MetaReviewer: An Online, Easy-To-Use Program for Conducting Systematic Reviews and Meta-Analyses

Image
Female researchers collaborating

Conducting a systematic review and meta-analysis is time-consuming, tedious, and labor intensive. The process requires research staff to find information from every study included in the systematic review and put that information in a database or spreadsheet. To assist with the process, researchers often turn to proprietary software, but existing programs are expensive or lack important features. To address this need, we developed a free, easy-to-use, collaborative software program called MetaReviewer.

The goal of MetaReviewer is to assist researchers in the process of conducting a systematic review and/or meta-analysis. The current version of MetaReviewer does this by helping research staff to:

  • develop a codebook for their project;
  • import citations and link multiple study citations together;
  • conduct comprehensive and consistent coding;
  • identify correct effect size data and estimate many effect types; and
  • export data in a ready-to-use format for quantitative synthesis.

MetaReviewer also has several project management functions that can assist researchers who are leading a systematic review. Most importantly, all members of a research team can access the synthesis project page and view progress in real-time via a web browser. Project leaders and staff never have to download or update software. With only a few mouse clicks, a project leader can: assign staff studies to code, view coding progress, validate completed study coding, and export entered data.

If you are interested in using MetaReviewer for your ongoing project, sign up now.

MetaReviewer was officially launched on December 1, 2023. Complete the web survey form at the link on the right to sign up now, and follow MetaReviewer on YouTube, Bluesky, and LinkedIn. You can also learn more about MetaReviewer's functionality and forthcoming features on our Learn page.

The MetaReviewer program was made possible through a grant from the National Science Foundation to AIR (EHR-2000672, EHR-2400530) and is supported by the Methods of Synthesis and Integration Center (MOSAIC) at AIR and the AIR Opportunity Fund. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Contact
Image of Megan Austin

Megan Austin

Principal Researcher
Image of Laura Michaelson

Laura Michaelson

Senior Researcher