ArticleBMC medical education2020
Selecting top candidates for medical school selection interviews- a non-compensatory approach.
Article in BMC medical education, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Insights into undergraduate medical student selection tools: a systematic review and meta-analysisJournal of educational evaluation for health professions · 2024Pooled it
- The innate aptitude's effect on the surgical task performance: a systematic review.Updates in surgery · 2021Pooled it
- Piloting Virtual Multiple Mini Interviews (MMI) on Undergraduate Medical Students: A Multisource Feedback Analysis.Advances in medical education and practice · 2025Article
- Prior degree and academic performance in medical school: evidence for prioritising health students and moving away from a bio-medical science-focused entry stream.BMC medical education · 2022Article
- Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive studyJournal of educational evaluation for health professions · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundMedical schools apply a range of selection methods to ensure that admitted students succeed in the program. In Australia, selection tools typically include measures of academic achievement (e.g. the Australian Tertiary Admission Rank - ATAR) and aptitude tests (e.g. the Undergraduate Medicine and Health Sciences Admissions Test - UMAT). These are most commonly used to determine which applicants are invited for additional selection processes, such as interviews. However, no previous study has examined the efficacy of the first part of the selection process. In particular, are compensatory or non-compensatory approaches more effective in evaluating the outcomes of cognitive and aptitude tests, and do they affect the demographics of students selected for interview?
methodsThis study utilised data from consecutive cohorts of mainstream domestic students who applied to enter the UNSW Medicine program between 2013 to 2018. A compensatory ranked selection model was compared with a non-compensatory ranked model. Initially, ATAR marks and UMAT scores for each applicant were ranked within each cohort. In the compensatory model, the mean of the ATAR and UMAT ranks were used to determine the outcome. In the non-compensatory model, the lowest rank of ATAR and UMAT determined the outcome for each applicant. The impact of each model on the gender and socioeconomic status of applicants selected to interview was evaluated across all cohorts.
resultsThe non-compensatory ranked selection model resulted in substantially higher ATAR and UMAT thresholds for invitation to interview, with no significant effect on the socioeconomic status of the selected applicants.
conclusionsThese results are important, demonstrating that it is possible to raise the academic threshold for selection to medicine without having any negative impact on applicants from low socioeconomic backgrounds. Overall, the evidence gathered in this study suggests that a non-compensatory model is preferable for selecting applicants for medical student selection interview.
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