Some people quit smoking on the
first try while others have to try to quit repeatedly. Using such mobile
technology as handheld computers and smartphones, a team of researchers from Penn State University and the University of Pittsburgh
is trying to find out why.
“One thing that really stood
out among the relapsers is how their urge to smoke just never dropped, in
contrast to those who were successful in quitting for a month—their urge dropped
quickly and systematically—almost immediately upon quitting,” said Stephanie
Lanza, scientific director of The Methodology Center at Penn State. “That
was surprising to see.”
With a new statistical model to
interpret data and the ability to collect data through mobile devices, the
researchers looked at how baseline nicotine dependence and negative emotional
states influenced people’s urge to smoke while they were trying to quit.
The Centers for Disease Control
found in a 2010 National Health Interview Survey of 27,157 adults that about
52% of cigarette smokers tried to quit during the year. Six percent of all
smokers—who had been smoking for two years or more—quit for at least six
months. Also in 2010, the CDC reported that even though cigarette smoking is
the leading cause of preventable death and disease in the United States,
nearly one in five Americans smokes.
The team found that those who
successfully quit during the four-week study period had a weaker association
between their urge to smoke and their ability to quit. However, those who were
unable to abstain did not show any association between their urge to smoke and
their self-confidence.
Saul Shiffman, professor of
psychology at the University
of Pittsburgh, followed
304 long-term cigarette smokers as they tried to quit. On average, the
participants smoked more than a pack a day for 23 years. Forty participants
quit smoking for the initial 24 hours, but subsequently relapsed. During the
two weeks after quitting, 207 participants remained relatively tobacco-free. If
smokers relapsed but smoked less than five cigarettes per day, they were
considered successful quitters in this study. The remaining 57 participants
were unable to quit for even 24 hours.
Five times randomly throughout
the day, mobile devices prompted participants to answer questions. These
questions asked the smokers about their emotional state, their urge to smoke
and if they were smoking. They rated their urge to smoke at that moment on a
scale of zero to 10. Using this data collection method, the researchers
collected data from subjects in their natural environments.
Researchers followed subjects for
two weeks prior to their attempt to quit, and for four weeks after their
attempt to quit, the researchers report online in Prevention Science.
The Penn State
team used a flexible statistical model—a time-varying effect model—that allows
the researchers to look at more than one variable at a time. This model is a
decade old, but until now was not user-friendly. The Methodology Center
created accessible software to analyze data that vary over time.
“To me, the biggest
innovation here is looking at how something like baseline dependence is
predictive of that behavior over time or (specifically) the urge to smoke over
time,” said Lanza. “It’s now expressed as a function of time. Instead
of saying ‘if you’re higher on dependence you’re going to have a higher urge to
smoke over time,’ you can now depict how that association between baseline
dependence and urge to smoke varies with time in a very fluid and naturalistic
way.”
One advantages of this model is
that researchers are not confined to changes in one dimension. Researchers can
look at time in a smooth way, viewing it as a gradual and constant variable and
simultaneously view two or more variables that can change over time, such as
smoking urges and negative affect. Lanza noted that this method could be used
to look at addiction and behavior in many other areas, such as obesity, alcohol
dependence, stress, and more.
“Our goal is to work
hand-in-hand with tobacco (and other) researchers, to help them understand
these really intricate processes that are happening,” said Lanza. “We
want to really understand addiction and how to break addiction, so that
interventions can be targeted and adaptable.”