Effect of station format on the psychometric properties of Multiple Mini Interviews
Bibliographic record
Abstract
BACKGROUND: Given the widespread use of Multiple Mini Interviews (MMIs), their impact on the selection of candidates and the considerable resources invested in preparing and administering them, it is essential to ensure their quality. Given the variety of station formats used and the degree to which that factor resides in the control of training programmes that we know so little about, format's effect on MMI quality is a considerable oversight. This study assessed the effect of two popular station formats (interview vs. role-play) on the psychometric properties of MMIs. METHODS: We analysed candidate data from the first 8 years of the Integrated French MMIs (IF-MMI) (2010-2017, n = 11 761 applicants), an MMI organised yearly by three francophone universities and administered at four testing sites located in two Canadian provinces. There were 84 role-play and 96 interview stations administered, totalling 180 stations. Mixed design analyses of variance (ANOVAs) were used to test the effect of station format on candidates' scores and stations' discrimination. Cronbach's alpha coefficients for interview and role-play stations were also compared. Predictive validity of both station formats was estimated with a mixed multiple linear regression model testing the relation between interview and role-play scores with average clerkship performance for those who gained entry to medical school (n = 462). RESULTS: Role-play stations (M = 20.67, standard deviation [SD] = 3.38) had a slightly lower mean score than interview stations (M = 21.36, SD = 3.08), p < 0.01, Cohen's d = 0.2. The correlation between role-play and interview stations scores was r = 0.5 (p < 0.01). Discrimination coefficients, Cronbach's alpha and predictive validity statistics did not vary by station format. CONCLUSION: Interview and role-play stations have comparable psychometric properties, suggesting format to be interchangeable. Programmes should select station format based on match to the personal qualities for which they are trying to select.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".