[Analysis of application scope and current state survey of the reporting guideline for large language models in healthcare research (TRIPOD-LLM)].

Abstract

Transparent reporting of a multivariable model for individual prognosis or diagnosis-large language models (TRIPOD-LLM) is a reporting guideline specifically developed for studies involving LLM in the healthcare domain. It aims to enhance the transparency, reproducibility, and methodological rigor of LLM-related research reporting. However, there is still a lack of systematic research regarding its applicable scope, current implementation status, and strategies for effective application. This study provides an in-depth analysis and discussion from three perspectives: the intended scope of TRIPOD-LLM, an investigation into its current application status, and how to better apply it, with the goal of assisting researchers in improving the standardization of the implementation and reporting of LLM-based studies. These findings suggest that the dissemination and application of TRIPOD-LLM are still at an early stage. Common challenges include limited understanding of specific checklist items and insufficient reporting of key methodological details. Strengthening awareness of the TRIPOD-LLM framework and promoting its adaptive use across diverse LLM research scenarios will help improve reporting quality and credibility, thereby advancing the responsible and standardized application of LLM in healthcare research.

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