Toward a Systematic Understanding of Suggestion Tactics in Persuasive Technologies

  • Adrienne Andrew
  • Gaetano Borriello
  • James Fogarty
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4744)


The unique capabilities of mobile, context-aware, networked devices make them an interesting platform for applying suggestion in persuasive technologies. Because these devices are nearly always with their owners, can sense relevant information about the context of their use, and nearly always have network access, they enable the principle of kairos, providing the right information at the best time. Relatively little work has examined providing opportunistic, right-time, right-place suggestions or notifications that encourage people to change their behavior. This paper first discusses some of the challenges facing designers incorporating suggestions into their persuasive technologies. We then review a set of relevant persuasive technologies, focusing primarily on technologies in the health domain. We then identify a design space that represents tactics for building persuasive technologies, particularly suggestion technologies. We then explore how this design space of suggestion tactics can be used to evaluate, compare, and inform the design of new persuasive technologies.


Mobile information systems persuasive technologies behavior modification 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bickmore, T., Picard, R.: Establishing and Maintaining Long-Term Human Computer Relationships. ACM Transactions on Human-Computer Interaction 12(2), 293–327 (2005)CrossRefGoogle Scholar
  2. 2.
    Fogarty, J., Hudson, S.E., Atkeson, C.G., Avrahami, D., Forlizzi, J., Kiesler, S., Lee, J.C., Yang, J.: Predicting human interruptibility with sensors. ACM Trans. Comput.-Hum. Interact. 12(1), 119–146 (2005)CrossRefGoogle Scholar
  3. 3.
    Fogg, B.J.: Persuasive Technology: Using Computers to Change What We Think and Do. Morgan Kaufmann Publishers, San Francisco (2003)Google Scholar
  4. 4.
    Khaled, R., Barr, P., Noble, J., Biddle, R., Fischer, R.: Our Place or Mine?: Exploration into Collectivism-Focused Persuasive Technology Design. In: IJsselsteijn, W., de Kort, Y., Midden, C., Eggen, B., van den Hoven, E. (eds.) PERSUASIVE 2006. LNCS, vol. 3962, Springer, Heidelberg (2006)Google Scholar
  5. 5.
    Mazzotta, I., de Rosis, F.: Artifices for persuading to improve eating habits. In: AAAI Spring Symposium on ”Argumentation for consumers of health care”, Stanford (March 2006)Google Scholar
  6. 6.
    Nawyn, J., Intille, S., Larson, K.: Embedding Behavior Modification Strategies into a Consumer Electronic Device: A Case Study. In: 8th International Conference on Ubiquitous Computing, Orange County, USA (September 2006)Google Scholar
  7. 7.
    Oliver, N., Flores-Mangas, F.: MPTrain: a mobile, music and physiology-based personal trainer. In: MobileHCI 2006. Proceedings of the 8th Conference on Human-Computer interaction with Mobile Devices and Services, Helsinki, Finland, September 12-15, 2006, vol. 159, pp. 21–28. ACM Press, New York, NY (2006)CrossRefGoogle Scholar
  8. 8.
  9. 9.
    World Health Organization, “Obesity and Overweight,” Chronic Disease Information Sheet,

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Adrienne Andrew
    • 1
  • Gaetano Borriello
    • 1
  • James Fogarty
    • 1
  1. 1.Department of Computer Science and Engineering, University of Washington, Seattle, WAUSA

Personalised recommendations