Why Won’t You Do What’s Good for You? Using Intelligent Support for Behavior Change

Abstract

Human health depends to a large extent on their behavior. Adopting a healthy lifestyle often requires behavior change. This paper presents a computational model of behavior change that describes formal relations between the determinants of behavior change, based on existing psychological theories. This model is developed to function as the core of a reasoning mechanism of an intelligent support system that is able to create theory-based intervention messages. The system first tries to determine the reason of the occurrence of the unwanted behavior by asking short questions via a mobile phone application and by gathering information from an online lifestyle diary. The system then attempts to influence the user using tailored information and persuasive motivational messages.

Personal Informatics, Self-Insight, and Behavior Change: A Critical Review of Current Literature

“…The TTM is well suited to application to PI and the self-improvement hypothesis because it deals with sustained behavior change: change as a long-term process of preparation, change, and subsequent maintenance of new behavior(s). In addition, many of the concepts and ideas from the TTM are shared by a variety of other behavior (change) models, like the theory of planned behavior (Ajzen, 1985), the health belief model (Rosenstock, 1974), and various others (Bagozzi, 2000;Bandura, 1977Bandura, , 1991De Vries et al, 2003;Fishbein, 2000;Hagger & Chatzisarantis, 2014;Klein, Mogles, & Van Wissen, 2011;Kluger & DeNisi, 1998;Maes & Gebhardt, 2000;Rogers, 1975;Ryan, 2009;Schwarzer, 2008;Witte, 1992). For these reasons, we use the TTM as a starting point in our discussion of existing behavior change models and how they compare to the self-improvement hypothesis.…”

“…Awareness can be triggered by knowledge (e.g., about problematic behavior, likely outcomes and possible alternative behaviors; De Vries et al, 2003) and cues that make the goal of behavior change more salient (e.g., an acquaintance having a heart attack; De Vries et al, 2003;Klein et al, 2011).…”

“…Originally proposed by Bandura (1977), selfefficacy and similar concepts like "perceived behavioral control" and "perceived competence" are now incorporated in many theories of behavior and behavior change (e.g. Bagozzi, 2000;De Vries et al, 2003;Fishbein, 2000;Hagger & Chatzisarantis, 2014;Klein et al, 2011;Maes & Gebhardt, 2000;Rogers, 1975;Ryan, 2009;Schwarzer, 2008).…”

Why option generation matters for the design of autonomous e-coaching systems

“…Intelligent, autonomous e-coaching systems are becoming more and more mainstream, offering people a wide variety of strategies and techniques intended to help them fulfill their goals for self-improvement (Blanson Henkemans et al 2009;Klein et al 2011;Kaptein et al 2012). While these innovative systems offer new and exciting opportunities for individualized coaching in a range of different domains, they also highlight a gap in our current understanding of the intimate relationship between an e-coaching system on the one hand, and a human user on the other hand, and the effect that this relationship has on the user in terms of his or her self-directedness, or autonomy.…”

“…A prominent example of such a system is Klein, Mogles and Van Wissen's eMate (Klein et al 2011), which promotes a healthy lifestyle for people managing chronic illness (e.g., diabetes type 2, HIV or cardiovascular disease) by inferring the person's behavior change state from individual measures and sending tailored motivational text messages to influence that state if deemed necessary. Clearly, there is a positive drive behind these innovations, but what is striking is that there seems to be very little awareness (except for a meta-study by Torning and Oinas-Kukkonen 2009) that such systems are in fact interfering with people's decisionmaking process by directly or indirectly offering suggestions for action.…”