Please use this identifier to cite or link to this item: https://doi.org/10.2196/jmir.9397
Title: Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies
Authors: Short, Camille E
DeSmet, Ann
Woods, Catherine
Williams, Susan L
Maher, Carol
Middelweerd, Anouk
Andre Matthias Mueller 
Wark, Petra A
Vandelanotte, Corneel
Poppe, Louise
Hingle, Melanie D
Crutzen, Rik
Keywords: evaluation studies
health promotion
internet
outcome and process assessment (health care)
telemedicine
treatment adherence and compliance
Issue Date: 16-Nov-2018
Citation: Short, Camille E, DeSmet, Ann, Woods, Catherine, Williams, Susan L, Maher, Carol, Middelweerd, Anouk, Andre Matthias Mueller, Wark, Petra A, Vandelanotte, Corneel, Poppe, Louise, Hingle, Melanie D, Crutzen, Rik (2018-11-16). Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies. Journal of Medical Internet Research 20 (11). ScholarBank@NUS Repository. https://doi.org/10.2196/jmir.9397
Rights: Attribution-NonCommercial-ShareAlike 4.0 International
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.
Source Title: Journal of Medical Internet Research
URI: http://scholarbank.nus.edu.sg/handle/10635/148863
ISSN: 14388871
DOI: 10.2196/jmir.9397
Rights: Attribution-NonCommercial-ShareAlike 4.0 International
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