Persuasive technology for overcoming food cravings and improving snack choices

ABSTRACT

A central challenge in weight management is the difficulty of overcoming desires for excessive and unhealthy food. Yet, studies show that when people are able to resist their desires for unhealthy choices, they experience pride and satisfaction. In order to alleviate the former and support the latter, we designed, implemented and tested a mobile application for improving snacking behavior. Our application delivers a food craving reduction intervention at the moment of need and allows users to track how often they successfully resisted cravings. Our craving reduction intervention is based on recent research that shows that food cravings can be reduced through imagery techniques. We conducted a week-long evaluation of our application, comparing the effectiveness of our application to a basic tracking application. We found that our imagery application significantly reduced both overall snacking and unhealthy snacking compared to a simple snack-tracking application.

References

1. Torning, K. and Kukkonen, H., Persuasive system design: state of the art and future directions. Proceedings of the 4th International Conference on Persuasive Technology, Springer, (2009), 30.
2. Brown, B., Chetty, G., and Harmon, E., A system for students to monitor diet and exercise. Proceedings of CHI(2012), 1807--1812.
3. Consolvo, S., McDonald, D., and Landay, J., Theory-Driven Design Strategies for Technologies that Support Behavior Change in Everyday Life. Proceedings of CHI 2009, ACM Press, (2009), 405--414.
4. Consolvo, S., Everitt, K, Smith, I I, and Landay, JA., Design requirements for technologies that encourage physical activity. Proceedings of CHI 2006, ACM Press, (2006), 457--466.
5. Lin, J, Mamykina, L, Lindtner, S, Delajoux, G, and Strub, H, Fish 'n' Steps: Encouraging physical activity with an interactive computer game. UbiComp 2006: Ubiquitous Computing, ACM Press, (2006), 261--278.
6. Consolvo, S., klasnja, P., McDonald, D., Avrahami, D. Froehlich J., LeGrand, L., Libby, R., Mosher, K., and Landay, J., Flowers or a robot army encouraging awareness and activity with personal, mobile displays. UbiComp 2008, ACM Press, (2008), 54--63.
7. Baumer, E. P. S., Katz, S. J., Freeman, J. E., Adams, P., Gonzales, A. L., Pllak, J. P., Retelny, D., Niederdeppe, J., Olson, C. M., and Gay, G. K, Prescriptive Persuasion and Open-Ended Social Awareness: Expanding the Design Space of Mobile Health. Proceedings of CHI 2012, ACM Press, (2012), 476--484.
8. Brown, Brandon, Chetty, Marshini, Grimes, Andrea, and Harmon, Ellie, Reflecting on health: a system for students to monitor diet and exercise. CHI'06 extended abstracts on Human factors in computing systems, ACM Press, (2006), 1807--1812.
9. Fehr, E. and Rangel, A., Neuroeconomic Foundations of Economic Choice-Recent Advances. Journal of Economic Perspectives, 25, (2011), 3--30.
10. Oinas-Kukkonen, H and Harjumaa, M, Persuasive systems design: Key issues, process model, and system features. Communications of the Association for Information Systems, 24, (2009), 28.
11. Oinas-Kukkonen, H, A foundation for the study of behavior change support systems. Personal and Ubiquitous Computing, 17, (2013), 1123--1135.
12. Fogg, B. J., Eckles, D., Bogost, I., Consolvo, S., Holmen, E, Spasojevic, M, Ulm, J, Tanguay, S, Walker, S, and White, S, Mobile Persuasion: 20 Perspectives of the Future of Behavior Change, Fogg, B. J. and Eckles, D., Stanford Captology Media,Stanford, 2007.
13. Rachuri, K, Musolesi, M, Mascolo, C, Rentfrow, P, Longworth, C, and Aucinas, A, EmotionSense: A Mobile Phones based Adaptive Platform for Experimental Social Psychology Research. Proceedings of the 12th ACM International Conference on Ubiquitous Computing, ACM Press, (2010),
14. Maitland, J. and Chalmers, M., Designing for Peer Involvement in Weight Management. Proceedings of CHI 2011, ACM Press, (2011), 315--324.
15. Lee, M., Kiesler, S., and Forlizzi, J., Mining Behavioral Economics to Design Persuasive Technology for Healthy Choices. Proceedings of CHI 2011, ACM Press, (2011), 325--334.
16. Maitland, J., Towards Negotiation as a Framework for Health Promoting Technology. ACM SIGHIT Record, 1, (2011), 10--19.
17. Hsu, A. and Blandford, A., Designing for Psychological Change: Individuals' Reward and Cost Valuations in Weight Management. Journal of Medical Internet Research(2014),
18. May, J., Andrade, J., Batey, H., Berry, L. M., and Kavanagh, D. J., Less food for thought. Impact of attentional instructions on intrusive thoughts about snack foods. Appetite, 55, (2010), 279--287.
19. Andrade, J., Pears, S., May, J., and Kavanagh, D. J., Use of a clay modeling task to reduce chocolate craving. Appetite, 58, (2012), 955--963.
20. Kemps, Eva and Tiggemann, Marika, Modalityspecific imagery reduces cravings for food: an application of the elaborated intrusion theory of desire to food craving. Journal of Experimental Psychology: Applied, 13, (2007), 95.
21. Harvey, Kirsty, Kemps, Eva, and Tiggemann, Marika, The nature of imagery processes underlying food cravings. British Journal of Health Psychology, 10, (2005), 49--56.
22. Hamilton, J, Fawson, S, May, J, Andrade, J, and Kavanagh, D J., Brief guided imagery and body scanning interventions reduce food cravings. Appetite, 71, (2013), 158--162.
23. May, J., Andrade, J., Panabokke, N., and Kavanagh, D., Images of desire: cognitive models of craving. Memory, 12, (2004), 447--461.
24. May, J., Andrade, J., and Kavanagh, D., Elaborated Intrusion Theory: A cognitive-emotional theory of food craving. Current Obesity Reports, 1, (2012), 114--121.
25. Knauper, B., Pillay, R., Lacaille, J., McCollam, A., and Kelso, E., Replacing craving imagery with alternative pleasant imagery reduces craving intensity. Appetite, 57, (2011), 173--178.
26. Baddeley, A D. and Andrade, J, Working memory and the vividness of imagery. Journal of Experimental Psychology: General, 129, (2000), 126.
27. Liu, Y., Gao, J. H., Liu, H. L., and Fox, P. T., The temporal response of the brain after eating revealed by functional MRI. Nature, 405, (29--6--2000), 10581062.
28. de, Lauzon B., Romon, M., Deschamps, V., Lafay, L., Borys, J. M., Karlsson, J., Ducimetiere, P., and Charles, M. A., The Three-Factor Eating Questionnaire-R18 is able to distinguish among different eating patterns in a general population. J.Nutr., 134, (2004), 2372--2380.

Index Terms

• Applied computing

  • Life and medical sciences

• Human-centered computing