Multiple mini-interviews: same concept, different approaches

Increasing numbers of educational institutions in the medical field choose to replace their conventional admissions interviews with a multiple mini-interview (MMI) format because the latter has superior reliability values and reduces interviewer bias. As the MMI format can be adapted to the conditions of each institution, the question of under which circumstances an MMI is most expedient remains unresolved. This article systematically reviews the existing MMI literature to identify the aspects of MMI design that have impact on the reliability, validity and cost-efficiency of the format.

Three electronic databases (OVID, PubMed, Web of Science) were searched for any publications in which MMIs and related approaches were discussed. Sixty-six publications were included in the analysis.

Forty studies reported reliability values. Generally, raising the number of stations has more impact on reliability than raising the number of raters per station. Other factors with positive influence include the exclusion of stations that are too easy, and the use of normative anchored rating scales or skills-based rater training. Data on criterion-related validities and analyses of dimensionality were found in 31 studies. Irrespective of design differences, the relationship between MMI results and academic measures is small to zero. The McMaster University MMI predicts in-programme and licensing examination performance. Construct validity analyses are mostly exploratory and their results are inconclusive. Seven publications gave information on required resources or provided suggestions on how to save costs. The most relevant cost factors that are additional to those of conventional interviews are the costs of station development and actor payments.

The MMI literature provides useful recommendations for reliable and cost-efficient MMI designs, but some important aspects have not yet been fully explored. More theory-driven research is needed concerning dimensionality and construct validity, the predictive validity of MMIs other than those of McMaster University, the comparison of station types, and a cost-efficient station development process.