Quality Measurement of Consumer Health Questions: Content and Language Perspectives

Health information consumers increasingly rely on question-and-answer (Q&A) communities to address their health concerns. However, the quality of questions posted significantly impacts the likelihood and relevance of received answers. This study aims to improve our understanding of the quality of health questions within web-based Q&A communities. We develop a novel framework for defining and measuring question quality within web-based health communities, incorporating content- and language-based variables. This framework leverages k-means clustering and establishes automated metrics to assess overall question quality. To validate our framework, we analyze questions related to kidney disease from expert-curated and community-based Q&A platforms. Expert evaluations confirm the validity of our quality construct, while regression analysis helps identify key variables. High-quality questions were more likely to include demographic and medical information than lower-quality questions (P