The aim of a systematic search is to uncover all relevant results related to your topic. Since systematic review searches can be extensive and yield a large volume of results, it is crucial to minimize the number of irrelevant results that need to be screened later on. In this part, you and your team will create search strategy to find these relevant articles.
Determine which databases are appropriate to search for your topic or field of interest. They can be multidisciplinary or subject-specific. Databases include articles from multiple journals, which is why it is important to search many databases for your review. You can access Brenau's full list of databases here.
When performing a literature search, you want to uncover as many relevant articles as possible using key terms or controlled vocabulary. You expand on each key term by thinking of synonyms or related words that might reveal different results.
Example PICO Question
Controlled Vocabulary
Controlled vocabulary is a standardized set of terms and phrases used consistently to describe and categorize information. This practice ensures that everyone uses the same terms in the same way, which improves the accuracy and efficiency of information retrieval and data management.
Depending on the database, controlled vocabulary might be called different names.
Nesting
A technique used to group search terms together using parentheses to control the order in which the search terms are processed. This helps create more precise and effective search queries, especially when combining multiple keywords with Boolean operators (AND, OR, NOT).
ALWAYS combine terms for a single concept inside one set of parenthesis.
Example:
(exercise [MeSH] OR "physical activity" OR "Physical Conditioning" OR "Endurance Training")
Field Tags
Field tags are specific identifiers used to limit the search to particular fields within a record. These tags help refine searches by specifying where the search terms should appear, such as in the title, author, abstract, or subject fields.
For systematic review searching, best practice is to apply field tags to each term for reproducibility.
When you combine these strategies, your search string may look like this:
(exercise [MeSH] OR "physical activity" [AB] OR "Physical Conditioning"[AB] OR "Endurance Training" [AB]) AND ("insulin resistance" [AB] OR "insulin resistant" [AB] OR "insulin sensitivity" [AB] or "insulin resistant diabetes" [AB]) AND ("adolescent [TX] OR teen [TX] OR Teenager [TX] OR Teenagers [TX] OR Youth [TX])
Grey literature refers to research that is not published through traditional commercial publishing channels. In the context of a systematic review, grey literature can include a variety of sources, such as:
Incorporating grey literature into a systematic review is crucial because it helps to:
Google Scholar
Google scholar is only a supplementary source. Results fluctuate and you must acknowledge constraints.
Using AI Tools for Research: Benefits and Cautions
You may choose to supplement your database searching with Artificial Intelligence (AI) tools such as ChatGPT, Elicit, Scite, or other research assistants. These tools can offer helpful features, such as:
Chat-style interaction to refine your research question
Identification of recent publications, including pre-prints
Access to more open-access literature
Summarization of articles or key concepts
However, use caution when incorporating AI into your research process:
Hallucinated (fake) citations: AI tools may generate references that do not exist or misattribute information.
Inaccurate summaries: Summaries may oversimplify or misrepresent complex findings.
Limited access to full-text: AI tools may not access the same full-text scholarly databases your library provides.
Lack of peer review: Not all suggested sources may be scholarly or peer-reviewed.
Best Practices:
Always verify citations in your library’s databases or Google Scholar.
Use critical appraisal tools to assess the credibility and quality of sources.
Do not rely solely on AI for literature reviews or evidence synthesis.
When in doubt, consult a librarian or your professor.
AI can be a helpful starting point, but should never replace rigorous, scholarly research methods.
Record. Report. Repeat
Documentation is important for transparency and replicability. For any questions that may arise throughout the review process, you can return to your notes for an answer. Additionally, any peer-reviewers who are assessing your review will want to know your process and intent.
Good Evidence = Good Healthcare.
*Note the rationale for database selection, choice of searchable concepts, tested/excluded terms, field for keyword searching, line combos, filters, etc. so your team understands.
*Note citations for definitions used.
*Create a list of validation articles that support why the study is needed.
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