ABSTRACT
Researchers in HCI and behavioral science are increasingly exploring the use of technology to support behavior change in domains such as health and sustainability. This work, however, remain largely siloed within the two communities. We begin to address this silo problem by attempting to build a bridge between the two disciplines at the level of behavioral theory. Specifically, we define core theoretical terms to create shared understanding about what theory is, discuss ways in which behavioral theory can be used to inform research on behavior change technologies, identify shortcomings in current behavioral theories, and outline ways in which HCI researchers can not only interpret and utilize behavioral science theories but also contribute to improving them.
- Adams, M. A., Norman, G. J., Hovell, M. F., Sallis, J. F., Patrick, K. (2009). Reconceptualizing decisional balance in an adolescent sun protection intervention: Mediating effects and theoretical interpretations. Healt Psychol, 28, 217--225.Google Scholar
Cross Ref
- Ajzen, I. (1991). The theory of planned behavior, Organizat Behav Hum Dec Proc, 50, 179--211.Google Scholar
Cross Ref
- Ajzen, I. (2002). Perceived Behavioral Control, Self-Efficacy, Locus of Control, and the Theory of Planned Behavior. J Appl Soc Psych, 32, 665--683.Google Scholar
Cross Ref
- Balaam, M. et al. (2011). Motivating mobility: designing for lived motivation in stroke rehabilitation. CHI'11, 3073--3082. Google Scholar
Digital Library
- Bandura, A. (1986). Social foundations of thought and action. Prentice Hall, Englewood Cliffs, NJ.Google Scholar
- Bandura, A. (1997). Self-Efficacy - The Exercise of Control. Worth Publishers, Inc. New York, NY.Google Scholar
- Bao, L. and Intille, S. S. (2004). Activity Recognition from User-Annotated Acceleration Data. Most, 1--17.Google Scholar
- Becker, M. (1974). The health belief model and personal health behavior, J Healt Soc Behav, 18, 348--366.Google Scholar
Cross Ref
- Bond, R. M., et al. (2012). A 61-million-person experiment in social influence and political mobilization. Nature 489, 295--298.Google Scholar
Cross Ref
- Buman, M. P., Giacobbi, P. R., Yasova, L. D., and McCrae, C. S. (2009). Using the constructive narrative perspective to understand physical activity reasoning schema in sedentary adults. J Healt Psychol, 14, 1174--83.Google Scholar
Cross Ref
- Collins, L., Dziak, J., and Li, R. (2009). Design of experiments with multiple independent variables: A resource management perspective on complete and reduced factorial designs. Psychol Meth, 14, 202--224.Google Scholar
Cross Ref
- Consolvo, S., Everitt, K., Smith, I., and Landay, J. (2006). Design requirements for technologies that encourage physical activity. CHI'06, 457--466. Google Scholar
Digital Library
- Consolvo, S., Klasnja, P., McDonald, D. W., & Landay, J. (2009). Goal-setting considerations for persuasive technologies that encourage physical activity. Persuasive '09, Article 8, 8 pgs. Google Scholar
Digital Library
- Consolvo, S., Klasnja, P., McDonald, D. W., et al. (2008). Flowers or a robot army? Encouraging awareness & activity with personal, mobile displays. UbiComp'08, 54--63. Google Scholar
Digital Library
- Consolvo, S., McDonald, D. W., and Landay, J. (2009) Theory-driven design strategies for technologies that support behavior change in everyday life. CHI'09, 405--414. Google Scholar
Digital Library
- Consolvo, S., McDonald, D. W., et al. (2008). Activity sensing in the wild: A field trial of UbiFit garden. CHI'08, 1797--1806. Google Scholar
Digital Library
- Corbin, J. and Strauss, A. (2008). Basics of qualitative research: Techniques and procedures for developing grounded theory. 3rd Ed. Sage, Thousand Oaks, CA.Google Scholar
- Deci, E. L. and Ryan, R. M. (1985) Intrinsic motivation and selfdetermination in human behavior. Plenum, New York, NY.Google Scholar
- Dervin, B. (1983). Sense-making theory and practice: An overview of user interests in knowledge seeking and use, J Know Manag, 36--46.Google Scholar
- Dobson, D. and Cook, T. (1980) Avoiding type III error in program evaluation: Results from a field experiment. Eval Prog Plan, 269--276.Google Scholar
- Dourish, P. (2010) HCI and environmental sustainability: the politics of design and the design of politics. DIS'10, 1--10. Google Scholar
Digital Library
- Dunton, G., Intille, S., Beaudin, J., and Pentz, M. A. (2009). Pilot test of a real-time data capture protocol to assess children's exposure to and experience of physical activity contexts using mobile phones. Obes 17, S150--S151.Google Scholar
- Eagle, N. and Pentland, A. (2006). Reality mining: sensing complex social systems. Pers Ubi Comp, 255--268.Google Scholar
- Erickson, T. (2005). Five Lenses: Towards a Toolkit for Interaction Design. Theories and Practice in Interaction Design.Google Scholar
- Fogg, B. J. (2002). Persuasive Technology: Using computers to change what we think and do. Ubiquity, December Issue, A-5. Google Scholar
Digital Library
- Froehlich, J., Findlater, L., and Landay, J. (2010). The design of eco-feedback technology. CHI'10. 1999--2008. Google Scholar
Digital Library
- Froehlich, J., Findlater, L., Ostergren, M. et al. (2012). The design and evaluation of prototype eco-feedback displays for fixture-level water usage data, CHI'12, 2367--2376. Google Scholar
Digital Library
- Froehlich, J. (2011). Sensing and feedback of everyday activities to promote environmental behaviors, UMI, 3501869.Google Scholar
- Gearing, R. and El-Bassel, N. (2011). Major ingredients of fidelity: A review and scientific guide to improving quality of intervention research implementation. Clin Psychol Rev, 79--88.Google Scholar
- Glanz, K., Rimer, B., and US-N.C.I. (1995). Theory at a glance: A guide for health promotion practice. NIH-NCI.Google Scholar
- Goffman, E. (2002). The presentation of self in everyday life.Google Scholar
- Grimes, A., Bednar, M., Bolter, J. D., and Grinter, R. E. (2008). EatWell: Sharing nutrition-related memories in a low-income community, CSCW'08, 87--96. Google Scholar
Digital Library
- Grimes, A. and Grinter, R. (2007). Designing persuasion: Health technology for low-income African American communities. Persuas Tech, 4744, 24--35. Google Scholar
Digital Library
- He, H., Greenberg, S., and Huang, E. (2010). One size does not fit all: Applying the transtheoretical model to energy feedback technology design, CHI'10, 927--936. Google Scholar
Digital Library
- Hekler, E. B., Buman, M. P., Otten, J., et al. (2012) Who responds better to a computer- vs. human-delivered physical activity intervention? Results from the community health advice by telephone (CHAT) trial. In Submission.Google Scholar
- Hekler, E. B., Buman, M. P., Poothakandiyil, N., et al. (2012) Exploring behavioral markers of long-term physical activity maintenance: A case study of system identification modeling within a behavioral intervention. In Submission.Google Scholar
- Hersen, M., and Barlow, D. H. (1976). Single-case experimental designs: Strategies for studying behavior change. Peramon, New York, NY.Google Scholar
- Kim, T., Hong, H., and Magerko, B. (2010). Design requirements for ambient display that supports sustainable lifestyle. DIS'10, 103--112. Google Scholar
Digital Library
- King, A. C., Sallis, J., Frank, L., et al., (2011). Aging in neighborhoods differing in walkability and income: Associations with physical activity and obesity in older adults. Soc Sci Med, 73, 1525--1533.Google Scholar
Cross Ref
- King, A. C., Hekler, E. B., Castro, C. M., et al. (2013). Exercise Advice by Humans versus Computers: Maintenance Effects at 18 Months. Healt Psychol.Google Scholar
- King, A. C., Stokols, D., Talen, E., Brassington, G. S., and Killingsworth, R. (2002). Forging a Transdisciplinary Paradigm. Am J Prev Med 23, 15--25.Google Scholar
Cross Ref
- King, A. C., Toobert, D., et al. (2006). Perceived environments as physical activity correlates and moderators of intervention in five studies. Am J. Healt Prom, 21, 24--35.Google Scholar
Cross Ref
- Klasnja, P., Consolvo, S., and Pratt, W. (2011). How to evaluate technologies for health behavior change in HCI research. CHI'11, 3063--3072. Google Scholar
Digital Library
- Kraemer, H. C. and Kiernan, M., Essex, M., and Kupfer, D. J. (2008). How and why criteria defining moderators and mediators differ between the Baron & Kenny and MacArthur approaches. Healt Psychol, 27, S101-S108.Google Scholar
Cross Ref
- Lee, M., Kiesler, S., and Forlizzi, J. (2011). Mining behavioral economics to design persuasive technology for healthy choices. CHI'11, 325--334. Google Scholar
Digital Library
- Lin, J., Mamykina, L., and Lindtner, S. (2006). Fish'n'Steps: Encouraging physical activity with an interactive computer game. UbiComp'06, 261--278. Google Scholar
Digital Library
- Locke, E. and Latham, G. (1990). A theory of goal setting & task performance, Prentice Hall, Englewood Cliffs, NJ USA.Google Scholar
- Maguire, M. (2001). Methods to support human-centered design. Intern J Hum Comp Stud, 55, 587--634. Google Scholar
Digital Library
- Mamykina, L. and Mynatt, E. (2008). MAHI: investigation of social scaffolding for reflective thinking in diabetes management. CHI'08, 477--486. Google Scholar
Digital Library
- Chetty, M., Tran, D. and Grinter, R. E. (2008). Getting to green: Understanding resource consumption in the home. UbiComp '08, 242--251. Google Scholar
Digital Library
- Michie, S. Ashford, S., Sniehotta, F. F., et al., (2011). A refined taxonomy of behaviour change techniques to help people change their physical activity and healthy eating behaviours: The CALORE taxonomy. Psychol Healt, 26, 1479--1498.Google Scholar
Cross Ref
- Miluzzo, E., Lane, N., Fodor, K., et al. (2008). Sensing meets mobile social networks: the design, implementation and evaluation of the cenceme application, SenSys'08, 337--350. Google Scholar
Digital Library
- Morin, C. and Bootzin, R. (2006). Psychological and behavioral treatment of insomnia: Update of the recent evidence (1998-2004). SLEEP, 29, 1398--1414.Google Scholar
Cross Ref
- Moyers, T. B., Martin, T., Manual, J. K., et al. (2005) Assessing competence in the use of motivational intervention. J Sub Abuse Treat, 28, 19--26.Google Scholar
Cross Ref
- Nickerson, R. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Rev Gen Psychol, 2, 175--220.Google Scholar
Cross Ref
- Nigg, C., Allegrante, J., and Ory, M. (2002). Theory-comparison and multiple-behavior research: Common themes advancing health behavior research. Healt Educ Res, 17, 670--679.Google Scholar
Cross Ref
- Ogden, J. (2003). Some problems with social cognition models: a pragmatic and conceptual analysis. Healt Psychol, 22, 424--428.Google Scholar
Cross Ref
- Prochaska, J., Wright, J., and Velicer, W. (2008). Evaluating theories of health behavior change: A hierarchy of criteria applied to the transtheoretical model. Appl Psychol, 57, 561--588.Google Scholar
Cross Ref
- Prochaska, J. O. and DiClemente, C. C. (1983). Stages and processes of self-change of smoking: toward an integrative model of change. J Consult Clin Psychol 51, 390--395.Google Scholar
- Purpura, S., Schwanda, V., Williams, K., et al. (2011). Fit4Life: The design of a persuasive technology promoting healthy behavior and ideal weight. CHI'11, 423--432. Google Scholar
Digital Library
- Riley, W. T., Rivera, D. E., Atienza, A. et al. (2011). Health behavior models in the age of mobile interventions: Are our theories up to the task? Trans Behav Med 1, 53--71.Google Scholar
Cross Ref
- Rovniak, L. S., Hovell, M. F., and Wojcik, J. R. (2005). Enhancing theoretical fidelity: an email-based walking program demonstration. Am J Healt Prom, 20, 85--95.Google Scholar
Cross Ref
- Sallis, J. F. and Owen, N. (1997). Ecological models. In K. Glanz, et al. eds., Health behavior and health education: Theory, research, and practice. Jossey Bass, San Francisco, 403--424.Google Scholar
- Sallis, J. F., Saelens, B. E., Frank, L. D., et al. (2009). Neighborhood built environment and income: examining multiple health outcomes. Social Sci Med, 68, 1285--1293.Google Scholar
Cross Ref
- Shove, E. (2010). Beyond the ABC: Climate change policies and theories in social change. Environ and Plan, A, 42(6), 1273.Google Scholar
- Velicer, W. F. and Prochaska, J. O. (2008). Stage and non-stage theories of behavior and behavior change: A comment on Schwarzer. Appl Psychol Interna Rev 57, 75--83.Google Scholar
Cross Ref
- Behavior Change Techniques Taxonomy. http://www.ucl.ac.uk/healthpsychology/BCTtaxonomy/index.php.Google Scholar
Index Terms
Mind the theoretical gap: interpreting, using, and developing behavioral theory in HCI research





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