5 - A Search Method to Identify Relevant Information for a Scoping Review: A Case Report on Systematic Citation Searching

Background: A librarian and a team of researchers from the United States and Brazil collaborated on a scoping review titled "The state of the art of participatory research in mental health in Brazil". To avoid some of the challenges associated with the vagueness of the concept, we used a multipronged approach to find relevant information.
To systematically identify relevant articles, we employed a bidirectional citation searching method (Hinde & Spackman, 2015) along with a targeted search of a variety of databases.

Description: The research team identified ten relevant studies (known as 'pearls'), and the librarian used these pearls to identify articles through a systematic search of their cited and citing articles using a variety of tools: citationchaser, SciELO, Scopus, Web of Science, and Google Scholar. The articles were collected in EndNote, and duplicates removed before uploading to Covidence for screening. Studies were screened by two screeners.
Using the included studies, relevant keyword terms were identified using the Systematic Review Accelerator WordFreq tool, and a targeted search strategy was developed. The following databases were searched: MEDLINE, Embase, PsycInfo, and Global Health, LILACS, Web of Science, Scopus, SciELO, BDTD, and the PBi Portal de Busca Integrada. Search results were limited to English and Portuguese titles.

Conclusion: Although the review is still in-progress; we have found that bidirectional searching can be a complementary method to traditional keyword searching for scoping reviews where the concept of the review is ambiguous; articles on the topic aren't published in journals that are indexed in major databases; or studies of interest are in a language other than the first language of the person developing the search strategy.
However, this method can be just as time consuming and complicated as traditional keyword searching, but we found this method can be successfully used to systematically identify articles.