Does a custom tailored program for getting a person to stop smoking work better than a one-size-fits all generic program? A new study published in Nature: Neuroscience seems to think so. Using brain imaging and statistics the study produces strong data that could result in radical changes to how we treat addicts.
Researchers have determined that using individually tailored method to induce smokers to quit has proven more effective than generic non-personalized treatment. Researchers used MRI brain scans to measure which part of the brain was activated while the participant was thinking about him or herself and used that data to predict how likely a participant was to quit smoking. What they found was that increased activity in certain parts of the brain was associated with introspective thinking was also linked with increased likelihood of quitting. The activation around these regions that are associated with thinking about one’s self showed a treatment that caused the patient to think about the personal impact of smoking to be more effective than a one size fits all approach. This finding has implications not just for research on smokers but for all treatment that involves self improvement whether that is weight loss or substance abuse. The link between introspective thinking, certain specific brain activity, and the resultant positive behavioral change had never been analyzed in a study before until now.
It has long been suggested that a tailored approach to patients with a behavioral problem was more effective than a generic one (as evidenced by the recent increase in high end “luxury” recovery centers such as this one in Malibu), however, the physical reasons for why this is the case have still been mostly unknown. While scanning the participants brains while exposing them to various messaging the researchers have finally shed some light on the physical underpinnings of this phenomenon. The messages ranged from neutral (“Sighted in the Pacific Ocean, the world's tallest sea wave was 112 feet.”) to untailored (“Many smokers quit because they are tired of spending money on cigarettes.”) to specific tailored messages (“You feel like your sister will help you stay on track once you quit.”) When subjected to this third type of message, the areas of the brain thought to be associated with thinking about one’s self – the prefrontal cortex and precuneus regions - showed significantly more activity.
Your brain when you look in the mirror
The researchers did not stop at merely identifying the relevant portions of the brain activated by custom tailored messaging, however. They then used this data to reliably predict which participants quit smoking 4 months later and which did not. In the third portion of the study the participants completed an intervention course – some tailored, others generic – and were given anti-smoking books as well as a 10 week supply of nicotine patches. When the researcher’s followed up 4 months later, they found those that exhibited the strongest responses in their prefrontal cortex were the mostly likely to have quit smoking. For the first time researchers have shed some light on the physical reasons why these personalized approaches work so well. This find paves the way for further research into an area that could have profound implications for behavioral science – particularly addiction control.
What shouldn’t get lost in the science behind this discovery is the fact that according to the CDC smoking is the single most preventable cause of disease, disability, and death in the United States with over 443,000 people dying annually. This discovery opens the door to a wealth of new research into the very best way to combat the plague of addiction. Without fully understanding the underlying physical characteristics of addiction – and more importantly – addiction control, one cannot truly solve the problem.
References:
Chua, Hannah F., S. S. Ho, Agnes J. Jasinska, Thad A. Polk, Robert C. Welsh, Israel Liberzon, and Victor J. Strecher. "Self-related Neural Response to Tailored Smoking-cessation Messages Predicts Quitting." Nature Neuroscience (2011). Web. 15 Mar. 2011.
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