A Mixed‐Method Usability Study on User Experience with Systematic Review Software

Manhua Wang · Mengqian Wang · Fei Yu

5 citations0/0 files storedProceedings of the Association for Information Science and Technology

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Meta-analysis and systematic reviews Software Engineering Techniques and Practices Usability and User Interface Design

Abstract

Abstract Systematic reviews are widely used in evidence‐based medicine. Conducting a systematic review requires intensive mental efforts, especially during the study screening process. This challenge has motivated the development of intelligent software. This study examined and compared the performance, workload, and user experience of two systematic review tools – Colandr with Artificial Intelligence (AI) features and Covidence without AI features by conducting a mixed‐method usability study. The results showed that reviewers had higher precision in citation screening using Colandr than using Covidence. However, the user experience with Colandr was not optimal due to problems in its user interface design. Therefore, we suggest that the design and development of AI‐enabled SR software emphasize the usability of the interface and apply user‐centered design principles.

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2011The Cochrane Collaboration's tool for assessing risk of bias in randomised trials 2016Rayyan—a web and mobile app for systematic reviews 2015Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement 2011Effect size estimates: Current use, calculations, and interpretation.2016Code Saturation Versus Meaning Saturation 2003Five Steps to Conducting a Systematic Review 2013Systematic reviews and meta-analysis: Understanding the best evidence in primary healthcare 2017Analysis of the time and workers needed to conduct systematic reviews of medical interventions using data from the PROSPERO registry

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