Bibliographic databases do not tend to use natural language interfaces, and even if they do, it is difficult to discern how the result set you got back was created. To perform a systematic review, you need to systematically plan how you will interrogate databases. Below we list some techniques you can use to create searches that will find the most comprehensive set of results and which are easily transferrable from one database to another.
Most databases use boolean logic to enable searching. It is therefore important to understand the major boolean operators:
AND - search terms joined with AND will find results that include all the search terms, but not one of the search terms on its own. This narrows your search.
OR - search terms joined with OR will find results were one of more of the search terms are featured. This broadens your search.
NOT - search terms joined with NOT will find results where the term mentioned after NOT. This narrows your search.
You can find a more detailed summary of how these operators work in the Smart Searching tutorial.
We have guides to help you plan your searches and reference what you find:
The initial step in planning a search strategy is choosing your keywords. Usually your keywords will appear in your research question. Discard the words that do not denote a concept.
So if our research question was "In patients recovering from heart attack, does exercise promote quicker recovery times than pharmacotherapy alone?", the keywords would be heart attack, exercise, recovery and pharmacotherapy.
Our next step would be to think about whether our terminology would be used in the literature and whether there are alternate terms for what we're searching. Examples of synonyms for our keywords:
heart attack could be myocardial infarct or cardiac arrest
exercise could be swimming, cycling, running, walking
pharmacotherapy could be drugs, medication
You can search for multiple words which share a word root through the use of truncation. A common symbol used in databases for truncation is the asterisk * and so if we were using truncation to find terms with the word root hero (i.e. hero, heroes, heroic, heroically, heroism) we would type hero* into the search.
Truncation symbols differ from database to database and will sometimes work in different ways, so it is important to check the help section of the database you are using to ensure you are using truncation correctly.
Connected to this is the concept of the wildcard. Wildcards are usually used to substitute for one or more characters within a word. The question mark ? is a common symbol for wildcards. So if you wanted to find both generalisation and generalization without typing both out, you could type generali?ation to find both.
The # can be used as a wildcard where the word may, or may not, have an extra character, e.g. colo#r. This will find color but also colour.
Again wildcards can be different depending on the database you are using, so always consult the help section.
For more advanced searching you may want to use proximity operators, such as NEAR or ADJ. These work like the AND function but allow you to specify how closely two words are related.
So if you are searching for children's perspectives on painful medical procedures, you may wish to use children's perspectives as one of your search terms. You may be aware though that authors may write this as "perspectives of children" or "looking at perspectives particularly those of children" and so may miss results if you search for "children's perspectives" as a phrase. With the proximity operators you can specify how many words can appear between the two terms.
E.g. On Ebsco databases, children N4 perspectives would find any results where the words "children" and "perspectives" appear within four words of each other.
On Ovid, this would be recorded as: children ADJ4 perspectives
As you can see, different databases use different operators so always check the help section of the database you are using to find the correct operator.
An important part of research is deciding which research to leave in and which to exclude. Limiters in databases allow you to exclude material. It is important to have a valid reason for excluding material, especially when creating a systematic literature review.