Dataset Information

Multi-topic assignment for exploratory navigation of consumer health information in NetWellness using formal concept analysis.

ABSTRACT:

Background

Finding quality consumer health information online can effectively bring important public health benefits to the general population. It can empower people with timely and current knowledge for managing their health and promoting wellbeing. Despite a popular belief that search engines such as Google can solve all information access problems, recent studies show that using search engines and simple search terms is not sufficient. Our objective is to provide an approach to organizing consumer health information for navigational exploration, complementing keyword-based direct search. Multi-topic assignment to health information, such as online questions, is a fundamental step for navigational exploration.

Methods

We introduce a new multi-topic assignment method combining semantic annotation using UMLS concepts (CUIs) and Formal Concept Analysis (FCA). Each question was tagged with CUIs identified by MetaMap. The CUIs were filtered with term-frequency and a new term-strength index to construct a CUI-question context. The CUI-question context and a topic-subject context were used for multi-topic assignment, resulting in a topic-question context. The topic-question context was then directly used for constructing a prototype navigational exploration interface.

Results

Experimental evaluation was performed on the task of automatic multi-topic assignment of 99 predefined topics for about 60,000 consumer health questions from NetWellness. Using example-based metrics, suitable for multi-topic assignment problems, our method achieved a precision of 0.849, recall of 0.774, and F? measure of 0.782, using a reference standard of 278 questions with manually assigned topics. Compared to NetWellness' original topic assignment, a 36.5% increase in recall is achieved with virtually no sacrifice in precision.

Conclusion

Enhancing the recall of multi-topic assignment without sacrificing precision is a prerequisite for achieving the benefits of navigational exploration. Our new multi-topic assignment method, combining term-strength, FCA, and information retrieval techniques, significantly improved recall and performed well according to example-based metrics.

SUBMITTER: Cui L

PROVIDER: S-EPMC4131492 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Multi-topic assignment for exploratory navigation of consumer health information in NetWellness using formal concept analysis.

Cui Licong L Xu Rong R Luo Zhihui Z Wentz Susan S Scarberry Kyle K Zhang Guo-Qiang GQ

BMC medical informatics and decision making 20140803

<h4>Background</h4>Finding quality consumer health information online can effectively bring important public health benefits to the general population. It can empower people with timely and current knowledge for managing their health and promoting wellbeing. Despite a popular belief that search engines such as Google can solve all information access problems, recent studies show that using search engines and simple search terms is not sufficient. Our objective is to provide an approach to organi ...[more]

PMID: 25086916

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Project description:Despite the wealth of mental-health information available online to consumers, research has shown that the mental-health information needs of consumers are not being met. This study contributes to that research by soliciting consumer questions directly, categorizing them, analyzing their form, and assessing the extent to which they can be answered from a trusted and vetted source of online information, namely the website of the US National Institute of Mental Health (NIMH). As an alternative to surveys and analyses of online activity, this study shows how consumer questions provide new insight into what consumers do not know and how they express their information needs. The study crowdsourced 100 consumer questions through Amazon Inc.'s Mechanical Turk. Categorization of the questions shows broad agreement with earlier studies in terms of the content of consumer questions. It also suggests that consumers' grasp of mental health issues may be low compared to other health topics. The majority of the questions (74%) were simple in form, with the remainder being multi-part, multifaceted or narrative. Even simple-form questions could, however, have complex interpretations. Fifty four questions were submitted to the search box at the NIMH website. For 32 questions, no answer could be found in the top one to three documents returned. Inadequacies in the search and retrieval technology deployed at websites account for some of the failure to find answers. The nature of consumer questions in mental health also plays a role. A question that has a false presupposition is less likely to have an answer in trusted and vetted sources of information. Consumer questions are also expressed with a degree of specificity that makes the retrieval of relevant information difficult. The significance of this study is that it shows what an analysis of consumer mental-health questions can tell us about consumer information needs and it provides new insight into the difficulties facing consumers looking for answers to their questions in online resources.

Dataset Information

Multi-topic assignment for exploratory navigation of consumer health information in NetWellness using formal concept analysis.

Background

Methods

Results

Conclusion

Publications

Multi-topic assignment for exploratory navigation of consumer health information in NetWellness using formal concept analysis.

Similar Datasets

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