Abstract
OBJECTIVE: Dietary supplements are widely used. However, dietary supplements are not always safe. For example, an estimated 23 000 emergency room visits every year in the United States were attributed to adverse events related to dietary supplement use. With the rapid development of the Internet, consumers usually seek health information including dietary supplement information online. To help consumers access quality online dietary supplement information, we have identified trustworthy dietary supplement information sources and built an evidence-based knowledge base of dietary supplement information-the integrated DIetary Supplement Knowledge base (iDISK) that integrates and standardizes dietary supplement related information across these different sources. However, as information in iDISK was collected from scientific sources, the complex medical jargon is a barrier for consumers' comprehension. The objective of this study is to assess how different approaches to simplify and represent dietary supplement information from iDISK will affect lay consumers' comprehension. MATERIALS AND METHODS: Using a crowdsourcing platform, we recruited participants to read dietary supplement information in 4 different representations from iDISK: (1) original text, (2) syntactic and lexical text simplification (TS), (3) manual TS, and (4) a graph-based visualization. We then assessed how the different simplification and representation strategies affected consumers' comprehension of dietary supplement information in terms of accuracy and response time to a set of comprehension questions. RESULTS: With responses from 690 qualified participants, our experiments confirmed that the manual approach, as expected, had the best performance for both accuracy and response time to the comprehension questions, while the graph-based approach ranked the second outperforming other representations. In some cases, the graph-based representation outperformed the manual approach in terms of response time. CONCLUSIONS: A hybrid approach that combines text and graph-based representations might be needed to accommodate consumers' different information needs and information seeking behavior.