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Updated: Sep 10, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Do cognitively based medical selection assessment scores predict doctors' clinical competency? A protocol for a
Taha Khan1, Karen Mattick2, Paul Alexander Tiffin3
1Hull York Medical School Centre for Health and Population Sciences, York, UK taha.khan6@nhs.net.
Introduction:
Internationally, medical schools increasingly use cognitively based selection assessments to select applicants. These tests evaluate cognitive performance and show some predictive validity for academic attainment during medical school, often incremental to that provided by secondary school grades. However, their use imposes burdens on applicants and institutions. They may also disadvantage certain under-represented groups. Therefore, to justify their adoption, these assessments should ideally predict doctors' future clinical competency, which can be evaluated by clinical outcomes or performance in post-qualification practical clinical examinations. Hence, this systematic review aims to collate and appraise evidence linking scores from these assessments to doctors' clinical competency.
Methods And Analysis:
A comprehensive search strategy, co-developed with stakeholders, will search eight databases and grey literature from January 2000 onwards. Study selection, data extraction, study quality and the risk of bias assessment will be performed independently by two authors. A narrative synthesis will be used to appraise and integrate the findings from the included studies.
Ethics And Dissemination:
Ethical approval is not required. The results will be published in a peer-reviewed journal and presented at relevant academic conferences.
Prospero Registration Number:
The protocol was registered prospectively on PROSPERO (CRD42024539112).
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