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Guidelines and Checklists for Artificial Intelligence (AI) in Surgical Education Research: A Comprehensive Narrative
Caitlin Silvestri1, Darian L Hoagland2, John M Woodward3
1Columbia/New York Presbyterian Hospital, New York, NY.
Objective:
Artificial intelligence (AI) has increasingly been used in clinical and healthcare research, prompting the development of new research guidelines to ensure its appropriate use. Similarly, AI has been applied to surgical education research, creating a need to assess the relevance and applicability of existing guidelines in this context. This narrative review synthesized guidelines and checklists related to AI in surgical education, providing researchers with an introductory roadmap for conducting rigorous, reproducible studies and identifying gaps for future framework development.
Design:
In April 2024, the authors conducted a search using Ovid (Embase and MEDLINE(R)) from 1946 to 2024 to identify guidelines and checklists related to AI research in healthcare and surgical education. Search teams included "artifical intelligence" and related terms, as well as "checklist", "recommendations", and terms related to evaluation, reporting, and guidelines. Titles and abstracts were screened and the authors reviewed eligible full-text articles for inclusion through consensus discussions.
Results:
From 200 studies identified, 47 full-text articles were reviewed, and 16 guidelines and checklists were included. These were grouped into six thematic categories: AI research with health education applications, Generative AI and Large Language Model studies, machine learning/prediction models, AI in imaging, and forthcoming guidelines. Key findings highlighted the diversity in purpose, methodology, and scope. Although gaps were identified in existing guidelines and checklists for surgical education, with only one tailored to AI research in healthcare education, the authors demonstrated how these other resources could be applied.
Conclusions:
This review highlighted that while existing guidelines and checklists could be applied in certain contexts, significant gaps remained in education-specific research guidance. Future efforts should focus on developing tailored guidelines to address the unique challenges and opportunities of AI integration in surgical education, ensuring rigorous and reproducible research.
