Predicting who applies to study medicine: Implication for diversity in UK medical schools

Abstract

Aims: Widening access to medical school is a priority in medical selection. If disadvantaged students do not apply, interventions cannot be effective. To date, no studies have examined factors that predict who chooses to apply to medicine and if socio-demographics influence the profile of those who apply to study medicine.

Methods: A large database provided by the UK University and Colleges Admissions Service on all 1,225,156 applicants to UK universities over a 3-year period (2002-2004) was analysed. The relationship between demographics, preference to study medicine and academic performance prior to entry (A level score) were explored using logistic and linear regression and path modelling.

Results: Those applying to study medicine were more likely to be female, non-white, of higher socio-economic status and from fee-paying schools. Applying to study medicine was associated with increased academic entrance performance over and above socio-demographic factors. Importantly, in those applying to study medicine socio-demographic inequalities in entrance exam performance was either reduced (for ethnicity and SES) or abolished (for sex and schooling).

Conclusions: It is argued that early interventions are needed to increase applications for certain groups to help to reduce socio-demographic inequalities in entrance exam performance and hence medical school admissions.

Acknowledgement

We gratefully acknowledge the contribution of Chris Rix of the Universities and Colleges Admission Service (UCAS) to this project for providing approval and the data for this study. Ethics Committee Chairs approval was attained for this study. There was no financial support for this study. There are no conflicts of interest for any of the authors and there are no financial interests associated with any of the authors. Eamonn Ferguson had substantial contributions to the conceptual basis of the paper, the statistical analysis and interpretation, drafting the initial paper and revising the article for intellectual content and the final approval. David James had substantial contributions to the conceptual basis of the paper, the statistical analysis/interpretation, drafting and revising the article for intellectual content and the final approval. Janet Yates (who is funded by the Service Increment for Teaching (SIFT) in the NHS) had substantial contributions to the conceptual basis of the paper, preparing the dataset, the statistical analysis and interpretation, drafting and revising the article for intellectual content and the final approval. Claire Lawrence had substantial contributions to the conceptual basis of the paper, the statistical analysis/interpretation, drafting and revising the article for intellectual content and the final approval.

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this article.