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A literature review of the predictive validity of European dental school selection methods
Author(s) -
Cunningham Claudia,
Patterson Fiona,
Cleland Jennifer
Publication year - 2019
Publication title -
european journal of dental education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.583
H-Index - 41
eISSN - 1600-0579
pISSN - 1396-5883
DOI - 10.1111/eje.12405
Subject(s) - predictive validity , psychology , dental research , selection (genetic algorithm) , medicine , clinical psychology , dentistry , computer science , artificial intelligence
Selection to dental school is the point at which there is the potential to assess a wide range of candidate attributes and select those most likely to learn, train and work within the profession. Despite this, little is known in terms of what works and what does not work in dental selection in terms of predicting future performance accurately and fairly. Given this, our aim was to synthesise the last 30 years of research investigating the predictive validity of dental school selection methods. Methods A search of the electronic databases SCOPUS, Pubmed and Embase was conducted. Results were limited to English language studies published between January 1987 and January 2017. Results Twenty‐one studies were included. Selection tools fell into five broad categories: tests of personal qualities; cognitive ability; academic attainment; psychomotor skills and combined ability tests. Most were retrospective, single‐site studies limited to early years of dental school. Weak correlations were reported, but in most cases, these were between small sections of the selection tool and/or the outcome measure. Discussion There was a notable dearth of published research examining dental schools selection processes across Europe over the last 30 years. Current literature was limited by weak study design and lack of long‐term follow‐up. Conclusion There is insufficient high‐quality evidence from which to draw any conclusions as to the best selection methods to use in dental school selection. Without this, designing selection frameworks for dentistry which are appropriately weighted, reliable and valid remains a challenge.