A Comparison of Behavioral and Multiple Mini-Interview Formats in Physician Assistant Program Admissions
Bibliographic record
Abstract
PURPOSE: The interview remains a widely used tool in health professions program admissions. The purpose of this study was to compare the use of a behavioral interview format with the multiple mini-interview format in measuring desired noncognitive behaviors. METHODS: This dual cohort, observational, comparative study used a polytomous rating-scale model to analyze the results from two homogeneous groups of physician assistant (PA) program applicants (total N = 176). One group (n = 93) participated in two 20-minute behavioral interviews conducted by two raters per interviewee. The behavioral format included questions related to past behaviors and performance as a way to identify latent professionalism characteristics. The second group (n = 83) completed ten separate 7-minute stations with one rater per station. Each of the mini-stations assigned a specific topic and/or task to be completed. The score distributions related to applicant performance and station difficulty were plotted using Rasch analysis software. RESULTS: The behavioral interview format and multiple mini-interview had similar model fit. The behavioral interview did not adequately measure differences in applicant characteristics. In contrast, the multiple mini-interview measured more variation in noncognitive traits and identified better matching of station difficulty and person ability. CONCLUSIONS: In this study the multiple mini-interview format was a more reliable admissions tool in detecting latent professionalism attributes among PA program applicants. The multiple mini-interview format appeared to measure professional potential and organizational fit better than the behavioral interview format. A larger study across several programs may provide additional support for these findings.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".