BURLINGTON, Vt. — It can be difficult for many parents to decide that their moody child isn’t just displaying typical teenage angst, and that there’s a more serious problem that needs professional attention. Now new technology could help make things easier. A wearable device developed as a mental health screening method for children has been found to detect anxiety and depression in youngsters with high accuracy in a matter of seconds.
Symptoms of anxiety and depression are being found more commonly in young children than ever before. According to some research, as many as 20% of children suffer from at least one of these conditions, sometimes beginning in preschool. It can be difficult for parents and professionals to detect these so-called “internalizing disorders” because the symptoms are often hidden.
“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,” says lead researcher Ryan McGinnis, a biomedical engineer at the University of Vermont, in a release.
McGinnis and co-author Ellen McGinnis, a clinical psychologist at the university, used a “mood induction task,” commonly used in this type of research to provoke specific behaviors and feelings, in this case, anxiety. The pair tested 63 children, including some who had documented internalizing disorders.
Participants were provided scripted statements in a dimly lit room. The statements were designed to start anticipation reactions, such as, “I have something to show you,” and, “Let’s be quiet so it doesn’t wake up.” The researchers placed a covered terrarium in the back of the room, which was uncovered and revealed to contain a fake snake. The children were reassured that the snake wasn’t real, and even allowed to play with it.
The authors monitored the children’s movement with a wearable motion sensor and a machine-learning algorithm to distinguish between children with anxiety or depression and those without. The algorithm identified differences in the movement of the two groups after processing the movement data.
Researchers found the algorithm could identify children with internalizing disorders with 81% accuracy, a great improvement over the standard parent questionnaire. They hope experts can use this technology to screen large numbers of children for internalizing disorders in the future.
“Children with anxiety disorders need an increased level of psychological care and intervention. Our paper suggests that this instrumented mood induction task can help us identify those kids and get them to the services they need,” says Ellen McGinnis.
The research was published in the journal PLOS One.