Automated search term selection for systematic reviews

Improve systematic reviews by automating search term selection using R package litsearchR.

modeling
Author

Eliza Grames

Published

November 29, 2022

In this workshop, Eliza Grames will explain how the R package litsearchR can be used for quick, objective, reproducible development of search strategies in systematic reviews. The package uses text-mining and keyword co-occurrence networks to identify important terms to include in a search strategy.

Please note that this workshop started at 16:00.

Join this workshop meeting on Zoom by clicking this link

Eliza Grames is a post-doctoral scholar at the University of Nevada Reno. Amongst other topics, she works on methods to conduct meta-analyses on disparate and diverse time series datasets. Eliza completed her PhD in Ecology and Evolutionary Biology in 2021 at the University of Connecticut, where she worked on developing new methods of evidence synthesis. Broadly speaking, she is interested in any involving cool research methods, birds, insects, conservation, quantitative ecology, and evidence synthesis. You can read more about Eliza and her work on her personal website.

Materials

In this compressed folder (ZIP file) are the script and data that contain a full example of using litsearchr from start to finish, with an example on de-escalation training effectiveness. Eliza will run through the full thing including the steps outside of R (e.g. exporting the search results).

Citation

For attribution, please cite this work as (Grames 2022)

References

Grames, E. 2022. NSC-R Workshops: Automated Search Term Selection for Systematic Review,” November.