Every time a new research article is published it adds to the existing knowledge base and in order to synthesize it all and make sense of it the evidence needs to be reviewed. This is particularly the case in the field of medicine where research often informs life and death decisions. In these fields systematic reviews are long-standing and articles are written and tagged with keywords so that they are easy to find. However, other fields have not had the benefit of this.

Eliza Grames is a doctoral candidate studying ecology and evolutionary biology and when she found that she would miss out on key terms she looked at how to develop software to help her conduct reviews more quickly. Traditionally a researcher needs to pull the papers based on a search term and then go through them. However, these searches would yield around 10,000 results many of which could end up being irrelevant. As the number of published papers increase so does the time it takes to review them.

The software was developed after a month of looking at ideas and then getting down to writing the code. The resulting open-source package has been named litsearchr and works by entering keywords into a few databases. Grimes says that this has reduced the amount of time needed to develop a search strategy by 90% and once the researcher has been given the most relevant articles there are a significantly lower number to process manually. This review stage has also been partially automated to further save time.

Litsearchr was the result of a collaboration by a group of researchers called metaverse. The program links many software packages and researchers can use it to perform their search from beginning to end. They can develop their own systematic reviews, import data and there is now the capability to write up the results. Not only that, the software is so simple it can be used by anyone and there is a step-by-step tutorial video to assist them.

The software is open source enabling users to draw attention to bugs that can then be rectified.

At present it is used by researchers conducting studies in insect populations, nutritional science and psychology.

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