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Usage intensity of mobile medical apps: A tale of two methods

dc.contributor.authorVeríssimo, José Manuel
dc.date.accessioned2025-03-27T09:26:08Z
dc.date.available2025-03-27T09:26:08Z
dc.date.issued2018
dc.description.abstractWeb 2.0 technologies have changed the traditional relationship model between doctors and third parties, and a plethora of apps are now available for the medical profession. This study presents unpublished findings about the potential drivers that currently influence mobile medical app usage intensity. Logistic regression and fuzzy-set qualitative comparative analysis (fsQCA) are both used to examine usage intensity. By using two research methods, rather than just one, the findings are greatly enhanced. Logistic regression results show that high usage intensity is explained by high perceived usefulness and high perceived ease of use. FsQCA, on the other hand, highlights that the combinations of multiple conditions are also significant, leading to the finding that low mobile medical app usage intensity is associated with low perceived ease of use, high perceived usefulness, low peer influence, high seniority, and younger female doctors.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationVeríssimo, José Manuel .(2018). “Usage intensity of mobile medical apps: A tale of two methods”. Journal of Business Research, Volume 89: pp. 442-447pt_PT
dc.identifier.doidoi.org/10.1016/j.jbusres.2017.12.026pt_PT
dc.identifier.issn0148-2963
dc.identifier.urihttp://hdl.handle.net/10400.5/99771
dc.language.isoengpt_PT
dc.publisherElsevierpt_PT
dc.subjectMobile Apppt_PT
dc.subjectm-Healthpt_PT
dc.subjectHealthcare Providerpt_PT
dc.subjectfsQCApt_PT
dc.subjectLogistic Regressionpt_PT
dc.subjectMixed Methods Researchpt_PT
dc.titleUsage intensity of mobile medical apps: A tale of two methodspt_PT
dc.typejournal article
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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