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Candidate Evaluation Using Targeted Construct Assessment in the Multiple Mini-Interview: A Multifaceted Rasch Model

Jacqueline E McLaughlin1, David Singer2, Wendy C Cox3

  • 1a Office of Strategic Planning and Assessment, UNC Eshelman School of Pharmacy, UNC Chapel Hill , North Carolina , USA.

Teaching and Learning in Medicine
|July 29, 2016
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Summary
This summary is machine-generated.

This study evaluated a 7-station multiple mini-interview (MMI) circuit for assessing health professions candidates. The multifaceted Rasch measurement analysis showed that candidate ability and interviewer severity explained most rating variance, indicating a viable assessment tool.

Keywords:
MFRMMultiple mini-interviewRasch modelingadmissionsstudent selection

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Area of Science:

  • Medical Education
  • Psychometrics
  • Health Professions Training

Background:

  • Multiple Mini-Interview (MMI) circuits are used for candidate assessment in health professions.
  • Minimizing construct-irrelevant variance in MMI is crucial for effective candidate selection.
  • Improving MMI validity enhances the identification of successful future health professionals.

Purpose of the Study:

  • To assess the validity and reliability of a 7-station Multiple Mini-Interview (MMI) circuit.
  • To evaluate the performance of MMI stations in assessing specific candidate constructs.
  • To apply multifaceted Rasch measurement analysis to MMI data.

Main Methods:

  • A 7-station MMI circuit was administered to 214 candidates, with 37 interviewers providing 1,498 ratings.
  • MMI stations targeted specific constructs: adaptability, empathy, integrity, critical thinking, and teamwork.
  • A 3-facet multifaceted Rasch measurement analysis was employed to analyze candidate ability, interviewer severity, and station difficulty.

Main Results:

  • The Rasch model accounted for 62.84% of the variance in MMI ratings.
  • Candidate ability explained 45.28% of the variance, while interviewer severity explained 16.09%.
  • Interviewer and station parameters demonstrated acceptable fit within the Rasch model.

Conclusions:

  • The study provides evidence for the acceptable fit of the multifaceted Rasch measurement model to MMI data in pharmacy education.
  • This research offers valuable insights for developing robust MMI tools for institutional decision-making.
  • The findings support the use of MMI for meaningful candidate assessment in health professions.