Talk of using virtual reality to help the mentally troubled by recreating triggers in a safe environment is not entirely new, but a dean from Tulane University wants to zero in on using that technique to help people with addiction. Patrick Bordnick, the dean of Tulane University’s School of Social Work, has a long history with VR experiments, and now believes that the technology is up to par with his vision. With the help of a startup with experience in this field, called Limbix, Bordnick hopes to be able to recreate situations that trigger cravings in addicts, but while addicts are in perfectly safe environments with professionals monitoring them. Learning how each patient reacts to certain triggers and craving cues can help in understanding how their particular addiction works, and thus how best to treat it. The tool, called Project Delta, is being developed for mobile VR ecosystems like Daydream and Gear VR and should be ready within 6 to 12 months.
The crux of Project Delta lies in putting addicts into exactly the sorts of situations that could make them relapse, in the real world. In one scenario given as an example, an addict is put into a realistic bar, full of convincing motion-captured avatars. The bartender stands in front of a brightly lit shelf of premium liquor, and asks them what they would like to drink. The immense social pressure and exposure in such a scenario would almost surely cause a relapse in a real alcoholic, and it can be quite easy for former alcohol addicts to wind up in a situation just like this, if they have friends or colleagues who still head to bars. When visiting the scenario, a professional psychologist would be on hand to help the addict to deal with their feelings, and analyze what’s going on in their head.
Bordnick is working on a similar program to tackle social issues for people with autism and other disorders that would affect human interaction, called the Quality of Life Project. VR experiments with a similar premise to these two projects have been talked about in the past, especially in the medical field. Clinical depression and stress management have been named as some of the statistically largest possible use cases for this and similar technology.