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

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Equitable assessment in medical training values learner identity and growth over peer comparison. This supports an anti-deficit model to enhance diversity and inclusion in medicine.

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Area of Science:

  • Medical Education
  • Health Equity
  • Physician Workforce Development

Background:

  • Equitable assessment in clinical settings is crucial for a diverse physician workforce.
  • Understanding learner preferences informs quality medical education and addresses healthcare disparities.

Purpose of the Study:

  • To gather evidence for a model of equitable assessment in clinical training.
  • To apply the Anti-Deficit Achievement framework to medical education assessment.

Main Methods:

  • A discrete choice experiment with 306 medical students and residents across 9 US institutions.
  • An instrument with 6 attributes at 2 levels assessed learner preferences for equitable assessment components.
  • A mixed-effects logit model identified the most valued assessment attributes.

Main Results:

  • Learners prioritized appreciation of identity, background, and trajectory, supervisor bias training, and narrative assessments over peer comparison.
  • No significant differences in attribute value were found between underrepresented in medicine (UIM) and non-UIM learners.
  • Residents placed higher value on supervisor recognition of learner identity and bias training compared to medical students.

Conclusions:

  • Findings support an anti-deficit model for equity in medical assessment.
  • This research informs initiatives to promote UIM learner success.
  • The study guides equity, diversity, and inclusion efforts in medical education.