Software Architecture Design for Health BCSS: Case Onnikka

  • Tuomas Alahäivälä
  • Harri Oinas-Kukkonen
  • Terhi Jokelainen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7822)


Behavior change support systems (BCSS) are a specific type of persuasive systems. They demand longer time spans and a very tight coupling with individual users’ multiple real-life contexts. However, in most cases research into these systems has described technical artifacts at such a general level that important implementation details such as the software architecture have been ignored. In this paper, we will present a software architecture design for a full-fledged BCSS. The architectural style suggested defines a layered architecture and its key system components. The architecture has been implemented in a real-life BCSS for supporting weight loss and maintenance in order to prevent health problems such as metabolic syndrome. The system development process and the selection of implemented persuasive features was carried out by utilizing the persuasive systems design model. The lessons learned and the architecture presented in this paper can be used in further software engineering research regarding persuasive and behavior change support systems.


Software Architecture User Context Architectural Style Uniform Resource Locator Persuasive Technology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Oinas-Kukkonen, H.: Behavior Change Support Systems: A Research Model and Agenda. In: Ploug, T., Hasle, P., Oinas-Kukkonen, H. (eds.) PERSUASIVE 2010. LNCS, vol. 6137, pp. 4–14. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  2. 2.
    Oinas-Kukkonen, H.: A foundation for the study of behavior change support systems. In: Personal and Ubiquitous Computing (2012) (Online First)Google Scholar
  3. 3.
    Lehto, T., Oinas-Kukkonen, H.: Persuasive Features in Six Weight Loss Websites: A Qualitative Evaluation. In: Ploug, T., Hasle, P., Oinas-Kukkonen, H. (eds.) PERSUASIVE 2010. LNCS, vol. 6137, pp. 162–173. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Segerståhl, K., Kotro, T., Väänänen-Vainio-Mattila, K.: Pitfalls in Persuasion: How Do Users Experience Persuasive Techniques in a Web Service? In: Ploug, T., Hasle, P., Oinas-Kukkonen, H. (eds.) PERSUASIVE 2010. LNCS, vol. 6137, pp. 211–222. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  5. 5.
    Lehto, T., Oinas-Kukkonen, H.: Persuasive Features in Web-Based Alcohol and Smoking Interventions: A Systematic Review of the Literature. Journal of Medical Internet Research 13(3), e46 (2011)Google Scholar
  6. 6.
    Chatterjee, S., Byun, J., Pottathil, A., Moore, M.N., Dutta, K., Xie, H(Q.): Persuasive Sensing: A Novel In-Home Monitoring Technology to Assist Elderly Adult Diabetic Patients. In: Bang, M., Ragnemalm, E.L. (eds.) PERSUASIVE 2012. LNCS, vol. 7284, pp. 31–42. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  7. 7.
    Mukhtar, H., Ali, A., Belaid, D., Sungyoung, L.: Persuasive Healthcare Self-Management in Intelligent Environments. In: 8th International Conference on Intelligent Environments, IE, pp. 190–197 (2012)Google Scholar
  8. 8.
    Oinas-Kukkonen, H., Harjumaa, M.: Persuasive systems design: Key issues, process model, and system features. Communications of the Association for Information Systems 24(1), 485–500 (2009)Google Scholar
  9. 9.
    Fogg, B.J.: Persuasive computers: Perspectives and research directions. In: Proc. of the SIGCHI Conference on Human Factors in Computing Systems, CHI, pp. 225–232 (1998)Google Scholar
  10. 10.
    Fielding, R.T., Taylor, R.N.: Principled design of the modern Web architecture. ACM Transactions on Internet Technology 2(2), 115–150 (2002)CrossRefGoogle Scholar
  11. 11.
    Perry, D.E., Wolf, A.L.: Foundations for the study of software architecture. ACM SIGSOFT Software Engineering Notes 17(4), 40–52 (1992)CrossRefGoogle Scholar
  12. 12.
    Enwald, H., Huotari, M.-L.: Preventing the Obesity Epidemic by Second Generation Tailored Health Communication: an Interdisciplinary Review. Journal of Medical Internet Research 12(2), e24 (2010)Google Scholar
  13. 13.
    Keränen, A.-M., Savolainen, M.J., Reponen, A.H., Kujari, M.L., Lindeman, S.M., Bloigu, R.S., Laitinen, J.H.: The effect of eating behavior on weight loss and maintenance during a lifestyle intervention. Preventive Medicine 49(1), 32–38 (2009)CrossRefGoogle Scholar
  14. 14.
    Krasner, G., Pope, S.: A Description of the {Model-View-Controller} User Interface Paradigm in the Smalltalk-80 System. Journal of Object Oriented Programming 1(3), 26–49 (1988)Google Scholar
  15. 15.
    Leff, A., Rayfield, J.T.: Web-application development using the Model/View/Controller design pattern. In: Proceedings of the Fifth IEEE International Enterprise Distributed Object Computing Conference, EDOC 2001, pp. 118–127 (2001)Google Scholar
  16. 16.
    Battle, R., Benson, E.: Bridging the Semantic Web and Web 2.0 with Representational State Transfer (REST). Web Semantics: Science, Services and Agents on the World Wide Web 6(1) (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Tuomas Alahäivälä
    • 1
    • 2
  • Harri Oinas-Kukkonen
    • 1
  • Terhi Jokelainen
    • 2
  1. 1.Department of Information Processing ScienceUniversity of OuluOuluFinland
  2. 2.Clinical Research Center, Department of Internal MedicineUniversity of OuluOuluFinland

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