NVivo has a long history of assisting qualitative researchers with managing, and analyzing their data, and being a part of complex research. What you might be interested to know, is that NVivo is also being used by mixed methods researchers to help get a wider picture of the data they’re examining.
Melody Goodman, PhD is a biostatistician and an Associate Professor in the Department of Biostatistics, at New York University Global Public Health. Her work is focused on racial disparities in urban settings, and she is particularly interested in examining how place is a determinant of disparity, and looking at the concept of how ‘where you live, work, play and pray’ impacts your health outcomes. She works in mixed methods research, and as a biostatistician, has a traditionally quantitative view. Much of Melody’s research has been on health and research literacy and how people understand and use health information.
Speaking about the impact of her research, Melody said “My attempt at working towards addressing disparities has been to increase the knowledge level of the receiver of the information. My work spans a wide spectrum from the generation of new statistical methods all the way out to community engaged research, including a program where we train community members on research methods. I don’t specialize in any particular disease area or any statistical methodological area.”
Introduction to NVivo
Melody is currently using NVivo to validate a quantitative survey tool that assesses the level of community partner engagement in research. When her team were required to evaluate their work, they found that there were no existing validated tools, and they would be required to create their own. “We thought that we could find some existing measure and use that to evaluate our programs. But when we went to the literature there really wasn’t any measures that assess how engaged people felt they were in research processes and research centers. So, we decided to develop our own measure, which was really trying to evaluate a big comprehensive research center that had multiple research projects” Melody said.
As the team were developing a brand new measure, and there was no “gold standard” to validate by, they found the qualitative work they undertook was important for a number of reasons; “We were trying to evaluate from the community health stakeholder’s point of view, instead of the academic’s perspective, and considering what the benefit is for a community member for participating in our research and how engaged they feel in the process” Melody said.
Development of a survey tool requires use of mixed-methods and the team uses NVivo to analyze qualitative data. However, they are also using the software as a project management tool, as Melody noted “We had so many different survey data sets and there’s a lot of rounds, with multiple surveys of experts and participants, we really used it to see where we were, and what data we’d collected. Not only were we using it to analyze the qualitative data, we also used it to keep everything in one place for this project.”
Further work with NVivo
Melody is also using NVivo for another project. Melody read some work by sociologist Elijah Anderson who created the term “white space”, meaning spaces which excluded anyone who wasn’t white, either explicitly or implied. It was particularly timely, given the current social climate, and the history of St Louis (where this project originated), with segregation, white flight, suburbanization, and gentrification.
Melody looked at this existing research from Anderson through the lens of her own work, and her own social experiences. “It’s great work, and he had lots of ethnographical stories, but for me as a biostatistician I really want to measure it. As a black person, I could relate to it, but I didn’t feel like I could convince someone who wasn’t black that this idea really existed. If you didn’t have those life experiences, you may view ethnographic work as anecdotal stories” she said.
Melody was interested in creating a survey measure that would assess if a space was a “white space”. “The first thing we needed to do was talk to residents of St Louis, and it became clear that we needed to speak to both black and white residents, and all up we collected around 50 interviews” Melody explained.
As a biostatistician, Melody was particularly interested in gaining a full picture of the areas participants were mentioning in their interviews, to help inform the research further. “In the interviews, the participants talked about different cities, towns, and places such as shopping malls. NVivo was great because I could link census data which has the actual racial composition, and other factors such as percentage of poverty and median household income, of all the places they mentioned, so we could then code the data not only for the town, but also call upon the quantitative data that goes along with it. This is where NVivo showed what it’s really powerful for in mixed methods work” Melody said.
As a mixed methods researcher, Melody thinks of the quantitative data as the ‘what’, and qualitative data and the ‘why’. Having the ability to merge those two together and compare, for example, if someone reports in an interview that a space is predominately white, with available census data, and triangulate that using NVivo, has been an important part of this project.
“Ultimately with this project, we want to create a quantitative survey tool that will allow others to assess whether a space is perceived to be a ‘white space’. Currently, we’re a long way off from that, but we had to start with the qualitative, asking people how they think about ‘white space’, how they talk about ‘white space’, how they define it, and if they even know what we’re talking about? It became so timely because of all the things that are going on in our country, and in this community in particular. We’ll probably get more from it than just the survey, because people really gave us so much information and were incredibly honest in their responses” Melody said.
When it came to selecting software for this project, Melody’s previous experience with NVivo led her to choosing to work with it again. “I had difficulty understanding competitor software. As a traditionally quantitative person, with NVivo I could make sense of what my team were doing, and they were able to generate reports that I could understand” Melody said.
“When I decided that I was going to learn a qualitative software package, I felt most comfortable attempting to learn NVivo. And it was a challenge to think like NVivo, mainly because I don’t think in qualitative terms, but I found the training to be immensely helpful. Once I did that, I could then go and play and learn more myself” she said.
As for the future of Melody’s mixed methods work, the outlook is positive. “I think I’m in a good space. There’s a need for researchers in mixed methods who can understand the quantitative, and the qualitative and go in and interrogate that data and triangulate the qualitative and quantitative findings” she said.
ABOUT THE AUTHOR
QSR International with Dr Melody Goodman, NYU
Dr. Goodman conducts applied biostatistical and survey research for community-based interventions and health disparities research with a strong focus on measurement. Additionally, through academic-community collaborations, she implements, evaluates, and enhances the infrastructure of community-engaged research, in order to mitigate health disparities. With numerous funders supporting her work, she has published over 70 peer-reviewed journal articles. Every day, QSR International helps 1.5 million researchers, marketers and others to utilize Qualitative Data Analysis (QDA) to uncover deeper insights contained within the “human data” collected via social media, consumer and community feedback and other means. We give people the power to make better decisions by uncovering more insights to advance their area of exploration.