Addiction does more than destroy individual lives—it destroys communities, friendships, and families as well. In the United States, addiction—in particular, opiate addiction—is growing at an alarming rate and with devastating effects (see HBO’s Documentary Heroin: Cape Cod, U.S.A. to understand just how real the problem is). The most dangerous element of addiction, and the biggest obstacle in preventing addicts from getting clean, is a relapse event.
While the public health system recognizes that opiate addiction and relapse are ubiquitous problems all over the world and that primary treatment and prevention are critical, it remains a fact that relapse is endemic among those who successfully complete treatment; it is also recurrent with successive rounds of treatment.
At the same time there is a scientific and market revolution in biosensors, embedded technology, wearables, and the use of neuroscience-based gaming. Our goal is to harness this innovation to prevent relapse.
The goal of this challenge is to develop technology capable of identifying the point of relapse—the neurological and biological signals (the “craving”) that manifest before the outward signals (solicitation, purchase, and use). By developing technology capable of highlighting the warning signs of relapse, we can better manage and mitigate addiction.
What we want is to help people get off the track before they get hit by the train. We want a technology that acts like a train whistle—a signal that says relapse is just around the corner, take action NOW!
Addiction treatment lacks funding, research, available data, and—most importantly—objectivity.
Society has a nasty reputation of putting the “blame” on the addict instead of the underlying brain chemistry causing the addiction. As a result, what should be treated as a disease gets undeservingly labeled as a conscious choice.
It’s not.
No addict wants to be an addict—they literally can’t help it.
Drugs (from alcohol and nicotine to heroin and cocaine) alter the chemistry of the brain. That chemical alteration makes addicts physically dependent upon the drugs they’re taking. It’s this chemical dependency that’s responsible for pushing addicts away from treatment and into relapse.
Additionally, the effective treatments that do exist are cumbersome, short-term and overly generalized, when they need to be simple, sustainable and specialized to the individual to have permanent efficacy.
Prisons, courtrooms, and short-term hospital beds are not the conduits through which addicts get clean—they are the conduits through which addicts slip into relapse.
We are committed to battling the current problems of addiction by facilitating the development of technology that focuses on relapse prevention. Pioneered by the work of Dr. G. Alan Marlatt, relapse prevention recognizes that relapsing is a process, a process that is driven by both internal and external imbalances.
By developing a technology that can classify and interrupt the process of relapse before physical indicators have manifested, physicians, friends, and family members can stop relapses as soon as (or even before) they start.
This relapse prevention technology will:
The winning solution will both effectively and objectively identify the neurological and biological triggers for relapse, thereby empowering the addict to remain in control of his or her own personal journey in recovery. In doing so, relapse can be managed at its earliest stage, before obvious physical signs have been fully expressed, creating an "early warning system" of sorts.
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The highest scoring team for the Concept Phase will be awarded a prize based on a formal judging process using the judging criteria stated in the challenge guidelines, below. A qualified judging panel will determine the winners.
The winning team of the Addiction Relapse Technology Challenge will propose a three-part solution.
The technology’s three-part solution is explained below. Innovators must complete the Submission Form questions directly related to these three components:
I. Detect Relapse
The winning technology is encouraged to incorporate both neurological and biological indicators to create the most accurate detecting tool for relapse. Once detected, the technology will alert the technological user (in this paper the term ‘user’ will refer to technological user) and his/her support network to provide help.
Teams are tasked to design a consumer-driven solution to monitor neurological and biological signals indicative of early relapse.
There are two known areas of the brain associated with addiction impulse and are predictors of relapse. The first area is the brain’s low inhibitory control network, typically hypo-active, making the addict's desire to say "no" more difficult. The second area is the brain’s reward circuitry where the high risks of certain situations are often ignored for instant gratification. (Reference: Carla Clark interview.) Currently, machinery found mostly in medical offices can monitor brain activity linked to addiction, such as an Functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), and Functional Near-Infrared Spectroscopy (fNIR).
Stress and anxiety are the most common biological predictors of relapse. A person’s stress response often mirrors withdrawal symptoms as seen through elevated heart rate, pulse rate, temperature change, skin conductance, etc. Stress can be measured by a multitude of means and positive or negative experiences can trigger vital signs associated with stress. To avoid false alarms due to a positive experience, it will be important for this technology to have check-ins with the user before setting off an alert.
II. Prevent Relapse
Creating a strong support structure helps to prevent relapse. Addiction is a chronic disease, and thus an ongoing element of support is needed to equip recovering addicts with the tools to deal with stressful situations. (Reference: Dr. Suzette Glasner-Edwards interview.) As a complement to the detecting part of the technology, a support feature should be included to promote healthy living, manage sobriety, and divert temptation when impulse hits.
A host of smartphone sobriety apps already exist to manage addiction. Our goal is to personalize the solution to the individual and make it accessible in the global marketplace. Customizing the technology will increase a person’s likelihood for compliance and may even alleviate time and money spent in medical offices.
This part of the solution can be integrated with the actual technology or stand-alone by linking with a smartphone or computer.
III. Collect biological, neurological and behavioural data
Research surrounding addiction recovery is poorly documented. Our goal is to record data that will improve our understanding of addiction and aid in the eradication of the pandemic. As people begin to use the technology, data will be collected about a person’s physical, neurological, and behavioral patterns. CLEAR Health Technology will have sole access to the data, while the technological user will be able to view their own data. A privacy feature will allow the technological user to opt out of having their data shared all together. CLEAR plans to utilize the data to draw more attention to addiction research, treatments, and recovery efforts.
Judges will review individual and team entries that are submitted by the deadline, February 16th, 2018, and evaluate by the criteria listed below. The judges may request additional information from teams.
| Metric Description | Points |
|---|---|
|
Accuracy and speed of neurological and biological indicators:
|
40 10 10 10 10 |
|
Early warning alert system:
|
20 10 5 5 |
|
Customization and Innovation:
|
25 5 5 5 5 5 |
|
Additional Components:
|
15 5 10 |
The Addiction Relapse Technology Challenge is open to all adult individuals, private teams, public teams, and collegiate teams. Teams may originate from any country. Submissions must be made in English. All challenge-related communication will be in English.
No specific qualification or expertise in the opioid field is required. Challenge organizers encourage outside individuals and non-expert teams to compete and propose new solutions. To be eligible to compete, you must comply with all the terms of the challenge as defined in the Challenge-Specific Agreement, which will be made available upon registration.
Submissions must be made online (only), via upload to the HeroX.com website, on or before the stated deadlines. All uploads must be in PDF format. No late submissions will be accepted.
Based on the winning criteria, prizes will be awarded per the Judging Criteria section above. In the case of a tie, the winner(s) will be selected based on the highest votes from the Judges.
The determination of the winners will be made by a group of people including experts in addiction who have treated addictive behavior, conducted extensive research in the field, sober coach and/or rehab counselor, technology expert and more.
CLEAR Health Technology Inc. will retain all rights of the intellectual property including the submission material and the actual technology device. Please review the Challenge-specific agreement made available upon registration for further information.
