Carnegie Mellon advances research and education with Sysrev

Faculty at Carnegie Mellon University first used Sysrev in 2021 for a literature review resulting in the publication Exploratory mapping of tumor associated macrophage nanoparticle article abstracts using an eLDA topic modeling machine learning approach.

While the research was led by the Dr. Elizabeth Wayne, then Assistant Professor of Biomedical and Chemical Engineering, it was guided by two members of the Evidence Synthesis team, Dr. Melanie Gainey and Sarah Young. In 2024, the Evidence Synthesis Team evolved into the Evidence Synthesis Program and was mandated to further help CMU faculty, staff, and students use methodologies, tools, and practices of modern scholarship. 

One gap in the Evidence Synthesis Program service portfolio was a licensed tool for supporting review projects. While the CMU team had experience using Sysrev, Rayyan, and Covidence, they appreciated unique features of Sysrev, particularly the adherence to FAIR principles, including the ability to export data, such as review decisions, in open file formats, as well as the ability to conduct projects beyond traditional evidence synthesis projects. In spring 2024, the program acquired an institution-wide license for Sysrev.

During the first year, over 70 individuals participated in 13 distinct research projects using Sysrev. Participants included students, departmental faculty, and staff including individuals from the Office of Undergraduate Research & Scholarship Development. 

Of the 13 research projects, three were library-led review projects and 10 were faculty- or student-led review projects. These projects covered a range of disciplines including robotics, human-computer interaction, psychology, political science, public policy, economics, and engineering

While a majority of the research projects involved evidence synthesis or literature review, at least three projects involved an alternative type of document analysis. Additionally, at least three projects incorporated Sysrev's auto-labeler to automate specific review tasks. Lastly, Sysrev was also found to be useful in the classroom and was used to support a required undergraduate seminar course, as well as an elective undergraduate summer research course. 

As the Evidence Synthesis Program's use of Sysrev grew, so did their vision for how it could be used. According to Sarah Young, "We initially intended for Sysrev to fill the gap for software to support traditional evidence synthesis projects like systematic and scoping reviews. But the integration of the auto-labeling feature significantly broadened the scope of potential applications and we were able to see the potential for Sysrev across many different research contexts." 

In fact, during the first year of the contract, at least four projects were initiated or conceptualized that employed the auto-labeling functionality to analyze documents or datasets beyond conventional published literature.  Sarah Young continues, "These examples highlight Sysrev’s versatility. We really want to emphasize to our faculty and students the wide range of potential applications of this software and will keep this in mind as we consider future outreach and marketing plans on our campus".

"This is also true of applications in classroom settings." added Dr. Gainey. "For example, the overview dashboard on Sysrev can be used to manage and motivate students as they work through tedious screening steps in a literature review project, and the various review settings make Sysrev a flexible option for class-based projects, unlike some of the other existing screening software we've used in other research contexts."