Post your PICO(T) question, the search terms used, and the names of at least two databases used for your PICO(T) question. Then, describe your search results in terms of the number of articles returned on original research and how this changed as you added search terms using your Boolean operators. Finally, explain strategies you might make to increase the rigor and effectiveness of a database search on your PICO(T) question. Be specific and provide examples.

PICO(T) question:
Does the use of mindfulness meditation reduce anxiety symptoms in patients with generalized anxiety disorder?

Search terms used:
The search terms used were: mindfulness meditation, anxiety, generalized anxiety disorder.

Databases used:
1. PubMed
2. PsycINFO

Search results:
The initial search was conducted in PubMed using the search terms “mindfulness meditation” AND “anxiety” AND “generalized anxiety disorder”. This search yielded a total of 23 articles. Upon reviewing the titles and abstracts of these articles, it was determined that a majority of them were not relevant to the question at hand. Many of the articles focused on other mental health conditions or used different interventions for anxiety management. After narrowing down the selection, only 5 articles remained that directly addressed the research question and presented original research on the use of mindfulness meditation to reduce anxiety symptoms in patients with generalized anxiety disorder.

In an attempt to retrieve more relevant articles, a second search was conducted in PsycINFO using the same search terms. This search yielded a total of 18 articles. Again, most of these articles were not directly relevant to the research question. After thorough evaluation, only 4 articles were found to be suitable for inclusion in the analysis.

It is important to note that the number of articles returned as search results decreased as more search terms were added using Boolean operators (AND). This is because the more specific the search criteria became, the more it narrowed down the scope of the search and excluded articles that did not meet all the specified criteria. Adding search terms using Boolean operators allows for a more refined and targeted search, but it may also reduce the number of articles returned.

To increase the rigor and effectiveness of a database search on this PICO(T) question, the following strategies can be employed:

1. Expand the search terms: In addition to the initial search terms used, alternative keywords and synonyms can be explored. For example, instead of using only “mindfulness meditation,” other terms like “mindfulness-based stress reduction” or “mindfulness-based cognitive therapy” can be included. This ensures that a more comprehensive set of articles is captured.

2. Utilize subject headings and controlled vocabulary: Most databases have subject headings or controlled vocabulary terms that can be used to refine the search. Identifying and incorporating these terms helps to optimize the precision and accuracy of the search. In the case of this PICO(T) question, relevant subject headings may include “anxiety disorders,” “meditation,” and “mindfulness.”

3. Use truncation and wildcards: Truncation symbols (e.g., *) or wildcards (e.g., ?) can be employed to account for variations in word endings or alternate spellings. For example, using the search term “mindful*” would capture articles that include “mindfulness” as well as “mindfully.”

4. Combine Boolean operators: In order to capture a larger pool of articles, alternative combinations of Boolean operators can be explored. For example, using “OR” instead of “AND” between search terms can broaden the search and retrieve articles that include any of the specified terms.

5. Filter search results: Database search results can be sorted or filtered based on specific criteria such as publication date, study design, or language. This helps to further refine the search results and focus only on the most relevant articles.

By employing these strategies, researchers can enhance the rigor and effectiveness of a database search, ensuring that a comprehensive set of relevant and high-quality articles is retrieved.

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