Abrangência nas estratégias de busca em Anestesiologia: descritores nas bases de dados MEDLINE e EMBASE - Volpato, Enilze de Souza Nogueira [UNESP] (2017)
Introduction: A high-quality electronic search is essential in ensuring accuracy and comprehensivness in identifying potentially relevant records in conducting a systematic review. To assist researchers in identifying terms when formulating a sensitive search strategy, librarians and educators instruct researchers to consult and include preferred and non-preferred terms of the controlled database. However, by using all available terms in the thesaurus (i.e. subject headings), strategies can be lengthy and very laborious. Objective: To identify the most efficient method for searching in both Medline through PubMed and EMBASE, covering search terms with different spellings, direct and indirect orders, and association (or lack thereof) with MeSH and EMTREE terms. Method: In our cross-sectional study of search strategies, we selected and analysed 37 search strategies specifically developed for the anesthesiology field. These search strategies were adapted in order to cover all potentially relevant search terms in terms of different spellings and direct and indirect orders, most efficiently. Results: When adapted to include different spellings and direct and indirect orders, adapted versions of the selected search strategies retrieved the same number of search results in the Medline (mean of 61,3%) and higher number in EMBASE (mean of 63,9%) of the analyzed sample. The number of results retrieved by the searches analysed was not identical using the association or not of MeSH and EMTREE terms; however the association of these terms from both controlled vocabularies retireved a large number of records compared to the use of either one of them. Conclusions: In view of these results, we recommend the use of search terms which include preferred and non-preferred terms (i.e., different spellings and direct/indirect order of the same term) and associated MeSH and EMTREE terms, in order to develop highly-sensitive search strategies for systematic reviews.