Center for Strategic Communication

How do you solve a problem like targeted violence? Photo: West Midlands Police/Flickr

In the years to come, a top group of military scientists believe, the Pentagon may be able to use genomics and bio-markers to spot when a soldier is about to snap. But that moment is not in the immediate future. So, for now, the only option is to try to prevent these troops from reaching the breaking point, rather than predicting when that point will come.

After Nidal Hasan, a U.S. Army Major, shot and killed 13 people in Fort Hood, Texas in November of 2009, the Defense Science Board (DSB) commissioned a task force. They were told to research and produce a report on how to predict violent behavior. The hope was that they might be able to propose ways to anticipate if military personnel in the future were about to go rogue. That report was recently released online. But the task force says the hope of predicting violent behavior is still far off.

The DSB task force report outlines what it calls a “stress response curve,” where performance is plotted on a graph against stress. As stress increases so does individual performance – believe it or not but people actually do perform better under pressure – up to a point.

Eventually, as stress continues to rise, an individual’s performance plateaus until it reaches a “tipping point.” Here performance crashes and the individual is at risk of losing it and exerting extreme, out of the ordinary behavior. Shooting into a crowd, for example.

The report says that “serious cases of unacceptable behavior could probably have been avoided had important data not been “stovepiped” or had leaders and teammates been better educated on behavioral precursors.”

The Task Force has proposed ways of increasing an individual’s resiliency, which it defines as “the ability to recover from, or easily adjust to, misfortune or chance, especially unanticipated change.” By increasing the resiliency of a person, their personal tipping point is pushed further along the stress response curve, making it less likely to be reached. In this way the Task Force hopes to prevent a potential violent outburst.

One of the Task Force’s recommendations is to collect and analyze data. Both from previous case studies of targeted violent behavior (such as Nidal Hasan) and from personnel files. That way it might know what behavioral markers and precursors to targeted violence to be on the look out for. If the two data types could be merged then “red flag” cases could be identified. They also suggest that resilience training should be increased and assessment programs put in place to keep tabs on things like sleep deprivation, which push people towards their tipping point.

The implementation of so called “bio-marker measurement programs” has also been endorsed by the Task Force to add what it calls “hard data” to the picture. The idea would be to evaluate physiological measures, such as concentrations of stress hormones. They also stipulate that as science improves they would like to see similar programs to monitor neurological and genetic bio-markers, but for the moment they recommend that the bulk of R&D should focus on physiological markers.

The knowledge that could be gained from such research programs may not only help to flag up an individual that may be about to reach his or her tipping but also help with training, says the Task Force. “Rather than trying to predict negative outcomes, and then intervene, this information may allow more optimal structural or contextual changes, training regimens (including resilience training,) or other policies and/or programs that could be applied more broadly and improve the performance of all personnel.”

But no matter how you look at it, whether the data will be used to help to de-stress and improve the working environment or whether the data will be used to red flag you as risky soldier, it’s still going to involve a lot of keeping tabs on people, many of which may be none too happy at the prospect.

[DSB: DOD Should Conduct ‘Modest’ Research On Violent Behavior] via [IWP]