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Durkheim Project leverages big data to prevent veteran suicides

Thor Olavsrud | Aug. 29, 2013
In partnership with social media networks and the U.S. Department of Veteran Affairs, a nonprofit research project is seeking to show that predictive analytics can identify U.S. veterans of Iraq and Afghanistan who are suicidal and need help.

Suicide has grown to epidemic proportions among U.S. veterans of Iraq and Afghanistan, and the Pentagon and U.S. Department of Veterans Affairs is hoping that social media and big data can help them identify at-risk veterans and get them the care they need.

Last year, more active-duty servicemen and servicewomen took their own lives than were killed combat. In February 2013, the Iraq and Afghanistan Veterans of America (IAVA) conducted its 2013 Member Survey of 4,104 veterans of Iraq and Afghanistan.

IAVA reported that 30 percent of respondents had considered taking their own lives, 45 percent said knew an Iraq or Afghanistan veteran who had attempted suicide and 37 percent knew an Iraq or Afghanistan veteran who had committed suicide. And 50 percent of respondents said someone close to them had suggested they seek care for a mental health injury.

Identifying people who are at risk of committing suicide is a tricky thing. Often, the people who are the most in need of help are the least likely to seek it. But Chris Poulin, principal partner of predictive analytics specialist Patterns and Predictions, started wondering: What if he took the tools for event-driven risk analytics used by Wall Street financial firms and applied them to the problem?

Can Facebook and Twitter Activity Predict Suicide Attempts?
The idea was deceptively simple. A veteran in distress may not be able to communicate that distress verbally. But they do frequently reach out via social media: Facebook posts, tweets and so on. If you can model key textual indicators of suicidality and analyze social media streams in real-time, you can potentially identify at-risk individuals and intervene before they harm themselves.

In 2011, with funding from the Defense Advanced Research Agency (DARPA) Poulin set out to determine whether his idea had legs by forming the non-profit Durkheim Project. He brought together a multidisiciplinary team of artificial intelligence (machine learning) and medical experts (psychiatrists) from Dartmouth Engineering, Dartmouth Medical School and the U.S. Veterans Administration dedicated to applied research on predictive suicide risk.

The project was named in honor of sociologist Emile Durkheim, who in 1897 published the paper Suicide, which defined early text analysis for suicide risk and provided a framework of theoretical explanations relating to societal disconnection.

Phase 1 of the Durkheim Project's research consisted of building a predictive model. Poulin (who at the time was co-director of the Dartmouth College Metalearning Working Group at Dartmouth Thayer School of Engineering) collaborated with researchers Paul Thompson, Thomas McAllister, MD and Laura Flashman, PhD, from the Geisel School of Medicine at Dartmouth and Brian Shiner, MD and Vince Watts, MD from the U.S. Department of Veterans Affairs.


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