There's an idea out there of what a drug-addled teen is supposed to look like: impulsive, unconscientious, smart, perhaps -- but not the most engaged.
While personality traits like that could signal danger, not every adolescent who fits that description becomes a problem drug user. So how do you tell who's who?
There's no perfect answer, but researchers report in Nature Communications that they've found a way to improve our predictions -- using brain scans that can tell, in a manner of speaking, who's bored by the promise of easy money, even when the kids themselves might not realize it.
According to a recent article in ScienceDaily, that conclusion grew out of a collaboration between a professor of psychology at Stanford, and a professor of medicine at Universitätsklinikum Hamburg Eppendorf. With support from the Stanford Neurosciences Institute's NeuroChoice program, the pair started sorting through an intriguing dataset covering, among other things, 144 European adolescents who scored high on a test of what's called novelty seeking -- roughly, the sorts of personality traits that might indicate a kid is at risk for drug or alcohol abuse.
Analyzing that data, Knutson and Büchel found they could correctly predict whether youngsters would go on to abuse drugs about two-thirds of the time based on how their brains responded to anticipating rewards. This is a substantial improvement over behavioral and personality measures, which correctly distinguished future drug abusers from other novelty-seeking 14-year-olds about 55 percent of the time, only a little better than chance.
"This is just a first step toward something more useful," Knutson said. "Ultimately the goal -- and maybe this is pie in the sky -- is to do clinical diagnosis on individual patients" in the hope that doctors could stop drug abuse before it starts, he said.
Knutson said the study first needs to be replicated, and he hopes to follow the kids to see how they do further down the line. Eventually, he said, he may be able not just to predict drug abuse, but also better understand it. "My hope is the signal isn't just predictive, but also informative with respect to interventions."
Story Source: Materials provided by Stanford University.