Library Search Engines use Boolean Operators as a means to express relationships between two or more keywords. Employing Boolean Operators in your search will enable the Database or Search Engine to return the most accurate set of results.
Use Boolean Operators to:
1. Use "AND" to narrow your search to include information resources that only contain both of your search terms.
2. Use "OR" to expand your search to include resources that contain all of your search terms--together or separately.
3. Use "NOT" to narrow your search by excluding certain keywords from your search.
In Algebra, parentheses combine a set of any two elements; the same principle is utilized in databases.
If you are using more than two terms, then you must be aware of the logical order databases use to connect strings of keywords and return results. Utilize parenthesis to connect multiple keywords and boolean operators into a searchable string that the database understands.
Correct:
(Small Bowel Obstruction OR Intestinal Atresia) AND (Diagnosis AND Physician-Patient Relations)
*Incorrect:
*This will produce results, but the database will return more, irrelevant results than you want.
Small Bowel Obstruction OR Intestinal Atresia AND Diagnosis AND Physician-Patient Relations
Search Engines tend less to focus on the whole, and instead focus on the sum of its parts. This means that a search for "Small Bowl Obstruction" has the potential to return results for articles containing the following keywords:
Wrapping a phrase/group of keywords using quotation marks will force the search engine to treat three keywords as one unit.
Phrase Searching Example:
("Small Bowel Obstruction" OR "Intestinal Atresia") AND (Diagnosis AND "Physician-Patient Relations")
Stop Words are keywords that Library Search Engines will ignore when executing a search. Stop Words are important for constructing sentences in natural language, but not so useful for search algorithms. However, there is one exception. If a stop word, such as "the", is part of a formal title (E.g. The Black Keys, The Beatles, etc.), then databases will include them in your search. It is important to recognize which words are automatically excluded from a search.
Typical stop words:
Natural Language Search:
The history of the Liston knife in surgery
What the database ignores and retrieves:
The history of the Liston knife in surgery
Truncation is a useful search technique that broadens your search by capturing root words with multiple endings.
Example: Nurs* = nurse, nurses, nursing, etc.
Wildcarding allows users to search for words that have the same meaning but are spelled differently. This becomes especially important if you are looking for research that has been published in different countries.
Example: A search for "Col?r" will return both Colour (United Kingdom) and Color (United States).
Proximity Searching is a useful technique that enables users to specify the distance, in keywords, that each keyword must appear from one another. The closer your keywords are to one another, the easier it can be for you to determine the 'aboutness' of a resource. Please be aware that not all databases use proximity operators, and some use different variations. Review the "about" or "help" sections of any search engine and database that you are searching to better understand how searches are executed.
"n#" or "n/" =near
The MeSH database is a controlled vocabulary thesaurus consisting of terms that are used to index journals, citations, books, audiovisuals, etc. in MEDLINE. The National Library of Medicine maintains the MeSH database and revises the thesaurus annually.
Term Mapping
When users execute searches in PubMed, their keywords will automatically be mapped to equivalent MeSH terms.
Example:
A search for "cancer" in PubMed will return articles that contain the terms: cancer and neoplasms.
Automatic Explosion
PubMed uses a feature called 'automatic explosion' which automatically includes all of the MeSH terms located below your search term in the hierarchy.
Example:
A PubMed search for "Eye" will capture the following terms: eye, eyelids, eyelashes, and eyebrows.
Subheadings
Subheadings are topical qualifiers that are contained within every MeSH record. Subheadings, unlike MeSH terms, will not be automatically mapped. If you want to include them in your search, you will need to add them manually. Before adding a Subheading to the search builder, it is recommended to review the notes page to better understand how each Subheading is be defined in MeSH. Additionally, Subheadings will 'automatically explode' when added to your search.
For example:
A search using the Subheading "epidemiology" will capture the following qualifiers: epidemiology, endemics, epidemics, frequency, incidence, morbidity, occurrence, outbreaks, prevalence, and surveillance
PubMed Search Builder
Once you have located the correct MeSH term and subheading (optional), the NLM enables you to search directly in PubMed using their "PubMed Search Builder".
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