Evaluation of a novel Conjunctive Exploratory Navigation Interface for consumer health information: a crowdsourced comparative study

Numerous consumer health information websites have been developed to provide consumers access to health information. However, lookup search is insufficient for consumers to take full advantage of these rich public information resources. Exploratory search is considered a promising complementary mech...

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Bibliographic Details
Published in:Journal of medical Internet research 2014-02, Vol.16 (2), p.e45-e45
Main Authors: Cui, Licong, Carter, Rebecca, Zhang, Guo-Qiang
Format: Article
Language:English
Subjects:
Analysis of Variance
Bias
Comparative studies
Computational linguistics
Consumer behavior
Consumer education
Consumer Health Information
Consumers
Cost analysis
Crowdsourcing
Design
Efficacy
Health information
Health status
Humans
Information retrieval
Information Storage and Retrieval - methods
Interface
Interfaces
Internet
Internet service providers
Keywords
Language processing
Natural language interfaces
Navigation
Online health care information services
Original Paper
Search engines
Search strategies
Topics
User interface
User-Computer Interface
Web sites
Websites
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Summary:Numerous consumer health information websites have been developed to provide consumers access to health information. However, lookup search is insufficient for consumers to take full advantage of these rich public information resources. Exploratory search is considered a promising complementary mechanism, but its efficacy has never before been rigorously evaluated for consumer health information retrieval interfaces. This study aims to (1) introduce a novel Conjunctive Exploratory Navigation Interface (CENI) for supporting effective consumer health information retrieval and navigation, and (2) evaluate the effectiveness of CENI through a search-interface comparative evaluation using crowdsourcing with Amazon Mechanical Turk (AMT). We collected over 60,000 consumer health questions from NetWellness, one of the first consumer health websites to provide high-quality health information. We designed and developed a novel conjunctive exploratory navigation interface to explore NetWellness health questions with health topics as dynamic and searchable menus. To investigate the effectiveness of CENI, we developed a second interface with keyword-based search only. A crowdsourcing comparative study was carefully designed to compare three search modes of interest: (A) the topic-navigation-based CENI, (B) the keyword-based lookup interface, and (C) either the most commonly available lookup search interface with Google, or the resident advanced search offered by NetWellness. To compare the effectiveness of the three search modes, 9 search tasks were designed with relevant health questions from NetWellness. Each task included a rating of difficulty level and questions for validating the quality of answers. Ninety anonymous and unique AMT workers were recruited as participants. Repeated-measures ANOVA analysis of the data showed the search modes A, B, and C had statistically significant differences among their levels of difficulty (P
ISSN:1438-8871
1439-4456
1438-8871
DOI:10.2196/jmir.3111