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Measuring engagement in eHealth and mHealth behavior change interventions : methodological overview

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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.
Keywords
telemedicine, internet, health promotion, evaluation studies, treatment adherence and compliance, outcome and process assessment (health care), ECOLOGICAL MOMENTARY ASSESSMENT, INTENSIVE LONGITUDINAL DATA, RANDOMIZED CONTROLLED-TRIAL, PHYSICAL-ACTIVITY DATA, USER ENGAGEMENT, SOCIAL MEDIA, WEIGHT-LOSS, CONCEPTUAL-FRAMEWORK, COMPUTER GAME, VIDEO GAMES

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Citation

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MLA
Short, Camille Elizabeth et al. “Measuring Engagement in eHealth and mHealth Behavior Change Interventions : Methodological Overview.” JOURNAL OF MEDICAL INTERNET RESEARCH 20.11 (2018): n. pag. Print.
APA
Short, C. E., DeSmet, A., Woods, C., Williams, S. L., Maher, C., Middelweerd, A., Müller, A. M., et al. (2018). Measuring engagement in eHealth and mHealth behavior change interventions : methodological overview. JOURNAL OF MEDICAL INTERNET RESEARCH, 20(11).
Chicago author-date
Short, Camille Elizabeth, Ann DeSmet, Catherine Woods, Susan L Williams, Carol Maher, Anouk Middelweerd, André Matthias Müller, et al. 2018. “Measuring Engagement in eHealth and mHealth Behavior Change Interventions : Methodological Overview.” Journal of Medical Internet Research 20 (11).
Chicago author-date (all authors)
Short, Camille Elizabeth, Ann DeSmet, Catherine Woods, Susan L Williams, Carol Maher, Anouk Middelweerd, André Matthias Müller, Petra A Wark, Corneel Vandelanotte, Louise Poppe, Melanie Hingle, and Rik Crutzen. 2018. “Measuring Engagement in eHealth and mHealth Behavior Change Interventions : Methodological Overview.” Journal of Medical Internet Research 20 (11).
Vancouver
1.
Short CE, DeSmet A, Woods C, Williams SL, Maher C, Middelweerd A, et al. Measuring engagement in eHealth and mHealth behavior change interventions : methodological overview. JOURNAL OF MEDICAL INTERNET RESEARCH. 2018;20(11).
IEEE
[1]
C. E. Short et al., “Measuring engagement in eHealth and mHealth behavior change interventions : methodological overview,” JOURNAL OF MEDICAL INTERNET RESEARCH, vol. 20, no. 11, 2018.
@article{8573453,
  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.}},
  articleno    = {{e292}},
  author       = {{Short, Camille Elizabeth and DeSmet, Ann and Woods, Catherine and Williams, Susan L and Maher, Carol and Middelweerd, Anouk and Müller, André Matthias and Wark, Petra A and Vandelanotte, Corneel and Poppe, Louise and Hingle, Melanie and Crutzen, Rik}},
  issn         = {{1438-8871}},
  journal      = {{JOURNAL OF MEDICAL INTERNET RESEARCH}},
  keywords     = {{telemedicine,internet,health promotion,evaluation studies,treatment adherence and compliance,outcome and process assessment (health care),ECOLOGICAL MOMENTARY ASSESSMENT,INTENSIVE LONGITUDINAL DATA,RANDOMIZED CONTROLLED-TRIAL,PHYSICAL-ACTIVITY DATA,USER ENGAGEMENT,SOCIAL MEDIA,WEIGHT-LOSS,CONCEPTUAL-FRAMEWORK,COMPUTER GAME,VIDEO GAMES}},
  language     = {{eng}},
  number       = {{11}},
  pages        = {{18}},
  title        = {{Measuring engagement in eHealth and mHealth behavior change interventions : methodological overview}},
  url          = {{http://dx.doi.org/10.2196/jmir.9397}},
  volume       = {{20}},
  year         = {{2018}},
}

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