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, accelerometer) with MotionSense (accelerometers, gyroscopes) on each wrist for three days prior to a quit attempt. The odds of minute-level smoking events were regressed on minute-level stress probabilities to identify person-specific dynamic models of smoking responses to stress. Simulated pulse responses to a continuous stress episode revealed a consistent pattern of increased odds of smoking either shortly after the beginning of the simulated stress episode or with a delay, for all participants. This pattern is followed by a dramatic reduction in the probability of smoking thereafter, for about half of the participants (49%). Sensor-detected stress probabilities indicate a vulnerability for smoking that may be used as a tailoring variable for just-in-time interventions to support quit attempts.
ABSTRACT
Breaking up sitting time with light- or moderate-intensity physical activity may help to alleviate some negative health effects of sedentary behavior, but few studies have examined ways to effectively intervene. This feasibility study examined the acceptability of a new technology (NEAT!) developed to interrupt prolonged bouts (≥20 min) of sedentary time among adults with type 2 diabetes. Eight of nine participants completed a 1-month intervention and agreed that NEAT! made them more conscious of sitting time. Most participants (87.5 %) expressed a desire to use NEAT! in the future. Sedentary time decreased by 8.1 ± 4.5 %, and light physical activity increased by 7.9 ± 5.5 % over the 1-month period. The results suggest that NEAT! is an acceptable technology to intervene on sedentary time among adults with type 2 diabetes. Future studies are needed to examine the use of the technology among larger samples and determine its effects on glucose and insulin levels.
