Our paper on personas in online health communities have been accepted to the Journal of Biomedical Informatics! We will keep you updated once the paper has the final camera-ready version.
Huh J, Kwon BC, Kim S-H, et al. Personas In Online Health Communities. J Biomed Inform. 2016. In Press. doi:10.1016/j.jbi.2016.08.019.
Many researchers and practitioners use online health communities (OHCs) to influence health behavior and provide patients with social support. One of the biggest challenges in this approach, however, is the rate of attrition. OHCs face similar problems as other social media platforms where user migration happens unless tailored content and appropriate socialization is supported. To provide tailored support for each OHC user, we developed personas in OHCs illustrating users’ needs and requirements in OHC use. To develop OHC personas, we first interviewed 16 OHC users and administrators to qualitatively understand varying user needs in OHC. Based on their responses, we developed an online survey to systematically investigate OHC personas. We received 184 survey responses from OHC users, which informed their values and their OHC use patterns. We performed open coding analysis with the interview data and cluster analysis with the survey data and consolidated the analyses of the two datasets. Four personas emerged—Caretakers, Opportunists, Scientists, and Adventurers. The results inform users’ interaction behavior and attitude patterns with OHCs. We discuss implications for how these personas inform OHCs in delivering personalized informational and emotional support.
We are developing a tool to help patients with breast cancer make decisions. To do this, we have been conducting foundational work, including understanding how patients perceive various surgical options, such as contralateral prophylactic mastectomy (CPM), which has become a controversial topic after Angelina Jolie’s announcement.
We are comparing various sources including online health communities, national trends in uptake of surgical options, and search logs to understand how the public perceives CPM and come to understand pros and cons for various decision making points in general. We systematically developed manual annotations around characterizing patients and their posts in online breast cancer communities. These data along with clinical data will be used to develop a prediction model that will help breast cancer patients understand other patients’ trajectory in comparison with their own. We started conducting interviews with breast cancer patients to understand their needs that will be incorporated into our design.
Our students (Lead: Rebecca Marmor) were included in the final 9 teams for the Design Challenge at AMIA 2016!
Rebecca Marmor, MD (Surgery resident, Project lead)
Meera Meghunathan (Medical student)
Elizabeth S. Epstein (Medical student)
Kenneth Trang (High school intern, data manager)
Xiaoqian Jiang, PhD (Machine learning)
Shuang Wang, PhD (Machine learning)
Jihoon Kim, MS (Biostatistics)
Sarah Blair, MD (Oncology)
Jina Huh, PhD (Human Computer Interaction, Social Analytics)
Preuss high school students
Mitchell Boldin (University of Michigan, MSI)