Sometimes when you search PubMed, you find far more articles than you need or expected, or the search results are not as relevant as you'd like. There are a few tips and tricks that can help you harness the power of PubMed and search more effectively.
To create more effective keyword searches, try these 2 minute tutorials:
More information about subject headings and keywords can be found in the boxes below.
Subject headings are assigned descriptors, similar to hashtags but from a controlled vocabulary, used in some databases to uniformly capture a concept. Searching using these standardized words or phrases, instead of text words, means you do not need to worry as much about synonyms and spelling variations, and also allows you to retrieve more precise results. In MEDLINE, the subject headings are MeSH terms, in Embase, they are EMTREE terms: It is important to keep in mind that the subject headings will in most cases by database-dependent.
Keep in mind that there may be a time delay between the addition of records to databases like MEDLINE and their indexing with subject headings like MeSH terms -- and in some databases, e.g., MEDLINE, some records will never be indexed, even when subject headings are available.
Example: The subject heading for cancer in MEDLINE (via PubMed) is the MeSH term Neoplasms. This means that all articles selected for indexing in MEDLINE that are about cancer at a general level will be tagged or indexed with this subject heading, or if the article is about a specific cancer like breast cancer, with a narrower term.
How you actually use subject headings in a database search (if they're even available) depends on the platform you're searching, e.g., to use the subject heading for 'Neoplasms' in PubMed or Ovid MEDLINE, which can both essentially be used to search MEDLINE:
For thorough searches, you would generally include subject headings and their text word equivalents, plus any alternative terms (related terms, broader terms if needed, specific terms, synonyms, alternative spellings or variants, abbreviations).
Keyword (or textword, natural language, or free-text) searching is when we, for example, search for words which we expect to find in the title, abstract, or author-assigned keywords of relevant articles; it is how we typically interrogate web search engines like Google. Draw up a list of words or phrases related to each key concept in your research question. When using this technique, you will need to be aware of synonyms and spelling variations.
Example: Keywords (or textwords) for cancer can include cancer / cancers / cancerous / malignancies / malignancy / malignant / metastasis / metastases / metastatic / neoplasia / neoplasm / neoplasms / neoplastic / tumor / tumors / tumour / tumours etc.
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Subject Headings |
Keywords (also called textwords, natural language terms, or free-text terms) |
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Pre-defined "controlled vocabulary" terms |
Natural language terms used by authors in the title, abstract, or author keyword fields (may also be terms used in full text) |
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Need to know the exact controlled vocabulary term |
Need to use the textword equivalents of the subject headings plus alternative terms |
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Less flexible. Not always an appropriate subject heading available: May need to combine more than one subject heading with AND to capture one concept or combine subject headings with OR when multiple subject headings could be considered synonyms of the same concept |
Quick & flexible way to start exploratory searches |
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Database looks for subjects only in the subject heading or descriptor field |
Database looks for terms in selected fields, e.g., title/abstract/author keywords (many databases also allow searching in other fields such as in the affiliation field or publication source field) |
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Highly relevant results |
Generates irrelevant results but can increase the sensitivity of the search (i.e., can pick up records that the subject headings may have missed) |
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