshops held at a medical school educational conference. RESULTS: Common core attributes of a good doctor were identified across a number of medical specialties. CONCLUSIONS: Consensus among clinicians from disparate specialties can be reached as to the most important generic attributes of good doctors and can be used to inform the choice of personal qualities and behaviours examined during undergraduate medical student selection process.