Women's Experience with Stress Urinary Incontinence: Insights from Social Media Analytics.

Abstract

We conducted a large-scale digital ethnographic analysis of anonymous online posts to capture the complete patient experience, knowledge and perceptions among women with stress urinary incontinence. Online posts were identified through data mining. Overall, 200 randomized posts were analyzed using grounded theory qualitative methods. To ensure full thematic discovery we also applied a Latent Dirichlet Allocation probabilistic topic modeling approach to the entire data set of identified posts. Latent Dirichlet Allocation topics are represented as a distribution of words, similar to a word cloud, which were manually reviewed to identify themes. A total of 985 online posts by 762 unique users were extracted from 98 websites. There was significant overlap between the grounded theory and Latent Dirichlet Allocation identified themes. Our analysis suggests that these online communities help women manage the quality of life impact of their stress urinary incontinence, navigate specialty care and reach a decision regarding surgical vs nonsurgical management. Additionally, we identified risk factors, prevention strategies and treatment recommendations discussed online. Findings demonstrated patient values that may influence decision making when seeking care for stress urinary incontinence and choosing a treatment. Social media interactions provide insight into patient behaviors that are important in order to improve patient centered care and decision making.