Search across guide titles, topics, keywords, and content throughout the Researcher's Field Guide.
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Conference proceedings can contain important research that journal searches miss, particularly in conference-oriented and rapidly developing fields. Learn when to search them, where to look, and how to handle conference papers and abstracts responsibly.
Read Guide →Important evidence does not always appear in academic journals. Learn where to find government reports, policy documents, official statistics, technical reports, and other nonjournal research and how to evaluate what you find.
Read Guide →The most important database is not necessarily the largest or most prestigious one. It is the database whose coverage, indexing, document types, and disciplinary focus best match the evidence your research question requires.
Read Guide →Discipline-specific repositories can reveal research outputs that conventional bibliographic databases do not capture, capture later, or represent differently. Their usefulness depends on what the repository contains and whether those materials matter to your research question.
Read Guide →Trial registries can reveal ongoing, completed, terminated, and sometimes unpublished trials that journal databases may not identify. They are particularly important for systematic reviews of interventions and questions involving clinical trials.
Read Guide →Registration extends beyond conventional clinical trials. Depending on your field and question, other study registries and preregistration systems may reveal planned, ongoing, completed, or otherwise difficult-to-discover research.
Read Guide →Institutional repositories can expose theses, manuscripts, conference materials, reports, and other research outputs produced by a particular university or organization. They are especially useful when institutional affiliation or locally deposited material matters to your search.
Read Guide →When a concept has no agreed name, searching for one preferred term can miss substantial parts of the literature. Build the concept from the language authors and databases actually use, then test those terms against known relevant records.
Read Guide →Different disciplines may study closely related phenomena using different terminology, theories, and indexing systems. A cross-disciplinary search should therefore identify the vocabulary used within each relevant field rather than translating one field's terminology unchanged into every database.
Read Guide →Older studies may describe populations using terminology that researchers would not choose today. A comprehensive historical search may therefore need those terms for retrieval while clearly distinguishing their search function from appropriate current language.
Read Guide →Terms can look similar, share an abbreviation, or occur in the same literature without representing the same concept. Check definitions, context, operationalization, and actual retrieval before combining apparently similar terms in a search.
Read Guide →Relevant studies may identify the same drug or product by a generic name, brand name, development code, or another identifier. For sensitive retrieval, search the names that actually appear in eligible literature rather than assuming one naming system will capture them all.
Read Guide →Relevant older records may use names that have since been replaced, renamed, reclassified, rebranded, or abandoned. Historical names should be included when they provide a plausible route to evidence within the time period and scope of your search.
Read Guide →Emerging topics rarely arrive with stable vocabulary. Build the search iteratively from seed records, competing labels, descriptive phrases, early terminology, and developing subject headings, then expect to revise it as the field matures.
Read Guide →There is no correct number of synonyms for a search concept. You probably have enough when the important ways of expressing the concept are represented, known relevant records are retrieved, and additional terms produce little meaningful new retrieval.
Read Guide →Parentheses tell a database which search terms belong together before different parts of a query are combined. They become especially important when AND and OR appear in the same search because missing or misplaced parentheses can change which records are retrieved.
Read Guide →Translating a search strategy means preserving its concepts and retrieval logic while adapting controlled vocabulary, fields, operators, and syntax for another database. It is not a copy-and-paste exercise.
Read Guide →A search strategy should evolve as you learn how the literature is described, but refinement can quietly change what the search means. Learn how to improve terminology, fields, operators, and database-specific syntax while keeping the underlying research question stable.
Read Guide →There is always another synonym, spelling variant, acronym, or related expression you could add to a database search. The useful stopping point comes when additional terms no longer meaningfully improve retrieval of relevant literature.
Read Guide →A search strategy can contain hundreds of terms and still retrieve the wrong literature. Length reflects complexity, not necessarily quality, so every concept, term, operator, and restriction still needs justification.
Read Guide →A research question and a database search string serve different purposes. Some concepts that are essential for deciding study eligibility may be poor retrieval concepts and can make the search unnecessarily restrictive.
Read Guide →An outcome may be essential to your research question without being a reliable search concept. Leaving it out can protect search sensitivity when outcomes are inconsistently described in titles, abstracts, or indexing.
Read Guide →A required study design does not always need to become a database search restriction. Design terms and filters can improve precision, but unreliable terminology or poorly performing filters may cause relevant studies to disappear.
Read Guide →Population filters can make a search more manageable, but they depend on how populations are described and indexed. When that information is incomplete or inconsistent, screening may be safer than restricting retrieval.
Read Guide →Database filters are convenient, but they are retrieval rules rather than guarantees of relevance. Depending on indexing, metadata, and filter design, an eligible study can disappear when a seemingly reasonable restriction is applied.
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