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Searching the Literature

Controlled Vocabularies and Subject Headings

When you search a database like PubMed or CINAHL, you might type in words that you think describe your topic like nursing orientation. But research authors might use different words to refer to the same thing: onboarding, induction, new hire training, transition to practice, and more! It's very cumbersome (and nearly impossible) to account for all the different ways to refer to a concept just by listing synonyms in a keyword search.

The word orientation also references a myriad of concepts in healthcare. If you search orientation, you'll find articles about sexual orientation, device orientation, whether a patient is alert and oriented, cultural orientation, molecular orientation... the list goes on. When you search with broad keywords, you not only risk missing relevant articles. You also risk ending up with thousands of irrelevant results that obscure relevant ones. Talk about searching for a needle in a haystack. 

Here's an example: We searched the word orientation in PubMed. In the search history, we can see how PubMed broke the word down and searched it. In the screenshot, the highlighted terms are those that are definitely not related to our topic, but other terms could still pull in irrelevant results.

This is where Controlled Vocabularies come in!

Controlled Vocabulary

Many databases use a system called a controlled vocabulary to organize articles. Controlled vocabularies are a list of official terms that the database uses to refer to a concept. When an article is added to a database, a trained indexer (or, increasingly, AI) reads it and assigns relevant terms/phrases from the list. These terms are often called subject headings. When a user searches using these terms, articles with the terms assigned to it will appear in the search. It's similar to hashtags on social media: you post a photo of your new dog and assign #puppy to it.

Here's why this helps:
  • It captures all of the different ways of saying the same thing. Even if one article says "nurse orientation" and another says "nurse onboarding," or even "RN training," they will both be assigned the same subject heading, which would be MH "Employee Orientation" in CINAHL, or "Inservice Training"[Mesh] in PubMed. When you search using those subject headings, you'll find both articles!
  • It filters out the unrelated concepts. Articles about irrelevant types of orientation won't appear in your results since they won't be tagged with the same subject heading (unless they manage to be about both nursing orientation AND mental status).

Natural Language Searching

The existence of controlled vocabularies implies the existence of non-controlled vocabularies, or words and phrases freely used without standardization. That is the basis of Natural Language Searching, a type of search where users type their query into the search box using everyday language, including full sentences. Such a search might look like "how do hospitals train new nurses?" or, "what's the best way to orient new nurses?" In simple terms, a natural language search is probably how you're searching in Google.

Natural Language Searching in Databases

While this method of searching is very familiar, it isn't very effective when it comes to database searching. Databases aren't designed to handle natural language like Google does. They're programmed to look for articles that contain the words you typed and do not know to distinguish between question words and the actual content you're looking for.

That means that your search might include a bunch of extra words that don't help the database find relevant articles, reducing the precision and recall of your search. Databases like CINAHL may also completely ignore some words (called stop words, read more HERE, and see a CINAHL-specific list HERE). 

Keyword Searching

Keyword searching is when you enter words or phrases - but not complete sentences - into a database search bar to search for information. It is familiar and flexible: you choose the terms, not the database.

This strategy is especially useful when:
  • You are searching for newer concepts that might not have subject headings, or if the coverage date of the heading doesn't go very far back.
  • You want to refine a search when the subject heading isn't giving you complete results.
  • You are doing a quick search that does not need to be comprehensive, reproducible, or formally documented.
But, beware!

Keyword searching, while quick and intuitive, has limitations. When keyword searching is used on its own, users risk missing relevant information or pulling in irrelevant information:

  • When using the keyword orientation, you're using the word that you would use to describe the concept. But researchers might use onboarding, new hire training, or transition to practice. If you don't include all variations (using Boolean operators, you may miss relevant articles. 
  • Keyword searching also doesn't "block out" unrelated types of orientation - your results may also include articles about mental status, device orientation, sexual orientation, cultural orientation, and more.

Simply put, the keyword orientation is not unique or specific enough to do the job.

Tips for More Effective Keyword Searching

  • Use multiple keywords to capture the different ways to express a concept. Try to come up with a list of synonyms for each word/concept.
  • Use truncation to capture all variations of a word. The most common way to do this is by typing the root of the word and ending it with an asterisk - *. For example, education becomes educat*, which captures education, educate, educating, educational, etc. This saves you from having to type each variation.
  • Use quotation marks around phrases in your search. This prompts the database to search for the exact phrase you've entered rather than searching each word separately. For example, "nursing orientation". However, keep in mind that using quotation marks is not compatible with using truncation.
  • Pay attention to the words authors use to reference your concept of interest in relevant abstracts and titles. You can add these words and phrases to your list of keywords, combining them with Boolean operators!

So, a search string using keyword searching might look something like nurs* orientat* OR nurs* onboarding OR" new hire training"  OR nurs* training.

Combining Subject Headings and Keywords

So which is better - controlled vocabulary or keyword searching? The answer is: neither. Each method has its strengths and limitations. And in some databases, you can only use one or the other.

The best search is one that combines both controlled vocabularies and keywords (in databases that allow it). This is especially the case for complex or comprehensive searches. A combined search allows you to take advantage of the precision and consistency of subject headings while also capturing newer or less standardized language with keywords.

How do you combine them?

Combine your search terms using Boolean operators and the advanced search option for multiple lines. In general, you will use the Boolean operator OR to combine synonyms on one line, and the Boolean operator AND to combine concepts across the different lines on a search. With this strategy, you will need to type OR, but not AND. Here's an example:

We'll cover the specifics PubMed and CINAHL on their respective pages.