Main Article Content
Medical School Admissions: A Review of Global Practices, Predictive Validity, and Practice Points for Africa
Abstract
Background: Processes for selection of candidates into medical schools vary globally. Knowledge of the predictive validity of a selection method is important for policy revision.
Aim: To survey the practices used by medical schools to select students and their predictive validity.
Methods: Search terms developed from the research problem were used to search Google Scholar, PubMed, and Educational Resources Information Centre (ERIC). These were “medical school,” “predictive validity,” “success,” “academic achievement” “admission criteria,” and “student selection.” Retrieved articles were screened for relevance and sorted according to countries of
publication. Authors narratively reviewed the articles from each country and collated the findings. Best practices were recommended for African-based medical schools.
Results: Articles retrieved from 14 countries were included in the review. USA, Canada, UK, Australia, and New Zealand operate centralized medical school admission programs and administer nationwide admission tests. These tests cover cognitive and non-cognitive domains. The validity of these tests in predicting medical school success were extensively studied and reported. Other countries do not operate centralized medical school admission programs. Most of these rely on cognitive excellence to select students. Few reports are available on the validity of selection practices in Africa. Most rely on cognitive excellence which highly predicted academic success during preclinical studies. Predictivity decreased during clinical phases and non-cognitive variables became better predictors of success.
Conclusion: Medical school admission processes should consider cognitive and non-cognitive factors. With non-cognitive factors, candidates with right attitudes are selected. African countries should align their practices to that of Western countries.
Keywords: Admission, undergraduate medical education, predictive value of tests, selection criteria, educational achievement