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A Hybrid Interview Model for Medical School Interviews: Combining Traditional and Multisampling Formats
Nikki L Bibler Zaidi1, Sally A Santen, Joel A Purkiss
1N.L. Bibler Zaidi is assistant director of evaluation and assessment, Office of Medical Student Education, University of Michigan Medical School, Ann Arbor, Michigan. S.A. Santen is assistant dean for educational research and quality improvement, Office of Medical Student Education, and associate professor and chair of education, Department of Emergency Medicine, University of Michigan Medical School, Ann Arbor, Michigan. J.A. Purkiss is director of evaluation and assessment, Office of Medical Student Education, and research investigator, Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, Michigan. C.A. Teener is director of admissions, Office of Medical Student Education, University of Michigan Medical School, Ann Arbor, Michigan. S.E. Gay is assistant dean for admissions, Office of Medical Student Education, and assistant professor, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan.
Problem:
Most medical schools have either retained a traditional admissions interview or fully adopted an innovative, multisampling format (e.g., the multiple mini-interview) despite there being advantages and disadvantages associated with each format.
Approach:
The University of Michigan Medical School (UMMS) sought to maximize the strengths associated with both interview formats after recognizing that combining the two approaches had the potential to capture additional, unique information about an applicant. In September 2014, the UMMS implemented a hybrid interview model with six, 6-minute short-form interviews-highly structured scenario-based encounters-and two, 30-minute semistructured long-form interviews. Five core skills were assessed across both interview formats.
Outcomes:
Overall, applicants and admissions committee members reported favorable reactions to the hybrid model, supporting continued use of the model. The generalizability coefficients for the six-station short-form and the two-interview long-form formats were estimated to be 0.470 and 0.176, respectively. Different skills were more reliably assessed by different interview formats. Scores from each format seemed to be operating independently as evidenced through moderate to low correlations (r = 0.100-0.403) for the same skills measured across different interview formats; however, after correcting for attenuation, these correlations were much higher.
Next Steps:
This hybrid model will be revised and optimized to capture the skills most reliably assessed by each format. Future analysis will examine validity by determining whether short-form and long-form interview scores accurately measure the skills intended to be assessed. Additionally, data collected from both formats will be used to establish baselines for entering students' competencies.
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