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DMSC 7005

Library Tutorial

Search for Articles Using Boolean Operators

Boolean is a type of very simple programming language that will let you tell databases what you are searching for much more exactly and greatly improve your chances of search success.

AND

  • use AND in between search terms to tell the database that your results must include both terms. This is a great way to narrow your results down if you are retrieving too many non-relevant articles. ie. diabetes AND children.

OR

  • Use OR in between search terms to tell the database that your results can include either or both of the search terms.
  • OR is often used to include many different terms that refer to the same topic. ie. children OR pediatrics OR adolesecent.

NOT

  • Use NOT to tell the database that you do not want articles including a search term within your results.
  • This can be used to exclude things irrelevant to your research, such as certain populations. ie. diabetes NOT children.

 

 

Boolean Punctuation

You can build complex search strings by using additional punctuation in your boolean searches. Some common ones include:

  • Parentheses
    • Use parentheses to group terms and tell the database what combination you want to search and in what order. This is similar to algebraic expressions.
  • Quotation Marks
    • Use quotation marks around a phrase to tell the database you want it to be searched for in exactly the entered spelling and order.
  • Wildcards/Truncation
    • Use * to tell the database to search all terms that start with a particular string of letters. For example, pharm* would search for pharmacology, pharmaceuticals, pharmacologists, and more.

((healthcare OR "health care") AND ethics) NOT nurses

  • As an example, the above search string would search for articles including either healthcare or health care and the word ethics, and exclude every article mentioning nurses.

 

Using Subject Headings

Subject headings, also known as thesauri, controlled vocabularies, or taxonomies, are a set of specific and controlled terms applied to research articles to clearly mark what topics a research article addresses. They are finding aids used to help researchers identify articles relevant to them, regardless of variations in terminology. Subject headings collect all articles on a particular topic, regardless of what terms the author uses. This controls for variations in spelling, such as with British v. American English, as well as with variations in terminology.

As an example, let's look at MeSH, the subject heading system used by PubMed. The MeSH term Drug Therapy is used for any articles that reference drug therapy, drug therapies, chemotherapy, chemotherapies, pharmacotherapy, and pharmacotherapies. So when you are using PubMed, you can do a search for the subject heading Drug Therapy to get comprehensive results, even if the author was using the alternative terminology listed above.

Subject headings are a great way to quickly narrow down search results to the most relevant research for your research question. While it may not catch everything (and may therefore not be ideal for literature reviews or systematic reviews), they are great for identifying key literature in a particular topic area, or for answering clinical questions.

Note that every database uses its own subject headings system. When using a new database, try looking for terms such as Subject Headings, Index Terms, or Thesaurus in its navigation or help menus to find their subject headings. Database help or support pages may also provide guidance on using subject headings.

Develop a chart of search terms

Turning a research question into a search string is a multi-stepped process:

  1. Break down your research question into searchable concepts
  2. Write down a list of keywords and synonyms for each concept
  3. Map each concept to relevant controlled vocabularies for each database (such as MeSH)

As you do test searches and read more relevant literature, you will be able to add additional keywords to your search concepts. It is recommended that you reach out to a librarian for assistance in generating keywords and mapping concepts to a controlled vocabulary.

Example Research question: Does obesity lead to heart disease and strokes?

Topic Keywords
Natural language
Pubmed
MeSH
CINAHL
Subject Headings
Academic Search Complete
Subject Terms
obesity obesity
overweight
obese
morbidly obese
"Obesity"[Mesh]
"Obesity, Morbid"[Mesh]
(MH "Obesity")
(MH "Obesity, Morbid")
DE "OBESITY"
DE "MORBID obesity"
heart disease heart disease
cardiac diseases
heart disorders
cardiovascular
"Heart Diseases"[Mesh] (MH "Heart Diseases") DE "HEART diseases"
stroke stroke
cerebrovascular accidents
"Stroke"[Mesh] (MH "Stroke") DE "STROKE"

Build your Search

Once all terms have been identified, you need to put them together in a search string. You can export your search strategy in addition to the results, to use in your search documentation.

A search string will generally look like:

(Topic A term 1 OR Topic A term 2) AND (Topic B term 1 OR Topic B term 2) AND (Topic C term 1 OR Topic C term 2)

If searching PubMed with our example research question, the search string would look like:

(obesity OR overweight OR obese OR "morbidly obese" OR "Obesity"[Mesh] OR "Obesity, Morbid"[Mesh]) AND ("heart disease" OR "cardiac diseases" OR "heart disorders" OR cardiovascular OR "Heart Diseases"[Mesh]) AND (stroke OR "cerebrovascular accidents" OR "Stroke"[Mesh])

The search string above was developed for PubMed. When adapting the string for another database, you want to have the strings operate as similarly as possible. You would replace the MeSH terms with the controlled vocabulary of the other databases used.

The search string above is searching with both keywords and MeSH terms. The MeSH terms will be searched in the MeSH field. The keywords will be searched in all fields, like the title, abstract, journal name, etc.

Translate your Search

In a systematic review, you will need to keep the search as similar as possible between different databases. In practice, you should only need to change a few things for each database:

  • Applying consistent search limiters to each database
  • Searching the same fields in each database
  • Applying the controlled vocabulary of each database

As experts in database searching, librarians can help you translate your search string between different databases.