Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies

被引:220
作者
Short, Camille E. [1 ]
DeSmet, Ann [2 ]
Woods, Catherine [3 ]
Williams, Susan L. [4 ]
Maher, Carol [5 ]
Middelweerd, Anouk [6 ]
Mueller, Andre Matthias [7 ,8 ]
Wark, Petra A. [9 ]
Vandelanotte, Corneel [4 ]
Poppe, Louise [2 ]
Hingle, Melanie D. [10 ]
Crutzen, Rik [11 ]
机构
[1] Univ Adelaide, Sch Med, Freemasons Fdn Ctr Mens Hlth, Adelaide, SA, Australia
[2] Univ Ghent, Dept Movement & Sports Sci, Brussels, Belgium
[3] Univ Limerick, Hlth Res Inst, Dept Phys Educ & Sport Sci, Ctr Phys Act & Hlth, Limerick, Ireland
[4] Cent Queensland Univ, Appleton Inst, Sch Hlth Med & Appl Sci, Phys Act Res Grp, Rockhampton, Qld, Australia
[5] Univ South Australia, Sansom Inst, Sch Hlth Sci, Alliance Res Exercise Nutr & Act, Adelaide, SA, Australia
[6] Erasmus MC, Dept Rheumatol, Rotterdam, Netherlands
[7] Natl Univ Singapore, Saw Swee Hock Sch Publ Hlth, Singapore, Singapore
[8] Univ Malaya, Ctr Sport & Exercise Sci, Kuala Lumpur, Malaysia
[9] Coventry Univ, Fac Hlth & Life Sci, Ctr Innovat Res Life Course, Coventry, W Midlands, England
[10] Univ Arizona, Coll Agr & Life Sci, Dept Nutr Sci, Tucson, AZ USA
[11] Maastricht Univ, Care & Publ Hlth Res Inst, Dept Hlth Promot, Maastricht, Netherlands
基金
澳大利亚国家健康与医学研究理事会; 英国医学研究理事会;
关键词
telemedicine; internet; health promotion; evaluation studies; treatment adherence and compliance; outcome and process assessment (health care); ECOLOGICAL MOMENTARY ASSESSMENT; PHYSICAL-ACTIVITY; USER ENGAGEMENT; CANCER SURVIVORS; WEIGHT-LOSS; CONCEPTUAL-FRAMEWORK; HEALTH; EXPERIENCE; TIME; VALIDATION;
D O I
10.2196/jmir.9397
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
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.
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页数:18
相关论文
共 139 条
[1]  
Alkhaldi G, 2017, INTERACT J MED RES, V6, DOI 10.2196/ijmr.6952
[2]   Do personally tailored videos in a web-based physical activity intervention lead to higher attention and recall? - an eye-tracking study [J].
Alley, Stephanie ;
Jennings, Cally ;
Persaud, Nayadin ;
Plotnikoff, Ronald C. ;
Horsley, Mike ;
Vandelanotte, Corneel .
FRONTIERS IN PUBLIC HEALTH, 2014, 2
[3]   Large-scale physical activity data reveal worldwide activity inequality [J].
Althoff, Tim ;
Sosic, Rok ;
Hicks, Jennifer L. ;
King, Abby C. ;
Delp, Scott L. ;
Leskovec, Jure .
NATURE, 2017, 547 (7663) :336-+
[4]  
[Anonymous], 2013, Handbook of research methods for studying daily life
[5]  
[Anonymous], 2006, Self-efficacy beliefs of adolescents
[6]  
Arden-Close Emily Julia, 2015, JMIR Hum Factors, V2, pe8, DOI 10.2196/humanfactors.4310
[7]   More than just tracking time: Complex measures of user engagement with an internet-based health promotion intervention [J].
Baltierra, Nina B. ;
Muessig, Kathryn E. ;
Pike, Emily C. ;
LeGrand, Sara ;
Bull, Sheana S. ;
Hightow-Weidman, Lisa B. .
JOURNAL OF BIOMEDICAL INFORMATICS, 2016, 59 :299-307
[8]   Immersion and emotion:: Their impact on the sense of presence [J].
Baños, RM ;
Botella, C ;
Alcañiz, M ;
Liaño, V ;
Guerrero, B ;
Rey, B .
CYBERPSYCHOLOGY & BEHAVIOR, 2004, 7 (06) :734-741
[9]   Importance of Frequency, Intensity, Time and Type (FITT) in Physical Activity Assessment for Epidemiological Research [J].
Barisic, Andriana ;
Leatherdale, Scott T. ;
Kreiger, Nancy .
CANADIAN JOURNAL OF PUBLIC HEALTH-REVUE CANADIENNE DE SANTE PUBLIQUE, 2011, 102 (03) :174-175
[10]  
Barkhuus L, 2003, 9 IFIP TC13 INT C HU