Tobacco withdrawal system recovery time assessed during smoking satiety predicts smoking behavior change among individuals who smoke cigarettes daily
Abstract
Objective: A network theory of tobacco withdrawal posits between-person differences in how withdrawal symptoms causally influence one another across time. Individuals with densely connected symptom networks that facilitate the perpetuation of withdrawal symptom activity across time are theorized to have more difficulty quitting due to intense withdrawal experiences that persist even after the events instigating initial increases in withdrawal intensity are no longer present. Method: By constructing withdrawal symptom networks using ecological momentary assessment data in 123 individuals who smoke cigarettes daily (Mage = 49.81 years, SD = 11.29; 63.4% women; 63.4% Black/African American) from a period during which they were smoking as usual, we test the extent to which between-person differences in these networks predict change in smoking behavior during a 10-day smoking abstinence period. Results: Individuals with symptom networks with longer recovery times following a simulated symptom perturbation had less pronounced decreases in smoking between the smoking-as-usual and smoking-abstinence conditions, b = 0.03, 95% CI [0.01, 0.06], β = .28, p = .01. Conclusions: Results support the utility of a network theory of tobacco withdrawal for predicting between-person differences in smoking during attempted abstinence. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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