The DOI matches its Crossref record; 49 of the 52 references it cites were found in a registry or an index.
How to evaluate technologies for health behavior change in HCI research
Abstract
New technologies for encouraging physical activity, healthy diet, and other types of health behavior change now frequently appear in the HCI literature. Yet, how such technologies should be evaluated within the context of HCI research remains unclear. In this paper, we argue that the obvious answer to this question - that evaluations should assess whether a technology brought about the intended change in behavior - is too limited. We propose that demonstrating behavior change is often infeasible as well as unnecessary for a meaningful contribution to HCI research, especially when in the early stages of design or when evaluating novel technologies. As an alternative, we suggest that HCI contributions should focus on efficacy evaluations that are tailored to the specific behavior-change intervention strategies (e.g., self-monitoring, conditioning) embodied in the system and studies that help gain a deep understanding of people's experiences with the technology.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“First, they focus on clinical outcomes, which are often more distal to the behavioral targets of specific BIT interventions and are unlikely to change within the timeframe necessary to inform design considerations or to submit BITs to rapid development, evaluation, and iteration [4].”
From The Behavioral Intervention Technology Model: An Integrated Conceptual and Technological Framework for eHealth and mHealth Interventions (2014) · cites this paper as [4]
In the citing paper
“First, they focus on clinical outcomes, which are often more distal to the behavioral targets of specific BIT interventions and are unlikely to change within the timeframe necessary to inform design considerations or to submit BITs to rapid development, evaluation, and iteration [4].”
From The Behavioral Intervention Technology Model: An Integrated Conceptual and Technological Framework for eHealth and mHealth Interventions (2014) · cites this paper as [4]
In the citing paper
“Much of the evaluation of BITs has focused on efficacy, which limits the growth in our knowledge regarding the mechanisms by which BITs achieve both their proximal intervention aims as well as the ultimate treatment goals [4].”
From The Behavioral Intervention Technology Model: An Integrated Conceptual and Technological Framework for eHealth and mHealth Interventions (2014) · cites this paper as [4]
Citations
Cites
The "what" and "why" of goal pursuits: Human needs and the self-determination of behavior
Deci, E. L., & Ryan, R. M. (2000) · Psychological Inquiry · doi:10.1207/s15327965pli1104_01 · Cited by 34,210
Social psychology: handbook of basic principles
Higgins, E., & Kruglanski, A. (2008) · Choice Reviews Online · doi:10.5860/choice.45-3496 · Cited by 5,535
Social psychology: handbook of basic principles
(1997) · Choice Reviews Online · doi:10.5860/choice.34-3595 · Cited by 4,970
Self-regulation and depletion of limited resources: Does self-control resemble a muscle?
Muraven, M., & Baumeister, R. F. (2000) · Psychological Bulletin · doi:10.1037/0033-2909.126.2.247 · Cited by 4,510
Validity and reliability of the Experience-Sampling Method
CSIKSZENTMIHALYI, M., & LARSON, R. (1987) · The Journal of Nervous and Mental Disease · doi:10.1097/00005053-198709000-00004 · Cited by 2,544
Knowledge activation: Accessibility, applicability, and salience.
Higgins, E. T. (1996) · Cited by 1,970
The automated will: nonconscious activation and pursuit of behavioral goals.
Bargh, J. A., Gollwitzer, P. M., Lee-Chai, A., Barndollar, K., & Trötschel, R. (2001) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.81.6.1014 · Cited by 1,865
Self-control as a limited resource: Regulatory depletion patterns.
Muraven, M., Tice, D. M., & Baumeister, R. F. (1998) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.74.3.774 · Cited by 1,724
Consolvo, S., McDonald, D. W., Toscos, T., Chen, M. Y., Froehlich, J. E., Harrison, B. L., Klasnja, P., LaMarca, A., LeGrand, L., Libby, R., et al. (2008) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1357054.1357335 · Cited by 1,133
Self-citationSystematic Review of the Literature
Wool, C. (2011) · Advances in Neonatal Care · doi:10.1097/anc.0b013e31821bd92d · Cited by 1,021
Cited by
Sorted by citations
Mohr, D. C., Schueller, S. M., Montague, E., Burns, M. N., & Rashidi, P. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3077 · Cited by 510
Mercer, K., Giangregorio, L., Schneider, E., Chilana, P., Li, M., & Grindrod, K. (2016) · JMIR mHealth and uHealth · doi:10.2196/mhealth.4225 · Cited by 419
Persuasive technology in the real world
Fritz, T., Huang, E. M., Murphy, G. C., & Zimmermann, T. (2014) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2556288.2557383 · Cited by 385
Exploring Goal-setting, Rewards, Self-monitoring, and Sharing to Motivate Physical Activity
Munson, S. A., & Consolvo, S. (2012) · International Conference on Pervasive Computing Technologies for Healthcare · doi:10.4108/icst.pervasivehealth.2012.248691 · Cited by 360
Self-citationMind the theoretical gap: interpreting, using, and developing behavioral theory in HCI research
Hekler, E. B., Klasnja, P., Froehlich, J. E., & Buman, M. P. (2013) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/2470654.2466452 · Cited by 328
Self-citationOpportunities and challenges in the collection and analysis of digital phenotyping data
Onnela, J.-P. “. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-0771-3 · Cited by 339
Rabbi, M., Pfammatter, A. F., Zhang, M., Spring, B. J., & Choudhury, T. (2015) · JMIR mhealth and uhealth · doi:10.2196/mhealth.4160 · Cited by 300
Noah, B., Keller, M. S., Mosadeghi, S., Stein, L., Johl, S., Delshad, S., Tashjian, V. C., Lew, D., Kwan, J. T., Jusufagic, A., et al. (2018) · npj Digital Medicine · doi:10.1038/s41746-017-0002-4 · Cited by 273
Zuckerman, O., & Gal-Oz, A. (2014) · Personal and Ubiquitous Computing · doi:10.1007/s00779-014-0783-2 · Cited by 273
Rabbi, M., Aung, M. H., Zhang, M., & Choudhury, T. (2015) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2750858.2805840 · Cited by 274
Beyond Self-Tracking and Reminders: Designing Smartphone Apps That Support Habit Formation
Stawarz, K., Cox, A. L., & Blandford, A. (2015) · Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems · doi:10.1145/2702123.2702230 · Cited by 237
Bentley, F. R., Tollmar, K., Stephenson, P. D., Levy, L. M., Jones, B. D., Robertson, S. L., Price, E., Catrambone, R., & Wilson, J. (2013) · ACM Transactions on Computer-Human Interaction · doi:10.1145/2503823 · Cited by 253
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
Mapping and Taking Stock of the Personal Informatics Literature
Epstein, D. A., Caldeira, C. M., Figueiredo, M. C., Lu, X., Silva, L. M., Williams, L., Lee, J. H., Li, Q., Ahuja, S., Chen, Q., et al. (2020) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3432231 · Cited by 243
Kay, M., Choe, E. K., Shepherd, J., Greenstein, B. M., Watson, N. F., Consolvo, S., & Kientz, J. A. (2012) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2370216.2370253 · Cited by 218
Self-citationMohr, D. C., Schueller, S. M., Riley, W. T., Brown, C. H., Cuijpers, P., Duan, N., Kwasny, M. J., Stiles-Shields, C., & Cheung, K. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4391 · Cited by 216
Seven lessons for interdisciplinary research on interactive digital health interventions
Blandford, A., Gibbs, J., Newhouse, N., Perski, O., Singh, A., & Murray, E. (2018) · DIGITAL HEALTH · doi:10.1177/2055207618770325 · Cited by 209
How do we engage with activity trackers?
Gouveia, R. H. D. F., Karapanos, E., & Hassenzahl, M. (2015) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2750858.2804290 · Cited by 211
Adams, A. T., Costa, J. M. D. R., Jung, M. F., & Choudhury, T. (2015) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2750858.2805843 · Cited by 192
Pocket Skills: A Conversational Mobile Web App To Support Dialectical Behavioral Therapy
Schroeder, J., Wilkes, C., Rowan, K., Toledo, A., Paradiso, A., Czerwinski, M., Mark, G., & Linehan, M. M. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173972 · Cited by 175
Ko, M., Yang, S., Lee, J., Heizmann, C., Jeong, J., Lee, U., Shin, D., Yatani, K., Song, J., & Chung, K. (2015) · ACM Conference on Computer Supported Cooperative Work (CSCW) · doi:10.1145/2675133.2675244 · Cited by 204
Use and Adoption Challenges of Wearable Activity Trackers
Shih, P. C., Han, K., Poole, E. S., Rosson, M. B., & Carroll, J. M. (2015) · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · Cited by 178
Personal Informatics, Self-Insight, and Behavior Change: A Critical Review of Current Literature
Kersten-van Dijk, E. T., Westerink, J. H. D. M., Beute, F., & IJsselsteijn, W. A. (2017) · Human–Computer Interaction · doi:10.1080/07370024.2016.1276456 · Cited by 171
Strategies for mHealth Research: Lessons from 3 Mobile Intervention Studies
Ben‐Zeev, D., Schueller, S. M., Begale, M. J., Duffecy, J. L., Kane, J. M., & Mohr, D. C. (2014) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-014-0556-2 · Cited by 181
Realizing the Potential of Behavioral Intervention Technologies
Schueller, S. M., Muñoz, R. F., & Mohr, D. C. (2013) · Current Directions in Psychological Science · doi:10.1177/0963721413495872 · Cited by 152
Paul, L., Wyke, S., Brewster, S. A., Sattar, N. A., Gill, J. M. R., Alexander, G., Rafferty, D., McFadyen, A. K., Ramsay, A., & Dybus, A. (2016) · Topics in Stroke Rehabilitation · doi:10.1080/10749357.2015.1122266 · Cited by 165
Hiniker, A., Hong, S.-S., Kohno, T., & Kientz, J. A. (2016) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858403 · Cited by 155
The Race Towards Digital Wellbeing
Roffarello, A. M., & Russis, L. D. (2019) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300616 · Cited by 185
HealthyTogether: exploring social incentives for mobile fitness applications
Chen, Y., & Pu, P. (2014) · Proceedings of the Second International Symposium of Chinese CHI · doi:10.1145/2592235.2592240 · Cited by 159
Roffarello, A. M., & De Russis, L. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3571810 · Cited by 137
Karkar, R., Schroeder, J., Epstein, D. A., Pina, L. R., Scofield, J., Fogarty, J. A., Kientz, J. A., Munson, S. A., Vilardaga, R., & Zia, J. K. (2017) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3025480 · Cited by 150
Torrado, J. C., Gomez, J., & Montoro, G. (2017) · Sensors · doi:10.3390/s17061359 · Cited by 130
Evaluating the Impact of Physical Activity Apps and Wearables: Interdisciplinary Review
McCallum, C., Rooksby, J., & Gray, C. M. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.9054 · Cited by 126
Bauer, J. S., Consolvo, S., Greenstein, B. M., Schooler, J. W., Wu, E., Watson, N. F., & Kientz, J. A. (2012) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2207676.2208600 · Cited by 121
Self-citationDesigning the Future of Children’s Mental Health Services
Lyon, A. R., Dopp, A. R., Brewer, S. K., Kientz, J. A., & Munson, S. A. (2020) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-020-01038-x · Cited by 120
Reconsidering the device in the drawer
Epstein, D. A., Kang, J. H., Pina, L. R., Fogarty, J. A., & Munson, S. A. (2016) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2971648.2971656 · Cited by 114
Uptake and usage of IntelliCare: A publicly available suite of mental health and well-being apps
Lattie, E. G., Schueller, S. M., Sargent, E., Stiles-Shields, C., Tomasino, K. N., Corden, M. E., Begale, M., Karr, C. J., & Mohr, D. C. (2016) · Internet Interventions · doi:10.1016/j.invent.2016.06.003 · Cited by 113
Understanding heart rate sharing
Slovák, P., Janssen, J. H., & Fitzpatrick, G. (2012) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2207676.2208526 · Cited by 113
Ko, M., Choi, S., Yang, S., Lee, J., & Lee, U. (2015) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2750858.2804283 · Cited by 111
Prescriptive persuasion and open-ended social awareness: expanding the design space of mobile health
Baumer, E. P. S., Katz, S. J., Freeman, J. E., Adams, P., Gonzales, A. L., Pollak, J., Retelny, D., Niederdeppe, J., Olson, C. M., & Gay, G. K. (2012) · Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work · doi:10.1145/2145204.2145279 · Cited by 107
Usability Evaluations of Mobile Mental Health Technologies: Systematic Review
İnal, Y., Wake, J. D., Guribye, F., & Nordgreen, T. (2019) · Journal of Medical Internet Research · doi:10.2196/15337 · Cited by 111
Chancellor, S., Hu, A., & Choudhury, M. D. (2018) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3174240 · Cited by 118
Loo Gee, B., Griffiths, K. M., & Gulliver, A. (2016) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv043 · Cited by 92
Changing Family Practices with Assistive Technology
Sonne, T., Müller, J., Marshall, P., Obel, C., & Grønbæk, K. (2016) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858157 · Cited by 97
Doyle, J., Murphy, E., Gavin, S., Pascale, A., Deparis, S., Tommasi, P., Smith, S., Hannigan, C., Smitt, M. S., van Leeuwen, C., et al. (2021) · Journal of Medical Internet Research · doi:10.2196/22672 · Cited by 91
HCI and mobile health interventions
Poole, E. S. (2013) · Translational Behavioral Medicine · doi:10.1007/s13142-013-0214-3 · Cited by 95
Storywell: Designing for Family Fitness App Motivation by Using Social Rewards and Reflection
Saksono, H., Castaneda‐Sceppa, C., Hoffman, J. A., Morris, V., El‐Nasr, M. S., & Parker, A. G. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376686 · Cited by 92
Mazilu, S., Blanke, U., Hardegger, M., Tröster, G., Gazit, E., & Hausdorff, J. M. (2014) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2556288.2557278 · Cited by 84
Lee, U., Han, K., Cho, H., Chung, K., Hong, H., Lee, S.-J., Noh, Y., Park, S., & Carroll, J. M. (2018) · Ad Hoc Networks · doi:10.1016/j.adhoc.2018.08.021 · Cited by 88
Khot, R. A., Lee, J., Aggarwal, D., Hjorth, L., & Mueller, F. (2015) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2702123.2702197 · Cited by 85
Automated vs. Human Health Coaching
Mitchell, E. G., Maimone, R., Cassells, A. N., Tobin, J. N., Davidson, P., Smaldone, A. M., & Mamykina, L. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449173 · Cited by 78
Motivational Technologies: A Theoretical Framework for Designing Preventive Health Applications
Sundar, S. S., Bellur, S. S., & Jia, H. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-31037-9_10 · Cited by 85
Designing Ambient Narrative-Based Interfaces to Reflect and Motivate Physical Activity
Murnane, E. L., Jiang, X., Kong, A., Park, M., Shi, W., Soohoo, C., Vink, L., Xia, I., Yu, X. K., Yang-Sammataro, J., et al. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376478 · Cited by 85
Jo, E., Jeong, Y., Park, S., Epstein, D. A., & Kim, Y. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642420 · Cited by 100
Wienrich, C., Döllinger, N., & Hein, R. M. (2021) · Frontiers in Virtual Reality · doi:10.3389/frvir.2021.627194 · Cited by 78
Mitchell, E. G., Heitkemper, E., Burgermaster, M., Levine, M. E., Miao, Y., Hwang, M. L., Desai, P. M., Cassells, A. N., Tobin, J. N., Tabak, E. G., et al. (2021) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445555 · Cited by 70
Miller, A., & Mynatt, E. D. (2014) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2556288.2557190 · Cited by 71
Ringland, K. E., Zalapa, R., Neal, M., Escobedo, L., Tentori, M. E., & Hayes, G. R. (2014) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2632048.2632065 · Cited by 69
Turning the Classic Snake Mobile Game into a Location–Based Exergame that Encourages Walking
Chittaro, L., & Sioni, R. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-31037-9_4 · Cited by 69
Rabbi, M., Aung, M. H., Gay, G. K., Reid, M. C., & Choudhury, T. (2018) · Journal of Medical Internet Research · doi:10.2196/10147 · Cited by 71
Carrasco-Hernandez, L., Jódar-Sánchez, F., Núñez-Benjumea, F., Moreno Conde, J., Mesa González, M., Civit-Balcells, A., Hors-Fraile, S., Parra-Calderón, C. L., Bamidis, P. D., & Ortega-Ruiz, F. (2020) · JMIR mHealth and uHealth · doi:10.2196/17530 · Cited by 65
Steps, Choices and Moral Accounting
Gorm, N., & Shklovski, I. (2016) · ACM Conference on Computer Supported Cooperative Work (CSCW) · doi:10.1145/2818048.2819944 · Cited by 63
Evaluating an mHealth App for Health and Well-Being at Work: Mixed-Method Qualitative Study
de Korte, E. M., Wiezer, N., Janssen, J. H., Vink, P., & Kraaij, W. (2018) · JMIR mHealth and uHealth · doi:10.2196/mhealth.6335 · Cited by 54
Rethinking Technologies for Behavior Change
Rapp, A., Tirassa, M., & Tirabeni, L. (2019) · ACM Trans. Comput. Hum. Interact. · doi:10.1145/3318142 · Cited by 42
Design Recommendations for Self-Monitoring in the Workplace: Studies in Software Development
Meyer, A. N., Murphy, G. C., Zimmermann, T., & Fritz, T. (2017) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3134714 · Cited by 60
Cheung, K., Ling, W., Karr, C. J., Weingardt, K. R., Schueller, S. M., & Mohr, D. C. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy023 · Cited by 61
Chen, A. T., Wu, S., Tomasino, K. N., Lattie, E. G., & Mohr, D. C. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103187 · Cited by 58
GPTCoach: Towards LLM-Based Physical Activity Coaching
Jörke, M., Sapkota, S., Warkenthien, L., Vainio, N., Schmiedmayer, P., Brunskill, E., & Landay, J. A. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713819 · Cited by 105
Parker, A. G., & Grinter, R. E. (2013) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2013.08.008 · Cited by 59
Social Reflections on Fitness Tracking Data
Saksono, H., Castaneda‐Sceppa, C., Hoffman, J. A., El‐Nasr, M. S., Morris, V., & Parker, A. G. (2019) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300543 · Cited by 59
Rapp, A., & Boldi, A. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3603497 · Cited by 57
Sleep tracking in the real world
Liang, Z., & Ploderer, B. (2016) · Australian Conference on Computer-Human Interaction (OzCHI) · doi:10.1145/3010915.3010988 · Cited by 56
Tollmar, K., Bentley, F. R., & Viedma, C. (2012) · International Conference on Pervasive Computing Technologies for Healthcare · doi:10.4108/icst.pervasivehealth.2012.248698 · Cited by 53
Suh, H., Porter, J. R., Hiniker, A., & Kientz, J. A. (2014) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2556288.2557386 · Cited by 53
Participatory Design of VR Scenarios for Exposure Therapy
Flobak, E., Wake, J. D., Vindenes, J., Kahlon, S., Nordgreen, T., & Guribye, F. (2019) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300799 · Cited by 53
Doyle, J., Walsh, L. C., Sassu, A., & McDonagh, T. (2014) · International Conference on Pervasive Computing Technologies for Healthcare · doi:10.4108/icst.pervasivehealth.2014.254950 · Cited by 52
Agapie, E., Colusso, L. F., Munson, S. A., & Hsieh, G. (2016) · ACM Conference on Computer Supported Cooperative Work (CSCW) · doi:10.1145/2818048.2819943 · Cited by 52
An assistive technology design framework for ADHD
Sonne, T., Marshall, P., Obel, C., Thomsen, P. H., & Grønbæk, K. (2016) · Australian Conference on Computer-Human Interaction (OzCHI) · doi:10.1145/3010915.3010925 · Cited by 65
MUBS: A Personalized Recommender System for Behavioral Activation in Mental Health
Rohani, D. A., Lopategui, A. Q., Tuxen, N., Faurholt‐Jepsen, M., Kessing, L. V., & Bardram, J. E. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376879 · Cited by 60
Reflective Informatics Through Family Storytelling: Self-discovering Physical Activity Predictors
Saksono, H., & Parker, A. G. (2017) · Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3025651 · Cited by 51
de Vries, R. A. J., Truong, K. P., Kwint, S., Drossaert, C. H. C., & Evers, V. (2016) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858229 · Cited by 51
Understanding Individual Differences for Tailored Smoking Cessation Apps
Paay, J., Kjeldskov, J., Skov, M. B., Lichon, L., & Rasmussen, S. (2015) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2702123.2702321 · Cited by 50
Family Health Promotion in Low-SES Neighborhoods
Saksono, H., Castaneda‐Sceppa, C., Hoffman, J. A., El‐Nasr, M. S., Morris, V., & Parker, A. G. (2018) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173883 · Cited by 50
Seven HCI Grand Challenges Revisited: Five-Year Progress
Stephanidis, C., Salvendy, G., Antona, M., Duffy, V. G., Gao, Q., Karwowski, W., Konomi, S., Nah, F. F., Ntoa, S., Rau, P. P., et al. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2450411 · Cited by 59
Hollis, V., Konrad, A., & Whittaker, S. (2015) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2702123.2702196 · Cited by 49
Exploring Cooperative Fitness Tracking to Encourage Physical Activity among Office Workers
Ren, X., Yu, B., Lü, Y., & Brombacher, A. (2018) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3274415 · Cited by 51
Kawas, S., Chase, S. K., Yip, J. C., Lawler, J. J., & Davis, K. S. (2019) · International Journal of Child-Computer Interaction · doi:10.1016/j.ijcci.2019.01.003 · Cited by 49
Toward Usable Evidence: Optimizing Knowledge Accumulation in HCI Research on Health Behavior Change
Klasnja, P., Hekler, E. B., Korinek, E. V., Harlow, J., & Mishra, S. R. (2017) · Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3026013 · Cited by 44
Self-citationFive Lenses for Designing Exertion Experiences
Mueller, F., & Young, D. R. (2017) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3025746 · Cited by 45
Investigating the Effectiveness of Cohort-Based Sleep Recommendations
Daskalova, N., Lee, B., Huang, J. J. S., Ni, C., & Lundin, J. (2018) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3264911 · Cited by 45
myPace: An Integrative Health Platform for Supporting Weight Loss and Maintenance Behaviors
Barnett, J. C., Harricharan, M., Fletcher, D., Gilchrist, B., & Coughlan, J. (2014) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2014.2366832 · Cited by 49
Enabling Good Work Habits in Software Developers through Reflective Goal-Setting
Meyer, A. N., Murphy, G. C., Zimmermann, T., & Fritz, T. (2019) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2019.2938525 · Cited by 49
Trajectories of Engagement and Disengagement with a Story-Based Smoking Cessation App
Smith, W., Ploderer, B., Wadley, G., Webber, S. E., & Borland, R. (2017) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3026054 · Cited by 43
Meyer, J., Simske, S. J., Siek, K. A., Gurrin, C. G., & Hermens, H. J. (2014) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/2559206.2560469 · Cited by 42
Construal Level Theory of Mobile Persuasion
Katz, S. J., & Byrne, S. E. (2013) · Media Psychology · doi:10.1080/15213269.2013.798853 · Cited by 43
de Korte, E., Wiezer, N. M., Roozeboom, M. B., Vink, P., & Kraaij, W. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.6363 · Cited by 45
Kankanhalli, A., Xia, Q., & Zhao, X. (2021) · AIS Transactions on Human-Computer Interaction · doi:10.17705/1thci.00152 · Cited by 45
Rapp, A., Marino, A., Simeoni, R., & Cena, F. (2017) · Behaviour and Information Technology · doi:10.1080/0144929x.2017.1365170 · Cited by 48
Zhu, J., Lei, Y., Shah, A., Schein, G., Ghaednia, H., Schwab, J., Harteveld, C., & Mueller, S. (2022) · Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology · doi:10.1145/3526113.3545705 · Cited by 40
Saksono, H., Castaneda‐Sceppa, C., Hoffman, J. A., El‐Nasr, M. S., & Parker, A. G. (2021) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445087 · Cited by 40
Metadata
- Authors
- Klasnja, P., Consolvo, S., & Pratt, W.
- Affiliations
- University of Washington (US)
- Intel (United States) (US)
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2011-05-07
- Pages
- 3063-3072
- OpenAlex
- W2003659858
- Cited by
- 414
- References
- 52
- Citations by year
- 2026: 14 · 2025: 23 · 2024: 24 · 2023: 21 · 2022: 24 · 2021: 38 · 2020: 24 · 2019: 26 · 2018: 36 · 2017: 33 · 2016: 43 · 2015: 40 · 2014: 34 · 2013: 21 · 2012: 11
- FWCI
- 16.21
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- health behavior change, technology evaluation, behaviour change interventions, self-monitoring, conditioning, physical activity, healthy eating, user experience, preliminary design
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
