Objectives Many countries are driving forward policies to widen the socioeconomic profile of medical students and to train more medical students for certain specialties. However, little is known about how socioeconomic origin relates to specialty choice. Nor is there a good understanding of the relationship between academic performance and specialty choice. To address these gaps, our aim was to identify the relationship between socioeconomic background, academic performance and accepted offers into specialty training.
Design Longitudinal, cohort study using data from the UK Medical Education Database (https://www.ukmed.ac.uk/).
Participants 6065 (60% females) UK doctors who accepted offers to a specialty training (residency) post after completing the 2-year generic foundation programme (UK Foundation Programme) between 2012 and 2014.
Main outcome measures Χ2 tests were used to examine the relationships between sociodemographic characteristics, academic ability and the dependent variable, specialty choice. Multiple data imputation was used to address the issue of missing data. Multinomial regression was employed to test the independent variables in predicting the likelihood of choosing a given specialty.
Results Participants pursuing careers in more competitive specialties had significantly higher academic scores than colleagues pursuing less competitive ones. After controlling for the presence of multiple factors, trainees who came from families where no parent was educated to a degree level had statistically significant lower odds of choosing careers in medical specialties relative to general practice (OR=0.78, 95% CI, 0.67 to 0.92). Students who entered medical school as school leavers, compared with mature students, had odds 1.2 times higher (95% CI, 1.04 to 1.56) of choosing surgical specialties than general practice.
Conclusions The data indicate a direct association between trainees’ sociodemographic characteristics, academic ability and career choices. The findings can be used by medical school, training boards and workforce planners to inform recruitment and retention strategies.
- widening access
- career choice
- multinomial regression
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Contributors JC led the funding bid which was reviewed by KW, BK and PJ. KW and PJ advised on the nature of the data. BK managed the data, carried out the data analysis under the supervision of GP and JC, and wrote the first manuscript. GP advised on all the statistical analysis. JC guided the first draft of the Introduction and Discussion sections of this paper. BK wrote the Methods and Results sections. JC edited the drafts. All authors reviewed and agreed on the final draft of the paper.
Funding A small grant from UKCAT Research Panel was used to cover the cost of publishing this article.
Competing interests This study is part of Ben Kumwenda’s doctoral programme of research funded by the UKCAT Research Panel, of which JC is a member. KW is the Special Advisor (Recruitment) for the UK’s Foundation Programme (UKFPO).
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement UK Medical Education Database (“UKMED”) UKMEDP 026 extract generated on 12/08/2016. Approved for publication on 27/03/2017. UKMED bears no responsibility for data analysis or interpretation. The dataset is held in safe haven and only members of the research, BK, GP and JC had access to the data. The data includes information derived from that collected by the Higher Education Statistics Agency Limited (“HESA”) and provided to the GMC (“HESA Data”). Source: HESA Student Record 2007/2008 and 2008/2009 Copyright Higher Education Statistics Agency Limited. The Higher Education Statistics Agency Limited makes no warranty as to the accuracy of the HESA Data, cannot accept responsibility for any inferences or conclusions derived by third parties from data or other information supplied by it.
Patient consent for publication Not required.