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Title: | Model for assessing quality of online health information: A Fuzzy VIKOR based method | ||||||||||
Author: | Afful-Dadzie, Eric; Nabareseh, Stephen; Komínková Oplatková, Zuzana; Klímek, Petr | ||||||||||
Document type: | Peer-reviewed article (English) | ||||||||||
Source document: | Journal of Multi-Criteria Decision Analysis. 2016, vol. 23, issue 1-2, p. 49-62 | ||||||||||
ISSN: | 1057-9214 (Sherpa/RoMEO, JCR) | ||||||||||
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DOI: | https://doi.org/10.1002/mcda.1558 | ||||||||||
Abstract: | Today, tens and thousands of websites provide health-related information on various topics to a growing number of consumers. However, the lay user is often faced with a challenge of determining the quality of information provided by one site from the other. To ensure the protection of users from sites that provide unreliable and unsafe information, there has to be a competent reviewing body that rates and ranks the quality of information provided by each site. This paper (i) proposes a new criteria framework for assessing the quality of online health information and (ii) uses a fuzzy 'visekriterijumska optimicija i kompromisno resenje' method to demonstrate how online health information providers could be assessed and ranked based on their quality. The fuzzy modelling uses pre-defined linguistic variables parameterized by triangular fuzzy numbers in the assessment and subsequent ranking of providers under a particular health topic. A numerical example is demonstrated using diabetes online information providers to show how the assessment and ranking is carried out. The proposed framework provides functional basis for evaluating the quality of internet health information providers on any particular health topic. Copyright (C) 2015 John Wiley & Sons, Ltd. | ||||||||||
Full text: | http://onlinelibrary.wiley.com/doi/10.1002/mcda.1558/full | ||||||||||
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