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Measuring engagement in eHealth and mHealth behavior change interventions: viewpoint of methodologies

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dc.contributor.author Short, Camille E.
dc.contributor.author DeSmet, Ann
dc.contributor.author Woods, Catherine B.
dc.contributor.author Williams, Susan L.
dc.contributor.author Maher, Carol A.
dc.contributor.author Middelweerd, Anouk
dc.contributor.author Müller, Andre Matthias
dc.contributor.author Wark, Petra A.
dc.contributor.author Vandelanotte, Corneel
dc.contributor.author Poppe, Louise
dc.contributor.author Hingle, Melanie D.
dc.contributor.author Crutzen, Rik
dc.date.accessioned 2018-11-27T15:55:10Z
dc.date.available 2018-11-27T15:55:10Z
dc.date.issued 2018
dc.identifier.uri http://hdl.handle.net/10344/7356
dc.description peer-reviewed en_US
dc.description.abstract Engagement in electronic health (eHealth) and mobile health (mHealth) behavior change interventions is thought to be important for intervention effectiveness, though what constitutes engagement and how it enhances efficacy has been somewhat unclear in the literature. Recently published detailed definitions and conceptual models of engagement have helped to build consensus around a definition of engagement and improve our understanding of how engagement may influence effectiveness. This work has helped to establish a clearer research agenda. However, to test the hypotheses generated by the conceptual modules, we need to know how to measure engagement in a valid and reliable way. The aim of this viewpoint is to provide an overview of engagement measurement options that can be employed in eHealth and mHealth behavior change intervention evaluations, discuss methodological considerations, and provide direction for future research. To identify measures, we used snowball sampling, starting from systematic reviews of engagement research as well as those utilized in studies known to the authors. A wide range of methods to measure engagement were identified, including qualitative measures, self-report questionnaires, ecological momentary assessments, system usage data, sensor data, social media data, and psychophysiological measures. Each measurement method is appraised and examples are provided to illustrate possible use in eHealth and mHealth behavior change research. Recommendations for future research are provided, based on the limitations of current methods and the heavy reliance on system usage data as the sole assessment of engagement. The validation and adoption of a wider range of engagement measurements and their thoughtful application to the study of engagement are encouraged. en_US
dc.language.iso eng en_US
dc.publisher JMIR Publications en_US
dc.relation.ispartofseries journal of Medical Internet Research;20 (11), e292
dc.relation.uri http://dx.doi.org/10.2196/jmir.9397
dc.subject telemedicine en_US
dc.subject internet en_US
dc.subject health promotion en_US
dc.subject evaluation studies en_US
dc.subject treatment adherence and compliance en_US
dc.subject outcome and process assessment en_US
dc.title Measuring engagement in eHealth and mHealth behavior change interventions: viewpoint of methodologies en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.2196/jmir.9397
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US


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