Triggr Health App Aims to Treat Addiction


May 12, 2017

The Triggr Health app uses a lot of the same principles as other modern applications. Generally speaking, it uses data to quantify our behavior, and then based on the findings, uses different techniques to modify this behavior towards a specific goal.

To list a few examples, a Fitbit may help you track calories or reach a step goal, or an app called “Moment” can determine which apps on your phone are used the most often. Triggr may have similar functions, but it is used to instead connect people suffering from drug addiction with the help they need to avoid relapse.


The Triggr Health App


Triggr is far from the first app attempting to tackle substance abuse issues, but it does approach the problem in a new way. While other addiction apps may include inspirational quotes, directions to rehab facilities, or even hypnosis, Triggr records your patterns of behavior to preemptively intervene when warning signs of a relapse begin to show themselves.

Triggr gathers data on your screen engagement, texting habits, phone logs, sleep patterns, and current location and supplements this primary information with individual answers provided to Triggr’s support team to identify when a relapse is about to occur. Furthermore, Triggr is also on the lookout for trigger words like “crave” or “stress” as another indication that the user is on the verge.

The app is not perfect, and there are certainly times when the staff responds to a false alarm. However, more often than not, Triggr intervenes at just the right time. Users are often on the way to their drug dealer’s residence or waiting outside a bar and considering entering.


Machine Learning

Triggr is an excellent example of machine learning. As more users continue to download the app and submit data to the ever-growing pool, the app becomes smarter. In 2016, Triggr was able to successfully predict a relapse scenario 85% of the time, and only a year later, that accuracy is up to 92%. The key is to establish an understood “routine” and search for any deviations in it. According to Triggr’s Data Scientist, John Santerre, the behavior preceding and leading to a relapse often has little to do with the substance at all. Rather, disruptions to an established routine large or small are enough to raise the risk of relapse for a few days.


Finding the Right Messaging

When a relapse event actually occurs and the Triggr staff sends the user a message to intervene, what they say is very important. The content of the response could mean the difference between a relapse and another day clean. Triggr further leverages data collected from all of their app customers by using it to determine what type of response the app user is most likely to respond to. Based on their history and preferences, a member of the recovery team is alerted as to the best way to respond.


Capturing Symptoms in the Wild

Jukka-Pekka Onnela, a professor of biostatistics at the T.H. Chan School of Public Heath, notes that the way in which Triggr collects its information is very different than research of the past. Our understanding of addiction and symptoms largely comes from observations in a laboratory. The power of the Triggr Health app is that it collects data from real users who are actually experiencing these symptoms in real time in the real world. It’s like “capturing symptoms in the wild,” and that can lead to a much greater understanding of addictions and how to overcome it.

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