Characterizing the past 5 years of integrated plastic surgery applicants: A Texas STAR analysis.
cross_sectional · Level IV
Where this comes from
- Record sourced from PubMed, PMID 40220587.
- Also identified by DOI 10.1016/j.bjps.2025.03.054.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
The Texas STAR (Seeking Transparency in Application to Residency) database is a new residency match database that provides data and subjective advice from successful and unsuccessful residency applicants to inform prospective applicants. This study used the database to elucidate the current trends in plastic surgery applicant statistics. Self-reported survey data from applicants to integrated plastic surgery residency programs between 2020 and 2024 were obtained from the Texas STAR database. Objective statistics from all applicants were analyzed using linear and logistic regression models to determine their significance with regards to match outcomes. Subjective advice from successful and unsuccessful applicants was extracted and summarized into general themes. A total of 327 integrated plastic surgery applicants responded to the Texas STAR survey from 2020 to 2024. Among these applicants, 247 matched (75.5%) and 80 did not match (24.5%). Matched applicants had a significantly higher number of interviews offered (16.2 vs. 7.8, p = 0.000), United States Medical Licensing Examination Step 2CK score (256.5 vs. 253.1, p = 0.020), clerkships honored (4.4 vs. 3.6, p = 0.012), percentage taking research years (29.6% vs. 16.3%, p = 0.011), abstracts/posters/presentations (9.3 vs. 7.9, p = 0.002), peer-reviewed publications (6.7 vs. 5.2, p = 0.001), and interviews attended (14.0 vs. 9.1, p = 0.000). Other factors were not significant. Furthermore, applicants cited away rotations, letters of recommendation, connections, and mentors as important. Number of applications, board scores, clerkship performance, research productivity, and leadership roles influence the number of interview invites, while the number of interview invites best predicted match status.
Medical subject headings
- Internship and Residency
- Surgery, Plastic
- Students, Medical
- Personnel Selection