Construction And Application Of Consumer Health Information Need Model

Consumer health information need is defined as desire and requirement of certain health information when patients or relatives feel uncomfortable and want to make sure of symptom. With the development of Internet technology and social Q&A community, consumers have more channels to obtain health information. Academe, healthcare department, and government pay more attention to consumer health information need. However, recently the researches about consumer health information need focus on only one disease, and take quantitative methods such as questionnaire, focus group, which result in the limitation of research sample, and certain findings could not apply to other diseases. From the angle of induction, this paper makes use of text mining information analysis as method, constructs consumer health information need model, then optimizes this model and discusses the applications of consumer health information model.Firstly, this paper reviews the current researches of consumer health information need, makes conclusion and analysis of research content and methods, to better understand main results, advantages and disadvantages of researches of consumer health information need.Secondly, this paper introduces several methods of extraction of feature words, and use TF-IDF methods to extract feature words. After that, this parer classifies these feature words (include general words and exclusive words) into ten health information need categories to construct consumer health information need model.Thirdly, this paper optimizes shotages of consumer health informaiton need model. To solve the inaccuracy of classification of general words, this paper uses cough question texts to turn ambiguity exclusive words into general words. To solve the problem of lack of exclusive words in some categories, this paper uses best answer texts of diabetes to optimize.At last, this paper discusses three applications of consumer health information need model, these are:improve public library health information service, optimize usability of health websites, and optimize consumer health information seeking behavior,.