Design framework for the development of tailored behavior change technologies

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Abstract

Today, so-called persuasive or motivational technologies are developing, which refer to technologies, applications or services designed to induce changes in attitudes and behavior in those who use them. This is the subject of research in Human-Computer Interaction in connection with theories from psychology related, for example, to behavior change or motivation. Research on these technologies suggests that in order to encourage long-term adherence, these "virtual coaches"need to be personalized and/or tailored according to the individual characteristics of the users (stage of behavior change, motivations, preferences, barriers). For example, according to the Self-Determination Theory (SDT), an individual can present different forms of motivation, more or less effective. The idea is to be able to identify the forms of motivation present in users in order to propose services to reinforce or develop them. The use of such systems in the field of health has the potential to induce and reinforce health behaviors that are sometimes difficult to establish by health professionals. Providing daily, personalized care represents a considerable human and financial cost for health professionals. A mobile application has the advantage of being able to deal with these constraints. The computer coach is designed with and for patients suffering from chronic low back pain. The aim is to help them manage their condition, particularly with regard to their pain and the practice of regular physical activity. The work presented presents an innovative design approach, combining user-centered methodologies and psychological theories, which we detail through a research phase and a design phase. Currently, a first version of the application has been developed and is being tested.

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Debackere, F., Clavel, C., Roren, A., Tran, V. T., Messai, Y., Rannou, F., … Martin, J. C. (2023). Design framework for the development of tailored behavior change technologies. In UMAP 2023 - Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization (pp. 140–146). Association for Computing Machinery, Inc. https://doi.org/10.1145/3563359.3596984

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