The Network Structure of Tobacco Withdrawal in a Community Sample of Smokers Treated With Nicotine Patch and Behavioral Counseling

Abstract

Introduction: Network theories of psychopathology highlight that, rather than being indicators of a latent disorder, symptoms of disorders can causally interact with one another in a network. This study examined tobacco withdrawal from a network perspective.

Methods: Participants (n = 525, 50.67% female) completed the Minnesota Tobacco Withdrawal Scale four times (2 weeks prior to a target quit day, on the target quit day, and 4 and 8 weeks after the target quit day) over the course of 8 weeks of treatment with nicotine patch and behavioral counseling within a randomized clinical trial testing long-term nicotine patch therapy in treatment-seeking smokers. The conditional dependence among seven withdrawal symptoms was estimated at each of the four measurement occasions. Influential symptoms of withdrawal were identified using centrality indices. Changes in network structure were examined using the Network Comparison Test.

Results: Findings indicated many associations among the individual symptoms of withdrawal. The strongest associations that emerged were between sleep problems and restlessness, and associations among affective symptoms. Restlessness and affective symptoms emerged as the most central symptoms in the withdrawal networks. Minimal differences in the structure of the withdrawal networks emerged across time.

Conclusions: The cooccurrence of withdrawal symptoms may result from interactions among symptoms of withdrawal rather than simply reflecting passive indicators of a latent disorder. Findings encourage greater consideration of individual withdrawal symptoms and their potential interactions and may be used to generate hypotheses that may be tested in future intensive longitudinal studies.

Implications: This study provides a novel, network perspective on tobacco withdrawal. Drawing on network theories of psychopathology, we suggest that the cooccurrence of withdrawal symptoms may result from interactions among symptoms of withdrawal over time, rather than simply reflecting passive indicators of a latent disorder. Results indicating many associations among individual symptoms of withdrawal are consistent with a network perspective. Other results of interest include minimal changes in the network structure of withdrawal across four measurement occasions prior to and during treatment with nicotine patch and behavioral counseling.

Figure 1.

The network structure of the seven tobacco withdrawal symptoms at each assessment. Blue edges represent positive associations among symptoms. Red edges represent negative associations. The network structure is estimated using a Gaussian graphical model. Each edge represents partial correlation coefficients between two variables after conditioning on all other variables. The size and transparency of the edges reflect the magnitude of the association between two symptoms, with the thickest edge set to a maximum of 0.65 across all four networks to facilitate comparisons across measurement occasions. Nodes were placed in a circular layout in order to facilitate visual comparison across assessments.