Large Language Model–Assisted Risk-of-Bias Assessment in Randomized Controlled Trials Using the Revised Risk-of-Bias Tool: Evaluation Study.

ABSTRACT:

Background

The revised Risk-of-Bias tool (RoB2) overcomes the limitations of its predecessor but introduces new implementation challenges. Studies demonstrate low interrater reliability and substantial time requirements for RoB2 implementation. Large language models (LLMs) may assist in RoB2 implementation, although their effectiveness remains uncertain.

Objective

This study aims to evaluate the accuracy of LLMs in RoB2 assessments to explore their potential as research assistants for bias evaluation.

Methods

We systematically searched the Cochrane Library (through October 2023) for reviews using RoB2, categorized by interest in adhering or assignment. From 86 eligible reviews of randomized controlled trials (covering 1399 RCTs), we randomly selected 46 RCTs (23 per c

SUBMITTER: Huang J 

PROVIDER: S-EPMC12238788 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature