- Healthcare providers and parents may someday be able to identify anxiety and depression in young children by tracking their activity with mHealth wearables.
Researchers at the University of Vermont and the University of Michigan have reported an 81 percent success rate using connected health devices and AI technology to detect “internalizing disorders” in children between the ages of 3 and 7. The results of a study conducted on some 63 children were recently reported in the journal PLOS ONE.
“The results … demonstrate that, when paired with machine learning, 20 seconds of wearable sensor data extracted from a fear induction task can be used to identify young children with internalizing disorders with a high level of accuracy, sensitivity, and specificity,” the researchers concluded. “These results point toward the future use of this approach for screening children for internalizing disorders.”
The study points to the value of wearables in care management and coordination for children with a wide variety of mental and behavioral health issues who may not be able to identify or describe their issues to providers. According to the researchers, roughly 20 percent of young children are diagnosed with these internalizing disorders.
“Because of the scale of the problem, this begs for a screening technology to identify kids early enough so they can be directed to the care they need,” Ryan McGinnis, a biomedical engineer at the University of Vermont and one of the study’s authors, said in a release issued by UVM.
“Children with anxiety disorders need an increased level of psychological care and intervention,” added Ellen McGinnis, a clinical psychologist at UVM and fellow researcher. “Our paper suggests that this instrumented mood induction task can help us identify those kids and get them to the services they need.”
According to the study, the children were tested with a “mood induction task,” a common research method designed to elicit specific behaviors and feelings such as anxiety. Traditionally, trained healthcare providers would watch children performing the task and make a diagnosis based on the child’s behavior and speech.
Using a mobile health device and AI technology, researchers were able to make that diagnosis in 20 seconds.
“Something that we usually do with weeks of training and months of coding can be done in a few minutes of processing with these instruments,” Ellen McGinnis said.
Maria Muzik, a member of the University of Michigan’s Department of Psychiatry who participated in the study, said the mHealth platform holds promise in helping healthcare providers more easily identify children with internalizing disorders. This, in turn, would enable these children to begin treatment much earlier.
“If anxiety symptoms do not get detected early in life, they might develop into a full-blown anxiety and mood disorder,” she said in the UVM release.
The next step, she added, is developing a more extensive mHealth platform that could be used in doctor’s offices, schools and other locations where children receive regular developmental screening.