The impact of the medical school admissions interview: a systematic review
Bibliographic record
Abstract
Background: Interviews are considered an important part of the medical school admissions process but have been critiqued based on bias and reliability concerns since the 1950s. To determine the impact of the interview, this systematic review investigated the characteristics and outcomes of medical students admitted with and without interviews. Methods: We searched four literature databases from inception through August 2022; all studies comparing medical students admitted with and without interviews were included. We excluded studies from outside the medical school setting and non-research reports. We reviewed interview type, study design, quality, and outcomes. Results: Eight studies from five institutions across five countries were included. Six reported no demographic differences between students admitted with and without interviews; one found that more men were admitted without than with semi-structured interviews, and both cohorts had similar academic and clinical performance. Structured interviews admitted students who scored higher on clinical exams and social competence and lower on academic exams. Cohorts admitted with and without structured interviews had similar mental health issues by their final year of medical school. Discussion: This review suggests that students admitted with and without unstructured and semi-structured interviews were similar demographically, academically, and clinically. Moreover, structured interviews selected more socially competent students who performed better clinically but worse academically. Further research is needed to determine the impact of the selection interview in medical school admissions.
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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 | 0.005 | 0.704 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.282 | 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".