Long-Term User Experience and Persuasion on 3DFysio, A Mobile Rehabilitation Application

  • Aino AhtinenEmail author
  • Anu Lehtiö
  • Marion Boberg
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11433)


This paper presents a field study of a persuasive mobile application, 3DFysio, to support patients’ motivation in rheumatoid arthritis rehabilitation. The study was conducted with 10 patients over the period of 9 months, to study the user experience of the application and its persuasive features. The research data was collected with interviews and questionnaires in several phases of the trial. The findings show that the patients perceived the application as a motivational tool to support their rehabilitation process. The main persuasive and motivational aspects for patients were the interactive rehabilitation program, accurate and easily available physiotherapy exercises presented by 3D avatar, and the connection to the personal physiotherapist. 3DFysio seemed to motivate through a combination of persuasive elements on the application and real life. It also supported the establishment of an exercise routine. This paper provides new knowledge of persuasive design to support long-term rehabilitation process by means of mobile applications.


Mobile rehabilitation Persuasive design User experience Mobile health apps 



This study was conducted as part of the 3DFysio project in a larger project about the development of telerehabilitation (Etäkuntoutus-hanke) financed by Kela, The Social Insurance Institution of Finland. We would like to express our gratitude to Kela, the project partners and the study participants.


  1. 1.
    Ahtinen, A., Andrejeff, E., Harris, C., Väänänen, K.: Let’s walk at work: persuasion through the brainwolk walking meeting app. In: Proceedings of the 21st International Academic Mindtrek Conference, pp. 73–82. ACM (2017)Google Scholar
  2. 2.
    Anderson, K., Burford, O., Emmerton, L.: Mobile health apps to facilitate self-care: a qualitative study of user experiences. PLoS One 11(5), e0156164 (2016)CrossRefGoogle Scholar
  3. 3.
    Antón, D., Berges, I., Bermúdez, J., Goñi, A., Illarramendi, A.: Knowledge-based telerehabilitation monitoring. In: Chbeir, R., Manolopoulos, Y., Maglogiannis, I., Alhajj, R. (eds.) AIAI 2015. IAICT, vol. 458, pp. 237–249. Springer, Cham (2015). Scholar
  4. 4.
    Azevedo, R., Bernardes, M., Fonseca, J., et al.: Smartphone application for rheumatoid arthritis self-management: cross-sectional study revealed the usefulness, willingness to use and patients’ needs. Rheumatol. Int. 35(10), 1675–1685 (2015)CrossRefGoogle Scholar
  5. 5.
    Botsis, T., Demiris, G., Pedersen, S., Hartvigsen, G.: Home telecare technologies for the elderly. J. Telemed. Telecare 14(7), 333–337 (2008)CrossRefGoogle Scholar
  6. 6.
    Cialdini, R.B.: Harnessing the science of persuasion. Harvard Bus. Rev. 79(9), 72–81 (2001)Google Scholar
  7. 7.
    Geuens, J., Swinnen, T.W., Westhovens, R., de Vlam, K., Geurts, L., Vanden Abeele, V.: A review of persuasive principles in mobile apps for chronic arthritis patients: opportunities for improvement. JMIR mHealth uHealth 4(4), e118 (2016)CrossRefGoogle Scholar
  8. 8.
    Grainger, R., Townsley, H., White, B., Langlotz, T., Taylor, W.J.: Apps for people with rheumatoid arthritis to monitor their disease activity: a review of apps for best practice and quality. JMIR mHealth uHealth 5(2), e7 (2017)CrossRefGoogle Scholar
  9. 9.
    Hailey, D., Roine, R., Ohinmaa, A., Dennett, L.: Evidence on the effectiveness of telerehabilitation applications. Institute of Health Economics and Finnish Office for Health Technology Assessment, Edmonton and Helsinki, Canada (2010)Google Scholar
  10. 10.
    Klasnja, P., Consolvo, S., Pratt, W.: How to evaluate technologies for health behavior change in HCI research. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 3063–3072. ACM, May 2011Google Scholar
  11. 11.
    López-Jaquero, V., Montero, F., Teruel, M.A.: Influence awareness: considering motivation in computer-assisted rehabilitation. J. Ambient Intell. Humaniz. Comput. 1–13 (2017)Google Scholar
  12. 12.
    Matthews, J., Win, K.T., Oinas-Kukkonen, H., Freeman, M.: Persuasive technology in mobile applications promoting physical activity: a systematic review. J. Med. Syst. 40(3), 72 (2016)CrossRefGoogle Scholar
  13. 13.
    Minet, L.R., Hansen, L.W., Pedersen, C.D., et al.: Early telemedicine training and counselling after hospitalization in patients with severe chronic obstructive pulmonary disease: a feasibility study. BMC Med. Inform. Decis. Making 15(1), 3 (2015)CrossRefGoogle Scholar
  14. 14.
    Oinas-Kukkonen, H., Harjumaa, M.: Persuasive systems design: key issues, process model, and system features. Commun. Assoc. Inf. Syst. 24(28), 484–501 (2009)Google Scholar
  15. 15.
    Pickrell, M., Bongers, B., van den Hoven, E.: Understanding persuasion and motivation in interactive stroke rehabilitation. In: MacTavish, T., Basapur, S. (eds.) Persuasive Technology. LNCS, vol. 9072, pp. 15–26. Springer, Cham (2015). Scholar
  16. 16.
    Pickrell, M., Bongers, B., van den Hoven, E.: Understanding changes in the motivation of stroke patients undergoing rehabilitation in hospital. In: Meschtscherjakov, A., De Ruyter, B., Fuchsberger, V., Murer, M., Tscheligi, M. (eds.) International Conference on Persuasive Technology. LNCS, vol. 9638, pp. 251–262. Springer, Cham (2016). Scholar
  17. 17.
    Revenäs, Å., Opava, C.H., Martin, C., et al.: Development of a web-based and mobile app to support physical activity in individuals with rheumatoid arthritis: results from the second step of a co-design process. JMIR Res. Protoc. 4(1), e22 (2015)CrossRefGoogle Scholar
  18. 18.
    Revenäs, Å., Opava, C.H., Ahlén, H., et al.: Mobile internet service for self-management of physical activity in people with rheumatoid arthritis: evaluation of a test version. RMD Open 2, e000214 (2016)CrossRefGoogle Scholar
  19. 19.
    Ryan, R.M., Deci, E.L.: Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am. Psychol. 55(1), 68 (2000)CrossRefGoogle Scholar
  20. 20.
    Smith, S.T., Schoene, D.: The use of exercise-based videogames for training and rehabilitation of physical function in older adults: current practice and guidelines for future research. Aging Health 8(3), 243–252 (2012)CrossRefGoogle Scholar
  21. 21.
    Stütz, T., Domhardt, M., Emsenhuber, G., et al.: An interactive 3D health app with multimodal information representation for frozen shoulder: co-creation and evaluation with patients. In: Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services, p. 3. ACM, September 2017Google Scholar
  22. 22.
    Synnott, J., et al.: ReApp – a mobile app for the rehabilitation of Ankle sprains. In: Bravo, J., Hervás, R., Villarreal, V. (eds.) AmIHEALTH 2015. LNCS, vol. 9456, pp. 61–67. Springer, Cham (2015). Scholar
  23. 23.
    Turunen, M., Hakulinen, J., Melto, A., et al.: SUXES – user experience evaluation method for spoken and multimodal interaction. In Proceedings of the 10th Annual Conference of the International Speech Communication Association (Interspeech), pp. 2567–2570 (2009)Google Scholar
  24. 24.
    Whitehead, L., Seaton, P.: The effectiveness of self-management mobile phone and tablet apps in long-term condition management: a systematic review. J. Med. Internet Res. 18(5), e97 (2016)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Tampere UniversityTampereFinland
  2. 2.Kineso OYKangasalaFinland

Personalised recommendations