title: Evidence regarding the utility of multiple mini-interview (MMI) for selection to undergraduate health programs: A BEME systematic review: BEME Guide No. 37.
abstract: BACKGROUND
  In the 11 years since its development at McMaster University Medical School, the multiple mini-interview (MMI) has become a popular selection tool. We aimed to systematically explore, analyze and synthesize the evidence regarding MMIs for selection to undergraduate health programs.
  
  
  METHODS
  The review protocol was peer-reviewed and prospectively registered with the Best Evidence Medical Education (BEME) collaboration. Thirteen databases were searched through 34 terms and their Boolean combinations. Seven key journals were hand-searched since 2004. The reference sections of all included studies were screened. Studies meeting the inclusion criteria were coded independently by two reviewers using a modified BEME coding sheet. Extracted data were synthesized through narrative synthesis.
  
  
  RESULTS
  A total of 4338 citations were identified and screened, resulting in 41 papers that met inclusion criteria. Thirty-two studies report data for selection to medicine, six for dentistry, three for veterinary medicine, one for pharmacy, one for nursing, one for rehabilitation, and one for health science. Five studies investigated selection to more than one profession. MMIs used for selection to undergraduate health programs appear to have reasonable feasibility, acceptability, validity, and reliability. Reliability is optimized by including 7-12 stations, each with one examiner. The evidence is stronger for face validity, with more research needed to explore content validity and predictive validity. In published studies, MMIs do not appear biased against applicants on the basis of age, gender, or socio-economic status. However, applicants of certain ethnic and social backgrounds did less well in a very small number of published studies. Performance on MMIs does not correlate strongly with other measures of noncognitive attributes, such as personality inventories and measures of emotional intelligence.
  
  
  CONCLUSIONS
  MMI does not automatically mean a more reliable selection process but it can do, if carefully designed. Effective MMIs require careful identification of the noncognitive attributes sought by the program and institution. Attention needs to be given to the number of stations, the blueprint and examiner training.
  
  
  CONCLUSIONS
  More work is required on MMIs as they may disadvantage groups of certain ethnic or social backgrounds. There is a compelling argument for multi-institutional studies to investigate areas such as the relationship of MMI content to curriculum domains, graduate outcomes, and social missions; relationships of applicants' performance on different MMIs; bias in selecting applicants of minority groups; and the long-term outcomes appropriate for studies of predictive validity.
authors.affiliation: a School of Medicine , Keele University , North Staffordshire , UK ;|b University Hospitals of North Midlands NHS Trust , North Staffordshire , UK ;
authors.forename: Eliot L
authors.initials: EL
authors.lastname: Rees
authors.affiliation: b University Hospitals of North Midlands NHS Trust , North Staffordshire , UK ;
authors.forename: Ashley W
authors.initials: AW
authors.lastname: Hawarden
authors.affiliation: a School of Medicine , Keele University , North Staffordshire , UK ;
authors.forename: Gordon
authors.initials: G
authors.lastname: Dent
authors.affiliation: c School of Medicine, University of Tasmania , Hobart , Australia ;
authors.forename: Richard
authors.initials: R
authors.lastname: Hays
authors.affiliation: d Centre for Health Education Scholarship , University of British Columbia , Vancouver , Canada.
authors.forename: Joanna
authors.initials: J
authors.lastname: Bates
authors.affiliation: a School of Medicine , Keele University , North Staffordshire , UK ;|b University Hospitals of North Midlands NHS Trust , North Staffordshire , UK ;
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Hassell
mesh_terms: D002755:Choice Behavior; D016208:Databases, Factual; D004504:Education, Medical, Undergraduate; D017408:Guidelines as Topic; D006801:Humans; D007407:Interviews as Topic; D012570:School Admission Criteria