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Digital behaviour change interventions to break and form habits
Pinder C., Vermeulen J., Cowan B., Beale R.  ACM Transactions on Computer-Human Interaction 25 (3): 1-66, 2018. Type: Article
Date Reviewed: Sep 27 2018

Whenever research on behavior is in progress, a special category is also under review in terms of habit. In the context of behavior change, it is of interest to find how habit could influence behavior, especially in digital environments. Thus, it is quite interesting to find ways in which digital technologies change people’s behaviors. There are many academic and practical deployments of digital technologies in the environmental sector, health applications, and marketing. The use of digital interventions to promote behavior change is not a new paradigm, but further research on practical and acceptable ways of using digital appliances for habit breaking and change is needed. This paper successfully follows this notion, and the authors present a new framework for digital behavior change.

Although behavior change is strongly individualized, Pinder et al. present the habit alteration model (HAM), a tool that combines dual process theory with modern habit theory and goal setting theory in order to shape an adaptable digital environment for habit change. The HAM is in fact a graphical simplification of external and internal impacts on habitual and nonhabitual behavior, providing a platform for a habit-targeting digital behavior change intervention mechanism. It is true that behavior, including habits, is part of a whole psychological system and does not exist in isolation. Digital interventions will be successful if they are tailored to individuals’ habits. Based on behavioral science and digital psychology, the authors explain fundamental principles and issues of behavior, including conscious and nonconscious habits, helping readers better understand the scope and issues of digital behavior change interventions. With such explanations of basic terms, the overall model design process is more readable. Furthermore, the HAM may also trigger further research in digital behavior change interventions, especially when we are speaking about habit alternation (breaking and forming habits). It is interesting how HAM uses a graphical net of principles based on theory-driven axioms that differs from most graphical nets used in modern psychology.

A significant notion from the authors relies on dual process theory’s “two distinct sets of processes”: nonconscious, for example, habits (type 1); and conscious, for example, behavioral intentions (type 2). Adding modern habit theory and goal setting theory, these theories form the HAM used for targeting habits based on principles such as understanding target behaviors, context, tailoring, and ethics. Although these principles are used in most digital behavior change intervention systems, the authors found that habit-targeting digital behavior change intervention systems should consist of yet another principle: interventions should adapt to individual users. As the authors state, behavior change interventions using technologies for ubiquitous and wearable computing are difficult to evaluate. This notion guides the HAM design. Hence, the authors expand this research with a review of digital psychology, and in discussing theoretical gaps in the HAM they make a valuable contribution to the literature. Recommended reading.

Reviewer:  F. J. Ruzic Review #: CR146255 (1901-0004)
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