Support from close others predicts smoking abstinence, yet little research has investigated what factors promote support. This study investigates predictors of support for a quit attempt. Partners of smokers (N = 131) reported their relationship quality, concern for partner's health, own smoking status, and intended support for a quit attempt. Smokers were less supportive than were nonsmokers. Relationship quality, concern for partners' health, and motivation to quit were positively associated, and nicotine dependence was negatively associated, with intended support. The findings suggest that support for smoking cessation depends on one's own smoking behaviors as well as characteristics of the relationship.

We explore physiological linkage (i.e., covariation of physiological channels between interacting partners; PL) among 34 same-sex male couples. Interbeat interval, an indicator of cardiovascular arousal, was collected across four conversational contexts in the lab: (1) a baseline period that did not involve conversation, (2) a conversation about body image, (3) a conversation about health goals, and (4) a recovery period that allowed for unstructured conversation. We used a newly developed R statistical package (i.e., rties; Butler and Barnard, 2019) that simplifies the use of dynamic models for investigating interpersonal emotional processes. We identified two different PL patterns: (1) a simple one that was characterized by stable synchronization and low frequency of oscillation; and (2) a complex one that was characterized by drifting synchronization, high frequency of oscillation, and eventual damping. Guided by social baseline theory and the reactive flexibility perspective, we explored the interactions between couple relationship functioning (i.e., love, conflict, commitment, sexual satisfaction, and relationship length) and conversational context as predictors of the PL patterns. The results suggest that partners in well-functioning relationships and emotionally challenging situations may be especially likely to show complex PL patterns that may reflect (or support) coregulatory processes.

Lapses in a quit attempt may change the nature of the support quitters receive. Interventions to improve communication between partners about the smoker's commitment to quitting and experienced challenges may result in better support.

We explore complex dynamic patterns of autonomic physiological linkage (i.e., statistical interdependence of partner’s physiology; PL), within the sympathetic and parasympathetic nervous systems (SNS and PNS), as potential correlates of emotional and regulatory dynamics in close relationships. We include electrodermal activity (EDA) as an indicator of SNS activation and respiratory sinus arrhythmia (RSA) as an indicator of regulatory and/or homeostatic processes within the PNS. Measures of EDA and RSA were collected in 10-second increments from 53 heterosexual couples during a mixed-emotion conversation in the laboratory. We used the R statistical package, rties (Butler & Barnard, 2019), to model the dynamics of EDA and RSA with a coupled oscillator model and then categorized couples into qualitatively distinct profiles based on the set of parameters that emerged. We identified two patterns for EDA and three patterns for RSA. We then investigated associations between the PL patterns and self-report measures of relationship and conversation quality and emotional valence using Bayesian multilevel and logistic regression models. Overall, we found robust results indicating that PL profiles were credibly predicted by valence and relationship quality reported prior to the conversations. In contrast, we found very little evidence suggesting that PL patterns predict self-reported conversation quality or valence following the conversation. Together, these results suggest that PL across autonomic subsystems may reflect different processes and therefore have different implications when considering interpersonal dynamics.