University of Worcester Worcester Research and Publications
 
  USER PANEL:
  ABOUT THE COLLECTION:
  CONTACT DETAILS:

Does the UKCAT predict performance in medical and dental school? A systematic review

Greatrix, R., Nicholson, Sandra ORCID logoORCID: https://orcid.org/0000-0002-7682-0828 and Anderson, S. (2021) Does the UKCAT predict performance in medical and dental school? A systematic review. BMJ Open, 11 (1). e040128. ISSN Online: 2044-6055

[thumbnail of does-the-ukcat-predict-performance-in-medical-and-dental-school_-a-systematic-review.bib] Text
does-the-ukcat-predict-performance-in-medical-and-dental-school_-a-systematic-review.bib
Restricted to Repository staff only

Download (2kB) | Request a copy
[thumbnail of e040128.full (1).pdf]
Preview
Text
e040128.full (1).pdf - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (893kB) | Preview

Abstract

Objectives For the first time, this systematic review provides a summary of the literature exploring the relationship between performance in the UK Clinical Aptitude Test (UKCAT) and assessments in undergraduate medical and dental training.

Design In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis, relevant studies were identified through systematic literature searches. Electronic searches were carried out on EBSCO, EMBASE, Educational Resources Information Centre, SCOPUS, Web of Knowledge. Studies which included the predictive validity of selection criteria including some element of the UKCAT were considered.

Results 22 papers were identified for inclusion in the study. Four studies describe outcomes from dental programmes with limited results reported. 18 studies reported on relationships between the UKCAT and performance in undergraduate medical training. Of these, 15 studies reported relationships between the UKCAT cognitive tests and undergraduate medical assessments. Weak relationships (r=0.00–0.29) were observed in 14 of these studies; four studies reported some moderate relationships (r=0.30–0.49). The strongest relationships with performance in medical school were observed for the UKCAT total score and the verbal reasoning subtest. Relationships with knowledge-based assessments scores were higher than those for assessments of skills as the outcome. Relationships observed in small (single and double centre studies) were larger than those observed in multicentre studies.

Conclusion The results indicate that UKCAT scores predict performance in medical school assessments. The relationship is generally weak, although noticeably stronger for both the UKCAT total score and the verbal reasoning subtest. There is some evidence that UKCAT continues to predict performance throughout medical school. We recommend more optimal approaches to future studies. This assessment of existing evidence should assist medical/dental schools in their evaluation of selection processes.

Item Type: Article
Additional Information:

http://creativecommons.org/licenses/by-nc/4.0/
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

Uncontrolled Discrete Keywords: UK Clinical Aptitude Test, Performance, Assessment, Prediction, Medical training, Dental training
Divisions: Three Counties Medical School
Related URLs:
Copyright Info: Open Access article
Depositing User: Sandra Nicholson
Date Deposited: 21 Aug 2023 12:12
Last Modified: 21 Aug 2023 12:12
URI: https://eprints.worc.ac.uk/id/eprint/13192

Actions (login required)

View Item View Item
 
     
Worcester Research and Publications is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.