Ellen McGinnis and Ryan McGinnis of the University of Vermont lead researchers on a study published in PLOS ONE that showed wearable sensors could detect hidden anxiety and depression in young children. (Credit: Josh Brown)

Anxiety and depression are surprisingly common among young children. But it can be hard to detect these conditions, known as “internalizing disorders,” because the symptoms are so inward-facing that parents, teachers and doctors often fail to notice them.

The issue isn’t insignificant. If left untreated, children with internalizing disorders are at greater risk of substance abuse and suicide later in life.

So, researchers have developed a tool that could help screen children for internalizing disorders to catch them early enough to be treated. The team used a “mood induction task,” a common research method designed to elicit specific behaviors and feelings such as anxiety. The researchers tested 63 children, some of whom were known to have internalizing disorders.

Children were led into a dimly lit room, while the facilitator gave scripted statements to build anticipation, such as “I have something to show you” and “Let’s be quiet so it doesn’t wake up.” At the back of the room was a covered terrarium, which the facilitator quickly uncovered, then pulled out a fake snake. The children were then reassured by the facilitator and allowed to play with the snake.

The algorithm determined that movement during the first phase of the task, before the snake was revealed, was the most indicative of potential psychopathology. Children with internalizing disorders tended to turn away from the potential threat more than the control group. It also picked up on subtle variations in the way the children turned that helped distinguish between the two groups.

This lines up well with what was expected from psychological theory. Children with internalizing disorders would be expected to show more anticipatory anxiety, and the turning-away behavior is the kind of thing that human observers would code as a negative reaction when scoring the video. The advantage is that the sensors and algorithm work much faster.

That opens the door to using technology like this to help screen large numbers of children to identify those that would benefit from further psychological help. Failing to catch these conditions early can be a problem for kids as they grow up says Muzik. “If anxiety symptoms do not get detected early in life, they might develop into a full-blown anxiety and mood disorder,” she says, with subsequently increased risk for substance abuse and suicide.

The next step will be to refine the algorithm and develop additional tests to analyze voice data and other information that will allow the technology to distinguish between anxiety and depression. The ultimate goal is to develop a battery of assessments that could be used in schools or doctors’ offices to screen children as part of their routine developmental assessments.