 Hello, my name is Emma Wilson. I'm a PhD student at the University of Edinburgh and I specialise in systematic review methodology. This short talk is all about managing your systematic review references using R. By references I mean information. Usually bibliographic details like the title, the journal and the DOI all about your publications in your systematic review. From your initial search down to your final set of included studies. This is very much a beginner talk. I will discuss the importance of managing your systematic review references, the limitations of using software such as EndNote and Excel and the benefits of using R instead. Additionally I will mention some R packages that can help you keep track of your systematic review references. Depending on your systematic review question or the publication rate in your field of interest, your systematic search could potentially retrieve hundreds or even thousands of references. It's really important that you can keep track of your references for your Prisma flow diagram. For instance, how many studies you retrieved in total, the number of unique studies after duplicate removal, the number of studies included through screening and the final number of studies included in your review. Keeping track of your references is also really important if you ever want to do a systematic review update. A lot of this comes down to good data management. The last thing you want is to finish your review, get ready to publish and you realise that you've only kept your included studies and you cannot remember how many were in your initial search results. I've seen a lot of guidance recommend software such as EndNote to keep track of your systematic review references. A partial experience that I've often struggled using EndNote particularly when it comes to good data management. So it's not an approach that I would generally recommend. But what are some of the reasons that people do use tools such as EndNote? A lot of EndNote and other reference managers features are actually quite useful to the systematic review process. It's possible to import searches from different scientific databases and there are features to remove duplicate records and retrieve full text PDF files. While these features are great, there are also limitations of using reference manager software in systematic reviews. Firstly, software such as EndNote does not allow version control so it can be hard to see and keep track of your records from your initial search down to your included studies. Workarounds can include having separate files for all of your retrieved references, unique references and your included references. We're splitting these up into groups in one single file but these can be hard to keep track of. Secondly, it's easier to make user errors. You might accidentally delete data or lose a reference. From my own experience using groups, I know how easy it can be to click move to trash instead of remove from group. Finally, although software such as EndNote are called reference managers, they are built for keeping track of references in the paper that you're writing or your thesis, not working through the various stages of a systematic review. So what are the benefits of using R instead? For me, a major benefit was greater data management and reproducibility. I can write R scripts which run through my entire systematic review and then porting my searches to analysing my results. Everything is all in one place and it's a lot easier to reproduce than we do. Errors can still happen. For me, typos in code are really common but these types of errors are so much easier to pick up and check, meaning that they can be fixed really easily. Something that makes using R in systematic reviews really powerful is the fact that there are so many purpose-built R packages and a growing community of coders contributing to these packages. Poding is generally a useful skill to learn, but in terms of a systematic review, it offers so much more flexibility to what you can do with your data. There are a lot of R packages available to help you through the various steps of the systematic review project. I've listed here some R packages which can perform similar functions to what you'd find in reference management software. Starting with searching or importing your search files to synthesise R package allows you to import the files from your database searches directly into R. There are also a variety of packages which allow you to perform systematic searches within R itself. This is a particularly useful solution for living evidence synthesis projects. These packages include RIS Med or PubMed and MedArchive R for MedArchive and BioArchive. Moving on to duplicate removal, both the synthesiser package and the assist package have functions which enable removal of duplicate records. Assist was actually developed by my colleague Dr. Katelyn here and the validation of assist found that it outperformed a not spawned duplicate removal function. Finally, there are various packages which enable automated retrieval of PDFs. MedArchive R can be used to retrieve fill text from MedArchive and BioArchive, R-O-A-D-O-I retrieves fill-free fill text available via Unpaywall, and R Crossref retrieves from Crossref. To run back over the key points in this talk, I hope that I've been able to convince you of the many benefits of using R in systematic reviews over typical reference management software, especially in terms of data management. And I've also introduced you to what is a large and growing community of R enthusiasts all producing purpose-built tools for systematic reviews. Thank you for listening. I hope that you've found this introductory talk useful, and if you haven't already, you'll consider making the switch to using R in your next systematic review project. If you have any questions, please do get in touch.