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The Influence of Extracurricular Activities on Radiology Resident Selection Decisions
Charles M Maxfield1, J Felipe Montano-Campos2, Jennifer Gould3
1Vice Chair of Education, Department of Radiology, Duke University Medical Center, Durham, North Carolina.
Purpose:
Extracurricular activities (EAs) listed on radiology residency applications can signal traits and characteristics desired in holistic reviews. The authors conducted an objective analysis to determine the influence of EAs on resident selection decisions.
Methods:
A discrete-choice experiment was designed to model radiology resident selection and determine the relative weights of EAs among academic and demographic application factors. Faculty members involved in resident selection at 30 US radiology programs chose between hypothetical pairs of applicant profiles between October 2021 and February 2022. Each applicant profile included one of 22 EAs chosen for study. A conditional logistic regression model assessed the relative weights of the attributes and odds ratios (ORs) were calculated.
Results:
Two hundred forty-four participants completed the exercise. Community-service EAs were ranked most highly by participants. LGBTQ Pride Alliance (OR, 1.56; 95% confidence interval [CI], 1.14-2.15; P = .006) and Young Republicans (OR, 0.60; 95% CI, 0.43-0.82; P = .001) significantly influenced decisions. The highest ranked EAs were significantly preferred over the lowest ranked EAs (OR, 1.916; 95% CI, 1.671-2.197; P < .001). Participants preferred EAs that reflected active over passive engagement (OR, 1.154; 95% CI, 1.022-1.304; P = .021) and progressive over conservative ideology (OR, 1.280; 95% CI, 1.133-1.447; P < .001). Participants who ranked progressive EAs more highly preferred applicants with progressive EAs (P < .05 for all).
Conclusions:
The influence of EAs on resident selection decisions is significant and likely to gain importance in resident selection as medical student performance metrics are further eliminated. Applicants and selection committees should consider this influence and the bias that EAs can bring to resident selection decisions.
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