Skip to Main Content

Searching for Literature for Evidence Synthesis

This guide goes through how to search for literature on databases for evidence synthesis research (Systematic Reviews, Scoping Reviews, Meta-Analyses)

Evidence Synthesis Definitions

The National Institutes of Health Library defines evidence synthesis as the following: 

Evidence synthesis is a process of identifying, selecting, and combining multiple studies to inform practice and policy decisions around a topic or specific research question. The process should be done in standardized ways to avoid bias and to be transparent and reproducible. There are many types of evidence syntheses. Systematic reviews are a well-known evidence synthesis review type, but there are other types (e.g., rapid, scoping, umbrella, narrative, meta-analysis with systematic review).

source: https://www.nihlibrary.nih.gov/services/evidence-synthesis

Define Your Research Question

Use frameworks to help structure your question

  • Select a framework according to the research domain and type of question

  • Describe each element of the question so it can be clearly understood by team members and future readers

  • The PICO format is an example of a common framework used for clinical topics

  • PCC works well for scoping reviews

    • Population Concept Context (PCC)

    • For patients with systemic lupus erythematosus [population], what patient-reported outcome measures [concept] are used in trials of pain relief [context]?

Source: https://www.nihlibrary.nih.gov/services/evidence-synthesis/start-here#:~:text=Use%20frameworks%20to,pain%20relief%20%5Bcontext%5D%3F 

Databases for Literature Searching

A core tenet of evidence synthesis reviews is reducing biases, and a comprehensive literature search is foundational to reducing bias. A comprehensive literature search cannot be dependent on a single database, nor on bibliographic databases (e.g., PubMed, Embase, Scopus, etc.) only.

Source: NIH

Controlled Vocabulary and Keyword Searching

JBI Chapter 10.2.5 Search Strategy

The search strategy for a scoping review should ideally aim to be as comprehensive as possible within the constraints of time and resources in order to identify both published and unpublished (gray or difficult to locate literature) primary sources of evidence, as well as reviews. Any limitations in terms of the breadth and comprehensiveness of the search strategy should be detailed and justified.

As recommended in all JBI types of reviews, a three-step search strategy is to be utilized. Each step must be clearly stated in this section of the protocol.

The first step is an initial limited search of at least two appropriate online databases relevant to the topic. The databases MEDLINE (PubMed or Ovid) and CINAHL would be appropriate for a scoping review on quality of life assessment tools. This initial search is then followed by an analysis of the text words contained in the title and abstract of retrieved papers, and of the index terms used to describe the articles.

A second search using all identified keywords and index terms should then be undertaken across all included databases.

Thirdly, the reference list of identified reports and articles should be searched for additional sources.

Source: https://jbi-global-wiki.refined.site/space/MANUAL/355862729/10.2.5+Search+Strategy

Controlled Vocabulary

Controlled vocabulary is a set of terminology assigned to citations to describe the content of each reference. Searching with controlled vocabulary can improve the relevancy of search results. Many databases assign controlled vocabulary terms to citations, but their naming schema is often specific to each database. For example, the controlled vocabulary system searchable via PubMed is MeSH, or Medical Subject Headings. 

Note: Controlled vocabulary may be outdated, and some databases allow users to submit requests to update terminology.


Keyword Terms

Not all citations are indexed with controlled vocabulary terms, however, so it is important to combine controlled vocabulary searches with keyword, or text word, searches. 

Authors often write about the same topic in varied ways and it is important to add these terms to your search in order to capture most of the literature. For example, consider these elements when developing a list of keyword terms for each concept:

  • Terms with similar meaning
    • flu
    • influenza
  • Terms that have different spelling
    • American versus British spelling
    • hyphenated terms
  • Acronyms
  • Concepts described inconsistently
    • quality of life
    • satisfaction
  • Broad versus specific terms
    • vaccination
    • influenza vaccination

There are several resources to consider when searching for synonyms. Scan the results of preliminary searches to identify additional terms. Look for synonyms, word variations, and other possibilities in Wikipedia, other encyclopedias or dictionaries, and databases. 


Source: https://guides.lib.unc.edu/scoping-reviews/search

Advanced Searching

Advanced Searching

 

Quotations "around phrases"

Phrase searching is looking up phrases rather than a set of keywords in random order. By using phrase searching, it narrows search results by being precise about how you want the words to appear. Databases can use different symbols to search a phrase, however the most common way to search is with "quotes around the phrase". [source: Drexel University Libraries Systematic Reviews LibGuide]


(Nesting in parentheses)

Nesting is a term that describes organizing search terms inside parentheses. This is important because, just like their function in math, commands inside a set of parentheses occur first. Parentheses let the database know in which order terms should be combined. 

Always combine terms for a single concept inside a parentheses set. For example: 

("Influenza Vaccines"[Mesh] OR "influenza vaccine" OR "influenza vaccines" OR "flu vaccine" OR "flu vaccines" OR "flu shot" OR "flu shots" OR "influenza virus vaccine" OR "influenza virus vaccines")

Additionally, you may nest a subset of terms for a concept inside a larger parentheses set, as seen below. Pay careful attention to the number of parenthesis sets and ensure they are matched, meaning for every open parentheses you also have a closed one.

("Influenza Vaccines"[Mesh] OR "influenza vaccine" OR "influenza vaccines" OR "flu vaccine" OR "flu vaccines" OR "flu shot" OR "flu shots" OR "influenza virus vaccine" OR "influenza virus vaccines" OR ((flu OR influenzaAND (vaccine OR vaccines OR vaccination OR immunization)))


Boolean operators

Boolean operators are used to combine terms in literature searches. Searches are typically organized using the Boolean operators OR or AND. OR is used to combine search terms for the same concept (i.e., influenza vaccine). AND is used to combine different concepts (i.e., influenza vaccine AND older adults AND pneumonia). An example of how Boolean operators can affect search retrieval is shown below. Using AND to combine the three concepts will only retrieve results where all are present. Using OR to combine the concepts will retrieve results that use all separately or together. It is important to note that, generally speaking, when you are performing a literature search you are only searching the title, abstract, keywords and other citation data. You are not searching the full-text of the articles.


Field tags

The last major element to consider when building systematic literature searches are field tags. Field tags tell the database exactly where to search. For example, you can use a field tag to tell a database to search for a term in just the title, the title and abstract, and more. Just like with controlled vocabulary, field tag commands are different for every database.

If you do not manually apply field tags to your search, most databases will automatically search in a set of citation data points. Databases may also overwrite your search with algorithms if you do not apply field tags. For scoping review searching, best practice is to apply field tags to each term for reproducibility.


Source: https://guides.lib.unc.edu/scoping-reviews/search