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- Title
Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive study.
- Authors
Shulruf, Boaz; Velan, Gary Mayer; Kennedy, Sean Edward
- Abstract
Purpose: The 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. Methods: Data 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. Results: Selection 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%). Conclusion: The 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.
- Subjects
AUSTRALIA; NEW South Wales; STATISTICS; MEDICAL students; RESEARCH methodology; MULTIPLE regression analysis; MULTIVARIATE analysis; INTERVIEWING; ACADEMIC achievement; HUMAN services programs; COMPARATIVE studies; INTER-observer reliability; UNIVERSITIES &; colleges; INTERPERSONAL relations; DESCRIPTIVE statistics; SOCIODEMOGRAPHIC factors; SCHOOL entrance requirements; ALGORITHMS; LONGITUDINAL method
- Publication
Journal of Educational Evaluation for Health Professions, 2022, Vol 19, p1
- ISSN
1975-5937
- Publication type
Article
- DOI
10.3352/jeehp.2022.19.31