RESEARCH LIBRARY
RESEARCH LIBRARY
View the latest publications from members of the NBME research team
JMIR Medical Education: Volume 8 - Issue 2 - e30988
This article aims to compare the reliability of two assessment groups (crowdsourced laypeople and patient advocates) in rating physician error disclosure communication skills using the Video-Based Communication Assessment app.
JMIR Medical Education: Volume 8 , Issue 4
The Video-based Communication Assessment (VCA) app is a novel tool for simulating communication scenarios for practice and obtaining crowdsourced assessments and feedback on physicians’ communication skills. This article aims to evaluate the efficacy of using VCA practice and feedback as a stand-alone intervention for the development of residents’ error disclosure skills.
Evaluation & the Health Professions: Volume: 43 issue: 3, page(s): 149-158
This study examines the innovative and practical application of DCM framework to health professions educational assessments using retrospective large-scale assessment data from the basic and clinical sciences: National Board of Medical Examiners Subject Examinations in pathology (n = 2,006) and medicine (n = 2,351).
Medical Teacher: Volume 40 - Issue 8 - p 838-841
Adaptive learning requires frequent and valid assessments for learners to track progress against their goals. This study determined if multiple-choice questions (MCQs) “crowdsourced” from medical learners could meet the standards of many large-scale testing programs.
Applied Psychological Measurement: Volume: 42 issue: 4, page(s): 291-306
The research presented in this article combines mathematical derivations and empirical results to investigate effects of the nonparametric anchoring vignette approach proposed by King, Murray, Salomon, and Tandon on the reliability and validity of rating data. The anchoring vignette approach aims to correct rating data for response styles to improve comparability across individuals and groups.
Applied Psychological Measurement: Volume: 42 issue: 8, page(s): 595-612
Conventional methods for evaluating the utility of subscores rely on reliability and correlation coefficients. However, correlations can overlook a notable source of variability: variation in subtest means/difficulties. Brennan introduced a reliability index for score profiles based on multivariate generalizability theory, designated as G, which is sensitive to variation in subtest difficulty. However, there has been little, if any, research evaluating the properties of this index. A series of simulation experiments, as well as analyses of real data, were conducted to investigate G under various conditions of subtest reliability, subtest correlations, and variability in subtest means.