That fancy phone in your pocket might be smart enough to detect whether you’re depressed, according to researchers at Northwestern University in Chicago.
Your smartphone can track the amount of time you’re using the phone to check your e-mail, Facebook and other apps, and can also track how many locations you visit every day through its GPS feature, according to the small study from researchers at Northwestern’s Feinberg School of Medicine.
How your phone could detect your mood
Researchers followed 28 adults ““ 20 women and eight men, with an average age of 29 ““ for two weeks, and tracked their phone usage and GPS data. The GPS data reported every five minutes.
The more time a subject spent on his or her phone, the more likely that person was to be depressed, said clinical psychologist David Mohr. He led the study and also directs the university’s Center for Behavioral Intervention Technologies.
On average, depressed individuals used their smartphones for about 68 minutes per day, while non-depressed individuals used them for about 17 minutes, according to the study. It was published July 15 in the Journal of Medical Internet Research.
Spending most of your time at home or in only one or two locations away from home is a sign of depression. Having a less regimented schedule every day ““ because of unemployment or illness or working at different times every day ““ also contributes to depression, researchers said in a university news release.
But, is it accurate?
Based on the phone sensor data, Northwestern scientists could identify people with depressive symptoms with 87 percent accuracy.
“The significance of this is we can detect if a person has depressive symptoms and the severity of those symptoms without asking them any questions,” said senior author David Mohr, director of the Center for Behavioral Intervention Technologies at Northwestern University Feinberg School of Medicine. “We now have an objective measure of behavior related to depression. And we’re detecting it passively. Phones can provide data unobtrusively and with no effort on the part of the user.”
Ultimately, the research could help fuel the development of apps that could help users get into treatment more quickly for their depression, Mohr said.
The smart phone data was more reliable in detecting depression than daily questions participants answered about how sad they were feeling on a scale of 1 to 10. Their answers may be rote and often are not reliable, said lead author Sohrob Saeb, a postdoctoral fellow and computer scientist in preventive medicine at Feinberg.
“The data showing depressed people tended not to go many places reflect the loss of motivation seen in depression,” said Mohr, who is a clinical psychologist and professor of preventive medicine at Feinberg. “When people are depressed, they tend to withdraw and don’t have the motivation or energy to go out and do things.”
While the phone usage data didn’t identify how people were using their phones, Mohr suspects people who spent the most time on them were surfing the web or playing games, rather than talking to friends.
“People are likely, when on their phones, to avoid thinking about things that are troubling, painful feelings or difficult relationships,” Mohr said. “It’s an avoidance behavior we see in depression.”
Putting an end to depression?
Researchers hope to passively detect depression and different levels of emotional states related to depression, Saeb said. The information ultimately could be used to monitor people who are at risk of depression to, perhaps, offer them interventions if the sensor detected depression or to deliver the information to their clinicians.
“We will see if we can reduce symptoms of depression by encouraging people to visit more locations throughout the day, have a more regular routine, spend more time in a variety of places or reduce mobile phone use,” Saeb said.
