Adam Grabell was recently awarded a seed grant of $15,000, with an additional $10,000 in facilities costs, from the Institute for Applied Life Sciences’ (IALS) Center for Personalized Health Monitoring to support a study of preschool children’s tantrums.
Collaborating with Jeremy Gummeson of the College of Information and Computer Sciences, the researchers plan to use a combination of wearable health monitoring devices to track preschool children’s tantrums in their homes over one month. Grabell, who studies emotion regulation in children and its relation to psychopathology, explains that tantrums are a common behavior exhibited in early childhood that caregivers nevertheless report to be a significantly distressing parenting challenge. At the same time, tantrums may signal an increased risk for persistent mental illness or indicate markers of family dysfunction and increased likelihood of child abuse. Despite the urgency to identify mental illness early in the lifespan, “it is currently very difficult to discriminate tantrums indicating a child is at risk for a disorder from tantrums that are normative early in life.”
Wearable health devices are emerging as a potentially powerful strategy for identifying and treating pediatric health problems, Gummeson and Grabell point out. They will use custom 3D printing capabilities at IALS to develop wristbands for use in this application. They also plan to collaborate with Spire Health, a healthcare company that makes small, non-invasive, continuous respiration sensing tags that adhere to clothing known as Spire Health Tags. Using these devices, the research team will collect continuous longitudinal recordings of child tantrums from the wearable devices to explore if it’s possible to more accurately identify tantrums that are precursors to mental illness.
They hope to contribute to developing more effective, home-based treatments for early childhood psychopathology, Grabell says. “If certain characteristics of childhood tantrums are found to be precursors to mental illness, these findings could potentially move the field toward a future of computer-assisted, home-based, early mental health detection and treatment.”