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Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies
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 defi...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6269627/ https://www.ncbi.nlm.nih.gov/pubmed/30446482 http://dx.doi.org/10.2196/jmir.9397 |
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author | Short, Camille E DeSmet, Ann Woods, Catherine Williams, Susan L Maher, Carol Middelweerd, Anouk Müller, Andre Matthias Wark, Petra A Vandelanotte, Corneel Poppe, Louise Hingle, Melanie D Crutzen, Rik |
author_facet | Short, Camille E DeSmet, Ann Woods, Catherine Williams, Susan L Maher, Carol Middelweerd, Anouk Müller, Andre Matthias Wark, Petra A Vandelanotte, Corneel Poppe, Louise Hingle, Melanie D Crutzen, Rik |
author_sort | Short, Camille E |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6269627 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-62696272018-12-28 Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies Short, Camille E DeSmet, Ann Woods, Catherine Williams, Susan L Maher, Carol Middelweerd, Anouk Müller, Andre Matthias Wark, Petra A Vandelanotte, Corneel Poppe, Louise Hingle, Melanie D Crutzen, Rik J Med Internet Res Viewpoint 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. JMIR Publications 2018-11-16 /pmc/articles/PMC6269627/ /pubmed/30446482 http://dx.doi.org/10.2196/jmir.9397 Text en ©Camille E Short, Ann DeSmet, Catherine Woods, Susan L Williams, Carol Maher, Anouk Middelweerd, Andre Matthias Müller, Petra A Wark, Corneel Vandelanotte, Louise Poppe, Melanie D Hingle, Rik Crutzen. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.11.2018. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Viewpoint Short, Camille E DeSmet, Ann Woods, Catherine Williams, Susan L Maher, Carol Middelweerd, Anouk Müller, Andre Matthias Wark, Petra A Vandelanotte, Corneel Poppe, Louise Hingle, Melanie D Crutzen, Rik Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies |
title | Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies |
title_full | Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies |
title_fullStr | Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies |
title_full_unstemmed | Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies |
title_short | Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies |
title_sort | measuring engagement in ehealth and mhealth behavior change interventions: viewpoint of methodologies |
topic | Viewpoint |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6269627/ https://www.ncbi.nlm.nih.gov/pubmed/30446482 http://dx.doi.org/10.2196/jmir.9397 |
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