Literature review of biotechnology research in health and agriculture using QDA Miner and WordStat August 25, 2016 - Blogs on Text Analytics
Why do many people embrace biotech research into healthcare in the search for new treatments for disease but the same people are opposed to biotech research into agriculture to develop crops that provide greater yields and are more resistant to disease? That is one of the questions being asked by Dante Israel Leon de la O as part of his PhD thesis at Cinvestav, Mexico City. Dante has a Masters in Bioengineering and Biotechnology and an undergraduate degree in biochemical engineering. Cinvestav, Mexico City is a Mexican research institute with nine centers across the country.
Dante is using QDA Miner and WordStat to perform a rigorous literature review of biotechnology research in health and agriculture. He is researching both scientific and mainstream publications. Part of Dante’s PhD thesis is focused on how Mexico is positioned versus the rest of the world, in terms of published articles in his field. As he says, “When I began my research I realized there was no specific data base related to my field of interest and featuring Mexico in particular so I had to start from scratch.”
A global search of the literature was a daunting task but he discovered that using QDA Miner’s Boolean text search is one of the best ways to filter data of a specific discipline in a database. The TEXT RETRIEVAL function searches for specific keyword or combination of keywords in documents. You can search in all documents in a project or restrict the search to specific document variables. Searches can also be restricted to specific coded segments. The boolean text search allows you to retrieve all text segments in documents that are related to a specific topic.
He also finds the query by example feature of QDA Miner very useful. The QUERY BY EXAMPLE search tool is an alternative to a keyword-based search. Rather than specifying a long list of keywords joined by Boolean operators, this query method looks for documents or text segments similar to a given example and presents them in an initial list of search hits in descending order of similarity. The user then marks specific items as relevant or irrelevant and then performs a new query. The system adjusts the initial query by taking into account the provided relevant information and often provides better search results. After a single or a few iterations, the user can then select relevant items for further processing.
To date Dante has analyzed more than 1800 publications on health biotechnology. Using categorization dictionaries of WordStat he furthered refined his search to find individual articles by isolating specific themes related to his subject, to identify areas of agreement and disagreement involving biotech research into health care and agriculture. Dante is currently working on the interview portion of his research and intends to use QDA Miner to fully analyze those interviews.