Researchers at Penn State are trying to find a mobile solution for two different types of smokers: One set quits on the first try, but the other requires multiple attempts, and relapses, before they find success, according to a university statement.
The main variable between the two appears to be a nicotine urge that in the first group wanes almost immediately after quitting, but for the second group, never seems to recede, researchers explain.
So researchers now are using smartphones to dig deeper into the nicotine dependence, and identify if time or other factors affect the second group more strongly. Participants are contacted via their smartphones data five times a day at random intervals, answering questions about how they're feeling, whether they have the urge to smoke, and what level that urge was on a scale of 1 to 10, researchers explain.
From there, researchers plug the data into an algorithm that allows them to view the respondents' answers over time, and identify any patterns. The algorithm itself isn't new--it's a decade old, researchers admit--but new software is making it easier to use, and allows the viewing of more than one variable at a time.
For example, researchers can trend a participant's baseline nicotine dependence, compared to the time of day urges strike, and whether negative emotional triggers play a role. In particular, researchers are testing the idea that nicotine dependence isn't a static thing, but rather something that changes over time, and according to events or other factors in the smokers' environment and life.
Understanding the underlying problems that prevent some smokers from quitting may help researchers improve other smoking cessation programs, like new telehealth services that are paid for by Medicare.
It also may explain the uneven results of several text-messaging programs that have tried to help smokers quit. For example, those who don't respond to text prompts or other messages may be those whose nicotine cravings haven't declined through the ongoing program.