In the OVID versions of Medline, Embase and Psycinfo the Search Tools feature offers a Map Term function for looking up the preferred term(s) for a given topic. Each is a hierarchical arrangement of broader terms, preferred and related terms, and narrower terms, designed to map the context and content of their respective fields. The lists of preferred terms in Medline (MeSH), Embase (Emtree)) and Psycinfo are particularly extensive. Use of the preferred term is a powerful and controlled way of directly accessing most if not all of the material within a field of study. Most databases offer a thesaurus or list of available subject headings that can be allocated to an article by the author or indexer.
OR/1-15) to create a set containing the results of all of the included terms. Search for OR/(first set)-(last set) (e.g. If using Ovid databases, then a short cut is available for combining many separate searches. Multiple terms covering the same concept are searched for with OR commands. If you see very irrelevant items appearing after using acronyms then it may be necessary to search for the acronym together with other terms that will improve the context of the results. It is often not appreciated that acronyms will have many meanings in different subject fields and may often be the names of gene fragments or biochemical compounds as well as your chosen meaning. For example, a search for the impact of the size of soft drink containers would include the term “can” which also appears in any sentence in the verb form (“can increase”, “can improve” etc.) Therefore the search would need to ensure that the search for can only returned items that also included related terms such as beverage or soft drink.īe careful to test any acronyms that are being searched for. Words that have multiple meanings are especially prone to creating havoc with the search strategies and will often need to be searched with other terms to get the correct context of the term. Try and identify major sources of irrelevant records and adjust the search strategy accordingly.
Run the strategy on the primary database to be used and if you get a large number of items returned examine each item in the first 50 records carefully to identify the source of the terms you included. The key to a good systematic review search strategy is lots of testing. Truncation may be used but again it is important to test each truncated term first to see that only expected terms are retrieved.īe careful not to create an overwhelming list of terms as this will only increase the amount of scanning through irrelevant items to be done. Each term should be tested in the major database to be used to identify what impact it is going to have on the search results received. It is important when doing this that the terms used are relevant to the concept being searched for and do not cross conceptual boundaries. See īrainstorming keywords for a search strategy for a systematic review is essential. But we recommend you consult the Subject Research Guide in your field for a more extensive list. Several suggestions for databases to search are listed below. The search engines to include in a systematic review will vary depending on the subject field and question being asked. If you are getting more than 3,000 items from the first database used with the search strategy for the review the scope of the research question or the structure of the search strategy should be examined closely. The scope of your research question should be kept narrow so that a large number of irrelevant items do not have to be excluded from your result. Often the best test is to search a new resource for a limited component of a review to see if new items are identified. However, there are no rules about how many resources should be included. Usually in systematic reviews a researcher will search enough resources to be able to state with confidence that the literature for the subject area has been comprehensively searched.