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One of the most important things to remember about library research databases is that they do not function like search engines such as Google. Google is most useful when you're looking for quick facts and simple questions. This is not the case for research, which by nature is much more complex. The algorithms used by search engines to index websites and return search results are vastly different than any of the algorithms used by research databases. Google works well when you ask your questions as phrases (i.e., "how many COVID-19 cases have been reported in Ohio", "why is chocolate deadly to dogs"), but research databases work best when you search using keyword strings.
Brainstorming possible keywords is the next thing you should do after identifying your research question. It has a couple of steps:
Your lists of synonyms and related terms are the keywords you'll need to begin your literature search.
Keep in mind that sometimes your subtopics may need to be broken down even further, depending on what you are interested in. For example, if my population is newborns undergoing heelstick, I need to break that down even further into sub-subtopics: newborns and heelstick.
While the video tutorial below does not specifically demonstrate the use of the PICO framework, the principles it discusses can be directly applied to it. You can treat each component of PICO the same way the video treats subtopics.
Let's go back to my newborns undergoing the heelstick procedure. This population can be broken down into two sub-subtopics: newborns and heelstick.
From here, I need to brainstorm additional keywords and synonyms for each of these subtopics. (Hint: here is where Google and Wikipedia can be useful. You shouldn't ever cite them as an authoritative source, but they are great tools for learning more about unfamiliar topics.)
This table lists some of the keywords I came up with for each of the two subtopics.
| newborns | heelstick |
|---|---|
| neonate | heel lance |
| infant | heel prick |
| capillary blood sampling |