Developing Evidence for Equitable Assessment Characteristics Based on Clinical Learner Preferences Using Discrete Choice Experiments-Reference-Cited by-同舟云学术

Developing Evidence for Equitable Assessment Characteristics Based on Clinical Learner Preferences Using Discrete Choice Experiments

Published:2023-08-01 Issue:11S Volume:98 Page:S108-S115
ISSN:1040-2446
Container-title:Academic Medicine
language:en
Short-container-title:

Author:

Perez Sandra¹,Schwartz Alan²,Hauer Karen E.³,Karani Reena⁴,Hirshfield Laura E.⁵,McNamara Margaret⁶,Henry Duncan⁷,Lupton Katherine L.⁸,Woods Majka⁹,Teherani Arianne¹⁰

Affiliation:

1. S. Perezis a resident, Department of Pathology, University of California, San Francisco, School of Medicine, San Francisco, California.

2. A. Schwartzis the Michael Reese Endowed Professor of Medical Education, Department of Medical Education, and research professor, Department of Pediatrics, University of Illinois at Chicago, Chicago, Illinois, and director, Association of Pediatric Program Directors Longitudinal Educational Assessment Research Network (APPD LEARN), McLean, Virginia; ORCID:.

3. K.E. Haueris professor, Department of Medicine, and associate dean for competency assessment and professional standards, University of California, San Francisco, School of Medicine, San Francisco, California; ORCID:.

4. R. Karaniis professor, Departments of Medicine, Medical Education, and Geriatrics and Palliative Medicine, and director, Institute for Medical Education, Icahn School of Medicine at Mount Sinai, New York, New York.

5. L.E. Hirshfieldis the Dr. Georges Bordage Medical Education Faculty Scholar, associate professor, PhD program codirector, and associate director of graduate studies, Department of Medical Education, University of Illinois College of Medicine, Chicago, Illinois; ORCID:.

6. M. McNamarais professor, Department of Pediatrics, and pediatric residency program director, University of California, San Francisco, School of Medicine, San Francisco, California.

7. D. Henryis associate professor, Department of Pediatrics, University of California, San Francisco, School of Medicine, San Francisco, California.

8. K.L. Luptonis professor, Department of Medicine, University of California, San Francisco, School of Medicine, San Francisco, California.

9. M. Woodsholds the Dibrell Family Professorship in the Art of Medicine, and is assistant professor, Department of Surgery, and vice dean for academic affairs, John Sealy School of Medicine at the University of Texas Medical Branch, Galveston, Texas.

10. A. Teheraniis professor, Department of Medicine, education scientist, Center for Faculty Educators, director of program evaluation and education continuous quality improvement, and founding codirector, University of California Center for Climate Health and Equity, University of California, San Francisco, School of Medicine, San Francisco, California; ORCID:.

Abstract

Purpose Medical education is only beginning to explore the factors that contribute to equitable assessment in clinical settings. Increasing knowledge about equitable assessment ensures a quality medical education experience that produces an excellent, diverse physician workforce equipped to address the health care disparities facing patients and communities. Through the lens of the Anti-Deficit Achievement framework, the authors aimed to obtain evidence for a model for equitable assessment in clinical training. Method A discrete choice experiment approach was used which included an instrument with 6 attributes each at 2 levels to reveal learner preferences for the inclusion of each attribute in equitable assessment. Self-identified underrepresented in medicine (UIM) and not underrepresented in medicine (non-UIM) (N = 306) fourth-year medical students and senior residents in medicine, pediatrics, and surgery at 9 institutions across the United States completed the instrument. A mixed-effects logit model was used to determine attributes learners valued most. Results Participants valued the inclusion of all assessment attributes provided except for peer comparison. The most valued attribute of an equitable assessment was how learner identity, background, and trajectory were appreciated by clinical supervisors. The next most valued attributes were assessment of growth, supervisor bias training, narrative assessments, and assessment of learner’s patient care, with participants willing to trade off any of the attributes to get several others. There were no significant differences in value placed on assessment attributes between UIM and non-UIM learners. Residents valued clinical supervisors valuing learner identity, background, and trajectory and clinical supervisor bias training more so than medical students. Conclusions This study offers support for the components of an antideficit-focused model for equity in assessment and informs efforts to promote UIM learner success and guide equity, diversity, and inclusion initiatives in medical education.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Education,General Medicine

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