Supporting self-experimentation of behavior change strategies

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Description
Desirable outcomes such as health and wellbeing are tightly linked to people’s behaviors, thus inspiring research on technologies that support productively changing those behaviors. Many behavior change technologies are designed by Human-Computer Interaction experts, but this approach makes it difficult

Desirable outcomes such as health and wellbeing are tightly linked to people’s behaviors, thus inspiring research on technologies that support productively changing those behaviors. Many behavior change technologies are designed by Human-Computer Interaction experts, but this approach makes it difficult to personalize support to each user’s unique goals and needs. As an alternative to the provision of expert-developed pre-fabricated behavior change solutions, the present study aims to empower users’ self-experimentation for behavior change. To this end, two levels of supports were explored. First, the provision of interactive digital materials to support users’ creation of behavioral plans was developed. In the initial step, a tutorial for self-experimentation for behavior change that was fully scripted with images in succession was created. The tutorial focuses on facilitating users’ learning and applying behavior change techniques. Second, users were equipped with a tool to support their implementation of context-aware just-in-time interventions. This tool enables prototyping of sensor-based responsive systems for home environments, integrating simple sensors (two-state magnetic sensors, etc.) and media event components (wireless sound, etc.).

To evaluate the effectiveness of these two approaches, a between-subject trial comparing the approaches to a sleep education control was conducted with 27 participants over 7 weeks. Although results did not reveal significant difference in sleep quality improvement between the conditions, trends indicating greater effectiveness in the two treatment groups were observed. Analysis of the plans participants created and their revision performance also indicated that the two treatment groups developed more specific and personalized plans compared with the control group.
Date Created
2016
Agent