To improve the accuracy of predictive models for behavior change, some researchers have started to try to combine behavioral economics models with existing models for behavior change ( Roberto and Kawachi, 2015). However, existing models for behavior change, such as “Social Cognitive Theory” and “Theory of Planned Behavior (TPB)” cannot sufficiently predict the occurrence probabilities of a considered behavior or its change through interventions ( Sniehotta et al., 2014). Several models for behavior change have converged to the hypothesis that attitudes, norms, and self-efficacy are important determinants of intentions and behavior ( Sheeran et al., 2016). How can we help them change people's behavior for the better? The problem of “behavior change” has long been studied in various research fields such as psychology, pedagogy, nursing, public health, medicine, and health promotion ( Fishbein and Ajzen, 2010). It is often difficult for clinicians, trainers, or teachers to change people's undesirable habitual or addictive behaviors, such as overeating, excessive drinking, lack of exercise, and smoking. In the present paper, we clarify the corresponding components between existing models for behavior change and EUT, and propose a new model, the Decision-Theoretic Model of behavior change (DTM), which is a natural extension of ordinary EUT. However, these attempts have failed because the existing models are not consistent with Expected Utility Theory (EUT), which underlies various behavioral economics models. To improve the accuracy of behavior-change models, some researchers have tried to combine behavioral economics models with existing models for behavior change. Several models for behavior change have converged to the hypothesis that attitudes, norms, and self-efficacy are important determinants of intentions and behavior. The issue of “behavior change” has long been studied in various research fields.
Undesirable habitual or addictive behaviors are often difficult to change.
1Brain Science Institute, Tamagawa University Brain Science Institute, Machida, Japan.Goggamespyi7b6ybpnpnlwhb4md6owgbijfsuj6z5hesqt3yfyz42rad.Kaosu Matsumori 1,2 * Kazuki Iijima 1 Yasuharu Koike 3 Kenji Matsumoto 1 * Please do not bug us with these sort of requests.
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