Advertisement

Designing Representations of Behavioral Data with Blended Causality: An Approach to Interventions for Lifestyle Habits

  • Kenny K. N. ChowEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11433)

Abstract

Many personal informatics systems present users’ behavioral data in numbers or graphs for their reflection, which may not be effective on a daily basis because people do not always act like data scientists. Representation of behavioral data in virtual environments can provide information at a glance. Grounded in conceptual blending theory, insights from social psychology, and existing persuasive design principles, this article is conceptual-theoretical. It argues that representations should be designed like virtual consequences of behavior and related to users’ existing knowledge of comparable cause-effect relationships in order to prompt one’s imaginative beliefs about the behavioral-virtual causality. It proposes a framework that guides designing representations of behavioral data, including (1) identifying scenarios with comparable causality, (2) examining and grounding the mappings in embodied experiences, (3) performing blends between the behavior and the identified scenario, with different virtual consequences corresponding to different user behaviors, and (4) rendering virtual consequences as feedback that dynamically anchors the scenario for similar blends in users. Design cases are presented and analyzed to demonstrate how embodied mappings can be constructed for interventions for lifestyle habits.

Keywords

Behavior change Personal informatics Blending theory 

Notes

Acknowledgements

This research benefits from projects supported by The Hong Kong Polytechnic University and Tung Wah Group of Hospitals.

References

  1. 1.
    Li, I., Dey, A., Forlizzi, J.: A stage-based model of personal informatics systems. In: CHI 2010, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM Press (2010)Google Scholar
  2. 2.
    Rooksby, J., Rost, M., Morrison, A., Chalmers, M.: Personal tracking as lived informatics. In: CHI 2014, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1163–1172. ACM (2014)Google Scholar
  3. 3.
    Wilson, G.T., Bhamra, T., Lilley, D.: The considerations and limitations of feedback as a strategy for behaviour change. Int. J. Sustain. Eng. 8, 186–195 (2015)CrossRefGoogle Scholar
  4. 4.
    Rooksby, J., Asadzadeh, P., Rost, M., Morrison, A., Chalmers, M.: Personal tracking of screen time on digital devices. In: CHI 2016, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 284–296. ACM Press (2016)Google Scholar
  5. 5.
    Consolvo, S., Klasnja, P., McDonald, D.W., Landay, J.A.: Designing for healthy lifestyles: design considerations for mobile technologies to encourage consumer health and wellness. Found. Trends Hum.-Comput. Interact. 6, 167–315 (2014)CrossRefGoogle Scholar
  6. 6.
    Lin, J.J., Mamykina, L., Lindtner, S., Delajoux, G., Strub, H.B.: Fish’n’Steps: encouraging physical activity with an interactive computer game. In: Dourish, P., Friday, A. (eds.) UbiComp 2006. LNCS, vol. 4206, pp. 261–278. Springer, Heidelberg (2006).  https://doi.org/10.1007/11853565_16CrossRefGoogle Scholar
  7. 7.
    Consolvo, S., et al.: Activity sensing in the wild: a field trial of UbiFit garden. In: CHI 2008, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1797–1806. ACM Press (2008)Google Scholar
  8. 8.
    Froehlich, J., et al.: UbiGreen: investigating a mobile tool for tracking and supporting green transportation habits. In: CHI 2009, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM Press (2009)Google Scholar
  9. 9.
    Chiu, M.-C., et al.: Playful bottle: a mobile social persuasion system to motivate healthy water intake. In: Ubicomp 2009. ACM Press (2009)Google Scholar
  10. 10.
    Shiraishi, M., Washio, Y., Takayama, C., Lehodonvirta, V., Kimura, H., Nakajima, T.: Using individual, social and economic persuasion techniques to reduce CO2 emissions in a family setting. In: Persuasive 2009. ACM (2009)Google Scholar
  11. 11.
    Varela, F.J., Thompson, E., Rosch, E.: The Embodied Mind: Cognitive Science and Human Experience. MIT Press, Cambridge (1991)CrossRefGoogle Scholar
  12. 12.
    Lakoff, G., Johnson, M.: Philosophy in the Flesh: The Embodied Mind and Its Challenge to Western Thought. Basic Books, New York (1999)Google Scholar
  13. 13.
    Fogg, B.J.: A behavior model for persuasive design. In: Persuasive 2009 (2009)Google Scholar
  14. 14.
    Oinas-Kukkonen, H., Harjumaa, M.: A systematic framework for designing and evaluating persuasive systems. In: Oinas-Kukkonen, H., Hasle, P., Harjumaa, M., Segerståhl, K., Øhrstrøm, P. (eds.) PERSUASIVE 2008. LNCS, vol. 5033, pp. 164–176. Springer, Heidelberg (2008).  https://doi.org/10.1007/978-3-540-68504-3_15CrossRefGoogle Scholar
  15. 15.
    Midden, C.J.H., Kaiser, F.G., McCalley, L.T.: Technology’s four roles in understanding individuals’ conservation of natural resources. J. Soc. Issues 63, 155–174 (2007)CrossRefGoogle Scholar
  16. 16.
    Ajzen, I.: From intentions to actions: a theory of planned behavior. In: Kuhl, J., Beckman, J. (eds.) Action-Control: From Cognition to Behavior, pp. 11–39. Springer, Heidelberg (1985).  https://doi.org/10.1007/978-3-642-69746-3_2CrossRefGoogle Scholar
  17. 17.
    Bargh, J.A., Chartrand, T.L.: The unbearable automaticity of being. Am. Psychol. 54, 462–479 (1999)CrossRefGoogle Scholar
  18. 18.
    Verplanken, B., Aarts, H.: Habit, attitude, and planned behaviour: is habit an empty construct or an interesting case of goal-directed automaticity? Eur. Rev. Soc. Psychol. 10, 101–134 (1999)CrossRefGoogle Scholar
  19. 19.
    Madsen, K.H.: A Guide to metaphorical design. Commun. ACM 37, 57–62 (1994)CrossRefGoogle Scholar
  20. 20.
    Mandler, J.M.: How to build a baby: II. Conceptual primitives. Psychol. Rev. 99, 587–604 (1992)CrossRefGoogle Scholar
  21. 21.
    Lakoff, G., Johnson, M.: Metaphors We Live by. University of Chicago Press, Chicago (2003)CrossRefGoogle Scholar
  22. 22.
    Lakoff, G.: Explaining embodied cognition results. Top. Cogn. Sci. 4, 773–785 (2012)CrossRefGoogle Scholar
  23. 23.
    Fauconnier, G., Turner, M.: The Way We Think: Conceptual Blending and the Mind’s Hidden Complexities. Basic Books, New York (2002)Google Scholar
  24. 24.
    Coulson, S., Fauconnier, G.: Fake guns and stone lions: conceptual blending and privative adjectives. In: Fox, B., Jurafsky, D., Michaelis, L. (eds.) Cognition and Function in Language. CSLI, Palo Alto (1999)Google Scholar
  25. 25.
    Fillmore, C.J.: Frames and the semantics of understanding. Quaderni di Semantica 6, 222–254 (1985)Google Scholar
  26. 26.
    Chow, K.K.N.: Sketching imaginative experiences: from operation to reflection via lively interactive artifacts. Int. J. Des. 12, 33–49 (2018)Google Scholar
  27. 27.
    Chow, K.K.N: Lock up the lighter: experience prototyping of a lively reflective design for smoking habit control. In: Meschtscherjakov, A., De Ruyter, B., Fuchsberger, V., Murer, M., Tscheligi, M. (eds.) PERSUASIVE 2016. LNCS, vol. 9638, pp. 352–364. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-31510-2_30CrossRefGoogle Scholar
  28. 28.
    Chow, K.K.N.: Time off: designing lively representations as imaginative triggers for healthy smartphone use. In: Ham, J., Karapanos, E., Morita, P.P., Burns, C.M. (eds.) PERSUASIVE 2018. LNCS, vol. 10809, pp. 135–146. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-78978-1_11CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of DesignThe Hong Kong Polytechnic UniversityHung HomHong Kong

Personalised recommendations