Rising suicide rates in the US are disproportionately affecting 10-24 year-olds, with suicide as the second leading cause of death after unintentional injuries. It’s a complex and multifaceted topic, and one that leaves those whose lives are impacted wondering what they could have done differently, to recognize the signs and intervene.
Researchers are fast at work figuring out whether a machine learning algorithm might be able to use data from an individual’s mobile device to assess risk and predict an imminent suicide attempt – before there may even be any outward signs. This work is part of the Mobile Assessment for the Prediction of Suicide (MAPS) study, involving 50 teenagers in New York and Pennsylvania. If successful, the effort could lead to a viable solution to an increasingly troubling societal problem.
Why It’s Hot
We’re just scratching the surface of the treasure trove of insights that might be buried in the mountains of data we’re all generating every day. Our ability to understand people more deeply, without relying on “new” sources of data, will have implications for the experiences brands and marketers deliver.