An Application Framework for Personalised and Adaptive Behavioural Change Support Systems

The paper analyzes current weaknesses of behavioural change support systems (BCSS) such as the failure of adequately taking into account the heterogeneity of target users. Based on this analysis the paper presents an application framework that comprises various components to accommodate user preferences and to adapt system interventions to individual users. Among these components is a goal hierarchy which can be set up to represent the goals a user wants to achieve. The higher-level goals can be broken down into more specific goals that can be measured and associated with appropriate activities. Furthermore, our BCSS framework includes components for adapting its interactions according to a user’s observed behavioural preferences as well as his or her previous reactions to system interventions. User adaptation also takes into account the preferences of similar users by employing a collaborative filtering approach. Thus, overall user acceptance should be improved and motivation for behavioural change sustained. The framework is currently being implemented and will subsequently be evaluated.

[1]  Ayman Atia,et al.  An Experimental Comparison Between Seven Classification Algorithms for Activity Recognition , 2015, AISI.

[2]  Neerincx,et al.  How to Develop Personalized eHealth for Behavioural Change : Method and Example , 2014 .

[3]  E. McGrady,et al.  Ethical Issues of Health Management Predictive Modeling , 2010 .

[4]  Harri Oinas-Kukkonen,et al.  Influencing Individually: Fusing Personalization and Persuasion , 2012, TIIS.

[5]  Manfred Tscheligi,et al.  Contextualise! personalise! persuade!: a mobile HCI framework for behaviour change support systems , 2013, MobileHCI '13.

[6]  Tyler Sax,et al.  Just a Fad? Gamification in Health and Fitness Apps , 2014, JMIR serious games.

[7]  Colin Atkinson,et al.  Model-Driven Development: A Metamodeling Foundation , 2003, IEEE Softw..

[8]  D. Asch,et al.  Wearable devices as facilitators, not drivers, of health behavior change. , 2015, JAMA.

[9]  Harri Oinas-Kukkonen,et al.  Persuasive Systems Design: Key Issues, Process Model, and System Features , 2009, Commun. Assoc. Inf. Syst..

[10]  Gediminas Adomavicius,et al.  Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.

[11]  Harri Oinas-Kukkonen,et al.  Behavior Change Support Systems: The Next Frontier for Web Science , 2010 .

[12]  Boris E. R. de Ruyter,et al.  Adaptive Persuasive Systems: A Study of Tailored Persuasive Text Messages to Reduce Snacking , 2012, TIIS.

[13]  Privender Saini,et al.  Individual Differences in Persuadability in the Health Promotion Domain , 2010, PERSUASIVE.

[14]  D. Kahneman.  Thinking, Fast and Slow , 2011 .

[15]  B. J. Fogg,et al.  Persuasive technology: using computers to change what we think and do , 2002, UBIQ.

[16]  E. A. Locke,et al.  Building a practically useful theory of goal setting and task motivation. A 35-year odyssey. , 2002, The American psychologist.

[17]  Dimitris Karagiannis,et al.  Metamodelling Platforms , 2002, EC-Web.

[18]  Edith Maier.  Smart Mobility – Encouraging sustainable mobility behaviour by designing and implementing policies with citizen involvement , 2012 .

[19]  Kevin G Volpp,et al.  Behavioral economics holds potential to deliver better results for patients, insurers, and employers. , 2013, Health affairs.

[20]  M. de Zwaan,et al.  What distinguishes weight loss maintainers of the German Weight Control Registry from the general population? , 2015, Obesity.

[21]  Julie A. Kientz,et al.  Personality and Persuasive Technology: An Exploratory Study on Health-Promoting Mobile Applications , 2010, PERSUASIVE.