A search strategy is a plan for how you will conduct your searches for a project or to answer a question. It may not be necessary to come up with a highly rigorous, systematic strategy for simple searches, but a strategy will be your best friend for complicated tasks, evidence-based practice projects, or research. In the case of research, your target journal may even require that you dedicate a section of your paper to your search strategy.
While it may seem that devising a formal search strategy is just yet another thing to make the process more cumbersome, as you gain skill, you will come to realize that a strategy makes searching easier and more efficient, and makes your results more relevant. Thus, if you dedicate sufficient time to strategizing, you'll spend way less time wading through hundreds or thousands of irrelevant results to find anything useful for your project.
When you use advanced searching techniques, your strategy will vary depending on the database - especially in terms of controlled vocabulary, syntax, filters, and more. However, every search, no matter which database you're using, shares a set of core components.
Understanding and using these components will help you build a structured, effective search that can be adapted across databases like PubMed, CINAHL, and others. A strong search typically includes elements like a clear topic, a searchable question, search terms (both keyword and controlled vocabulary), a defined scope, lots of iterations, and more.
Among the tabs below, you will find information about each component of the search strategy. We use the same example across the concepts: orientation programs for newly hired nurses in an inpatient setting.
Your topic is the foundation of your search. It should be a clear, concise statement of the issue you're investigating. Clearly defining your topic - what it is, and equally importantly, what it isn't - helps your search stay focused, avoid scope creep, and align your work with your inclusion and exclusion criteria.
You are interested in how hospitals onboard new hire nurses in hospital systems.
Keep these ideas in mind when selecting key terms and phrases for your search.
A searchable question is one that breaks your topic into distinct concepts, and is highly compatible with the multiple search lines available in advanced searching. Using formal frameworks like PICO(T) can be very helpful in making sure you've got a searchable question.
For newly hired nurses in a hospital system do structured orientation programs improve retention and performance when compared to the current informal staff onboarding process?
These criteria define which studies you will include in or exclude from your results. Your criteria may include population, intervention, outcomes, study design, or publication/study type. Some disciplines or projects focus on specific levels of evidence, which may also impact your criteria. Journals will often require researchers to document and describe these criteria, so it is important to consider it early on. Additionally, having clear selection criteria will guide your use of filters and limiters, and can even make your results list more manageable if you retrieve a large number of results.
When you are writing for publication, you will need to write your criteria out in full sentences and be prepared to explain the logic behind them. A bulleted list will be sufficient at the preparation stage, though!
Different databases include different content. Seek alignment between your topic and database(s)'s subject coverage. For more information on database selection, visit the Choosing a Database page of the guide!
Search terms are the words that you'll enter into the search box(es) to retrieve information. They include both keywords (words from your natural language) and controlled vocabulary terms (subject headings like MeSH terms or CINAHL subject headings). For more information on subject headings and controlled vocabulary, visit the Subject Headings and Controlled Vocabulary page of this guide!
Boolean operators are connectors that help refine your search. They can expand and restrict your results - sometimes doing both at the same time. The most commonly used are "AND," "OR," and "NOT."
* Wondering why it's called a "Boolean" operator? These operators are named after George Boole, a 19th century mathematician and logician. Check out a list of additional kinds of logic, functions, and more named after Boole.
The ideal search would include a combination of keywords and subject headings (when applicable), but this example has been simplified just to illustrate how Boolean operators work.
Limits and filters are the post-search button options that let you further refine your results. Available filters and their functionality vary from database to database. Many databases offer the ability to narrow your results by:
You can plan ahead for which filters you plan to use by considering concepts like the standards of currency for your field or acceptable levels of evidence for your project. For more information about this topic, check out the Filters, Levels of Evidence, and Standards of Currency page of this guide.
For this project, we define "current" literature as publications from the last 10 years, and we only want high levels of evidence. So we'd use the following limiters or filters, subject to change depending on what the database offers:
In this scenario, we would likely not need to filter by age/population - it's unlikely that there will be pediatric patients in the mix since healthcare workers are always, to our knowledge, adults (you may, however, retrieve results for nurses working in pediatrics). We also would not add the language filter right off the bat, only when it's necessary.
Searching is an iterative process, meaning that you will likely make many attempts at different versions of your search to find the information that you need. For many searchers, this is the most frustrating piece! Rest assured, you are not alone. Even librarians can get overwhelmed.
From here, you continue tweaking your search strategy until you get a sufficient amount of relevant, helpful articles.
Formal documentation is often unnecessary for quick searches, but is necessary for many searches that contribute to a research project. Many journals require researchers to document and present their search strategy in their writing. Properly documenting your strategy supports reproducibility and transparency, as well as makes it easier to revise your search for future iterations.
Begin formally documenting your process from the beginning instead of trying to remember and replicate later (spoiler alert: you will not be able to replicate what you did later). It's also helpful to write down your reasoning for the terms you choose, filters you apply, etc. If you are conducting a systematic review, follow the applicable standards in your discipline. At a minimum, you should document the following items from your search:
Some databases, like PubMed, allow you to export your search history as a .csv file. This file contains all of the information you'll need for documentation, so it's a good trick to become familiar with. Be sure that all aspects of the search carry over to the .csv file including filters/limiters - sometimes, those do not export with the search history and must be manually added to the documentation.
When you've finished a search session, you export your search history from the database you're working in. You make sure that the history includes date/time and filters/limiters - if not, you add them to the exported document. If the database does not allow you to export your history, you copy and paste it into a document and add all additional relevant information like the date/time, limits/filters.
After exporting, you also document your reasoning for the choices you made throughout the search. You explained the study type filters you chose (because you wanted high level evidence), eliminating orientation as a keyword on its own (because it was giving too many false hits), etc.
Once you've found the articles, you'll need to keep track of all of them. A great way to do this is to create a folder, collection, or project (different names, same function) in your database of choice to save articles. As you work through your search, click check boxes next to relevant articles to save for later. Once you've completed the search, you can review your saved articles to determine which full-texts you'd like to retrieve. You can also export your results into a file compatible with citation management software, a .csv file, or even a Word document.
For more information and guidance on citation management, visit the Citations guide!
You are doing your search in CINAHL. You create an account and save relevant articles to a Project (previously called a folder) while searching in CINAHL. When you are done with the search, you review all of the articles in your folder, tracking down the full-texts or requesting interlibrary loans of the best articles. Then, you export the relevant citations to EndNote to keep track of the articles you'll use in your project.
After you have created your search strategy, you'll need to transform it into a data-base friendly search. Below is a worksheet that will help you through this process in PubMed and CINAHL.
