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dc.contributor.authorMarco-Ruiz, Luis
dc.contributor.authorBønes, Erlend
dc.contributor.authorde la Asuncion Gonzalez, Estela
dc.contributor.authorGabarron, Elia
dc.contributor.authorSolis, Juan Carlos Aviles
dc.contributor.authorLee, Eunji
dc.contributor.authorTraver, Vicente
dc.contributor.authorSato, Keiichi
dc.contributor.authorBellika, Johan Gustav
dc.date.accessioned2018-02-07T13:30:31Z
dc.date.available2018-02-07T13:30:31Z
dc.date.issued2017-09-09
dc.description.abstractSymptom checkers are software tools that allow users to submit a set of symptoms and receive advice related to them in the form of a diagnosis list, health information or triage. The heterogeneity of their potential users and the number of different components in their user interfaces can make testing with end-users unaffordable. We designed and executed a two-phase method to test the respiratory diseases module of the symptom checker Erdusyk. Phase I consisted of an online test with a large sample of users (n = 53). In Phase I, users evaluated the system remotely and completed a questionnaire based on the Technology Acceptance Model. Principal Component Analysis was used to correlate each section of the interface with the questionnaire responses, thus identifying which areas of the user interface presented significant contributions to the technology acceptance. In the second phase, the think-aloud procedure was executed with a small number of samples (n = 15), focusing on the areas with significant contributions to analyze the reasons for such contributions. Our method was used effectively to optimize the testing of symptom checker user interfaces. The method allowed kept the cost of testing at reasonable levels by restricting the use of the think-aloud procedure while still assuring a high amount of coverage. The main barriers detected in Erdusyk were related to problems understanding time repetition patterns, the selection of levels in scales to record intensities, navigation, the quantification of some symptom attributes, and the characteristics of the symptoms.en_US
dc.descriptionAccepted manuscript version. Published version available in <a href=http://doi.org/10.1016/j.jbi.2017.09.002>Journal of Biomedical Informatics, 2017;74:104-122</a>en_US
dc.identifier.citationMarco-Ruiz, L., Bønes, E., de la Asuncion Gonzalez, E., Gabarron, E., Solis, J.C.A., Lee, E., ... Bellika, J.G. Combining multivariate statistics and the think-aloud protocol to assess Human-Computer Interaction barriers in symptom checkers. Journal of Biomedical Informatics. 2017;74:104-122en_US
dc.identifier.cristinIDFRIDAID 1508252
dc.identifier.doi10.1016/j.jbi.2017.09.002
dc.identifier.issn1532-0464
dc.identifier.issn1532-0480
dc.identifier.urihttps://hdl.handle.net/10037/12102
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.journalJournal of Biomedical Informatics
dc.relation.projectIDnfo:eu-repo/grantAgreement/RCN/IKTPLUSS/248150/Norway/Assessing the feasibility of the Learning Healthcare System toolboxen_US
dc.rights.accessRightsopenAccessen_US
dc.subjectVDP::Medisinske Fag: 700::Klinisk medisinske fag: 750en_US
dc.subjectVDP::Medical disciplines: 700::Clinical medical disciplines: 750en_US
dc.titleCombining multivariate statistics and the think-aloud protocol to assess Human-Computer Interaction barriers in symptom checkersen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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