EAI Endorsed Transactions on Pervasive Health and Technology 18(13): e6

Research Article

Mobile Stress Interventions: Mechanisms and Implications

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  • @ARTICLE{10.4108/eai.28-2-2018.154343,
        author={Luis G Jaimes and Robert Steele},
        title={Mobile Stress Interventions: Mechanisms and Implications},
        journal={EAI Endorsed Transactions on Pervasive Health and Technology},
        volume={18},
        number={13},
        publisher={EAI},
        journal_a={PHAT},
        year={2018},
        month={2},
        keywords={Time Series Forecasting,Mobile Stress Interventions, Ecological Momentary Intervention, Just-in-Time Intervention, Ubiquitous Sensing, Mobile Health},
        doi={10.4108/eai.28-2-2018.154343}
    }
    
  • Luis G Jaimes
    Robert Steele
    Year: 2018
    Mobile Stress Interventions: Mechanisms and Implications
    PHAT
    EAI
    DOI: 10.4108/eai.28-2-2018.154343
Luis G Jaimes1,*, Robert Steele1
  • 1: Florida Polytechnic University, 4700 Research Way, Lakeland, FL 33805, US
*Contact email: ljaimes@floridapoly.edu

Abstract

According to the American Psychological Association, 49% of the U.S. population su ers from chronic, daily stress. Chronic stress also has significant long-term behavioral and physical health consequences, including an increased risk of cardiovascular disease, cancer, anxiety and depression. In this work, we examine how smartphones and mobile sensing can help address the short and long-term consequences of stress. First, we define a conceptual framework for thinking about the interaction between real-time pervasive devices and the real-time physiology of stress. Second, using this framework, we propose a set of guidelines or requirements for pervasive just-in-time intervention (JITI) systems. Third, based on these guidelines, we specify a three-layer software/hardware architecture to support just-in-time interventions for stress. Several themes emerge from this discussion, including the need for robust and accurate context-sensitive forecasting of future stress. Fourthly we describe our experiments and results demonstrating the feasibility of forecasting future stress from current measurements and the e ectiveness of the intervention management approach. Finally we discuss the broader implications of mobile-based stress interventions. Whilst this work focuses on chronic stress, we believe the ideas presented are generalizable to other types of just-in-time pervasive interventions.