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Effective Measurement and Intervention of Adolescent Stress Levels with Social Robots

Author: Raida Karim Faculty Mentor: Dr. Maya Cakmak Department: Computer Science & Engineering Institution: University of Washington Institutional Address with Zip or Postal code: Seattle, WA 98195, USA

Adolescents are victims of high levels of stress in their lives that usually result from school, relationships, and family life. Approximately 27% of US teens report very high levels of daily stress, and 31% report to feel overwhelmed from negative stress. Reportedly, school stress is the biggest source of stress for teens worldwide. The data of fluctuating stress levels throughout the day can facilitate formulating effective stress measurement and reduction techniques for teens, which is imperative to support this vulnerable population. Today’s teens are the first generation to spend a lifetime living and increasingly experiencing human-computer interaction. According to far-seeing scholars, it is critically necessary to innovate, design, and prototype technologies enhancing the connection between humans and robots targeting next generation and post humanism. A wide array of research in human-robot interaction (HRI) focuses on specific age groups, where assistive technologies are mostly used to help the populations of elderly people and young children. However, very little research has been conducted to address teen-stress, or teen-robot interaction. My research in Project EMAR (Ecological Momentary Assessment Robot) conducts therapeutic activities for teens with a social robot EMAR (see Fig.1) focusing specifically on interventions for Dialectic Behavioral Therapy (DBT), and Acceptance and Commitment Therapy (ACT). Ecological Momentary Assessment (EMA) data is traditionally collected by answering questions on paper, cell phone or tablet. Although the process is straightforward, it is not necessarily engaging. Enhancing that engagement, my research focuses on making EMAR interact with teens on an intimate level to collect data measuring moods and stress with the EMA technique. Using virtual social robots to collect and evaluate these data, and to suggest appropriate therapeutic techniques can come invaluably handy in the COVID-19 pandemic circumstances to intervene higher stress, low mood, and critical mental health in home-stuck adolescents worldwide.




Additional Abstract Information

Presenter: Raida Karim

Institution: University of Washington

Type: Poster

Subject: Computer Science

Status: Approved


Time and Location

Session: Poster 5
Date/Time: Tue 12:30pm-1:30pm
Session Number: 4061