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Differential Item Functioning Analysis of United States Medical Licensing Examination Step 1 Items

Dados Bibliográficos

ID21612901
AutoresJonathan D Rubright (J.D. Rubrightis vice president, Office of Research Strategy, National Board of Medical Examiners, Philadelphia, Pennsylvania., autor correspondente), Michael Jodoin (M. Jodoinis vice president, United States Medical Licensing Examination, National Board of Medical Examiners, Philadelphia, Pennsylvania.), Michael G Jodoin (National Board of Medical Examiners), Stephanie Woodward (S. Woodwardis data analyst III, National Board of Medical Examiners, Philadelphia, Pennsylvania.), MICHAEL BARONE (0000-0002-4724-784X, M.A. Baroneis vice president, Competency Based Assessment, National Board of Medical Examiners, Philadelphia, Pennsylvania.)
Ano2022
Volume97
Fascículo5
Páginas718-722
Data de publicação2022-05-01
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoAcademic Medicine (JOURNAL)
Identificadores do periódicoISSN: 1040-2446 • E-ISSN: 1938-808X
EditoraOxford University Press (OUP) (PUBLISHER)
DOI10.1097/acm.0000000000004567
PMID34907964
OpenAlexW4200078168
IdiomaEN
Referências citadas11

PURPOSE: Previous studies have examined and identified demographic group score differences on United States Medical Licensing Examination (USMLE) Step examinations. It is necessary to explore potential etiologies of such differences to ensure fairness of examination use. Although score differences are largely explained by preceding academic variables, one potential concern is that item-level bias may be associated with remaining group score differences. The purpose of this 2019-2020 study was to statistically identify and qualitatively review USMLE Step 1 exam questions (items) using differential item functioning (DIF) methodology. METHOD: Logistic regression DIF was used to identify and classify the effect size of DIF on Step 1 items meeting minimum sample size criteria. After using DIF to flag items statistically, subject matter expert (SME) review was used to identify potential reasons why items may have performed differently between racial and gender groups, including characteristics such as content, format, wording, context, or stimulus materials. USMLE SMEs reviewed items to identify the group difference they believed was present, if any; articulate a rationale behind the group difference; and determine whether that rationale would be considered construct relevant or construct irrelevant. RESULTS: All identified DIF rationales were relevant to the constructs being assessed and therefore did not reflect item bias. Where SME-generated rationales aligned with statistical differences (flags), they favored self-identified women on items tagged to women's health content categories and were judged to be construct relevant. CONCLUSIONS: This study did not find evidence to support the hypothesis that group-level performance differences beyond those explained by prior academic performance variables are driven by item-level bias. Health professions examination programs have an obligation to assess for group differences, and when present, investigate to what extent, if any, measurement bias plays a role

Construct validity · Differential item functioning · Item response theory · Logistic regression · Medical education · Medical school · Psychometrics · United States Medical Licensing Examination · Applied Psychology · Clinical Psychology · Computer Science · Innovations in Medical Education · Medical Education and Admissions · Medicine · Psychology · Psychometric Methodologies and Testing · Social Psychology

  • Detecting Differential Item Functioning Using Logistic Regression Procedures

    Open Access•Hariharan Swaminathan, H Jane Rogers•Journal of Educational Measurement•1990

  • Using Statistical Procedures to Identify Differentially Functioning Test Items

    Open Access•Brian E Clauser, Kathleen M Mazor•Educational Measurement: Issues…•1998

  • The association of USMLE Step 1 and Step 2 CK scores with residency match specialty and location

    Open Access•Jacqueline L Gauer, J Brooks Jackson•Medical Education Online•2017

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