Interviews, Multiple Mini-Interviews, and Selection Centers

Knorr, Mirjana; Hissbach, Johanna; Hampe, Wolfgang

doi:10.1007/978-3-319-94971-0_5

Cited by 4 publications

(7 citation statements)

References 91 publications

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“…The larger dataset in this current study also included some cases of students who were rejected at their first MMI attempt but were admitted in the following years, which might have lessened the effect of range restriction. On the other hand, we did find a positive relationship between MMI and OSCE overall performance in the previous study [7], which was not replicated in this study. Future studies focusing on the validity of the Hamburg MMI should therefore take possible cohort effects into account.…”

Section: Discussioncontrasting

confidence: 99%

“…Results are ambiguous, with some institutions reporting significant differences in MMI performance based on gender, age or other variables, while other studies have found no such differences [6]. In our summary of the latest MMI research, we concluded that these heterogeneous findings most likely stem from the different MMI designs and should be further explored [7]. Likewise, in their recent systematic review of MMIs for undergraduate student selection, Rees et al [3] recommended further exploration of the performance of minority groups and possible bias in MMIs.…”

Section: Introductionmentioning

confidence: 84%

“…We chose OSCE results as the criterion for predictive fairness because they have proven to be the most consistent criterion for analysing the predictive validity of MMIs [7] and we were previously able to demonstrate this relationship for the Hamburg MMI in particular [13].…”

Section: Introductionmentioning

confidence: 99%

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Exploring sociodemographic subgroup differences in multiple mini-interview (MMI) performance based on MMI station type and the implications for the predictive fairness of the Hamburg MMI

et al. 2019

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Background Sociodemographic subgroup differences in multiple mini-interview (MMI) performance have been extensively studied within the MMI research literature, but heterogeneous findings demand a closer look at how specific aspects of MMI design (such as station type) affect these differences. So far, it has not been investigated whether sociodemographic subgroup differences imply that an MMI is biased , particularly in terms of its predictive validity. Methods Between 2010 and 2017, the University Medical Centre Hamburg-Eppendorf (UKE) tested 1438 candidates in an MMI who also provided sociodemographic data and agreed to participate in this study. Out of these, 400 candidates were admitted and underwent a first objective structured clinical examination (OSCE) after one and a half years, including one station assessing communication skills. First, we analyzed the relationship between gender, age, native language and medical family background and MMI station performance including interaction terms with MMI station type (simulation, interview, and group) in a hierarchical linear model. Second, we tested whether the prediction of OSCE overall and communication station performance in particular differed depending on sociodemographic background by adding interaction terms between MMI performance and gender, age and medical family background in a linear regression model. Results Young female candidates performed better than young male candidates both at interview and simulation stations. The gender difference was smaller (simulation) or non-significant (interview) in older candidates. There were no gender or age effects in MMI group station performance. All effects were very small, with the overall model explaining only 0.6% of the variance. MMI performance was not related to OSCE overall performance but significantly predicted OSCE communication station performance with no differences in the prediction for sociodemographic subgroups. Conclusions The Hamburg MMI is fair in its prediction of OSCE communication scores. Differences in MMI station performance for gender and age and their interaction with MMI station type can be related to the dimensions assessed at different station types and thus support the validity of the MMI. Rather than being threats to fairness, these differences could be useful for decisions relating to the design and use of an MMI.

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Section: Discussioncontrasting

confidence: 99%

Section: Introductionmentioning

confidence: 84%

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Exploring sociodemographic subgroup differences in multiple mini-interview (MMI) performance based on MMI station type and the implications for the predictive fairness of the Hamburg MMI

et al. 2019

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“…They were first implemented at McMaster for medical school selection in 2002 [ 2 ] and were designed to reduce the context specificity observed with traditional interviews. They generally consist of a series of short structured or semi-structured interviews or role-plays with actors [ 3 ] and, depending on their implementation parameters, may show conceptual overlap with Assessment Centers (AC), which also have multiple components aimed to assess specific behaviors [ 4 ]. Since MMIs are usually a very high-stake assessment tool, evidence for their validity is of the utmost importance.…”

Section: Introductionmentioning

confidence: 99%

“…The goal is to provide evidence related to 1) how the instrument was developed (content and scoring), 2) the accuracy or stability of the scores obtained (reliability and generalizability), 3) the constructs that are assessed and possible sources of unwanted variance (extrapolation) and 4) the credibility and implications of the decisions that flow from the process [6,7]. A recent review suggested that more data was needed regarding the construct validity evidence of MMI [4], which consists mostly of extrapolation validity evidence in Kane's framework.…”

Section: Introductionmentioning

confidence: 99%

Are different station formats assessing different dimensions in multiple mini-interviews? Findings from the Canadian integrated French multiple mini-interviews

et al. 2022

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Background Multiple mini-interviews (MMI) are used to assess non-academic attributes for selection in medicine and other healthcare professions. It remains unclear if different MMI station formats (discussions, role-plays, collaboration) assess different dimensions. Methods Based on station formats of the 2018 and 2019 Integrated French MMI (IFMMI), which comprised five discussions, three role-plays and two collaboration stations, the authors performed confirmatory factor analysis (CFA) using the lavaan 0.6-5 R package and compared a one-factor solution to a three-factor solution for scores of the 2018 (n = 1438) and 2019 (n = 1440) cohorts of the IFMMI across three medical schools in Quebec, Canada. Results The three-factor solution was retained, with discussions, role-plays and collaboration stations all loading adequately with their scores. Furthermore, all three factors had moderate-to-high covariance (range 0.44 to 0.64). The model fit was also excellent with a Comparative fit index (CFI) of 0.983 (good if > 0.9), a Tucker Lewis index of 0.976 (good if > 0.95), a Standardized Root Mean Square Residual of 0.021 (good if < .08) and a Root Mean Square Error of 0.023 (good if < 0.08) for 2018 and similar results for 2019. In comparison, the single factor solution presented a lower fit (CFI = 0.819, TLI = 0.767, SRMR = 0.049 and RMSEA = 0.070). Conclusions The IFMMI assessed three dimensions that were related to stations formats, a finding that was consistent across two cohorts. This suggests that different station formats may be assessing different skills, and has implications for the choice of appropriate reliability metrics and the interpretation of scores. Further studies should try to characterize the underlying constructs associated with each station format and look for differential predictive validity according to these formats.

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Interactional competencies in medical student admission– what makes a “good medical doctor”?

Fleck,

Amelung,

Fuchs

et al. 2024

Adv in Health Sci Educ

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Doctors’ interactional competencies play a crucial role in patient satisfaction, well-being, and compliance. Accordingly, it is in medical schools’ interest to select candidates with strong interactional abilities. While Multiple Mini Interviews (MMIs) provide a useful context to assess such abilities, the evaluation of candidate performance during MMIs is not always based on a solid theoretical framework. The newly developed selection procedure “Interactional Competencies – Medical Doctors (IC-MD)” uses an MMI circuit with five simulation patient scenarios and is rated based on the theoretically and empirically grounded construct of emotional availability. A first validation study with N = 70 first-semester medical students took place in 2021. In terms of convergent validity, IC-MD ratings showed strong correlations with simulation patients’ satisfaction with the encounter (r =.57) but no association with emotional intelligence measures. IC-MD ratings were not related to high school performance or a cognitive student aptitude test, indicating divergent validity. Inter-rater reliability (ICC = 0.63) and generalizability (Eρ2 = 0.64) were satisfactory. The IC-MD proved to be fair regarding participants’ age and gender. Participants with prior work experience in healthcare outperformed those without such experience. Participant acceptance of the procedure were good. The IC-MD is a promising selection procedure capable of assessing interactional competencies relevant to the medical setting. Measures of interactional competencies can complement the use of cognitive selection criteria in medical student admission. The predictive validity of the IC-MD needs to be addressed in future studies.

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Interviews, Multiple Mini-Interviews, and Selection Centers

Cited by 4 publications

References 91 publications

Exploring sociodemographic subgroup differences in multiple mini-interview (MMI) performance based on MMI station type and the implications for the predictive fairness of the Hamburg MMI

Exploring sociodemographic subgroup differences in multiple mini-interview (MMI) performance based on MMI station type and the implications for the predictive fairness of the Hamburg MMI

Are different station formats assessing different dimensions in multiple mini-interviews? Findings from the Canadian integrated French multiple mini-interviews

Interactional competencies in medical student admission– what makes a “good medical doctor”?

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