U.S. Medical School Graduates' Placement in Graduate Medical Education: A National Study.

Purpose: This study describes graduate medical education (GME) placement outcomes for recent U.S. medical school graduates and examines racial and ethnic differences in GME placement among these graduates.

Examining ChatGPT Performance on USMLE Sample Items and Implications for Assessment.

Purpose: In late 2022 and early 2023, reports that ChatGPT could pass the United States Medical Licensing Examination (USMLE) generated considerable excitement, and media response suggested ChatGPT has credible medical knowledge. This report analyzes the extent to which an artificial intelligence (AI) agent's performance on these sample items can generalize to performance on an actual USMLE examination and an illustration is given using ChatGPT.

Method: As with earlier investigations, analyses were based on publicly available USMLE sample items.

Effects and Unforeseen Consequences of Accessing References on a Maintenance of Certification Examination: Findings From a National Study.

Purpose: Increasing criticism of maintenance of certification (MOC) examinations has prompted certifying boards to explore alternative assessment formats. The purpose of this study was to examine the effect of allowing test takers to access reference material while completing their MOC Part III standardized examination.

Method: Item response data were obtained from 546 physicians who completed a medical subspecialty MOC examination between 2013 and 2016.

The Interaction of Ability Differences and Guessing When Modeling Differential Item Functioning With the Rasch Model: Conventional and Tailored Calibration.

In educational testing, differential item functioning (DIF) statistics must be accurately estimated to ensure the appropriate items are flagged for inspection or removal. This study showed how using the Rasch model to estimate DIF may introduce considerable bias in the results when there are large group differences in ability (impact) and the data follow a three-parameter logistic model. With large group ability differences, difficult non-DIF items appeared to favor the focal group and easy non-DIF items appeared to favor the reference group.