Finding the right search terms

Selecting the right combinations of keywords and subject headings is a critical step in developing a comprehensive literature search strategy, requiring careful planning to retrieve relevant articles without producing irrelevant results.

Effective search terms include both keywords, the natural‑language terms used to describe the main concepts of an article, and subject headings, the standardized terms assigned by databases. Using both together creates a comprehensive and reliable search strategy. Keywords are useful for identifying articles that have not yet been indexed, while subject headings retrieve articles regardless of the terminology individual authors choose. Together, these approaches capture variations in language and help ensure that relevant literature is not overlooked.

By breaking a research question into core concepts and identifying, testing, and refining search terms, researchers can build a search strategy that is thorough, reproducible, and tailored to their topic.

Six steps to identify effective search terms

Step 1: Formulate your research question.

• Clearly define the research problem or objective.
• Identify the main concepts embedded in the question.

Sample research question:

How does food insecurity affect glycemic control among patients with type 2 diabetes in community clinics?

Step 2: Gather key articles.

• Identify and collect highly relevant or foundational articles on your topic through preliminary database searches, recommendations from instructors or colleagues, reference lists, or citation tracking.
• Organize these articles in a reference management system so they can be easily retrieved.
• Use these key articles to test the effectiveness of your search strategy later in Step 5. A well-constructed strategy should successfully retrieve them.

Step 3: Extract terms from your key articles.

Your key articles are an important source of potential search terms. Organize the terms you identify by concept in a search log using a document, spreadsheet, or table.

When examining key articles:

• Look at author-provided keywords.
• Review important terms in the title and abstract.
• Use frequency analyzer tools to identify commonly occurring terms.
• Build a list of synonyms, alternate spellings, acronyms, and related terms.

Keyword example for concept two:

The following frequency analyzer tools can help identify commonly used keywords and subject headings across relevant articles.

• Yale MeSH Analyzer – Retrieves keywords and MeSH terms from an article’s PMID.
• Web of Science – The Analyze Results and "Citation Topics" tools help identify frequently used terms.
• Ovid MEDLINE: Analyze Results – Shows which MeSH headings appear most frequently in your search results and maps keywords to controlled vocabulary.
• Swift-Review – Highlights recurring keywords and themes across multiple articles.  

Once your keywords are organized, map them to standardized subject headings to improve retrieval and ensure consistency across databases.

Step 4: Map keywords to subject headings.

Review your key articles and note the subject headings assigned in each database you plan to search.

Examples of database-controlled vocabularies include:

• PubMed uses MeSH (Medical Subject Headings)
• Embase uses Emtree terms
• PsycINFO uses APA Thesaurus of Psychological Index Terms
• CINAHL uses CINAHL Headings

Match each keyword to its corresponding subject heading and record these in your search log. Consider both broader and narrower terms to balance recall and precision.

Subject heading example for concept 2:

Helpful tool:

• MeSH on Demand- Suggests MeSH terms based on article text and abstracts.

Step 5: Test your terms.

Using your key articles as a benchmark, run test searches combining your identified keywords and subject headings to evaluate whether your terms are working effectively.

• Confirm that your key articles appear in the search results. If they do not, your terms may need adjustment.
• Assess whether the results are relevant to your research question.
• Verify that all core concepts are represented, spelling variants and acronyms are included, and database-specific syntax has been applied correctly.
• Note any new relevant terms that appear in the results and add them to your search log.

The appropriate number of results depends on your project. The goal at this stage is not to finalize your results, but to ensure your terms are retrieving relevant material before moving on to refinement.

Step 6: Refine and document.

Refine your search by adding new terms discovered during testing and removing terms that do not improve retrieval.

Document your final search strategy clearly and thoroughly. Consider documenting your strategy in:

• A spreadsheet or table listing keywords and subject headings for each concept
• A Word document or research notebook describing search decisions and revisions

In addition, save your searches within databases to support reproducibility and future updates.

Beyond format, documentation should also include:

• Justification for including or excluding specific terms.
• Notes on which terms performed best and why.
• Database-specific syntax.
• Search date and number of results retrieved.
• Earlier versions to show the development process.

Clear documentation supports transparency and is often required in review protocols and methodology sections.

Final considerations

Identifying effective search terms is an iterative process. Refining keywords and subject headings over time helps ensure your search strategy is both comprehensive and accurate. Search strategies may need to be adjusted depending on the type of review, the scope of literature, delays in database indexing, and the emergence of new terminology.

Ultimately, decisions about which terms to include should be guided by subject expertise, review goals, and a commitment to transparent documentation.