You completed a systematic review or meta-analysis using a formal workflow. You won the lottery in big-picture thinking and perspective. However, time passes with peer review or change (and most fields are prolific even monthly in publishing to your journal set). You need to update the process. Here is a brief workflow for that process.
Updating a search
- Revisit the same bibliometrics tool initially used such as Scopus or Web Science.
- Record date of current instance and contrast with previous instance documented.
- Repeat queries with exact same terms. Use ‘refine’ function or specific ‘timespan’ to year since last search. For instance, last search for an ongoing synthesis was Sept 2019, and we are revising now in Jan 2020. Typically, I use a fuzzy filter and just do 2019-2020. This will generate some overlap. The R package wosr is an excellent resource to interact with Web of Science in all instances and enables reproducibility. The function ‘query_wos’ is fantastic, and you can specify timespan using the argument PY = (2019-2020).
- Use a resource that reproducibly enables matching to explore overlaps from first set of studies examined to current updated search. I use the R-package Bibliometrix function ‘duplicatedMatching’, and if there is uncertainty, I then manually check via DOI matching using R code.
- Once you have generated your setdiff, examine new entries, collect data, and update both meta-data and primary dataframes.
- Science is rapid, evolving, and upwards of 1200 publications per month are published in some disciplines.
- Consider adding a search date to your dataframe. It would be informative to examine the rate that one can update synthesis research.
- Repeat formal syntheses, and test whether outcomes are robust.
- Examine cumulative meta-analytical statistics.
- Ensure your code/workflow for synthesis is resilient to change and replicable through time – you never know how long reviews will take if you are trying to publish your synthesis.