Model for assessing quality of online health information: a fuzzy VIKOR based method

dc.contributor.authorAfful‐Dadzie, E.
dc.contributor.authorAfful‐Dadzie, A.
dc.contributor.authorNabareseh, S.
dc.contributor.authorOplatková, Z.K.
dc.contributor.authorKlímek, P.
dc.date.accessioned2019-02-12T15:29:10Z
dc.date.available2019-02-12T15:29:10Z
dc.date.issued2015
dc.description.abstractToday, tens and thousands of websites provide health-related information on various topics to a growing number ofconsumers. However, the lay user is often faced with a challenge of determining the quality of information provided byone site from the other. To ensure the protection of users from sites that provide unreliable and unsafe information, therehas 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 couldbe assessed and ranked based on their quality. The fuzzy modelling uses pre-defined linguistic variables parameterized bytriangular fuzzy numbers in the assessment and subsequent ranking of providers under a particular health topic. A numericalexample 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 anyparticular health topicen_US
dc.identifier.otherDOI: https://doi.org/10.1002/mcda.1558
dc.identifier.urihttp://ugspace.ug.edu.gh/handle/123456789/27454
dc.language.isoenen_US
dc.publisherJohn Wiley & Sons, Ltden_US
dc.subjectonline health informationen_US
dc.subjectdecision making modelen_US
dc.subjectfuzzy VIKORen_US
dc.subjectunsafe informationen_US
dc.subjecthealth info websitesen_US
dc.titleModel for assessing quality of online health information: a fuzzy VIKOR based methoden_US
dc.typeArticleen_US

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