Relationship between sociodemographic factors and selection into UK postgraduate medical training programmes: a national cohort study

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Introduction

Knowledge about allocation of doctors into postgraduate training programmes is essential in terms of workforce planning, transparency and equity issues. However, this is a rarely examined topic. To address this gap in the literature, the current study examines the relationships between applicants’ sociodemographic characteristics and outcomes on the UK Foundation Training selection process.

Methods

A longitudinal, cohort study of trainees who applied for the first stage of UK postgraduate medical training in 2013–2014. We used UK Medical Education Database (UKMED) to access linked data from different sources, including medical school admissions, assessments and postgraduate training. Multivariable ordinal regression analyses were used to predict the odds of applicants being allocated to their preferred foundation schools.

Results

Applicants allocated to their first-choice foundation school scored on average a quarter of an SD above the average of all applicants in the sample. After adjusting for Foundation Training application score, no statistically significant effects were observed for gender, socioeconomic status (as determined by income support) or whether applicants entered medical school as graduates or not. Ethnicity and place of medical qualification were strong predictors of allocation to preferred foundation school. Applicants who graduated from medical schools in Wales, Scotland and Northern Ireland were 1.17 times, 3.33 times and 12.64 times (respectively), the odds of applicants who graduated from a medical school in England to be allocated to a foundation school of their choice.

Conclusions

The data provide supportive evidence for the fairness of the allocation process but highlight some interesting findings relating to ‘push-pull’ factors in medical careers decision-making. These findings should be considered when designing postgraduate training policy.

Related collections

Most cited references 29

Record: found
Abstract: found
Article: found

Is Open Access

Ethnicity and academic performance in UK trained doctors and medical students: systematic review and meta-analysis

Katherine Woolf, Henry Potts, Ian McManus (2011)

Objective To determine whether the ethnicity of UK trained doctors and medical students is related to their academic performance. Design Systematic review and meta-analysis. Data sources Online databases PubMed, Scopus, and ERIC; Google and Google Scholar; personal knowledge; backwards and forwards citations; specific searches of medical education journals and medical education conference abstracts. Study selection The included quantitative reports measured the performance of medical students or UK trained doctors from different ethnic groups in undergraduate or postgraduate assessments. Exclusions were non-UK assessments, only non-UK trained candidates, only self reported assessment data, only dropouts or another non-academic variable, obvious sampling bias, or insufficient details of ethnicity or outcomes. Results 23 reports comparing the academic performance of medical students and doctors from different ethnic groups were included. Meta-analyses of effects from 22 reports (n=23 742) indicated candidates of “non-white” ethnicity underperformed compared with white candidates (Cohen’s d=−0.42, 95% confidence interval −0.50 to −0.34; P<0.001). Effects in the same direction and of similar magnitude were found in meta-analyses of undergraduate assessments only, postgraduate assessments only, machine marked written assessments only, practical clinical assessments only, assessments with pass/fail outcomes only, assessments with continuous outcomes only, and in a meta-analysis of white v Asian candidates only. Heterogeneity was present in all meta-analyses. Conclusion Ethnic differences in academic performance are widespread across different medical schools, different types of exam, and in undergraduates and postgraduates. They have persisted for many years and cannot be dismissed as atypical or local problems. We need to recognise this as an issue that probably affects all of UK medical and higher education. More detailed information to track the problem as well as further research into its causes is required. Such actions are necessary to ensure a fair and just method of training and of assessing current and future doctors.

0 comments Cited 106 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

The UKCAT-12 study: educational attainment, aptitude test performance, demographic and socio-economic contextual factors as predictors of first year outcome in a cross-sectional collaborative study of 12 UK medical schools

Ian McManus, Chris Dewberry, Sandra Nicholson … (2013)

Background Most UK medical schools use aptitude tests during student selection, but large-scale studies of predictive validity are rare. This study assesses the United Kingdom Clinical Aptitude Test (UKCAT), and its four sub-scales, along with measures of educational attainment, individual and contextual socio-economic background factors, as predictors of performance in the first year of medical school training. Methods A prospective study of 4,811 students in 12 UK medical schools taking the UKCAT from 2006 to 2008 as a part of the medical school application, for whom first year medical school examination results were available in 2008 to 2010. Results UKCAT scores and educational attainment measures (General Certificate of Education (GCE): A-levels, and so on; or Scottish Qualifications Authority (SQA): Scottish Highers, and so on) were significant predictors of outcome. UKCAT predicted outcome better in female students than male students, and better in mature than non-mature students. Incremental validity of UKCAT taking educational attainment into account was significant, but small. Medical school performance was also affected by sex (male students performing less well), ethnicity (non-White students performing less well), and a contextual measure of secondary schooling, students from secondary schools with greater average attainment at A-level (irrespective of public or private sector) performing less well. Multilevel modeling showed no differences between medical schools in predictive ability of the various measures. UKCAT sub-scales predicted similarly, except that Verbal Reasoning correlated positively with performance on Theory examinations, but negatively with Skills assessments. Conclusions This collaborative study in 12 medical schools shows the power of large-scale studies of medical education for answering previously unanswerable but important questions about medical student selection, education and training. UKCAT has predictive validity as a predictor of medical school outcome, particularly in mature applicants to medical school. UKCAT offers small but significant incremental validity which is operationally valuable where medical schools are making selection decisions based on incomplete measures of educational attainment. The study confirms the validity of using all the existing measures of educational attainment in full at the time of selection decision-making. Contextual measures provide little additional predictive value, except that students from high attaining secondary schools perform less well, an effect previously shown for UK universities in general.

0 comments Cited 50 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Fair access to medicine? Retrospective analysis of UK medical schools application data 2009-2012 using three measures of socioeconomic status

Kathryn Steven, Jon Dowell, Cathy Jackson … (2016)

Background Medical students have historically largely come from more affluent parts of society, leading many countries to seek to broaden access to medical careers on the grounds of social justice and the perceived benefits of greater workforce diversity. The aim of this study was to examine variation in socioeconomic status (SES) of applicants to study medicine and applicants with an accepted offer from a medical school, comparing the four UK countries and individual medical schools. Methods Retrospective analysis of application data for 22 UK medical schools 2009/10-2011/12. Data were analysed for all 32,964 UK-domiciled applicants aged <20 years to 22 non-graduate medical schools requiring applicants to sit the United Kingdom Clinical Aptitude Test (UKCAT). Rates of applicants and accepted offers were compared using three measures of SES: (1) Postcode-assigned Index of Multiple Deprivation score (IMD); (2) School type; (3) Parental occupation measured by the National Statistics Socio Economic Classification (NS-SEC). Results There is a marked social gradient of applicants and applicants with accepted offers with, depending on UK country of residence, 19.7–34.5 % of applicants living in the most affluent tenth of postcodes vs 1.8–5.7 % in the least affluent tenth. However, the majority of applicants in all postcodes had parents in the highest SES occupational group (NS-SEC1). Applicants resident in the most deprived postcodes, with parents from lower SES occupational groups (NS-SEC4/5) and attending non-selective state schools were less likely to obtain an accepted offer of a place at medical school further steepening the observed social gradient. Medical schools varied significantly in the percentage of individuals from NS-SEC 4/5 applying (2.3 %–8.4 %) and gaining an accepted offer (1.2 %–7.7 %). Conclusion Regardless of the measure, those from less affluent backgrounds are less likely to apply and less likely to gain an accepted offer to study medicine. Postcode-based measures such as IMD may be misleading, but individual measures like NS-SEC can be gamed by applicants. The previously unreported variation between UK countries and between medical schools warrants further investigation as it implies solutions are available but inconsistently applied.

0 comments Cited 47 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Journal ID (nlm-ta): BMJ Open

Journal ID (iso-abbrev): BMJ Open

Journal ID (hwp): bmjopen

Journal ID (publisher-id): bmjopen

Title: BMJ Open

Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )

ISSN (Electronic): 2044-6055

Publication date Collection: 2018

Publication date (Electronic): 30 June 2018

Volume: 8

Issue: 6

Electronic Location Identifier: e021329

Affiliations

[1 ] departmentCentre for Healthcare Education Research and Innovation (CHERI), School of Medicine, Medical Sciences and Nutrition , University of Aberdeen , Aberdeen, UK

[2 ] departmentMedical Statistics Team, School of Medicine, Medical Sciences & Nutrition , University of Aberdeen , Aberdeen, UK

[3 ] departmentNHS Grampian , NHS Education for Scotland and UK Foundation Programme , Aberdeen, UK

[4 ] departmentNHS Education for Scotland , Scotland Deanery , Aberdeen, UK

Author notes

[Correspondence to ] Ben Kumwenda; r01bk15@ 123456abdn.ac.uk

Author information

Ben Kumwenda http://orcid.org/0000-0003-1600-8229

Article

Publisher ID: bmjopen-2017-021329

DOI: 10.1136/bmjopen-2017-021329

PMC ID: 6042613

PubMed ID: 29961026

SO-VID: e27f217e-8a47-41a5-a01c-99481b7b2d2b

License:

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

History

Date received : 21 December 2017

Date revision received : 09 May 2018

Date accepted : 25 May 2018

Funding

Funded by: UKCAT Research Panel;

Custom metadata

special-feature unlocked

ScienceOpen disciplines: Medicine

Keywords: cohort study,ordinal logistic regression,postgraduate training,equality,socio-economic class

Data availability:

ScienceOpen disciplines: Medicine

Keywords: cohort study, ordinal logistic regression, postgraduate training, equality, socio-economic class

Relationship between sociodemographic factors and selection into UK postgraduate medical training programmes: a national cohort study

Read this article at

Abstract

Introduction

Methods

Results

Conclusions

Related collections

UCL: UN SDG 05 Gender Equality

Most cited references 29

Ethnicity and academic performance in UK trained doctors and medical students: systematic review and meta-analysis

The UKCAT-12 study: educational attainment, aptitude test performance, demographic and socio-economic contextual factors as predictors of first year outcome in a cross-sectional collaborative study of 12 UK medical schools

Fair access to medicine? Retrospective analysis of UK medical schools application data 2009-2012 using three measures of socioeconomic status

Author and article information

Journal

Affiliations

Author notes

Author information

Article

History

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 198

Cited by 11

Most referenced authors 182