Current Research

  • Co-design self-monitoring technology with healthcare provider

    This study explores the information needs and design insights of personal tracking devices capable of overseeing uncontrolled chronic conditions. We co-design with healthcare providers from community-based health center to understand how technologies could be designed to facilitate capturing, representing, and managing various uncontrolled chronic conditions.
    Research Methods: Co-design, Interview, Qualitative Analysis

  • Designing tool for critical reflection on mood

    This study seeks to understand if digital tools can promote critical reflection . Critical reflection is classified as transformative reflection which is situated, and cyclic, using multiple perspectives and considering aspects beyond the current context [1, 2]. We conducted a field deployment of two different interactive prototypes that ask people to track their moods .
    Research Methods: Survey (closed- and open-ended), Interview, Qualitative Analysis

    [1] D. Eisenberg, J. Hunt, N. Speer, and K. Zivin, “Mental Health Service Utilization Among College Students in the United States,”The Journal of Nervous and Mental Disease, vol. 199, no. 5, pp. 301–308, May 2011, doi10.1097/NMD.0b013e3182175123.
    [2] R. Fleck and G. Fitzpatrick, “Reflecting on reflection: Framing a design landscape,” Jan. 2010, pp. 216–223. doi: 10.1145/1952222.1952269.

Past Research

  • Current Landscape of Self-Reflection for Mental Health Interventions


    In recent years, we have seen a growing prevalence of mental health concerns, resulting in a need for more research on scalable, effective interventions. Self-reflection is an important, evidence-based skill that can improve mental health. In response to the growing demand for digital interventions that support self-reflection and mental health, we review how self-reflection has been conceptualized in HCI research thus far. Using a scoping review, we look at prior work designing and evaluating self-reflection for mental health (SRMH) interventions. We found no uniform definition of “self-reflection,” so we present a five-component definition that allows for a flexible definition. This five- component definition gives researchers and designers the ability to communicate their ideas using a systematic approach, compare components of SRMH interventions, and uncover novel interventions. We present recommendations and avenues of research that will standardized and promote innovation within SRMH interventions and digital mental health tools.
    Research Methods: Systematic Review, Grounded Theory, Qualitative Analysis

    This paper is currently under review.

  • Predict the stress level of non-responding day during pregnancy


    In this study, we analyzed EMA and physiological data collected from 100 pregnant women over 12 weeks. Through categorizing the stress levels and visualizing the changes in stress levels among participants in the control group and intervention group, we used machine learning algorithms to predict the stress level of non-responding days.
    Research Methods: Survey, Quantitative Analysis

  • An Agent-Based Modeling Approach for Informing the U.S. Plastic Waste Management Process


    Recycling is one of the most significant issues in the waste management system. As the use and demand for plastics increase every year, finding efficient and environment-friendly solutions to handle the plastics in the plastic waste management system gets more challenging. There are economic, environmental, and educational factors affecting plastic waste management. This paper investigates the effects of educational campaigns and system-wide improvement. For this, we used an Agent-Based Modeling and Simulation approach in the NetLogo environment. We provided various scenarios in the current plastics waste life cycle using a real dataset to validate our model, which was from the American Chemistry Council and the National Association for PET Container Resources from 2018. We found that education, technology, and infrastructure changes should be considered holistically to overcome this problem at a system level.
    Research Methods: Modeling and Simulation, Qualitative Analysis

    Huang, Y., Karabiyik, T., Madamanchi, A., & Magana, A.J. “An Agent-Based Modeling Approach for Informing the U.S. Plastic Waste Management Process,” in International Journal on Advances in Software, 2021, p. 65 to 71.

    Our poster won the second-runner at the meeting of Future Work and Learning 2021, West Lafayette, IN