ArticleJournal of educational evaluation for health professions2022
Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive study
Article in Journal of educational evaluation for health professions, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Insights into undergraduate medical student selection tools: a systematic review and meta-analysisJournal of educational evaluation for health professions · 2024Pooled it
- Medical student selection interviews: insights into nonverbal observable communications: a cross-sectional study.Korean journal of medical education · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe study investigates the efficacy of new features introduced to the selection process for medical school at the University of New South Wales, Australia: (1) considering the relative ranks rather than scores of the Undergraduate Medicine and Health Sciences Admission Test and Australian Tertiary Admission Rank; (2) structured interview focusing on interpersonal interaction and concerns should the applicants become students; and (3) embracing interviewers’ diverse perspectives.
methodsData from 5 cohorts of students were analyzed, comparing outcomes of the second year in the medicine program of 4 cohorts of the old selection process and 1 of the new process. The main analysis comprised multiple linear regression models for predicting academic, clinical, and professional outcomes, by section tools and demographic variables.
resultsSelection interview marks from the new interview (512 applicants, 2 interviewers each) were analyzed for inter-rater reliability, which identified a high level of agreement (kappa=0.639). No such analysis was possible for the old interview since it required interviewers to reach a consensus. Multivariate linear regression models utilizing outcomes for 5 cohorts (N=905) revealed that the new selection process was much more effective in predicting academic and clinical achievement in the program (R2=9.4%–17.8% vs. R2=1.5%–8.4%).
conclusionThe results suggest that the medical student selection process can be significantly enhanced by employing a non-compensatory selection algorithm; and using a structured interview focusing on interpersonal interaction and concerns should the applicants become students; as well as embracing interviewers’ diverse perspectives.
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