We have previously written about Breathalyzer-style tests that cops may one day be able to use in the event that they suspect a person to be driving under the influence of marijuana. But what if there was an app which could let users carry out a quick self-assessment to find out just how impaired they are after an evening with the wacky ‘baccy? That is what researchers at the University of Chicago claim to have created with an in-development mobile application called, subtly, “Am I Stoned?”
“We have developed an initial prototype of a phone application that measures THC-induced cognitive and psychomotor impairments,” Elisa Pabon, a doctoral candidate at the University of Chicago’s Pritzker School of Medicine, told Digital Trends. “The application is comprised of four tasks, which span a variety of cognitive and psychomotor skills. These were based on prior findings stating THC consumption led to impairments or changes in attention, reaction time, and various facets of memory.”
The idea of the app is to gauge a baseline sober and under-the-influence performance from users, thereby allowing the app to work out an accurate personalized impairment measure. Am I Stoned? comprises a variety of minigame-style activities, including a test of how quickly you can tap the screen, a memory game, and a test that requires you to shake your smartphone whenever a blue dot appears on the display.
The app’s efficacy has been measured by its creators on 24 irregular marijuana users, who each took a capsule containing either a placebo or 7.5 or 15 milligrams of tetrahydrocannabinol (THC), the cannabis ingredient which causes intoxication. The findings were promising, although the researchers still say that work needs to be done before the finished product is released to the public — if, indeed, this happens at all.
“[The app still] needs to be optimized and continually tested in order to confirm its validity and reliability,” Pabon continued. “I hope it is a first step toward developing discrete and reliable measure of THC-induced impairments. This would prove immensely beneficial for users who want to understand the level of impairment they are experiencing and how it may differ from their own perception.”
