Data gathered by a smartphone’s sensors might one day be able to identify whether someone suffers from symptoms of depression, a study published today in the Journal of Medical Internet Research shows. By tracking average daily phone use and recording GPS data, scientists say they were able to identify people with depressive symptoms with a high level of accuracy. Unfortunately, the small size of the study and missing data points suggests that this method isn’t exactly ready for prime time.
Major depression is one of the most common mental health issues in the US. In 2012, about 16 million adults — or 6.9 percent of all US adults — experienced at least one major depressive episode. That’s why finding new ways of keeping track of patients is so important. Harnessing a phone’s sensors could help identify people who are at risk for depression, and ensure that patients receive treatments more promptly, says David Mohr, a behavioral scientist at Northwestern University and co-author of the study.
In the study, the researchers used a Craigslist ad to recruit 40 people between the ages of 19 and 58. The researchers asked the participants to fill out a common depression survey. Then, they tracked the participants’ movements and phone usage for a period of two weeks through an Android app called “Purple Robot.”
People who suffer from depression tend to frequent fewer locations than people who don’t, and from a social standpoint, they tend to be more withdrawn. So, the researchers analyzed the data of 28 participants to see if there was a relationship between high levels of phone usage — a proxy for being withdrawn — or GPS data, and depression. (Because of certain technical and adherence issues, 12 participants couldn’t be included in the study.)
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