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J Educ Eval Health Prof > Epub ahead of print
J Educ Eval Health Prof. 2019; 16: 7.
Published online April 10, 2019.
DOI: https://doi.org/10.3352/jeehp.2019.16.7
[Epub ahead of print]
An expert-led and artificial intelligence system-assisted tutoring course to improve the confidence of Chinese medical interns in suturing and ligature skills: a prospective pilot study
Ying-Ying Yang1,2,3  , Boaz Shulruf4 
1Division of Clinical Skills Training and High-fidelity Medical Simulation for Holistic Care and Inter-Professional Collaboration, Department of Medical Education, Taipei Veterans General Hospital, Taipei, Taiwan
2Department of Medicine, National Yang-Ming University, Taipei, Taiwan
3Division of General Medicine, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
4Office of Medical Education, University of New South Wales Australia, Sydney, Australia
Correspondence  Ying-Ying Yang ,Email: yangyy@vghtpe.gov.tw
Editor:  Sun Huh, Hallym University, Korea
Submitted: February 9, 2019  Accepted after revision: April 9, 2019
Abstract
Purpose
Lack of confidence in suturing/ligature skills due to insufficient practice and assessments is common among novice Chinese medical interns. This study aimed to improve the skill acquisition of medical interns through a new intervention program.
Methods
In addition to regular clinical training, expert-led or expert-led plus artificial intelligence (AI) system tutoring courses were implemented during the first 2 weeks of the surgical block. Interns could voluntarily join the regular (no additional tutoring), expert-led tutoring, or expert-led+AI tutoring groups freely. In the regular group, interns (n=25) did not receive additional tutoring. The expert-led group received 3-hour expert-led tutoring and in-training formative assessments after 2 practice sessions. After a similar expert-led course, the expert-led+AI group (n=23) practiced and assessed their skills on an AI system. Through a comparison with the internal standard, the system automatically recorded and evaluated every intern’s suturing/ligature skills. In the expert-led+AI group, performance and confidence were compared between interns who participated in 1, 2, or 3 AI practice sessions.
Results
The end-of-surgical block objective structured clinical examination (OSCE) performance and self-assessed confidence in suturing/ligature skills were highest in the expert-led+AI group. In comparison with the expert-led group, the expert-led+AI group showed similar performance in the in-training assessment and greater improvement in the end-of-surgical block OSCE. In the expert-led+AI group, the best performance and highest post-OSCE confidence were noted in those who engaged in 3 AI practice sessions.
Conclusion
This pilot study demonstrated the potential value of incorporating an additional expert-led+AI system–assisted tutoring course into the regular surgical curriculum.
Keywords: Artificial intelligence; Suturing and ligature skills; Tutoring course ; Taiwan
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