Share to Seek: The Effects of Disease Complexity on Health Information–Seeking Behavior

Abstract

BackgroundWeb-based question and answer (Q&A) sites have emerged as an alternative source for serving individuals’ health information needs. Although a number of studies have analyzed user-generated content in web-based Q&A sites, there is insufficient understanding of the effect of disease complexity on information-seeking needs and the types of information shared, and little research has been devoted to the questions concerning multimorbidity. ObjectiveThis study aims to investigate seeking of health information in Q&A sites at different levels of disease complexity. Specifically, this study investigates the effects of disease complexity on information-seeking needs, types of information shared, and stages of disease development. MethodsFirst, we selected a random sample of 400 questions separately from each of the Q&A sites: Yahoo Answers and WebMD Answers. The data cleaning resulted in a final set of 624 questions from the two sites. We used a mixed methods approach, including qualitative content analysis and quantitative statistical analysis. ResultsThe one-way results of ANOVA showed significant effects of disease complexity (single vs multimorbid disease questions) on two information-seeking needs: diagnosis (F1,622=5.08; P=.02) and treatment (F1,622=4.82; P=.02). There were also significant differences between the two levels of disease complexity in two stages of disease development: the general health stage (F1,622=48.02; P<.001) and the chronic stage (F1,622=54.01; P<.001). In addition, our results showed significant effects of disease complexity across all types of shared information: demographic information (F1,622=32.24; P<.001), medical diagnosis (F1,622=11.04; P<.001), and treatment and prevention (F1,622=14.55; P<.001). ConclusionsOur findings present implications for the design of web-based Q&A sites to better support health information seeking. Future studies should be conducted to validate the generality of these findings and apply them to improve the effectiveness of health information in Q&A sites.