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. 2016 Apr;263(4):673-91.
doi: 10.1097/SLA.0000000000001283.

Can We Predict Technical Aptitude?: A Systematic Review

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Can We Predict Technical Aptitude?: A Systematic Review

Marisa Louridas et al. Ann Surg. 2016 Apr.

Abstract

Objective: To identify background characteristics and cognitive tests that may predict surgical trainees' future technical performance, and therefore be used to supplement existing surgical residency selection criteria.

Background: Assessment of technical skills is not commonly incorporated as part of the selection process for surgical trainees in North America. Emerging evidence, however, suggests that not all trainees are capable of reaching technical competence. Therefore, incorporating technical aptitude into selection processes may prove useful.

Methods: A systematic search was carried out of the MEDLINE, PsycINFO, and Embase online databases to identify all studies that assessed associations between surrogate markers of innate technical abilities in surgical trainees, and whether these abilities correlate with technical performance. The quality of each study was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation system.

Results: A total of 8035 records were identified. After screening by title, abstract, and full text, 52 studies were included. Very few surrogate markers were found to predict technical performance. Significant associations with technical performance were seen for 1 of 23 participant-reported surrogate markers, 2 of 25 visual spatial tests, and 2 of 19 dexterity tests. The assessment of trainee Basic Performance Resources predicted technical performance in 62% and 75% of participants.

Conclusions: To date, no single test has been shown to reliably predict the technical performance of surgical trainees. Strategies that rely on assessing multiple innate abilities, their interaction, and their relationship with technical skill may ultimately be more likely to serve as reliable predictors of future surgical performance.

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    Dries DJ. Dries DJ. Air Med J. 2017 Nov-Dec;36(6):282-286. doi: 10.1016/j.amj.2017.09.006. Air Med J. 2017. PMID: 29132587 No abstract available.

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