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Award ID contains: 1814132

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  1. ; ; ; ; ; ; ; (, SIGCHI bulletin)
    Given the prevalence and adverse impact of anxiety, there is considerable interest in using technology to regulate anxiety. Evaluating the efficacy of such technology in terms of both the average effect (the intervention success) and the heterogeneous effect (for whom and in what context the intervention was effective) is of paramount importance. In this paper, we demonstrate the efficacy of PIV, a personalized breathing pacer, in reducing anxiety in the presence of a cognitive stressor. This is the first mixed-design study of a vibrotactile affect regulation technology which accounts for individual differences and user-technology engagement in relation to the technology’s efficacy in the presence of a specific stressor. Guidelines in this paper can be applied for designing and evaluating other affect regulation technologies 
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  2. ; ; ; ; ; ; ; ; ; (, ACM Transactions on Computer-Human Interaction)
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  3. ; ; ; ; ; ; ; (, CHI EA '18 Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems)
    Emotion regulation in the wild (ER-in-the-wild) is an important grand challenge problem of increasing focus, and is hard to approach effectively with point solutions. We provide HCI researchers and designers thinking about ER- in-the-wild with an ER-in-the-wild system architecture derived from mHealth, the Emotion Regulation Process Model (PM), and a circular biofeedback model that can be used when designing an ER system. Our work is based on literature reviews of and collaborations with experts from the domains of wearables, emotion regulation, haptics and biofeedback (WEHAB) as well as systems. In addition to providing a generic model for ER-in-the-Wild, the system architecture presented in this paper explains different kinds of emotion regulatory interventions and their characteristics. 
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