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dc.contributor.authorRivera-Romero, Octavio
dc.contributor.authorGabarron, Elia
dc.contributor.authorRopero, Jorge
dc.contributor.authorDenecke, Kerstin
dc.date.accessioned2024-04-05T11:50:03Z
dc.date.available2024-04-05T11:50:03Z
dc.date.created2023-09-17T08:55:29Z
dc.date.issued2023
dc.identifier.citationJournal of Biomedical Informatics. 2023, 146, Artikkel 104500.en_US
dc.identifier.issn1532-0464
dc.identifier.urihttps://hdl.handle.net/11250/3125092
dc.description.abstractIntroduction: Mobile health, or mHealth, is based on mobile information and communication technologies and provides solutions for empowering individuals to participate in healthcare. Personalisation techniques have been used to increase user engagement and adherence to interventions delivered as mHealth solutions. This study aims to explore the current state of personalisation in mHealth, including its current trends and implementation. Materials and Methods: We conducted a review following PRISMA guidelines. Four databases (PubMed, ACM Digital Library, IEEE Xplore, and APA PsycInfo) were searched for studies on mHealth solutions that integrate personalisation. The retrieved papers were assessed for eligibility and useful information regarding integrated personalisation techniques. Results: Out of the 1,139 retrieved studies, 62 were included in the narrative synthesis. Research interest in the personalisation of mHealth solutions has increased since 2020. mHealth solutions were mainly applied to endocrine, nutritional, and metabolic diseases; mental, behavioural, or neurodevelopmental diseases; or the promotion of healthy lifestyle behaviours. Its main purposes are to support disease selfmanagement and promote healthy lifestyle behaviours. Mobile applications are the most prevalent technological solution. Although several design models, such as user-centred and patient-centred designs, were used, no specific frameworks or models for personalisation were followed. These solutions rely on behaviour change theories, use gamification or motivational messages, and personalise the content rather than functionality. A broad range of data is used for personalisation purposes. There is a lack of studies assessing the efficacy of these solutions; therefore, further evidence is needed. Discussion: Personalisation in mHealth has not been well researched. Although several techniques have been integrated, the effects of using a combination of personalisation techniques remain unclear. Although personalisation is considered a persuasive strategy, many mHealth solutions do not employ it. Conclusions: Open research questions concern guidelines for successful personalisation techniques in mHealth, design frameworks, and comprehensive studies on the effects and interactions among multiple personalisation techniques.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.subjectpersonalisationen_US
dc.subjectmHealthen_US
dc.subjectdesign methodsen_US
dc.subjectbehavioral changeen_US
dc.subjectreviewen_US
dc.titleDesigning personalised mHealth solutions: An overviewen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2023 The Authors.en_US
dc.subject.nsiVDP::Medisinske Fag: 700en_US
dc.subject.nsiVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550en_US
dc.source.volume146en_US
dc.source.journalJournal of Biomedical Informaticsen_US
dc.identifier.doi10.1016/j.jbi.2023.104500
dc.identifier.cristin2175757
dc.source.articlenumber104500en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal