Evidence map›Paper›PMID 39327343›Full record

ArticleJournal of general internal medicine2025

Internal Medicine Residency Program Applicant Perceptions of the SPLIT Recruitment Model Before and After Universal Virtual Interviews.

Priyanka K Chilukuri, Christina R Bergin, Melisa P Celaya, Kory A Johnson, Cheryl W O'Malley

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Article in Journal of general internal medicine, 2025. 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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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Priyanka K ChilukuriThe University of Arizona College of Medicine - Phoenix, Phoenix, AZ, USA.
Christina R BerginThe University of Arizona College of Medicine - Phoenix, Phoenix, AZ, USA.
Melisa P CelayaThe University of Arizona College of Medicine - Phoenix, Phoenix, AZ, USA.
Kory A JohnsonThe University of Arizona College of Medicine - Phoenix, Phoenix, AZ, USA.
Cheryl W O'MalleyThe University of Arizona College of Medicine - Phoenix, Phoenix, AZ, USA. comalley@arizona.edu.ORCID 0000-0003-0693-6582

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEnhancing residency recruitment with modifications to interviews has been an area of national interest, further catalyzed by the transition to universal virtual interviewing (UVI). In 2018, our internal medicine residency program redesigned the recruitment process using virtual interviews.

objectiveEvaluating this recruitment model allows programs to identify applicant perceptions of each component as they consider enhancements.

designThe new model, termed "SPLIT," included separating optional applicant visit days (AVD) from interviews (S), a pre-interview supplemental form (P), learning program information from a dedicated website (L), virtual interviews (I), and flexible timing (remote interview day and site visit) (T).

participantsApplicants for the 2019 to 2023 Match who interviewed at one university-based internal medicine residency program. MAIN MEASURES: After rank list certification and before the annual Match, interviewed applicants were surveyed regarding their perceptions of the SPLIT process. Responses before (2019-2020 Matches) and after (2021-2023 Matches) UVIs were compared. KEY

resultsA total of 386 (75%) of 515 respondents favored video interviews. This preference was stronger in the post-UVI group (92%) than in the pre-UVI group (57%) (p < 0.001). In total, 76% of respondents attended an AVD (virtual or in-person). Applicants in the post-UVI group also favored having interviews separated from the AVD (p = 0.006) and optional AVDs (p < 0.001), more than those in the pre-UVI group. In the pre-UVI cohort, those who attended an in-person AVD tended to report a higher program understanding (OR 7.8), satisfaction with SPLIT (OR 2.1), and a better recruitment experience (OR 2.0).

conclusionsVirtual interviews were highly rated with increased preference following universal adoption. Optional AVDs separated from virtual interviews enhance applicant understanding of the program and were more effective when offered in-person before the pandemic-related restrictions. As programs begin to reintroduce in-person elements, the SPLIT recruitment model offers an innovative approach that addresses applicant and program needs.

Indexed as

Internal MedicineInternship and ResidencyInterviews as TopicPersonnel SelectionAdultFemaleHumansMaleSurveys and QuestionnairesInterviewsMatchRecruitmentResidencyVirtual

Identifiers

PMID39327343
PMCPMC11780007

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.