Smartphones Can Predict Depression? Find Out How

smart-phoneMore and more of us can be considered “heavy” smartphone users; we carry them everywhere (including the bathroom!) and refer to them hundreds of times a day.  In fact, according to the Pew Research Center 64% of American adults own a smartphone, 44% of cell owners admit to sleeping with their phone next to their bed, and 29% of cell owners describe their phone as “something they can’t imagine living without.”

And most of us now understand that our smartphones collect data about our behavior through apps and other functions, like location, that can be used for targeted marketing purposes by brands, services and corporations.

But we may not have realized that some of this data can also infer other things about us from our usage and behavior.  New research is pointing towards how our phone data could potentially be used in the treatment of mental health.  A study done at Northwestern University Feinberg School of Medicine and released in the Journal of Medical Internet Research showed that phone data could predict depressive symptoms in its user with 87% accuracy.

The small study, led by David Mohr, PhD, director of the Center for Behavioral Intervention Technologies at Northwestern University Feinberg School of Medicine, recruited 28 people ages 19-58 from Craigslist and added monitoring software to their smartphones to track location and other usage.  Participants answered a standardized questionnaire at the beginning of the study to measure depressive symptoms with the results showing half had symptoms and half did not.  The study followed these participants for two weeks while the software tracked their GPS location every five minutes and asked users questions about their mood multiple times daily.

What the research revealed was not only a strong correlation between the data and depression, but that the data was better at predicting depression than the users own answers to the daily questions.  It also showed that users with higher depression indicators spent more time on their phone each day as well as more time at home.  Mohr, who has studied Depression for 20 years, suggested this may be because a depressed user uses the phone as a “distraction” from daily stressors as an avoidant behavior often seen in depression.

While this is preliminary research that needs further study, Mohr and his team hope to add to the number of sensors in the tracking software to help spot depressive behavior  more quickly, without the user having to engage.

What do you think, is this type of technology the future of mental health evaluation and diagnosis?

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