Abstract
With the rapid emergence of mobile technologies in recent years, mobile health (m-health) has become fundamental to healthcare. Persuasion strategies and behavior change support features are widely used in m-health applications to increase the effectiveness of these applications on users. However, in the literature, there is a lack of research to analyze the current situation of m-health applications particularly from the perspective of behavior change approaches. In this study, the workout applications in the health and fitness category of Google Play store were selected and explored in terms of the relation of the features with the number of downloads and rating statistics obtained from the store. The findings are expected to be a guideline for application developers in order for m-health applications to be more effective in changing users’ behaviors to lead a healthy life.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Istepanian, R.S.H., Pattichis, C.S., Laxminarayan, S.: Introduction to mobile M-health systems. In: Micheli-Tzanakou, E. (ed.) M-Health: Emerging Mobile Health Systems, pp. 3–14. Springer, New York (2006)
Norris, A.C., Stockdale, R.S., Sharma, S.: A strategic approach to M-Health. Health Inform. J. 15(3), 244–253 (2009)
Fogg, B.J.: Persuasive technology: using computers to change what we think and do. Ubiquity 3(44), 2 (2002)
Oinas-Kukkonen, H.: A foundation for the study of behavior change support systems. Pers. Ubiquitous Comput. 17(6), 1223–1235 (2012)
Oinas-Kukkonen, H., Harjumaa, M.: Persuasive systems design: key issues, process model, and system features. Commun. Assoc. Inf. Syst. 24, 485–500 (2009)
Ploderer, B., Reitberger, W., Oinas-Kukkonen, H., van Gemert-Pijnen, J.: Social interaction and reflection for behaviour change. Pers. Ubiquitous Comput. 18, 1667–1676 (2014)
Munson S., Consolvo, S.: Exploring goal-setting, rewards, self-monitoring, and sharing to motivate physical activity. In: Proceedings of the 6th International Conference on Pervasive Computing Technologies for Healthcare, pp. 25–32. IEEE Press, San Diego (2012)
Liu, C., Zhu, Q., Holroyd, K.A., Seng, E.K.: Status and trends of mobile-health applications for ios devices: a developer’s perspective. J. Syst. Softw. 84(11), 2022–2033 (2011)
Harjumaa, M., Segerståhl, K., Oinas-Kukkonen, H.: Understanding Persuasive System Functionality in Practice: A Field Trial of Polar FT60. In: Proceedings of the Fourth International Conference on Persuasive Technology, PERSUASIVE 2009, Claremont, California, USA (2009)
Dennison, L., Morrison, L., Conway, G., Yardley, L.: Opportunities and challenges for smartphone applications in supporting health behavior change: qualitative study. J. Med. Internet Res. 15(4), e86 (2013)
Chang, T., Kaasinen, E., Kaipainen, K.: What Influences users’ decisions to take apps into use? A framework for evaluating persuasive and engaging design in mobile apps for well-being. In: Proceedings of the 11th International Conference on Mobile and Ubiquitous Multi Proceeding, MUM 2012, pp. 1–10. ACM New York (2012)
Unal, P., Temizel, T.T., Eren, P.E.: An exploratory study on the outcomes of influence strategies in mobile application recommendations. In: 2nd International Workshop on Behavior Change Support Systems, pp. 27–40 (2014)
Butler, M.: Android: changing the mobile landscape. IEEE Pervasive Comput. 10(1), 4–7 (2011)
Gavalas, D., Economou, D.: Development platforms for mobile applications: status and trends. IEEE Softw. 28(1), 77–86 (2011)
Peng, H., Long, F., Ding, C.: Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans. Pattern Anal. Mach. Intell. 27(8), 1226–1238 (2005)
Cohen, J.: A power primer. Psychol. Bull. 112(1), 155–159 (1992)
Oduor, M., Alahäivälä, T., Oinas-Kukkonen, H.: Persuasive software design patterns for social influence. Pers. Ubiquitous Comput. 18(7), 1689–1704 (2014)
Stibe, A.: Advancing typology of computer-supported influence: moderation effects in socially influencing systems. In: MacTavish, T., Basapur, S. (eds.) PERSUASIVE 2015. LNCS, vol. 9072, pp. 253–264. Springer, Cham (2015). doi:10.1007/978-3-319-20306-5_23
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Ünal, P., Cavdar, S.K., Temizel, T.T., Eren, P.E., Iyengar, S. (2017). Exploring Behavior Change Features for Mobile Workout Applications. In: Younas, M., Awan, I., Holubova, I. (eds) Mobile Web and Intelligent Information Systems. MobiWIS 2017. Lecture Notes in Computer Science(), vol 10486. Springer, Cham. https://doi.org/10.1007/978-3-319-65515-4_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-65515-4_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-65514-7
Online ISBN: 978-3-319-65515-4
eBook Packages: Computer ScienceComputer Science (R0)