Google Scholar is a freely accessible search engine which provides a simple way for researchers to broadly search for scholarly literature using the keywords of their research projects. Unlike research databases such as PubMed, Google Scholar conducts its searches across all internet sources, even within the full text of paid articles and can return much more diverse results.
Low-risk devices which are unlikely to be the primary focus of a clinical research often suffer from low results from literature since most databases will not scan the full-text of the article for the keywords, nor will the title and abstract mention the devices. In scenarios like these, indirect clinical evidence is also valuable.
Google Scholar searches the entirety of the scholarly work for the keywords that you search for and returns the snippet from the full text which contains the searched keywords. Hence, with the correct combinations of search operators and keywords, you can find clinical studies using your device of interest even if the device was not mentioned in the abstract. Google Scholar will also notify you of the presence of your keyword in the article, even if the article is not open access (yes, we’re amazed too).
Take a look at the results from PubMed vs Google Scholar for the same search parameters:
Figure 1: Search results from PubMed
Figure 2: Search results from Google Scholar for the same keywords and search filters. The text below the Title and Authors is not the abstract, but a “snippet” from the full text containing the searched keywords.
At its core, Google Scholar is simply a search engine. One of the major advantages of using Google Scholar is that searches for keywords are conducted within the full text of articles and returned as snippets from the same, meaning it not only helps researchers find very specific results relevant to the device of interest, but , which wouldn’t have been visible in a standard Level 1 review.
Google Scholar searches the full text of both open access and paid research articles, and other related information from across the internet and is not limited to title and abstract searching only, giving you more results to consider for your Level 1 review, which ultimately leads to a better CER or PER.
Does this mean you shouldn’t use databases such as PubMed? No, that’s not the case; PubMed, Embase and other research databases play a critical role in every review, especially with regards to the quality of the evidence.
With over 100 million records, it certainly is a powerful research tool.
However, the disadvantage of this search engine is that search results also include Grey Literature; considered as materials or research produced by organizations outside of traditional commercial or academic publishing and distribution channels. Common grey literature publication types include reports, working papers, government documents, white papers and evaluations. Grey Literature often does not contain the highest quality of evidence and will likely be excluded; however, this is not necessarily a disadvantage if you want to include certain grey literature items in your final reports.
Moreover, search results obtained from Google Scholar are not easy to extract from the search engine (when compared to direct exports from databases like PubMed and Embase). The extraction activity requires a significant amount of manual effort which could negatively impact your timeline in terms of effort and can often be an error-prone task.
At Celegence, we understand operational challenges faced by device manufacturers and medical writers alike and use technology to overcome these challenges. Hence, we integrated the Google Scholar search and extraction feature within the CAPTIS™ platform. You can now retrieve data directly from Google Scholar in an efficient manner without any extra manual input.
To search on Google Scholar within the CAPTIS™ platform, you simply need to enter the Google Scholar search string, filters and run the query. CAPTIS™ matches the Google Scholar results with entries on other databases likes PubMed (where applicable) and returns all the information medical writers need for their Level 1 Screenings – title, abstract and publication details, along with additional information such as hyperlinks, snippets, keywords, descriptors, and publication type which normal Google Scholar searches outside of the CAPTIS™ platform do not give.
What’s more, you can export all CAPTIS™ results into an RIS file for easy imports to a Reference Management Software such as EndNote, Mendeley, Zotero and others.
Figure 3: Screenshot of a Google Scholar result from CAPTIS™
Here are some of the benefits of using the Google Scholar Search feature within CAPTIS™:
- Automatic and easy extraction of detailed search results
- Article mapping with other databases for additional information
- Offers resource efficiency
- Offers cost efficiency
- Allows rapid extraction of full texts
- Access to a substantial body of grey literature as well as academic literature
- Easy export of bulk or single citations to an external Reference Management tool
Your medical writing team can benefit from CAPTIS™ with faster turnaround times for systematic literature reviews and more accurate end-to-end MDR/IVDR documentation support. To learn more and view a comprehensive demo of CAPTIS™, reach out to email@example.com today or contact us online to connect with a Celegence representative.