Context

Search Builder version 1.0 was created by a member of the authorship team (B.B.K.) as part of a systematic review and meta-analysis course at the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland. During this course, four- to five-member student teams produced systematic review manuscripts with guidance from skilled experts in systematic review methodology. For the search strategy process, the student teams were instructed to use traditional search methods, including manually listing relevant search terms (using keywords from literature on the topic, medical subject headings [“MeSH”] indexed on PubMed, and search strategies from previous systematic reviews), constructing a search text string using appropriate syntax, and iteratively testing the search string in online biomedical search engines such as PubMed and Embase. Because all team members were expected to perform this step, individual efforts to construct search strings resulted in person-to-person variability in search terms included, syntax used, and observed search results, thus slowing an already cumbersome process. Moreover, attempted use of available online search builder tools offered by PubMed and Embase revealed them to be inefficient for use as a group, and difficult to save due to the online-only, login-required interface.

To overcome the inconveniences of the search strategy process, the first author (B.B.K.) created a file in Microsoft Excel® that could automatically add search string syntax to a user-provided list of search terms. A prototype-version of this file was quickly adopted by the systematic review team and lauded as a valuable time-saving tool due to features such as offline usage, rapid inclusion and exclusion of search terms, and the ability to save, share, and repeatedly edit versions of the search string. After successful use of the search builder prototype for the systematic review course, the first author (B.B.K.) received assistance from an engineer and Microsoft Excel® expert (B.S.K.) who fine-tuned the builder program, and a team of research associates (P.A.S., S.S., J.O.) tested the builder product. After completion of pilot testing, Search Builder 1.0 was finalized for public dissemination.

Description

Search Builder 1.0 is a Microsoft Excel® tool that takes a user-defined list of search terms and automatically assembles a search string that can be copied and pasted into PubMed or Embase (see Table 1). Users of Search Builder 1.0 enter desired search terms into the spreadsheet and subsequently assign each with a “PICO” (Population, Intervention, Comparison group, and Outcome) category, limit (i.e., language, article type, species), or a custom user-defined category, and a field code (i.e., PubMed: title/abstract = [tiab], [All Fields], medical subject headings = [MeSH Terms], Embase: explosion = /exp, synonym = /syn, title/abstract = :ti,ab). Once the term list is populated, simple buttons on the spreadsheet instantly sort and group the terms, assign Boolean operators, create the search string, and copy the string to the clipboard for pasting into PubMed or Embase. For search terms not falling under traditional “PICO” categories, users can manually enter custom category labels for Search Builder 1.0 that can automatically be sorted, grouped, and processed in a similar manner as PICO terms. Once the search string is generated, users may quickly add or subtract terms to the string using a yes/no option, facilitating the rapid iterative search string edits necessary to reach a desired search result. Importantly, users do not need to directly edit the search string text, minimizing the possibility of parenthetical and Boolean typographical errors that may cause search errors. To ensure the reproducibility of search strategies for future searches, the user can save, archive, and share the search string file at any time, and in any location on their personal computer.

Table 1.

Developing a Search Strategy for Systematic Review