The DOI matches its Crossref record; 113 of the 114 references it cites were found in a registry or an index.
Applying and advancing behavior change theories and techniques in the context of a digital health revolution: proposals for more effectively realizing untapped potential
Open accessAbstract
As more behavioral health interventions move from traditional to digital platforms, the application of evidence-based theories and techniques may be doubly advantageous. First, it can expedite digital health intervention development, improving efficacy, and increasing reach. Second, moving behavioral health interventions to digital platforms presents researchers with novel (potentially paradigm shifting) opportunities for advancing theories and techniques. In particular, the potential for technology to revolutionize theory refinement is made possible by leveraging the proliferation of "real-time" objective measurement and "big data" commonly generated and stored by digital platforms. Much more could be done to realize this potential. This paper offers proposals for better leveraging the potential advantages of digital health platforms, and reviews three of the cutting edge methods for doing so: optimization designs, dynamic systems modeling, and social network analysis.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Furthermore, to conform to the complexity of behavior change, eHealth technologies often consist of multiple components that may interact in reaching a certain effect and that people can use in many different ways in terms of the elements they use as well as the frequency, time, and place of use [7,8].”
From Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data (2017) · cites this paper as [8]
In the citing paper
“However, a technology can be designed for multiple target groups and, depending on the individual user goals and the desired outcomes, technology can be used in many different ways in terms of the features that are used, as well as the frequency, time, and place of use [13,14].”
From Clarifying the Concept of Adherence to eHealth Technology: Systematic Review on When Usage Becomes Adherence (2017) · cites this paper as [14]
In the citing paper
“Such analyses are a promising approach to explain the outcomes of the more traditional methods, such as RCTs, by gaining insight into the mediating mechanisms that contribute to the found effects [8,9] and have also the potential to identify unexpected effects of a technology.”
From Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data (2017) · cites this paper as [8]
In the citing paper
“The analyses of log data (anonymous records of real-time actions performed by each user) can provide continuous and objective insights into the actual usage of the technology.”
From Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data (2017) · cites this paper as [8]
In the citing paper
“However, the possibilities of log data in eHealth research have not been exploited to their fullest extent.”
From Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data (2017) · cites this paper as [8]
In the citing paper
“Log data analyses can also provide answers to more fundamental research questions related to existing models and theories [8].”
From Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data (2017) · cites this paper as [8]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Self-efficacy: The exercise of control
Bandura, A., Freeman, W. H., & Lightsey, R. (1999) · Journal of Cognitive Psychotherapy · doi:10.1891/0889-8391.13.2.158 · Cited by 46,835
Self-efficacy: Toward a unifying theory of behavioral change
Bandura, A. (1977) · Psychological Review · doi:10.1037/0033-295x.84.2.191 · Cited by 43,925
Kytle, J., & Bandura, A. (1978) · Contemporary Sociology · doi:10.2307/2065952 · Cited by 25,422
Self-efficacy: the exercise of control
(1997) · Choice Reviews Online · doi:10.5860/choice.35-1826 · Cited by 24,451
System Identification: Theory for the User
Lennart Ljung, A. (1987) · Cited by 17,690
Self-efficacy: Toward a unifying theory of behavioral change
Bandura, A. (1978) · Advances in Behaviour Research and Therapy · doi:10.1016/0146-6402(78)90002-4 · Cited by 10,586
Pierce, W. D., & Bandura, A. (1977) · The Canadian Journal of Sociology · doi:10.2307/3340496 · Cited by 9,742
System identification—Theory for the user
Sinha, N. K. (1989) · Automatica · doi:10.1016/0005-1098(89)90019-8 · Cited by 9,310
Estimating the reproducibility of psychological science
Open Science Collaboration (2015) · Science · doi:10.1126/science.aac4716 · Cited by 8,515
Bandura, A. (1977) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.15521699 · Cited by 7,585
The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods
Tausczik, Y. R., & Pennebaker, J. W. (2010) · Journal of Language and Social Psychology · doi:10.1177/0261927x09351676 · Cited by 5,774
Introduction to Statistical Mediation Analysis
MacKinnon, D. P. (2012) · doi:10.4324/9780203809556 · Cited by 5,618
BERKMAN, L. F., & SYME, S. L. (1979) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a112674 · Cited by 5,341
The Spread of Obesity in a Large Social Network over 32 Years
Christakis, N. A., & Fowler, J. H. (2007) · New England Journal of Medicine · doi:10.1056/nejmsa066082 · Cited by 5,007
From social integration to health: durkheim in the new millennium
Berkman, L. F., Glass, T., Brissette, I., & Seeman, T. E. (2000) · Social Science & Medicine · doi:10.1016/s0277-9536(00)00065-4 · Cited by 4,821
Computer-Mediated Communication: Impersonal, Interpersonal, and Hyperpersonal Interaction
WALTHER, J. B. (1996) · Communication Research · doi:10.1177/009365096023001001 · Cited by 4,798
Resnick, P., & Varian, H. R. (1997) · Communications of the ACM · doi:10.1145/245108.245121 · Cited by 3,772
Field Theory in Social Science: Selected Theoretical Papers.
Price, D. O., Lewin, K., & Cartwright, D. (1951) · American Sociological Review · doi:10.2307/2087618 · Cited by 3,519
Webb, T. L., Joseph, J., Yardley, L., & Michie, S. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1376 · Cited by 2,517
Self-citationSelf-Determination Theory Applied to Health Contexts: A Meta-Analysis
Ng, J. Y. Y., Ntoumanis, N., Thøgersen-Ntoumani, C., Deci, E. L., Ryan, R. M., Duda, J. L., & Williams, G. C. (2012) · Perspectives on Psychological Science · doi:10.1177/1745691612447309 · Cited by 1,959
Michie, S., Johnston, M., Francis, J., Hardeman, W., & Eccles, M. (2008) · Applied Psychology · doi:10.1111/j.1464-0597.2008.00341.x · Cited by 1,789
Self-citationMichie, S., Ashford, S., Sniehotta, F. F., Dombrowski, S. U., Bishop, A., & French, D. P. (2011) · Psychology & Health · doi:10.1080/08870446.2010.540664 · Cited by 1,756
Self-citationSmith, K. P., & Christakis, N. A. (2008) · Annual Review of Sociology · doi:10.1146/annurev.soc.34.040507.134601 · Cited by 1,638
Field Theory in Social Science: Selected Theoretical Papers
Lewin, K., & Cartwright, D. (1975) · Medical Entomology and Zoology · Cited by 1,417
Davis, R., Campbell, R., Hildon, Z., Hobbs, L., & Michie, S. (2015) · Health Psychology Review · doi:10.1080/17437199.2014.941722 · Cited by 1,411
Self-citationA taxonomy of behaviour change methods: an Intervention Mapping approach
Kok, G., Gottlieb, N. H., Peters, G.-J. Y., Mullen, P. D., Parcel, G. S., Ruiter, R. A. C., Fernández, M. E., Markham, C., & Bartholomew, L. K. (2016) · Health Psychology Review · doi:10.1080/17437199.2015.1077155 · Cited by 1,137
Understanding and Promoting Effective Engagement With Digital Behavior Change Interventions
Yardley, L., Spring, B. J., Riper, H., Morrison, L. G., Crane, D. H., Curtis, K., Merchant, G. C., Naughton, F., & Blandford, A. (2016) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2016.06.015 · Cited by 1,118
Self-citationMohr, D. C., Cuijpers, P., & Lehman, K. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1602 · Cited by 1,097
Collins, L. M., Murphy, S. A., & Strecher, V. (2007) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2007.01.022 · Cited by 1,082
Health behavior models in the age of mobile interventions: are our theories up to the task?
Riley, W. T., Rivera, D. E., Atienza, A. A., Nilsen, W., Allison, S. M., & Mermelstein, R. (2011) · Translational Behavioral Medicine · doi:10.1007/s13142-011-0021-7 · Cited by 978 · cited 2×
“have been developed on the basis of group differences and cross-sectional designs rather than on the basis of change within individuals (Davies et al., 2014; Michie et al., 2014; Riley et al., 2011).”
BackgroundFacebook as a toolkit: A uses and gratification approach to unbundling feature use
Smock, A. D., Ellison, N. B., Lampe, C., & Wohn, D. Y. (2011) · Computers in Human Behavior · doi:10.1016/j.chb.2011.07.011 · Cited by 948
Mobile Health Technology Evaluation
Kumar, S., Nilsen, W. J., Abernethy, A., Atienza, A., Patrick, K., Pavel, M., Riley, W. T., Shar, A., Spring, B., Spruijt-Metz, D., et al. (2013) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2013.03.017 · Cited by 900
Are interventions theory-based? Development of a theory coding scheme.
Michie, S., & Prestwich, A. (2010) · Health Psychology · doi:10.1037/a0016939 · Cited by 855
Self-citationReclaiming conversation: the power of talk in a digital age
(2016) · Choice Reviews Online · doi:10.5860/choice.195873 · Cited by 842
Borrelli, B., Sepinwall, D., Ernst, D., Bellg, A. J., Czajkowski, S., Breger, R., DeFrancesco, C., Levesque, C., Sharp, D. L., Ogedegbe, G., et al. (2005) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.73.5.852 · Cited by 803
The European Health Psychologist
Todorova, I. L. G., Araújo‐Soares, V., & Sniehotta, F. F. (2005) · European Health Psychologist · Cited by 777
Michie, S., Wood, C. E., Johnston, M., Abraham, C., Francis, J. J., & Hardeman, W. (2015) · Health Technology Assessment · doi:10.3310/hta19990 · Cited by 680
Self-citationDoi, S. A. R., Barendregt, J. J., Khan, S., Thalib, L., & Williams, G. M. (2015) · Contemporary Clinical Trials · doi:10.1016/j.cct.2015.05.009 · Cited by 596
Choice and Ego-Depletion: The Moderating Role of Autonomy
Moller, A. C., Deci, E. L., & Ryan, R. M. (2006) · Personality and Social Psychology Bulletin · doi:10.1177/0146167206288008 · Cited by 596
Self-citationPredicting personality with social media
Golbeck, J., Robles, C., & Turner, K. (2011) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/1979742.1979614 · Cited by 584
Influence of Pokémon Go on Physical Activity: Study and Implications
Althoff, T., White, R. W., & Horvitz, E. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.6759 · Cited by 584
Social physics: how good ideas spread--the lessons from a new science
Pentland, A. (2014) · Choice Reviews Online · doi:10.5860/choice.52-0805 · Cited by 573
Nahum-Shani, I., Hekler, E. B., & Spruijt-Metz, D. (2015) · Health Psychology · doi:10.1037/hea0000306 · Cited by 568
Self-citationDoes theory influence the effectiveness of health behavior interventions? Meta-analysis
Prestwich, A., Sniehotta, F. F., Whittington, C., Dombrowski, S. U., Rogers, L., & Michie, S. (2014) · Health Psychology · doi:10.1037/a0032853 · Cited by 562
Self-citationDombrowski, S. U., Sniehotta, F. F., Avenell, A., Johnston, M., MacLennan, G., & Araújo-Soares, V. (2012) · Health Psychology Review · doi:10.1080/17437199.2010.513298 · Cited by 504
Davies, E. B., Morriss, R., & Glazebrook, C. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3142 · Cited by 499
Behavior Change Techniques in Top-Ranked Mobile Apps for Physical Activity
Conroy, D. E., Yang, C., & Maher, J. P. (2014) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2014.01.010 · Cited by 466
Self-citationAlmirall, D., Nahum-Shani, I., Sherwood, N. E., & Murphy, S. A. (2014) · Translational Behavioral Medicine · doi:10.1007/s13142-014-0265-0 · Cited by 453 · cited 1×
“A further complexity arises when interventions are ‘adaptive’ in that they change over time and potentially in continuous fashion according to feedback from the user (Almirall et al., 2014; Lagoa et al., 2014).”
BackgroundMisleading tests of health behavior theories
Weinstein, N. D. (2007) · Annals of Behavioral Medicine · doi:10.1207/s15324796abm3301_1 · Cited by 418
Huang, G. C., Unger, J. B., Soto, D. W., Fujimoto, K., Pentz, M. A., Jordan‐Marsh, M., & Valente, T. W. (2013) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2013.07.001 · Cited by 382
Social Network Assessments and Interventions for Health Behavior Change: A Critical Review
Latkin, C., & Knowlton, A. (2015) · Behavioral Medicine · doi:10.1080/08964289.2015.1034645 · Cited by 351
Collins, L. M., Dziak, J. J., Kugler, K. C., & Trail, J. B. (2014) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2014.06.021 · Cited by 335
Self-citationA Content Analysis of Popular Smartphone Apps for Smoking Cessation
Abroms, L. C., Westmaas, J. L., Bontemps-Jones, J. E., Ramani, R., & Mellerson, J. L. (2013) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2013.07.008 · Cited by 325
Evidence-Based Strategies in Weight-Loss Mobile Apps
Pagoto, S., Schneider, K., Jojic, M., DeBiasse, M., & Mann, D. (2013) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2013.04.025 · Cited by 325
Direito, A., Dale, L. P., Shields, E., Dobson, R., Whittaker, R., & Maddison, R. (2014) · BMC Public Health · doi:10.1186/1471-2458-14-646 · Cited by 308
The Creative Destruction of Medicine: How the Digital Revolution Will Create Better Health Care
Topol, E. J. (2011) · Thammasat University Digital Collections · Cited by 306
The Multiphase Optimization Strategy for Engineering Effective Tobacco Use Interventions
Collins, L. M., Baker, T. B., Mermelstein, R. J., Piper, M. E., Jorenby, D. E., Smith, S. S., Christiansen, B. A., Schlam, T. R., Cook, J. W., & Fiore, M. C. (2011) · Annals of Behavioral Medicine · doi:10.1007/s12160-010-9253-x · Cited by 300
There Is Nothing So Theoretical as a Good Method
Greenwald, A. G. (2012) · Perspectives on Psychological Science · doi:10.1177/1745691611434210 · Cited by 292
Identification of behaviour change techniques to reduce excessive alcohol consumption
Michie, S., Whittington, C., Hamoudi, Z., Zarnani, F., Tober, G., & West, R. (2012) · Addiction · doi:10.1111/j.1360-0443.2012.03845.x · Cited by 288
Self-citationPeters, G.-J., de Bruin, M., & Crutzen, R. (2013) · Health Psychology Review · doi:10.1080/17437199.2013.848409 · Cited by 278
Weight loss—there is an app for that! But does it adhere to evidence-informed practices?
Breton, E. R., Fuemmeler, B. F., & Abroms, L. C. (2011) · Translational Behavioral Medicine · doi:10.1007/s13142-011-0076-5 · Cited by 276
Web-Based Smoking-Cessation Programs
Strecher, V. J., McClure, J. B., Alexander, G. L., Chakraborty, B., Nair, V. N., Konkel, J. M., Greene, S. M., Collins, L. M., Carlier, C. C., Wiese, C. J., et al. (2008) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2007.12.024 · Cited by 266
Jiang, L. C., Bazarova, N. N., & Hancock, J. T. (2011) · Human Communication Research · doi:10.1111/j.1468-2958.2010.01393.x · Cited by 265
Reclaiming conversation the power of talk in a digital age
Turkle, S. 1. (2015) · Cited by 260
Advances in the meta-analysis of heterogeneous clinical trials II: The quality effects model
Doi, S. A. R., Barendregt, J. J., Khan, S., Thalib, L., & Williams, G. M. (2015) · Contemporary Clinical Trials · doi:10.1016/j.cct.2015.05.010 · Cited by 227
Designing Insurance to Promote Use of Childhood Obesity Prevention Services
Rask, K. J., Gazmararian, J. A., Kohler, S. S., Hawley, J. N., Bogard, J., & Brown, V. A. (2013) · Journal of Obesity · doi:10.1155/2013/379513 · Cited by 218
Spruijt‐Metz, D., Hekler, E. B., Saranummi, N., Intille, S. S., Korhonen, I., Nilsen, W., Rivera, D. E., Spring, B. J., Michie, S., Asch, D. A., et al. (2015) · Translational Behavioral Medicine · doi:10.1007/s13142-015-0324-1 · Cited by 217
Self-citationAgile science: creating useful products for behavior change in the real world
Hekler, E. B., Klasnja, P., Riley, W. T., Buman, M. P., Huberty, J., Rivera, D. E., & Martin, C. A. (2016) · Translational Behavioral Medicine · doi:10.1007/s13142-016-0395-7 · Cited by 208
Self-citationSepah, S. C., Jiang, L., & Peters, A. L. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4052 · Cited by 206
Advancing Physical Activity Theory
Rhodes, R. E., & Nigg, C. R. (2011) · Exercise and Sport Sciences Reviews · doi:10.1097/jes.0b013e31821b94c8 · Cited by 204
Social Media and the Science of Health Behavior
Centola, D. M. (2013) · Circulation · doi:10.1161/circulationaha.112.101816 · Cited by 204
Implementation of Behavior Change Techniques in Mobile Applications for Physical Activity
Yang, C., Maher, J. P., & Conroy, D. E. (2015) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2014.10.010 · Cited by 178
Self-citationBehavior Change Techniques in Popular Alcohol Reduction Apps
Crane, D., Garnett, C., Brown, J., West, R., & Michie, S. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4060 · Cited by 177
Self-citationAdvancing Models and Theories for Digital Behavior Change Interventions
Hekler, E. B., Michie, S., Pavel, M., Rivera, D. E., Collins, L. M., Jimison, H. B., Garnett, C., Parral, S., & Spruijt-Metz, D. (2016) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2016.06.013 · Cited by 174
Self-citationMaher, C., Ferguson, M., Vandelanotte, C., Plotnikoff, R., De Bourdeaudhuij, I., Thomas, S., Nelson-Field, K., & Olds, T. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4086 · Cited by 171
Collins, L. M., Kugler, K. C., & Gwadz, M. V. (2015) · AIDS and Behavior · doi:10.1007/s10461-015-1145-4 · Cited by 166
Self-citationBalatsoukas, P., Kennedy, C., Buchan, I. E., Powell, J., & Ainsworth, J. D. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.3662 · Cited by 162
A Mobile App to Aid Smoking Cessation: Preliminary Evaluation of SmokeFree28
Ubhi, H. K., Michie, S., Kotz, D., Wong, W. C., & West, R. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.3479 · Cited by 149
Self-citationJake‐Schoffman, D. E., Turner‐McGrievy, G. M., Jones, S. J., & Wilcox, S. (2013) · Translational Behavioral Medicine · doi:10.1007/s13142-013-0206-3 · Cited by 145
Lyzwinski, L. N. (2014) · Journal of Personalized Medicine · doi:10.3390/jpm4030311 · Cited by 124
Collins, L. M., Trail, J. B., Kugler, K. C., Baker, T. B., Piper, M. E., & Mermelstein, R. J. (2014) · Translational Behavioral Medicine · doi:10.1007/s13142-013-0239-7 · Cited by 119
Self-citationTesting theory in practice: The example of self-determination theory-based interventions
Silva, M. N., Marques, M. M., & Teixeira, P. J. (2014) · European Health Psychologist · Cited by 113
Estrin, D. L. (2014) · Communications of the ACM · doi:10.1145/2580944 · Cited by 109
Merchant, G., Weibel, N., Patrick, K., Fowler, J. H., Norman, G. J., Gupta, A. E., Servetas, C., Calfas, K. J., Raste, K., Pina, L. R., et al. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3267 · Cited by 107
Self-citationYoung, S. D., Holloway, I. W., Jaganath, D., Rice, E. R. W., Westmoreland, D. A., & Coates, T. J. (2014) · American Journal of Public Health · doi:10.2105/ajph.2014.301992 · Cited by 104
Hales, S. B., Davidson, C. R., & Turner‐McGrievy, G. M. (2014) · Translational Behavioral Medicine · doi:10.1007/s13142-014-0274-z · Cited by 98
Devlin, A. M., Lennon, M., O’Donnell, C. A., Bouamrane, M.-M., Agbakoba, R., O’Connor, S., Grieve, E., Finch, T. L., Wyke, S., Watson, N., et al. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv097 · Cited by 97
Teammates and Social Influence Affect Weight Loss Outcomes in a Team‐Based Weight Loss Competition
Leahey, T. M., Kumar, R., Weinberg, B. M., & Wing, R. R. (2012) · Obesity · doi:10.1038/oby.2012.18 · Cited by 91
Pellegrini, C. A., Hoffman, S. A., Collins, L. M., & Spring, B. J. (2014) · Contemporary Clinical Trials · doi:10.1016/j.cct.2014.05.007 · Cited by 88
Development of a dynamic computational model of social cognitive theory
Riley, W. T., Martín, C. A., Rivera, D. E., Hekler, E. B., Adams, M. A., Buman, M. P., Pavel, M., & King, A. C. (2015) · Translational Behavioral Medicine · doi:10.1007/s13142-015-0356-6 · Cited by 88
Self-citationSpecifying Evidence-Based Behavior Change Techniques to Aid Smoking Cessation in Pregnancy
Lorencatto, F., West, R., & Michie, S. (2012) · Nicotine & Tobacco Research · doi:10.1093/ntr/ntr324 · Cited by 85
Self-citation“Hidden” Social Networks in Behavior Change Interventions
Hunter, R. F., McAneney, H., Davis, M. C., Tully, M. A., Valente, T. W., & Kee, F. (2015) · American Journal of Public Health · doi:10.2105/ajph.2014.302399 · Cited by 74
Nandola, N. N., & Rivera, D. E. (2013) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2011.2177525 · Cited by 64 · cited 1×
“These methods include strategies such as system identification (Ljung, 1999), and model-predictive control (Nandola & Rivera, 2013).”
MethodInvestigating theoretical explanations for behaviour change: The case study of ProActive
Michie, S., Hardeman, W., Fanshawe, T., Prevost, A. T., Taylor, L., & Kinmonth, A. L. (2007) · Psychology and Health · doi:10.1080/08870440701670588 · Cited by 63
Self-citationPersonalized Coaching Systems to support healthy behavior in people with chronic conditions
Hermens, H. J., den Akker, H. O., Tabak, M., Wijsman, J., & Vollenbroek-Hutten, M. M. R. (2014) · Journal of Electromyography and Kinesiology · doi:10.1016/j.jelekin.2014.10.003 · Cited by 62
Wyrick, D. L., Rulison, K. L., Fearnow-Kenney, M., Milroy, J. J., & Collins, L. M. (2014) · Translational Behavioral Medicine · doi:10.1007/s13142-013-0247-7 · Cited by 57
West, R., Evans, A., & Michie, S. (2011) · Nicotine & Tobacco Research · doi:10.1093/ntr/ntr120 · Cited by 56
Self-citationA smart mirror to promote a healthy lifestyle
Colantonio, S., Coppini, G., Germanese, D., Giorgi, D., Magrini, M., Marraccini, P., Martinelli, M., Morales, M. A., Pascali, M. A., Raccichini, G., et al. (2015) · Biosystems Engineering · doi:10.1016/j.biosystemseng.2015.06.008 · Cited by 47
Leroux, J. S., Moore, S., & Dubé, L. (2013) · Journal of Obesity · doi:10.1155/2013/348249 · Cited by 47
Realizing Effective Behavioral Management of Health: The Metamorphosis of Behavioral Science Methods
Hekler, E. B., Klasnja, P., Traver, V., & Hendriks, M. (2013) · IEEE Pulse · doi:10.1109/mpul.2013.2271681 · Cited by 45
Self-citationCarson, T. L., Eddings, K., Krukowski, R. A., Love, S. J., Harvey‐Berino, J., & West, D. S. (2013) · Journal of Obesity · doi:10.1155/2013/480630 · Cited by 38
Social embeddedness in an online weight management programme is linked to greater weight loss
Poncela-Casasnovas, J., Spring, B. J., McClary, D. J., Moller, A. C., Mukogo, R., Pellegrini, C. A., Coons, M. J., Davidson, M., Mukherjee, S., & Amaral, L. A. N. (2015) · Journal of The Royal Society Interface · doi:10.1098/rsif.2014.0686 · Cited by 32
Self-citationDesigning adaptive intensive interventions using methods from engineering.
Lagoa, C. M., Bekiroglu, K., Lanza, S. T., & Murphy, S. A. (2014) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0037736 · Cited by 30
Methodologies for optimizing behavioral interventions: introduction to special section
Riley, W. T., & Rivera, D. E. (2014) · Translational Behavioral Medicine · doi:10.1007/s13142-014-0281-0 · Cited by 28
Martin, C. A., Rivera, D. E., & Hekler, E. B. (2016) · 2016 American Control Conference (ACC) · doi:10.1109/acc.2016.7525468 · Cited by 20
Self-citationConroy, D. E., Dubansky, A., Remillard, J., Murray, R. D., Pellegrini, C. A., Phillips, S. M., & Streeper, N. M. (2016) · Urology · doi:10.1016/j.urology.2016.09.015 · Cited by 19
Self-citationA Call for a Science of Engagement: Comment on Rus and Cameron
Pagoto, S., & Waring, M. E. (2016) · Annals of Behavioral Medicine · doi:10.1007/s12160-016-9839-z · Cited by 15
On the mathematical modeling of the effect of treatment on human physical activity
Ashour, M., Bekiroglu, K., Yang, C., Lagoa, C. M., Conroy, D. E., Smyth, J. M., & Lanza, S. T. (2016) · The proceedings of the IEEE Conference on Control Applications/The proceedings of the ... IEEE Conference on Control Applications · doi:10.1109/cca.2016.7587951 · Cited by 12
Self-citationLeveraging intensive longitudinal data to better understand health behaviors
Timms, K. P., Martín, C. A., Rivera, D. E., Hekler, E. B., & Riley, W. T. (2014) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2014.6945211 · Cited by 7
Self-citationAssessment of Wearable Sensor Technologies for Biosurveillance
Hirschberg, D. L., Betts, K. D., Emanuel, P. D., & Caples, M. (2014) · Cited by 4
Predicting Agents' Behavior by Measuring their Social Preferences
Cheng, K.-L., Zuckerman, I., Nau, D. S., & Golbeck, J. (2014) · Frontiers in artificial intelligence and applications · doi:10.3233/978-1-61499-419-0-985 · Cited by 2
Smokefree.gov: 10 years of disseminating evidence-based cessation interventions
Taylor, S. C. (2013) · 141st APHA Annual Meeting and Exposition (November 2 - November 6, 2013) · Cited by 1
Valdiviezo, D. A. C., Martín, C. A., Mistiri, M. E., Rivera, D. E., & Hekler, E. B. (2022) · Revista Iberoamericana de Automática e Informática Industrial RIAI · doi:10.4995/riai.2022.16798 · Cited by 1
Self-citation
Research works printed but not linked: 3
- Berli, C., Rauers, A., Luscher, J., Hohl, D. H., Keller, J., & Stadler, G. (2016). Social exchange processes and their association with health regulation and health-related outcomes. Symposium presented at the European Health Psychology Society (EHPS) and the British Psychological Society’s Division of Health Psychology (DHP) Dynamic Systems Modeling Expert Meeting, Aberdeen, Scotland. Retrieved from http://ehps2016.org/files/EHPS2016_Abstracts_Book_08082016.pdf
- Meeker, M. (2016). Internet trends 2016—Code conference (p. Kleiner Perkins Caufield & Byers website.). Retrieved from www.kpcb.com/internet-trends
- Sutton, S. (2010). Using social cognition models to develop health behaviour interventions: The theory of planned behaviour as an example. In D. P. French, K. Vedhara, A. A. Kaptein, & J. Weinman (Eds.), Health Psychology (2nd ed., Vol. 122). New York: BPS Blackwell.
Cited by
Sorted by citations
Objective user engagement with mental health apps: systematic search and panel-based usage analysis
Baumel, A., Muench, F., Edan, S., & Kane, J. M. (2019) · Journal of Medical Internet Research · doi:10.2196/14567 · Cited by 965
Sieverink, F., Kelders, S. M., & van Gemert-Pijnen, J. E. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.8578 · Cited by 331
Kemp, E., Trigg, J. L., Beatty, L., Christensen, C., Dhillon, H. M., Maeder, A., Williams, P. A. H., & Koczwara, B. (2020) · Health Promotion Journal of Australia · doi:10.1002/hpja.387 · Cited by 280
Digital Behaviour Change Interventions to Break and Form Habits
Pinder, C., Vermeulen, J., Cowan, B. R., & Beale, R. (2018) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3196830 · Cited by 235
Bogale, B., Mørkrid, K., O’Donnell, B., Ghanem, B., Abu Ward, I., Abu Khader, K., Isbeih, M., Frost, M., Baniode, M., Hijaz, T., et al. (2020) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-019-1002-x · Cited by 234
Metadata
- Authors
- Moller, A. C., Merchant, G., Conroy, D. E., West, R., Hekler, E., Kugler, K. C., & Michie, S.
- Affiliations
- Northwestern University (US)
- University of California San Diego (US)
- Pennsylvania State University (US)
- University College London (GB)
- Arizona State University (US)
- Corresponding author
- Moller, Arlen C.
- Venue
- Journal of Behavioral Medicine
- Published
- 2017-01-05
- Volume
- 40
- Issue
- 1
- Pages
- 85-98
- ISSN
- 0160-7715 (ISSN-L)
- 1573-3521
- PMC
- PMC5532801
- OpenAlex
- W2570133882
- Cited by
- 151
- References
- 114
- Citations by year
- 2026: 6 · 2025: 12 · 2024: 17 · 2023: 16 · 2022: 23 · 2021: 16 · 2020: 16 · 2019: 21 · 2018: 14 · 2017: 9
- FWCI
- 18.78
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Behavioral Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Cancer Research UK (14135)
- National Institute for Health and Care Research (NF-SI-0512-10002)
- Medical Research Council (MR/K023195/1)
- Economic and Social Research Council (ES/G007489/1)
- National Institute on Drug Abuse (P50DA039838)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
- Keywords
- behaviour change theory, digital health interventions, behavioral health, theory refinement, big data, design optimization, dynamic system modeling, social network analysis, intervention development
- MeSH terms
- Behavior Therapy, Health Promotion, Health Services, Humans, Health Behavior, Behavioral Research
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
