Protocol for developing the reporting guidelines for the use CHatbots and other gEnerative AI tools in mEdical Research (CHEER)
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Background
The integration of artificial intelligence (AI) has revolutionized medical research, offering innovative solutions for data collection, patient engagement, and information dissemination. Powerful generative AI (GAI) tools like ChatGPT and other similar chatbots have emerged, facilitating user interactions with virtual conversational agents. However, the increasing use of GAI tools in medical research presents challenges, including ethical concerns, data privacy issues, and the potential for generating false content. These issues necessitate standardization of reporting to ensure transparency and scientific rigor.
Objective
The development of the CHatbots and other gEnerative AI tools in mEdical Research (CHEER) reporting guidelines aims to establish a comprehensive, standardized guideline for reporting the use of GAI tools in medical research.
Methods
The CHEER guidelines are being developed following the methodology recommended by the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) network, involving scoping reviews and expert Delphi consensus. The process consists of three stages: preparatory work, Delphi survey, and testing and dissemination. The study is approved by the Ethics Committee of the Institute of Health Data Science at Lanzhou University (approval number: HDS-202406-01).
Expected results
The CHEER project was launched in July 2023 by the Evidence-Based Medicine Center of Lanzhou University and the WHO Collaborating Centre for Guideline Implementation and Knowledge Translation, and is scheduled to conclude in July 2024. The expected outcome of the CHEER project is a reporting checklist, accompanied by relevant terminology, examples, and explanations, to guide stakeholders in better reporting the use of GAI tools.
Conclusion
CHEER aims to guide researchers, reviewers, and editors in the transparent and scientific application of GAI tools in medical research. By providing a standardized reporting framework, CHEER seeks to enhance the clarity, completeness, and integrity of research involving GAI tools, promoting collaboration, comparability, and cumulative knowledge generation in AI-driven healthcare technologies.
Trial Registration
We registered this protocol on the EQUATOR Network ( https://www.equator-network.org/library/reporting-guidelines-under-development/reporting-guidelines-under-development-for-other-study-designs/#CHEER ) .
