Observational studyBMC medical education2026
Equity in medical school interviews: a cross-sectional analysis of school type, gender, and widening participation status.
Observational study in BMC medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
backgroundMultiple Mini Interviews (MMIs) are widely used in medical school admissions to assess non-academic attributes. While MMIs are designed to promote fairness, questions remain about how applicant background may influence performance. In 2015, a single-institution UK study found no significant impact of school background or socioeconomic status on MMI scores. A decade later, this study re-examines those associations in a similar UK context.
methodsIn this cross-sectional observational study, we analysed data from 545 home applicants to Imperial College School of Medicine during the 2025 admissions cycle. Using multiple linear regression, we explored the relationship between total MMI score and applicant gender, school type, and widening participation (WP) status. Station-level regressions were also conducted.
resultsThe regression model was statistically significant and explained 7.6% of total score variance. Out of a maximum score of 70, female applicants scored on average 3.2 points higher than males (95% CI: 2.1 to 4.2, p < 0.001). Applicants from independent and state-selective schools scored 2.4 (95% CI: 1.0 to 3.9, p = 0.001) and 1.3 points higher (95% CI: 0.0 to 2.7, p = 0.046), respectively, than state non-selective peers. WP status was not a significant predictor. Station-level analyses revealed no consistent disadvantage for WP applicants.
conclusionOur findings suggest that, unlike earlier UK research, school background and gender now show modest associations with MMI performance. WP applicants, however, perform comparably to their peers, indicating progress towards equitable access. Future work should explore the potential impact of coaching and familiarity with interview formats to inform MMI design.
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