Advertisement

Persuasive Technologies and Behavior Modification Through Technology: Design of a Mobile Application for Behavior Change

  • Andreas Hamper
  • Isabella Eigner
  • Alexander Popp
Chapter
Part of the Healthcare Delivery in the Information Age book series (Healthcare Delivery Inform. Age)

Abstract

Even though there are numerous health and fitness applications at the app stores and the majority of people have downloaded at least one of them, they have a limited effect, or people stop using them after a short period of time. This work tries to solve these problems by tailoring behavioral interventions to individual users with the aim to achieve a long-term behavior change.

By influencing motivational factors and most relevant processes of change, there is an abstraction that allows tailoring these interventions to a limited number of target groups instead of every single user. Additionally, the motivational factors, as well as the processes of change, can be translated into functional and nonfunctional requirements, which are the link between the theoretical framework and the practical implementation.

The result of this work is a ready-to-use Android application that demonstrates the theoretic model behind the tailored interventions by leading the user to a long-term behavior change, like being more physically active. Furthermore, one specific service, that is necessary for some target groups, has been developed to complete this model as well as to showcase the details of tailored interventions.

Keywords

Healthcare Personal health Ubiquitous computing Mobile service Prevention Tailored intervention 

References

  1. Android: Fragments. (2016). Retrieved December 19, 2016, from https://developer.android.com/guide/components/fragments.html
  2. Apple: Health & Fitness Apps. (2016). Retrieved December 19, 2016, from https://itunes.apple.com/us/genre/ios-health-fitness/id6013
  3. Assmann, G., Cullen, P., & Schulte, H. (2002). Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Münster (PROCAM) study. Circulation, 105(3), 310–315.CrossRefPubMedGoogle Scholar
  4. Bock, B. C., Marcus, B. H., Pinto, B. M., & Forsyth, L. (2001). Maintenance of physical activity following an individualized motivationally tailored intervention. Annals of Behavioral Medicine, 23(2), 79–87.CrossRefPubMedGoogle Scholar
  5. Boehm, B. W. (1984). Verifying and validating software requirements and design specifications. IEEE Software, 1(1), 75–88.CrossRefGoogle Scholar
  6. Chung, L., & do Prado Leite, J. C. (2009). On non-functional requirements in software engineering. In Conceptual modeling: Foundations and applications (pp. 363–379). Berlin Heidelberg: Springer.CrossRefGoogle Scholar
  7. Cortez, R., & Vazhenin, A. (2013). Developing re-usable components based on the Virtual-MVC design pattern. In International Workshop on Databases in Networked Information Systems (pp. 132–149). Springer Berlin Heidelberg.CrossRefGoogle Scholar
  8. Dennison, L., Morrison, L., Conway, G., & Yardley, L. (2013). Opportunities and challenges for smartphone applications in supporting health behavior change: Qualitative study. Journal of Medical Internet Research, 15(4), e86.CrossRefPubMedPubMedCentralGoogle Scholar
  9. Fogg, B. J. (2009). A behavior model for persuasive design. In Proceedings of the 4th International Conference on Persuasive Technology (p. 40). ACM.Google Scholar
  10. Glanz, K., Rimer, B. K., & Viswanath, K. (Eds.). (2008). Health behavior and health education: Theory, research, and practice. San Francisco: John Wiley & Sons.Google Scholar
  11. Glinz, M. (2007). On non-functional requirements. In 15th IEEE International Requirements Engineering Conference (RE 2007) (pp. 21–26). IEEE.Google Scholar
  12. Hofer, S. (2016). Consumer Healthcare Wearables – A teardown of health and fitness solutions to understand their impact on behavior change. Master’s Thesis, Friedrich Alexander Universität Erlangen-Nürnberg.Google Scholar
  13. Institute of Electrical and Electronics Engineers. (1984). IEEE guide to software requirements specifications. IEEE.Google Scholar
  14. Krebs, P., & Duncan, D. T. (2015). Health App use among US mobile phone owners: A national survey. JMIR mHealth uHealth, 3(4), e101.CrossRefPubMedPubMedCentralGoogle Scholar
  15. Li, K., Hüsing, A., & Kaaks, R. (2014). Lifestyle risk factors and residual life expectancy at age 40: A German cohort study. BMC Medicine, 12(1), 59.CrossRefPubMedPubMedCentralGoogle Scholar
  16. Lightsey, B. (2001). Systems engineering fundamentals. Ft. Belvoir: Defense Acquisition University.Google Scholar
  17. openEHR Foundation. (2007). In T. Beale & S. Heard (Eds.), Archetype definitions and principles. 1.0.Google Scholar
  18. Prochaska, J. O., DiClemente, C. C., & Norcross, J. C. (1992). In search of how people change: applications to addictive behaviors. American Psychologist, 47(9), 1102.CrossRefPubMedGoogle Scholar
  19. Prochaska, J. O., & Velicer, W. F. (1997). The transtheoretical model of health behavior change. American Journal of Health Promotion, 12(1), 38–48.CrossRefPubMedGoogle Scholar
  20. Psychologisches Institut Freiburg. (2001). Erfassung der “Stages of Change” im Transtheoretischen Modell Prochaska’s – eine Bestandsaufnahme. Forschungsberichte des Psychologischen Instituts der Albert-Ludwigs-Universität Freiburg i. Br.Google Scholar
  21. Rütten, A., Abu-Omar, K., Adlwarth, W., & Meierjürgen, R. (2007). Sedentary lifestyles. Classification of different target groups for the promotion of health-enhancing physical activities. Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)), 69(7), 393–400.CrossRefGoogle Scholar
  22. Spittaels, H., Bourdeaudhuij, I. D., Brug, J., & Vandelanotte, C. (2007). Effectiveness of an online computer-tailored physical activity intervention in a real-life setting. Health Education Research, 22(3), 385–396.CrossRefPubMedGoogle Scholar
  23. Statista: App Store Categories. (2016). Retrieved December 19, 2016, from https://www.statista.com/statistics/270291/popular-categories-in-the-app-store/
  24. Statista: Smartphone Market. (2016). Retrieved December 19, 2016, from https://www.statista.com/topics/2711/us-smartphone-market/
  25. Vlissides, J., Helm, R., Johnson, R., & Gamma, E. (1995). Design patterns: Elements of reusable object-oriented software. Reading: Addison-Wesley, 49(120), 11.Google Scholar
  26. Wiegers, K., & Beatty, J. (2013). Software requirements. London: Pearson Education.Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Andreas Hamper
    • 1
  • Isabella Eigner
    • 1
  • Alexander Popp
    • 1
  1. 1.University Erlangen-Nuremberg, Institute of Information SystemsNurembergGermany

Personalised recommendations