Have a look to see how they have reported their search strategy, you can document the words in the title, abstract and subject words that are relevant to your search.
Nurses[Subject Heading] OR nurses
(Nurses[Subject Heading] OR nurses) AND (covid-19 OR sars-cov-2)
nurse* (searches for nurse, nurses etc.)
"nursing care"
Population | Nurses | Nurse[Subject Heading] OR nurse[Free text word] OR nurses[Free text word] |
Exposure | Caring for patients with Covid-19 | Covid-19[Subject Heading] OR SARS-CoV-2[Subject Heading] OR covid-19[Free text word] OR SARS-CoV-2[Free text word] |
Outcome | Psychological stress | Stress, Psychological[Subject Heading] OR psychological stress[Free text word] OR burnout[Free text word] |
(Nurse[Subject Heading] OR nurse[Free text word] OR nurses[Free text word]) AND (Covid-19[Subject Heading] OR SARS-CoV-2[Subject Heading] OR covid-19[Free text word] OR SARS-CoV-2[Free text word]) AND (Stress, Psychological[Subject Heading] OR psychological stress[Free text word] OR burnout[Free text word])
In order to make searches as exhaustive as possible, methods other than searching databases can also be used. You can, for example:
Citation chaining, sometimes called snowballing, is a search method where you look at the bibliographies of key articles to find other related articles. The articles retrieved this way might not have been retrieved in your database searches, making it a complementary search method. There are two main types of citation chaining, backward chaining and forward chaining.
Several of the subject specific databases in the list found under "Searching in databases" lets you do forward chaining.
The are also citation databases specifically intended for forward chaining, where you can find out how an article has been cited by other researchers.
You can also use Google Scholar to do forward chaining, search for the title and click "Cited by..." to get a list of other articles where the authors have cited the article you're looking at.
Another chaining method, is using the database feature "Related articles". The articles featured shares similar features with your key article, so this might be a good way of finding more articles. Several of the the databases from the library shows related articles. The databases uses different names for this feature, for example "Suggested sources", "Related records" and "Similar articles".