User Modeling and User-Adapted Interaction

, Volume 21, Issue 4–5, pp 341–376 | Cite as

Motivating reflection about health within the family: the use of goal setting and tailored feedback

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Abstract

It is widely acknowledged that obesity is a serious health issue. Despite governments’ campaigns and initiatives to raise the level of awareness, the proportion of adults classified as overweight or obese is increasing steadily. As a result, there has been a growing interest in Human Computer Interaction and User Modelling to study how to support health behaviour change. While most of the work to date has focused on individuals, medical research has shown that family engagement plays an important role on health behaviour. To consider the family context, we are developing technology that facilitates health discussions and encourages supportive behaviour within the family. We investigate how to motivate members of a family to reflect upon their lifestyle and think of ways in which they can make it healthier. In particular, we have looked at whether providing explicit goals and tailored feedback can have an impact. During a two week trial with families in which we explored these strategies, we found that setting a collective goal for the family influenced how much the family as a whole contributed, and that feedback increased significantly mothers’ participation. Our results also suggest that establishing a family goal encouraged families to work together and, in particular, to help each other find ways to be healthier. Finally, 76% of participants reported discussing the task with someone in their family, and, also discussing it together as a family (57%).

Keywords

Motivation strategies Goal setting theory Lifestyle and wellbeing Family support Health behaviour Evaluation 
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References

  1. Ali-Hasan, N., Gavales, D., Peterson, A. Raw, M.: Fitster: social fitness information visualizer, In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2006)—Student Design Competition, Montréal, QC. pp. 1795–1800 (2006)Google Scholar
  2. Arroyo, E., Bonanni, L., Selker, T.: Waterbot: exploring feedback and persuasive techniques at the sink, In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2005), Portland, OR. pp. 631–639 (2005)Google Scholar
  3. Austin J.T.: Effects of shifts in goal origin on goal acceptance and attainment. Organ. Behav. Hum. Decis. Process. 44, 415–435 (1989)CrossRefGoogle Scholar
  4. Australian Bureau of Statistics: National Nutrition Survey. http://www.abs.gov.au/ausstats/abs@.nsf/mf/4802.0 (1995). Accessed 29 Sep 2009
  5. Australian Bureau of Statistics: ‘National Health Survey: summary of results’. http://www.ausstats.abs.gov.au/ (2009). 29 Sep 2009
  6. Ball D., McKenry P., Price-Bonham S.: Use of repeated-measures designs in family research. J. Marriage Fam. 45(4), 885–896 (1983)CrossRefGoogle Scholar
  7. Bandura A.: Health promotion by social cognitive means. Health Educ. Behav. 31(2), 143–164 (2004)CrossRefGoogle Scholar
  8. Bandura A.: Guide for constructing self-efficacy scales. In: Pajares, F., Urdan, T. (eds) Self-efficacy Beliefs of Adolescents, pp. 307–337. Information Age Publishing, Greenwich (2006)Google Scholar
  9. Barkhuus, L.: Designing ubiquitous computing technologies to motivate fitness and health. In: Proceedings of the Grace Hopper Conference, 4–7 Oct, San Diego, CA. pp. 384–492 (2006)Google Scholar
  10. Becker L.: Joint effect of feedback and goal setting on performance: a field study of residential energy conservation. J. Appl. Psychol. 63, 428–433 (1978)CrossRefGoogle Scholar
  11. Bental D., Cawsey A., Jones R.: Patient information systems that tailor to the individual. Patient Educ. Couns. 36(2), 171–180 (1999)CrossRefGoogle Scholar
  12. Brug J., Steenhuis I., van Assema P., de Vries H.: The impact of a computer-tailored nutrition intervention. Prev. Med. 25, 236–242 (1996)CrossRefGoogle Scholar
  13. Brug J., Campbell M., van Assema P.: The application and impact of computer-generated personalized nutrition education: A review of the literature. Patient Education and Counseling 36, 145–156 (1999)CrossRefGoogle Scholar
  14. Camerini, L., Giacobazzi, M., Boneschi, M., Schulz, P.G., Rubinelli, S.: Design and implementation of a web-based tailored gymnasium to enhance self-management of fibromyalgia. User modeling and user-adapted interaction. J. Person. Res. 21 (2010). doi: 10.1007/s11257-010-9088-y
  15. Campbell, T., Ngo, B., Fogarty, J.: Game design principles in everyday fitness applications. In: the Proceedings of Computer Supported Cooperative Work Conference (CSCW 2008), San Diego. pp. 249–252 (2008)Google Scholar
  16. Cawsey A.J., Jones R.B., Pearson J.: The evaluation of a personalised health information system for patients with cancer. User Model. User-Adapt. Interact. 10(1), 47–72 (2000)CrossRefGoogle Scholar
  17. Colineau, N., Paris, C., Marendy, P., Bhandari, D., Shu, Y.: Family engagement in weight management. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2009)—Extended Abstract, 3–9 Apr 2009, Boston, MA. pp. 3991–3996 (2009)Google Scholar
  18. Consolvo, S., Everitt, K., Smith, I., Landay, J.A.: Design requirements for technologies that encourage physical activity. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2006), Montréal, QC. pp. 457–466 (2009)Google Scholar
  19. Consolvo, S., McDonald. D.W., Toscos, T., Chen, M.Y., Froehlich, J., Harrison, B., Klasnja, P., LaMarca, A., LeGrand, L., Libby, R., Smith, I., Landay, J.A.: Activity sensing in the wild: a field trial of UbiFit garden. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2008), Florence. pp. 1797–1806 (2008a)Google Scholar
  20. Consolvo, S., Klasnja, P., McDonald. D.W., Avrahami, D., Froehlich, J., LeGrand, L., Libby, R., Mosher, K., Landay, J.A.: Flowers or a robot army?: Encouraging awareness & activity with personal, mobile displays. In: Proceedings of the 10th International Conference on Ubiquitous computing (UbiComp’08), Seoul. Vol. 344, pp. 54–63 (2008b)Google Scholar
  21. Consolvo, S., Klasnja, P.V., McDonald, D.W., Landay, J.A.: Goal-setting considerations for persuasive technologies that encourage physical activity. In: Proceedings of 4th International Conference on Persuasive Technology (Persuasive 2009), 26–29 Apr, Claremont, CA (2009)Google Scholar
  22. De Bourdeaudhuij I.: Perceived family members’ influence on introducing healthy food into the family. Health Educ. Res. 12(1), 77–90 (1997)CrossRefGoogle Scholar
  23. De Bourdeaudhuij I., Brug J.: Tailoring dietary feedback to reduce fat intake: an intervention at the family level. Health Educ. Res. 15(4), 449–462 (2000)CrossRefGoogle Scholar
  24. DiMarco C., Bray P., Covvey D., Cowan D., DiCiccio V., Hovy E., Lipa J., Yang C.: Authoring and generation of individualised patient education materials. J. Inform. Technol. Healthc. 6(1), 63–71 (2008)Google Scholar
  25. Erriquez, E., Grasso, F.: Generation of personalised advisory messages: an ontology based approach. In: The Proceedings of the 21st IEEE International Symposium on computer-Based Medical Systems, (CBMS 2008), Special Track on Personalisation for e-Health, 17–19 June 2008, Jyväskylä. pp. 437–442 (2008)Google Scholar
  26. Eysenbach, G.: The law of attrition. J. Med. Internet Res. 7(1), e11 (2005). www.jmir.org/2005/1/e11/
  27. Fogg B.J.: Persuasive Technology: Using Computers to Change What We Think and Do. Morgan Kaufmann Publishers, San Francisco (2003)Google Scholar
  28. Gasser R., Brodbeck D., Degen M., Luthiger J., Wyss R., Reichlin S. (ed.): Persuasiveness of a Mobile Lifestyle Coaching Application Using Social Facilitation, Lecture Notes in Computer Science, Vol. 3962, pp. 27–38. Springer, Berlin (2006)Google Scholar
  29. Grasso, F.: Exciting avocados and dull pears: combining behavioural and argumentative theory for producing effective advice. In: The Proceedings of the 20th Annual Meeting of the Cognitive Science Society. University of Wisconsin-Madison, WI. pp. 436–441 (1998)Google Scholar
  30. Grimes, A., Bednar, M., Bolter, J.D., Grinter, R.E.: EatWell: sharing nutrition-related memories in a low-income community. In: The Proceedings of Computer Supported Cooperative Work Conference (CSCW 2008), San Diego. pp. 87–96 (2008)Google Scholar
  31. Grimes, A., Desney, T., Morris, D.: Toward technologies that support family reflections on health. In: Proceedings of the ACM 2009 Group Conference, 10–13 May, Sanibel Island, FL. pp. 311–320 (2009)Google Scholar
  32. Hardeman W., Griffin S., Johnston M., Kinmonth A.L., Wareham N.J.: Interventions to prevent weight gain: a systematic review of psychological models and behaviour change methods. Int. J. Obes. 24, 131–143 (2000)CrossRefGoogle Scholar
  33. Heimendinger J., Uyeki T., Andhara A., Marshall J.A., Scarbro S., Belansky E., Crane L.: Coaching process outcomes of a family visit nutrition and physical activity intervention. Health Educ. Behav. 34(1), 71–89 (2007)CrossRefGoogle Scholar
  34. Jafarinaimi, N., Forlizzi, J., Hurst, A., Zimmerman, J.: Breakaway: an ambient display designed to change human behavior. In: Proceedings of the SIGCHI conference on Human Factors in computing systems (CHI 2005), Portland, OR. pp. 1945–1948 (2005)Google Scholar
  35. Jones, D., Beach, S., Jackson, H.: Family influences on health: a framework to organize research and guide intervention. In: Handbook of Family Communication, pp. 647–672. Lawrence Erlbaum Assoc., Mahwah, NJ. (2004)Google Scholar
  36. Kappel, K., Grechenig, T.: “show-me”: water consumption at a glance to promote water conservation in the shower. In: Proceedings of 4th International Conference on Persuasive Technology (Persuasive 2009), 26–29 Apr, Claremont, CA (2009)Google Scholar
  37. Karau S.J., Williams K.D.: Social loafing: a meta-analytic review and theoretical integration. J. Person. Soc. Psychol. 65, 681–706 (1993)CrossRefGoogle Scholar
  38. Kreuter M.W., Bull F.C., Clark E.M., Oswald D.L.: Understanding how people process health information: a comparison of tailored and nontailored weight-loss materials. Health Psychol. 18(5), 487–494 (1999)CrossRefGoogle Scholar
  39. Kreuter M.W., Farrell D., Olevitch L., Brennan L.: Tailoring health messages: customizing communication with computer technology. Erlbaum, Mahwah, NJ (2000)Google Scholar
  40. Kroeze W., Werkman A., Brug J.: A systematic review of randomized trials on the effectiveness of computer-tailored education on physical activity and dietary behaviors. Ann. Behav. Med. 31(3), 205–223 (2006)CrossRefGoogle Scholar
  41. Lieberman, D.A.: Dance games and other exergames: what the research says. University of California, Santa Barbara http://www.comm.ucsb.edu/lieberman_flash.htm (2006). Accessed 9 Oct 2009
  42. Lin, J.J., Mamykina, L., Lindtner, S., Delajoux, G., Strub, H.B.: Fish’n’Steps: encouraging physical activity with an interactive computer game. In: Proceedings of UbiComp 2006, Orange County, CA. pp. 261–278 (2006)Google Scholar
  43. Locke E.A., Latham G.P.: Building a practically useful theory of goal setting and task motivation. Am. Psychol. 57(9), 705–717 (2002)CrossRefGoogle Scholar
  44. Lustria M.L., Cortese J., Seth N., Glueckauf R.: Computer-tailored health interventions delivered over the web: review and analysis of key components. Patient Educ. Couns. 74(2), 156–173 (2009)CrossRefGoogle Scholar
  45. Maitland, J., Sherwood, S., Barkhuus, L., Anderson, I., Hall, M., Brown, B., Chalmers, M., Muller, H.: Increasing the awareness of daily activity levels with pervasive computing. In: The Proceedings of Pervasive Health ‘06, Innsbruck. pp. 1–9 (2006)Google Scholar
  46. McLean N., Griffin S., Toney K., Hardeman W.: Family involvement in weight control, weight maintenance and weight-loss interventions: a systematic review of randomised trials. Int. J. Obes. 27, 987–1005 (2003)CrossRefGoogle Scholar
  47. Mokka, S., Väätänen, A., Heinilä, J., Välkkynen, P.: Fitness computer game with a bodily user interface. In: Proceedings of the 2nd ACM International Conference on Entertainment computing, Vol. 38, Pittsburgh, PA. pp. 1–3 (2003)Google Scholar
  48. Mueller, F.: Exertion in networked games. In: Proceedings of the ACM 4th International Conference on Foundations of Digital Games. Doctoral Consortium Extended Abstracts, Orlando, FL. pp. 346–348 (2009)Google Scholar
  49. Mueller F., Stevens G., Thorogood A., O’Brien S., Wulf V.: Sports over a distance. Pers. Ubiquitous Comput. 11(8), 633–645 (2007)CrossRefGoogle Scholar
  50. Nakajima, T., Lehdonvirta, V., Tokunaga, E., Kimura, H.: Reflecting human behavior to motivate desirable lifestyle. In: Proceedings of the 7th ACM Conference on Designing Interactive Systems (DIS 2008), Cape Town. pp. 405–414 (2008)Google Scholar
  51. Nawyn J., Intille S.S., Larson K.: Embedding behavior modification strategies into a consumer electronic device: a case study. In: Dourish P., Friday A. (eds.) The Proceedings of UbiComp’06. Lecture Notes in Computer Science vol. 4206, pp. 297–314. Springer-Verlag, Berlin (2006)Google Scholar
  52. Noar S.M., Benac C.N., Harris M.S.: Does tailoring matter? Meta-analytic review of tailored print health behaviour change interventions. Psychol. Bull. 133(4), 673–693 (2007)CrossRefGoogle Scholar
  53. Petty R.E., Cacioppo J.T., Strathman A., Priester J.R.: To think or not to think: exploring two routes to persuasion. In: Shavitt, S., Brock, T.C. (eds) Persuasion: Psychological Insights and Perspectives, pp. 113–147. Allyn & Bacon, New York (1994)Google Scholar
  54. Prochaska J.O., Velicer W.F.: The transtheoretical model of health behavior change. Am. J. Health Promot. 12, 38–48 (1997)Google Scholar
  55. Saini, P., Lacroix, J.: Self-setting of physical activity goals and effects on perceived difficulty, importance and competence. In: Proceedings of 4th International Conference on Persuasive Technology (Persuasive 2009), 26–29 Apr, Claremont, CA (2009)Google Scholar
  56. Schumm W., Bugaighis M., Jurich A.: Using repeated measures designs in program evaluation of family therapy. J. Marital Fam. Ther. 11(1), 87–94 (1985)CrossRefGoogle Scholar
  57. Shilts M.K., Horowitz M., Townsend M.S.: Goal setting as a strategy for dietary and physical activity behavior change: A review of the literature. Am. J. Health Promot. 19(2), 81–93 (2004)Google Scholar
  58. Spittaels H., De Bourdeaudhuij I., Brug J., Vandelanotte C.: Effectiveness of an online computer-tailored physical activity intervention in a real-life setting. Health Educ. Res. 22(3), 385–396 (2007)CrossRefGoogle Scholar
  59. Strecher V.J., Seijts G.H., Kok G.J.: Goal setting as a strategy for health behavior change. Health Educ. Quart. 22, 190–200 (1995)Google Scholar
  60. Suggs L.S., Cowdery J.E., Carroll J.B.: Tailored program evaluation: past, present, future. Eval. Prog. Plan. 29, 426–432 (2006)CrossRefGoogle Scholar
  61. Toscos, T., Faber, A., Shunying, A., Praful Ghandhi, M.: Chick clique: persuasive technology to motivate teenage Girls to exercise. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2006)—Extended Abstract, 22–27 Apr 2006, Montreal. pp. 1873–1878 (2006)Google Scholar
  62. Toscos, T., Faber, A., Connelly, K., Mutsuddi Upoma, A.: Encouraging physical activity in teens—can technology help reduce barriers to physical activity in adolescent girls? In: Proceedings of the 2nd International conference on Pervasive Computing Technologies for Healthcare (Pervasive Healthcare), 31 Jan–2 Feb 2008, Tampere. pp. 219–221 (2008)Google Scholar
  63. Weldon E., Weingart L.R.: Group goals and group performance. Br. J. Soc. Psychol. 32, 307–334 (1993)Google Scholar
  64. Wright P.M., Kacmar K.M.: Mediating roles of self-set goals, goal commitment, self-efficacy, and attractiveness in the incentive-performance relation. Hum. Perform. 8(4), 263–296 (1995)CrossRefGoogle Scholar
  65. Woodruff, A., Hasbrouck, J., Augustin, S.: A bright green perspective on sustainable choices. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2008), Florence. pp. 313–322 (2008)Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.CSIRO – ICT CentreEppingAustralia

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