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Selecting top candidates for medical school selection interviews- a non-compensatory approach

BACKGROUND: Medical 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 Med...

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Autores principales: Shulruf, Boaz, O’Sullivan, Anthony, Velan, Gary
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7161246/
https://www.ncbi.nlm.nih.gov/pubmed/32295582
http://dx.doi.org/10.1186/s12909-020-02031-6
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author Shulruf, Boaz
O’Sullivan, Anthony
Velan, Gary
author_facet Shulruf, Boaz
O’Sullivan, Anthony
Velan, Gary
author_sort Shulruf, Boaz
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description BACKGROUND: Medical 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? METHODS: This 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. RESULTS: The 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. CONCLUSIONS: These 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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spelling pubmed-71612462020-04-22 Selecting top candidates for medical school selection interviews- a non-compensatory approach Shulruf, Boaz O’Sullivan, Anthony Velan, Gary BMC Med Educ Research Article BACKGROUND: Medical 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? METHODS: This 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. RESULTS: The 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. CONCLUSIONS: These 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. BioMed Central 2020-04-15 /pmc/articles/PMC7161246/ /pubmed/32295582 http://dx.doi.org/10.1186/s12909-020-02031-6 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Shulruf, Boaz
O’Sullivan, Anthony
Velan, Gary
Selecting top candidates for medical school selection interviews- a non-compensatory approach
title Selecting top candidates for medical school selection interviews- a non-compensatory approach
title_full Selecting top candidates for medical school selection interviews- a non-compensatory approach
title_fullStr Selecting top candidates for medical school selection interviews- a non-compensatory approach
title_full_unstemmed Selecting top candidates for medical school selection interviews- a non-compensatory approach
title_short Selecting top candidates for medical school selection interviews- a non-compensatory approach
title_sort selecting top candidates for medical school selection interviews- a non-compensatory approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7161246/
https://www.ncbi.nlm.nih.gov/pubmed/32295582
http://dx.doi.org/10.1186/s12909-020-02031-6
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