Startup uses smartphone data to predict mental health crises

Smartphone predicts mental health crises

While mental health care in the U.S. needs several major upgrades, one of the biggest challenges is identifying people in need of care. According to the Treatment Advocacy Center, about 7.9 million adults have been diagnosed with a severe mental illness. However, an estimated 3.8 million people do not receive treatment for their mental conditions. This leads to approximately 13,000 suicides and 400,000 newly incarcerated mentally ill prisoners every year.

Identifying when people are in danger of a mental health episode was the primary goal of Anmol Madan​, CEO and co-founder of, a behavioral health analytics startup that recently released a smartphone app that can predict when patients with mental health illnesses are symptomatic, MIT News reported.

Madan developed the app at the Massachusetts of Technology’s world-famous Media Lab. The program uses normal cell phone behaviors like texting and movement to predict when patients are most in need of treatment.

“If someone is depressed, for instance, they isolate themselves, have a hard time getting up to go to school or work, they’re lethargic and don’t like communicating with others the way they typically do,” Madan told MIT News. “Turns out you see those same features change in their mobile-phone sensor data in their movement, features, and interactions with others.”

Madan explained that the app sends message to both patient and health care provider. It might let the user know that he or she texted two fewer people today than yesterday, and enough of these triggers prompts a warning to the HCP. tested the app in a trial at the University of California, Davis, where it was touted as a low cost but effective early screening device for mental health intervention services. Currently, more than 25 health care and academic centers in the U.S. use’s app, with more to come in the future.


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