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Bridging the Technology Divide in the COVID-19 Era: Using Virtual Outreach to Expose Middle and High School Students to Imaging Technology

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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.

Journal of the American College of Radiology : JACR

|November 3, 2023

Summary

Extracurricular activities significantly influence radiology residency selection. Community service and progressive-leaning activities are favored, while conservative activities may hinder applications, impacting holistic review.

Keywords:

Residency application bias

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Published on: September 11, 2011

Area of Science:

Medical Education
Residency Admissions
Socio-political Factors in Medicine

Background:

Extracurricular activities (EAs) are considered in holistic reviews for radiology residency.
Objective analysis is needed to understand the impact of EAs on selection decisions.

Purpose of the Study:

To objectively analyze the influence of extracurricular activities (EAs) on radiology resident selection.
To determine the relative importance of EAs compared to academic and demographic factors.

Main Methods:

A discrete-choice experiment involving 244 faculty members from 30 US radiology programs.
Analysis of hypothetical applicant profiles featuring 22 distinct EAs.
Conditional logistic regression to calculate odds ratios (ORs) for EA influence.

Main Results:

Community-service EAs were ranked highest.
LGBTQ Pride Alliance (OR=1.56) positively influenced decisions, while Young Republicans (OR=0.60) negatively influenced them.
Active engagement (OR=1.154) and progressive ideology (OR=1.280) were preferred.

Conclusions:

Extracurricular activities significantly impact radiology residency selection.
EAs are likely to increase in importance as performance metrics are de-emphasized.
Applicants and committees must acknowledge the influence and potential biases of EAs.