Radiology resident selection factors predict resident performance
| Autor: | Jeffrey R. Tseng, Young S. Kang, Jiwon Youm, Rajul Pandit |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Resident selection
medicine.medical_specialty business.industry education Rank (computer programming) Medical school Internship and Residency Regression analysis United States Statistical significance Linear regression Medicine Humans Radiology Nuclear Medicine and imaging Radiology Educational Measurement business Selection (genetic algorithm) |
| Zdroj: | Clinical imaging. 80 |
| ISSN: | 1873-4499 |
| Popis: | Purpose To determine selection factors that predict radiology resident performance. Methods 59 consecutive radiology residents from 2002 to 2015 were ranked on performance during residency. Correlations and multiple regression analyses were performed to predict resident performance from the following selection factors: United States Medical Licensing Exam (USMLE) Step 1 score, medical school rank, Alpha Omega Alpha (AOA) membership, honors in clinical rotations, Medical Student Performance Evaluation (MSPE), and interview score. Results were compared against predictions from Match rank position. Results Five selection factors showed significant or marginally significant correlations with resident performance (r = 0.2 to 0.3). The interview score was not significantly correlated. A multiple regression model comprised of the USMLE Step 1 score, medical school rank, AOA membership, and interview score predicted resident performance, with an adjusted R2 of 0.19. The interview score was included in the model but did not achieve statistical significance. Match rank did not predict resident performance, with an R2 of 0.01. Conclusions A multiple regression model comprised of the USMLE Step 1 score, medical school rank, and AOA membership predicted radiology resident performance and may assist with resident selection. |
| Databáze: | OpenAIRE |
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