Objectives: Many medical students take commercial preparation courses to prepare for the USMLE Step 1. This investigation examined the relationships among Step 1 performance, preparation method, and academic achievement in medical school.
Method: A survey was conducted on 148 junior students at a medical school in July 2000 regarding their preparation methods for Step 1. Additional data was collected on student Step 1 scores, attendance record on preparation courses, and course grades in medical school.
Results: One hundred students (68%) responded to the survey including 32 preparation course participants. Course participants had significantly lower Step 1 scores and second-year GPAs than those of the non-participants (p < 0.05). However, the effect of preparation method was not significant by using ANCOVA when the second-year GPA was used as a covariate (p = 0.71).
Conclusion: Performance on Step 1 is related to academic performance in medical school and not the type of preparation methods.
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http://dx.doi.org/10.1007/s10459-004-3925-x | DOI Listing |
Cureus
November 2024
Department of Medical Education, Nova Southeastern University Dr. Kiran C. Patel College of Allopathic Medicine, Fort Lauderdale, USA.
Medical school exams, like those by the National Board of Medical Examiners (NBME) and the United States Medical Licensing Examination (USMLE), assess essential knowledge and skills for safe patient care, essential for student advancement and securing competitive residencies. Understanding the correlation between exam scores and medical school performance, as well as identifying trends among high scorers, provides valuable insights for both medical students and educators. This review examines the link between study resources and NBME exam scores, as well as psychological factors influencing these outcomes.
View Article and Find Full Text PDFUrology
December 2024
University of Kansas, Department of Urology, Kansas City, KS.
Objective: To provide a cross-sectional view of the current opinions surrounding the urology match by analyzing data from the annual Society of Academic Urologists Program Director Surveys conducted between 2022 and 2024.
Methods: Data collected through surveys distributed to all urology program directors (PD) consisting of questions covering program demographics, applicant selection criteria, preference signals (PS), virtual interviews (VI), and other relevant topics.
Results: 89, 90, and 89 PD participated in the surveys for the years 2022, 2023, and 2024, respectively.
J Grad Med Educ
December 2024
is Core Faculty, Department of Emergency Medicine, Allegheny Health Network, Erie, Pennsylvania, USA.
Pac Symp Biocomput
December 2024
Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
The United States Medical Licensing Examination (USMLE) is a critical step in assessing the competence of future physicians, yet the process of creating exam questions and study materials is both time-consuming and costly. While Large Language Models (LLMs), such as OpenAI's GPT-4, have demonstrated proficiency in answering medical exam questions, their potential in generating such questions remains underexplored. This study presents QUEST-AI, a novel system that utilizes LLMs to (1) generate USMLE-style questions, (2) identify and flag incorrect questions, and (3) correct errors in the flagged questions.
View Article and Find Full Text PDFJ Gen Intern Med
December 2024
Division of Hospital Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA.
Standardized examinations measure progress throughout medical education. Successful completion of the American Board of Internal Medicine Certification Examination (ABIM-CE) benchmarks completion of internal medicine (IM) residency training. Recent declines in initial ABIM-CE pass rates may prompt residency programs to examine strategies to improve learner performance.
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