Showing 1 - 10 of 28 Research Library Publications
Posted: | John Norcini, Irina Grabovsky, Michael A. Barone, M. Brownell Anderson, Ravi S. Pandian, Alex J. Mechaber

Academic Medicine: Volume 99 - Issue 3 - p 325-330

 

This retrospective cohort study investigates the association between United States Medical Licensing Examination (USMLE) scores and outcomes in 196,881 hospitalizations in Pennsylvania over 3 years.

Posted: | Victoria Yaneva, Peter Baldwin, Daniel P. Jurich, Kimberly Swygert, Brian E. Clauser

Academic Medicine: Volume 99 - Issue 2 - p 192-197

 

This report investigates the potential of artificial intelligence (AI) agents, exemplified by ChatGPT, to perform on the United States Medical Licensing Examination (USMLE), following reports of its successful performance on sample items. 

Posted: | Thai Ong, Becky Krumm, Margaret Wells, Susan Read, Linda Harris, Andrea Altomare, Miguel Paniagua

Academic Medicine: Volume 99 - Issue 7 - Pages 778-783

 

This study examined score comparability between in-person and remote proctored administrations of the 2020 Internal Medicine In-Training Examination (IM-ITE) during the COVID-19 pandemic. Analysis of data from 27,115 IM residents revealed statistically significant but educationally nonsignificant differences in predicted scores, with slightly larger variations observed for first-year residents. Overall, performance did not substantially differ between the two testing modalities, supporting the continued use of remote proctoring for the IM-ITE amidst pandemic-related disruptions.

Posted: | Michael A. Barone, Jessica L. Bienstock, Elise Lovell, John R. Gimpel, Grant L. Lin, Jennifer Swails, George C. Mejicano

Journal of Graduate Medical Education: Volume 14, Issue 6, Pages 634-638

 

This article discusses recent recommendations from the UME-GME Review Committee (UGRC) to address challenges in the UME-GME transition—including complexity, negative impact on well-being, costs, and inequities.

Posted: | Christopher Runyon, Polina Harik, Michael Barone

Diagnosis: Volume 10, Issue 1, Pages 54-60

 

This op-ed discusses the advantages of leveraging natural language processing (NLP) in the assessment of clinical reasoning. It also provides an overview of INCITE, the Intelligent Clinical Text Evaluator, a scalable NLP-based computer-assisted scoring system that was developed to measure clinical reasoning ability as assessed in the written documentation portion of the now-discontinued USMLE Step 2 Clinical Skills examination. 

Posted: | Hilary Barnes, Asefeh Faraz Covelli, Jonathan D. Rubright

Research in Nursing & Health: Volume 46, Issue 1, Pages 127-135

 

As interest in supporting new nurse practitioners' (NPs) transition to practice increases, those interested in measuring the concept will need an instrument with evidence of reliability and validity. The Novice NP Role Transition (NNPRT) Scale is the first instrument to measure the concept. Using a cross-sectional design and data from 210 novice NPs, the purpose of this study was to confirm the NNPRT Scale's internal factor structure via confirmatory factor analysis (CFA).

Posted: | Hanin Rashid, Christopher Runyon, Jesse Burk-Rafel, Monica M. Cuddy, Liselotte Dyrbye, Katie Arnhart, Ulana Luciw-Dubas, Hilit F. Mechaber, Steve Lieberman, Miguel Paniagua

Academic Medicine: Volume 97 - Issue 11S - Page S176

 

As Step 1 begins to transition to pass/fail, it is interesting to consider the impact of score goal on wellness. This study examines the relationship between goal score, gender, and students’ self-reported anxiety, stress, and overall distress immediately following their completion of Step 1.

Posted: | Jennifer L. Swails, Steven Angus, Michael Barone, Jessica Bienstock, Jesse Burk-Rafel, Michelle Roett, Karen E. Hauer

Academic Medicine: Volume 98 - Issue 2 - Pages 180-187

 

This article describes the work of the Coalition for Physician Accountability’s Undergraduate Medical Education to Graduate Medical Education Review Committee (UGRC) to apply a quality improvement approach and systems thinking to explore the underlying causes of dysfunction in the undergraduate medical education (UME) to graduate medical education (GME) transition.

Posted: | Erfan Khalaji, Sukru Eraslan, Yeliz Yesilada, Victoria Yaneva

Behavior & Information Technology

 

This study builds upon prior work in this area that focused on developing a machine-learning classifier trained on gaze data from web-related tasks to detect ASD in adults. Using the same data, we show that a new data pre-processing approach, combined with an exploration of the performance of different classification algorithms, leads to an increased classification accuracy compared to prior work.

Posted: | Chunyan Liu, Dan Jurich

Applied Psychological Measurement: Volume 47, issue 1, page(s) 34-47

 

This study used simulation to investigate the performance of the t-test method in detecting outliers and compared its performance with other outlier detection methods, including the logit difference method with 0.5 and 0.3 as the cutoff values and the robust z statistic with 2.7 as the cutoff value.