The validity of a behavioural multiple-mini-interview within an assessment centre for selection into specialty training
Open accessAbstract
BACKGROUND: Entry into specialty training was determined by a National Assessment Centre (NAC) approach using a combination of a behavioural Multiple-Mini-Interview (MMI) and a written Situational Judgement Test (SJT). We wanted to know if interviewers could make reliable and valid decisions about the non-cognitive characteristics of candidates with the purpose of selecting them into general practice specialty training using the MMI. Second, we explored the concurrent validity of the MMI with the SJT. METHODS: A variance components analysis estimated the reliability and sources of measurement error. Further modelling estimated the optimal configurations for future MMI iterations. We calculated the relationship of the MMI with the SJT. RESULTS: Data were available from 1382 candidates, 254 interviewers, six MMI questions, five alternate forms of a 50-item SJT, and 11 assessment centres. For a single MMI question and one assessor, 28% of the variance between scores was due to candidate-to-candidate variation. Interviewer subjectivity, in particular the varying views that interviewer had for particular candidates accounted for 40% of the variance in scores. The generalisability co-efficient for a six question MMI was 0.7; to achieve 0.8 would require ten questions. A disattenuated correlation with the SJT (r = 0.35), and in particular a raw score correlation with the subdomain related to clinical knowledge (r = 0.25) demonstrated evidence for construct and concurrent validity. Less than two per cent of candidates would have failed the MMI. CONCLUSION: The MMI is a moderately reliable method of assessment in the context of a National Assessment Centre approach. The largest source of error relates to aspects of interviewer subjectivity, suggesting enhanced interviewer training would be beneficial. MMIs need to be sufficiently long for precise comparison for ranking purposes. In order to justify long term sustainable use of the MMI in a postgraduate assessment centre approach, more theoretical work is required to understand how written and performance based test of non-cognitive attributes can be combined, in a way that achieves acceptable generalizability, and has validity.
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In Roberts et al. (2014), the generalizability coefficient for a six-question MMI was 0.7; to achieve 0.8 would require ten questions.
“The generalizability co-efficient for a six question MMI was 0.7; to achieve 0.8 would require ten questions.”
From Multiple Mini Interview as an admission tool in higher education: Insights from a systematic review (2019) · cites this paper as Roberts C. et al., (58) 2014
In Roberts et al. (2014), for a single MMI question and one assessor, 28% of the variance between scores was due to candidate-to-candidate variation.
“For a single MMI question and one assessor, 28% of the variance between scores was due to candidate-to-candidate variation.”
From Multiple Mini Interview as an admission tool in higher education: Insights from a systematic review (2019) · cites this paper as Roberts C. et al., (58) 2014
In Roberts et al. (2014), the varying views that interviewers had for particular candidates accounted for 40% of the variance in scores.
“The varying views that interviewer had for particular candidates accounted for 40% of the variance in scores.”
From Multiple Mini Interview as an admission tool in higher education: Insights from a systematic review (2019) · cites this paper as Roberts C. et al., (58) 2014
In Roberts et al. (2014), a disattenuated correlation with the SJT (r=0.35), and a raw score correlation with the subdomain related to clinical knowledge (r=0.25), demonstrated evidence for construct and concurrent validity.
“A disattenuated correlation with the SJT (r = 0.35), and in particular a raw score correlation with the subdomain related to clinical knowledge (r = 0.25) demonstrated evidence for construct and concurrent validity.”
From Multiple Mini Interview as an admission tool in higher education: Insights from a systematic review (2019) · cites this paper as Roberts C. et al., (58) 2014
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- Authors
- Roberts, C., Clark, T., Burgess, A., Frommer, M., Grant, M., & Mossman, K.
- Affiliations
- The University of Sydney (AU)
- Corresponding author
- Roberts, Chris
- Venue
- BMC Medical Education
- Published
- 2014-08-13
- Volume
- 14
- Issue
- 1
- Pages
- 169-169
- ISSN
- 1472-6920 (ISSN-L)
- PMC
- PMC4136634
- OpenAlex
- W2121365658
- Cited by
- 49
- References
- 45
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 1 · 2023: 3 · 2022: 1 · 2021: 5 · 2020: 5 · 2019: 6 · 2018: 11 · 2017: 4 · 2016: 3 · 2015: 4 · 2014: 1
- FWCI
- 3.96
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- BMC Medical Education (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- The Sydney eScholarship Repository (The University of Sydney) (submittedVersion)
- Funders
- University of Sydney
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Medical Education and Admissions
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
- Keywords
- multiple mini-interviews, situational judgment tests, assessment centers, measurement reliability, concurrent validity, construct validity, generalizability coefficient, non-cognitive skills, variance component analysis
- MeSH terms
- Adult, Aged, Australia, Clinical Competence, Education, Medical, Female, Humans, Interviews as Topic, Judgment, Male, Medicine, Middle Aged, School Admission Criteria, Reproducibility of Results, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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