Predictive validity of the multiple mini‐interview for selecting medical trainees
Bibliographic record
Abstract
INTRODUCTION: In this paper we report on further tests of the validity of the multiple mini-interview (MMI) selection process, comparing MMI scores with those achieved on a national high-stakes clinical skills examination. We also continue to explore the stability of candidate performance and the extent to which so-called 'cognitive' and 'non-cognitive' qualities should be deemed independent of one another. METHODS: To examine predictive validity, MMI data were matched with licensing examination data for both undergraduate (n = 34) and postgraduate (n = 22) samples of participants. To assess the stability of candidate performance, reliability coefficients were generated for eight distinct samples. Finally, correlations were calculated between 'cognitive' and 'non-cognitive' measures of ability collected in the admissions procedure, on graduation from medical school and 18 months into postgraduate training. RESULTS: The median reliability of eight administrations of the MMI in various cohorts was 0.73 when 12 10-minute stations were used with one examiner per station. The correlation between performance on the MMI and number of stations passed on an objective structured clinical examination-based licensing examination was r = 0.43 (P < 0.05) in a postgraduate sample and r = 0.35 (P < 0.05) in an undergraduate sample of subjects who sat the MMI 5 years prior to sitting the licensing examination. The correlation between 'cognitive' and 'non-cognitive' assessment instruments increased with time in training (i.e. as the focus of the assessments became more tailored to the clinical practice of medicine). DISCUSSION: Further evidence for the validity of the MMI approach to making admissions decisions has been provided. More generally, the reported findings cast further doubt on the extent to which performance can be captured with trait-based models of ability. Finally, although a complementary predictive relationship has consistently been observed between grade point average and MMI results, the extent to which cognitive and non-cognitive qualities are distinct appears to depend on the scope of practice within which the two classes of qualities are assessed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".