Impact of Preference Signals on Interview Selection Across Multiple Residency Specialties and Programs.

Adena E Rosenblatt,Jennifer LaFemina, Lonika Sood,Jennifer Choi, Jennifer Serfin, Bobby Naemi,Dana Dunleavy

Journal of graduate medical education(2023)

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摘要
Background Program signaling is an innovation that allows applicants to express interest in specific programs while providing programs the opportunity to review genuinely interested applicants during the interview selection process. Objective To examine the influence of program signaling on "selected to interview" status across specialties in the 2022 Electronic Residency Application Service (ERAS) application cycle. Methods Dermatology, general surgery-categorical (GS), and internal medicine-categorical (IM-C) programs that participated in the signaling section of the 2022 supplemental ERAS application (SuppApp) were included. Applicant signal data was collected from SuppApp, applicant self-reported characteristics collected from the MyERAS Application for Residency Applicants, and 2020 program characteristics collected from the 2020 GME Track Survey. Applicant probability of being selected for interview was analyzed using logistic regression, determined by the selected to interview status in the ERAS Program Director's WorkStation. Results Dermatology had a 62% participation rate (73 of 117 programs), GS a 75% participation rate (174 of 232 programs), and IM-C an 86% participation rate (309 of 361 programs). In all 3 specialties examined, on average, signaling increased the likelihood of being selected to interview compared to applicants who did not signal. This finding held across gender and underrepresented in medicine (UIM) groups in all 3 specialties, across applicant types (MDs, DOs, international medical graduates) for GS and IM-C, and after controlling for United States Medical Licensing Examination Step 1 scores. Conclusions Although there was variability by program, signaling increased likelihood of being selected for interview without negatively affecting any specific gender or UIM group.
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