Magazine article Addiction Professional

Wearing Recovery on One's Sleeve

Magazine article Addiction Professional

Wearing Recovery on One's Sleeve

Article excerpt

Research examines the potential of biomonitoring technology to prevent relapse

While there have been many advances in the treatment of addiction, relapse remains a common problem.1,2 Research indicates that 25 to 50% of people who have undergone addiction treatment moved back and forth between periods of abstinence and heavy drinking or drug use.3,4 Not surprisingly, rates of relapse increase consistently as more time passes since treatment.

Although most field experts consider addiction to be a chronic disease, there are often limited provisions for clients who have completed treatment to manage their addictive disorders through ongoing monitoring or "checkups," which are seen more commonly with other chronic disorders.5 Recent studies indicate that the key to preventing addiction relapse often lies in experiences and events in the hours and even minutes leading up to the onset of an episode of returning to substance use.6 Some of the most common reasons for first relapses are negative emotions, social pressure, and cravings to use a substance.7 One explanation for these relationships is that people return to substance use as a way to escape from distress or as a means of coping with stress and negative emotions.8

Importantly, each of these stressors that contribute toward relapse reveals itself in physiologic forms within the body-all of which can be detected via wearable biomonitoring technology available on the market today.

"We know that stress is the most accurate predictor of relapse, and relapse is often preceded by stressful episodes characterized by strong negative moods," says Timothy Baker, PhD, professor of psychology at the University of WisconsinMadison. "This suggests that autonomie nervous or somatic system activity associated with stress may be used to detect stressful episodes and make people aware of their state of mind. One reason this is important is that laboratory research shows that individuals may actually be unaware of when they are becoming stressed or experiencing negative moods, so they don't always know to seek out the help they may need to maintain a successful recovery program."

Our research team at the University of Wisconsin has begun testing the potential of how body monitoring instruments can be used to prevent relapse. This research is part of a larger initiative called "Innovations for Recovery" that is focused on exploring how technology can improve outcomes in addiction treatment.9 The idea we pursue here is the feasibility of using physiologic monitoring to detect stress and to trigger data services such as a text message or phone call to the user asking if he/she needs support.

Possible applications

Consider the following scenario of how a wearable biomonitoring system might help prevent relapse. A woman in recovery from alcoholism is waiting at home for her husband to return from a fishing trip. He is often late and has already promised to be home in time for a dinner engagement they had made with friends weeks earlier. As the time for their dinner approaches, the woman feels increasingly anxious and tempted to open a bottle of wine that her husband had received over the holidays. Her wearable biomonitoring device detects her distress and sends a message to her mobile phone asking if she needs any support. Likewise, the sudden increase in her stress levels triggers text messages to the mobile phones of people in her support network, such as her peer sponsor and a therapist. They immediately phone to make sure she is managing her stress appropriately (i.e., not drinking).

The most appropriate application we could identify to pursue this research aim of exploring how such a system might work was the BodyMedia Sense Wear body monitoring system (www.bodymedia. com), a monitor that collects the physiologic information needed to measure arousal and that incorporates integrated wireless data transmission and Web-based interfaces for interpreting results. …

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