Towards the automatic risk of bias assessment on randomized controlled trials: A comparison of RobotReviewer and humans

RobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two different approaches: (1) manually by human reviewers, and (2) automatically by the RobotReviewer. The manual assessment was based on two groups independently, with two additional rounds of verification. The agreement between RobotReviewer and humans was measured via the concordance rate and Cohen's kappa statistics, based on the comparison of binary classification of the risk of bias (low vs. high/unclear) as restricted by RobotReviewer. The concordance rates varied by domain, ranging from 63.07% to 83.32%. Cohen's kappa statistics showed a poor agreement between humans and RobotReviewer for allocation concealment (κ = 0.25, 95% CI: 0.21-0.30), blinding of outcome assessors (κ = 0.27, 95% CI: 0.23-0.31); While moderate for random sequence generation (κ = 0.46, 95% CI: 0.41-0.50) and blinding of participants and personnel (κ = 0.59, 95% CI: 0.55-0.64). The findings demonstrate that there were domain-specific differences in the level of agreement between RobotReviewer and humans. We suggest that it might be a useful auxiliary tool, but the specific manner of its integration as a complementary tool requires further discussion.

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Publication Details

Journal
Research Synthesis Methods
Published
2024-09-26
DOI
https://doi.org/10.1002/jrsm.1761
Citations
5
Primary Topic
Meta-analysis and systematic reviews
Type
article
Field-Weighted Citation Impact
2.31

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article

Towards the automatic risk of bias assessment on randomized controlled trials: A comparison of RobotReviewer and humans

Yuan Tian, Suhail A.R. Doi, Joey SW Kwong, Luis Furuya‐Kanamori et al.
5 citations
Research Synthesis Methods
Meta-analysis and systematic reviews
2.31
article

Towards the automatic risk of bias assessment on randomized controlled trials: A comparison of RobotReviewer and humans

Yuan Tian, Suhail A.R. Doi, Joey SW Kwong, Luis Furuya‐Kanamori, Lifeng Lin, Chang Xu, Xi Yang
article en
5 citations

Abstract

RobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two different approaches: (1) manually by human reviewers, and (2) automatically by the RobotReviewer. The manual assessment was based on two groups independently, with two additional rounds of verification. The agreement between RobotReviewer and humans was measured via the concordance rate and Cohen's kappa statistics, based on the comparison of binary classification of the risk of bias (low vs. high/unclear) as restricted by RobotReviewer. The concordance rates varied by domain, ranging from 63.07% to 83.32%. Cohen's kappa statistics showed a poor agreement between humans and RobotReviewer for allocation concealment (κ = 0.25, 95% CI: 0.21-0.30), blinding of outcome assessors (κ = 0.27, 95% CI: 0.23-0.31); While moderate for random sequence generation (κ = 0.46, 95% CI: 0.41-0.50) and blinding of participants and personnel (κ = 0.59, 95% CI: 0.55-0.64). The findings demonstrate that there were domain-specific differences in the level of agreement between RobotReviewer and humans. We suggest that it might be a useful auxiliary tool, but the specific manner of its integration as a complementary tool requires further discussion.

Research Synthesis MethodsVol. 15(6)
University of Arizona (US), The University of Queensland (AU), Second Military Medical University (CN), Anhui Medical University (CN), St. Luke's International University (JP), Eastern Hepatobiliary Surgery Hospital (CN), Qatar University (QA)
British Society for Research on Ageing, National Natural Science Foundation of China, Fonds National de la Recherche Luxembourg, Qatar National Research Fund
No poverty
Openalex Percentile: Top 11%
Meta-analysis and systematic reviews
2.31
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