In most cases, the core search for a health sciences evidence synthesis project is built in PubMed or Ovid MEDLINE (or, less commonly, Embase). It's then translated across other databases.
PubMed and Ovid MEDLINE both search the MEDLINE dataset, which contains millions of citations in the health and life sciences from journals explicitly selected for indexing in MEDLINE. However, PubMed and Ovid MEDLINE do have some differences.
Whether you use PubMed or Ovid MEDLINE to built your core search strategy is entirely up to you, but most searchers who are not librarians or information specialists tend to choose PubMed. Many researchers are already familiar with it and find the learning curve of moving from casual to systematic searching less steep than with Ovid MEDLINE.
PubMed's default search uses Automatic Term Mapping (ATM) to make an educated guess as to what a researcher is looking for, based on the terms entered into the search box. The most important thing ATM checks for is whether there is a good match for the words or phrases in the search within PubMed's controlled vocabulary (MeSH, or Medical Subject Headings).
While ATM is good for basic searching (e.g., to find a few recent articles on a topic) or exploratory searching, a systematic search requires a detailed strategy and full control of what PubMed is doing. That means identifying appropriate controlled vocabulary and constructing complex search strings using PubMed's database syntax.
The controlled vocabulary used in PubMed is called MeSH, or Medical Subject Headings. This tutorial, Searching PubMed: Medical Subject Headings (MeSH), provides an introduction to MeSH, including what it is, how to locate MeSH in a PubMed record, and how to search for terms in the MeSH Database.
Click the image (or the link below it) to open the tutorial in a new window. You will be asked to register if you do not yet have a Reach 360 account.
PubMed uses a complicated syntax to build searches. This tutorial, Searching PubMed: Constructing a Systematic Search Using PubMed's Syntax, walks you through the essential elements of constructing a systematic search in PubMed. This includes using:
Click the image (or the link below it) to open the tutorial in a new window. You will be asked to register if you do not yet have a Reach 360 account.
When using search field tags, remember:
Common search field tags used in systematic searches are:
[mesh] - Searches only the MeSH field.
[mesh:noexp] - Searches only in MeSH, and explicitly excludes the narrower terms underneath your MeSH term in the hierarchy (turns off "exploding").
[tiab] - Searches in title, abstract, and author keywords (as well as collection title and other abstract).
[tw] - Searches in lots of different fields including, but not limited to, title, abstract, MeSH, MeSH subheadings, publication types, substance names, various author name fields, and more.
The wildcard symbol in PubMed is the asterisk (*). As with search field tags, using a wildcard disables Automatic Term Mapping. The following rules apply to wildcards:
Examples:
To search for two or more words together as a single search string (i.e., as a phrase), use quotation marks around them: "college athletics" [tiab]
You can use wildcards in phrase searches: "colleg* athlet*" [tiab]
PubMed first checks to see if the phrase appears in its phrase index. If it does, PubMed executes the search as requested. If it doesn't, PubMed ignores the search field tag and tries to match the words x AND y using Automatic Term Mapping. If your string isn't in the phrase index, you can use proximity searching to look for it instead.
To search for free text terms (not MeSH) near one another, but not necessarily as a phrase, use proximity searching. The syntax is: "search terms" [search field tag:~N]
"search terms" - two or more words; will be searched as individual words appearing in any order; no wildcards allowed
[search field tag:] - either [tiab:] or [ti:]
~N - ~ (the tilde mark, located to the left of the number 1 key on your keyboard) tells PubMed to search using proximity; N is the maximum number of words that can appear between search terms.
Example: "college athletes" [tiab:~3]
Proximity searching, with an N of zero, can be used to find search terms next to one another when a phrase is not found in PubMed's phrase index.
Example: instead of "zombies run" [tiab], which is not in the phrase index, try "zombies run" [tiab:~0]
To download your search history, go to the Advanced Search page and tap the Download button at the top right of the History and Search Details box.

Open the csv file in Excel. You can expand the cell sizes and wrap the text to see the search strings more clearly. Note: because Excel has a character limit for each cell, you may need to open your csv file in a text editor like Notepad to see the full text of very long search strings.
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