Supporting effective health and biomedical information retrieval and navigation: A novel facet view interface evaluation

There is a need to provide a more effective user interface to facilitate non-domain experts' health information seeking in authoritative online databases such as MEDLINE. We developed a new topic cluster based information navigation system called SimMed. Instead of offering a list of documents, SimMed presents users with a list of ranked clusters. Topically similar documents are grouped together to provide users with a better overview of the search results and to support exploration of similar literature within a cluster. We conducted an empirical user study to compare SimMed to a traditional document list based search interface. A total of 42 study participants were recruited to use both interfaces for health information exploration search tasks. The results showed that SimMed is more effective in terms of users' perceived topic knowledge changes and their engagement in user-system interactions. We also developed a new metric to assess users' efforts to find relevant citations. On average, users need significantly fewer clicks to find relevant information in SimMed than in the baseline system. Comments from study participants indicated that SimMed is more helpful in finding similar citations, providing related medical terms, and presenting better organized search results, particularly when the initial search is unsatisfactory. Findings from the study shed light on future health and biomedical information retrieval system and interface designs.