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dc.contributor.authorBradway, Meghan
dc.contributor.authorGabarron, Elia
dc.contributor.authorJohansen, Monika Alise
dc.contributor.authorZanaboni, Paolo
dc.contributor.authorJardim, Patricia
dc.contributor.authorJoakimsen, Ragnar Martin
dc.contributor.authorPape-Haugaard, Louise
dc.contributor.authorÅrsand, Eirik
dc.date.accessioned2020-06-17T07:50:53Z
dc.date.available2020-06-17T07:50:53Z
dc.date.issued2020-04-30
dc.description.abstract<i>Background</i>: Despite the prevalence of mobile health (mHealth) technologies and observations of their impacts on patients’ health, there is still no consensus on how best to evaluate these tools for patient self-management of chronic conditions. Researchers currently do not have guidelines on which qualitative or quantitative factors to measure or how to gather these reliable data.<p><p> <i>Objective</i>: This study aimed to document the methods and both qualitative and quantitative measures used to assess mHealth apps and systems intended for use by patients for the self-management of chronic noncommunicable diseases.<p><p> <i>Methods</i>: A scoping review was performed, and PubMed, MEDLINE, Google Scholar, and ProQuest Research Library were searched for literature published in English between January 1, 2015, and January 18, 2019. Search terms included combinations of the description of the intention of the intervention (eg, self-efficacy and self-management) and description of the intervention platform (eg, mobile app and sensor). Article selection was based on whether the intervention described a patient with a chronic noncommunicable disease as the primary user of a tool or system that would always be available for self-management. The extracted data included study design, health conditions, participants, intervention type (app or system), methods used, and measured qualitative and quantitative data.<p><p> <i>Results</i>: A total of 31 studies met the eligibility criteria. Studies were classified as either those that evaluated mHealth apps (ie, single devices; n=15) or mHealth systems (ie, more than one tool; n=17), and one study evaluated both apps and systems. App interventions mainly targeted mental health conditions (including Post-Traumatic Stress Disorder), followed by diabetes and cardiovascular and heart diseases; among the 17 studies that described mHealth systems, most involved patients diagnosed with cardiovascular and heart disease, followed by diabetes, respiratory disease, mental health conditions, cancer, and multiple illnesses. The most common evaluation method was collection of usage logs (n=21), followed by standardized questionnaires (n=18) and ad-hoc questionnaires (n=13). The most common measure was app interaction (n=19), followed by usability/feasibility (n=17) and patient-reported health data via the app (n=15).<p><p> <i>Conclusions</i>: This review demonstrates that health intervention studies are taking advantage of the additional resources that mHealth technologies provide. As mHealth technologies become more prevalent, the call for evidence includes the impacts on patients’ self-efficacy and engagement, in addition to traditional measures. However, considering the unstructured data forms, diverse use, and various platforms of mHealth, it can be challenging to select the right methods and measures to evaluate mHealth technologies. The inclusion of app usage logs, patient-involved methods, and other approaches to determine the impact of mHealth is an important step forward in health intervention research. We hope that this overview will become a catalogue of the possible ways in which mHealth has been and can be integrated into research practice.en_US
dc.identifier.citationBradway M, Gabarron E, Johansen MA, Zanaboni P, Jardim P, Joakimsen RM, Pape-Haugaard L, Årsand E. Methods and Measures Used to Evaluate Patient-Operated Mobile Health Interventions: Scoping Literature Review. JMIR mhealth and uhealth. 2020;8(4)en_US
dc.identifier.cristinIDFRIDAID 1811148
dc.identifier.doi10.2196/16814
dc.identifier.issn2291-5222
dc.identifier.urihttps://hdl.handle.net/10037/18576
dc.language.isoengen_US
dc.publisherJMIR Publicationsen_US
dc.relation.ispartofBradway, M. (2021). mHealth: opportunities and challenges for diabetes intervention research. (Doctoral thesis). <a href=https://hdl.handle.net/10037/20544>https://hdl.handle.net/10037/20544</a>
dc.relation.journalJMIR mhealth and uhealth
dc.relation.projectIDinfo:eu-repo/grantAgreement/RCN/IKTPLUSS/247974/Norway/Full Flow of Health Data Between Patients and Health Care Systems//en_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2020 The Author(s)en_US
dc.subjectVDP::Medical disciplines: 700en_US
dc.subjectVDP::Medisinske Fag: 700en_US
dc.titleMethods and Measures Used to Evaluate Patient-Operated Mobile Health Interventions: Scoping Literature Reviewen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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