Dynamic models of stress-smoking responses based on high-frequency sensor data.

ABSTRACT: Self-reports indicate that stress increases the risk for smoking; however, intensive data from sensors can provide a more nuanced understanding of stress in the moments leading up to and following smoking events. Identifying personalized dynamical models of stress-smoking responses can improve characterizations of smoking responses following stress, but techniques used to identify these models require intensive longitudinal data. This study leveraged advances in wearable sensing technology and digital markers of stress and smoking to identify person-specific models of stress and smoking system dynamics by considering stress immediately before, during, and after smoking events. Adult smokers (n = 45) wore the AutoSense chestband (respiration-inductive plethysmograph, electrocardiogram, acce

SUBMITTER: Hojjatinia S 

PROVIDER: S-EPMC8611062 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature