Exploring the impact of linguistic signals transmission on patients’ health consultation choice: web mining of online reviews

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dc.contributor.authorShah, Adnan Muhammad
dc.contributor.authorAli, Mudassar
dc.contributor.authorQayyum, Abdul
dc.contributor.authorBegum, Abida
dc.contributor.authorHan, Heesup
dc.contributor.authorAriza-Montes, Antonio
dc.contributor.authorAraya-Castillo, Luis
dc.date.accessioned2023-11-14T15:55:12Z
dc.date.available2023-11-14T15:55:12Z
dc.date.issued2021-09
dc.descriptionIndexación: Scopuses
dc.description.abstractBackground: Patients face difficulties identifying appropriate physicians owing to the sizeable quantity and uneven quality of information in physician rating websites. Therefore, an increasing dependence of consumers on online platforms as a source of information for decision-making has given rise to the need for further research into the quality of information in the form of online physician reviews (OPRs). Methods: Drawing on the signaling theory, this study develops a theoretical model to examine how linguistic signals (affective signals and informative signals) in physician rating websites affect consumers’ decision making. The hypotheses are tested using 5521 physicians’ six-month data drawn from two leading health rating platforms in the U.S (i.e., Healthgrades.com and Vitals.com) during the COVID-19 pandemic. A sentic computing-based sentiment analysis framework is used to implicitly analyze patients’ opinions regarding their treatment choice. Results: The results indicate that negative sentiment, review readability, review depth, review spelling, and information helpfulness play a significant role in inducing patients’ decision-making. The influence of negative sentiment, review depth on patients’ treatment choice was indirectly medi-ated by information helpfulness. Conclusions: This paper is a first step toward the understanding of the linguistic characteristics of information relating to the patient experience, particularly the emerg-ing field of online health behavior and signaling theory. It is also the first effort to our knowledge that employs sentic computing-based sentiment analysis in this context and provides implications for practice. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.es
dc.description.urihttps://www.mdpi.com/1660-4601/18/19/9969
dc.identifier.citationInternational Journal of Environmental Research and Public Health Open Access Volume 18, Issue 19September 2021 Article number 9969es
dc.identifier.doi10.3390/ijerph18199969
dc.identifier.issn1661-7827
dc.identifier.urihttps://repositorio.unab.cl/xmlui/handle/ria/53964
dc.language.isoenes
dc.publisherMDPIes
dc.rights.licenseAtribución 4.0 Internacional (CC BY 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/deed.es
dc.subjectConsumer decision-makinges
dc.subjectCOVID-19es
dc.subjectOnline review helpfulnesses
dc.subjectPhysician rating websiteses
dc.subjectSentiment analysises
dc.subjectSignaling theoryes
dc.titleExploring the impact of linguistic signals transmission on patients’ health consultation choice: web mining of online reviewses
dc.typeArtículoes
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