ArticleAddictive behaviors2021
Network analysis reveals the associations of past quit experiences on current smoking behavior and motivation to quit.
Article in Addictive behaviors, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Crossed Pathways: Tobacco-Cannabis Co-Use and Motivation to Quit in Young Adults in France.Drug and alcohol review · 2026Article
- Demographics and psychosocial determinants of quit intention among oral smokeless tobacco users: an analytical cross-sectional study in Saudi Arabia.BMC public health · 2025Article
- The role of sleep difficulties in the relation between pain and smoking cessation processes.Journal of behavioral medicine · 2025Article
- A Network Analysis of Cigarette Craving.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2023Article
- Comparison of the baseline characteristics and influencing factors of successful smoking cessation before and during the coronavirus disease pandemic.Tobacco induced diseases · 2023Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
introductionSmoking is a leading cause of morbidity and mortality in the United States. While most smokers endorse a desire to quit, achieving abstinence is notoriously difficult. Network analysis is a method for understanding the complex relationships of factors that maintain smoking behavior and impact motivation to quit.
methodsThis study examined self-report prescreen data from treatment-seeking smokers (N = 3913). The number of prior quit attempts and withdrawal symptoms experienced, as well as current smoking behavior and motivation to quit were modeled as interconnected nodes in a network. Two key network metrics were examined: 1) edge weights, which quantify the strength and direction of the associations of interest, and 2) the sum of each node's edge weights, which quantifies the expected influence of a node on the overall network.
resultsThe withdrawal symptom of craving, r = 0.10, 95% CI [0.07, 0.13] and digestive problems, r = -0.06, 95% CI [-0.09, -0.03], had the strongest positive and negative association with daily cigarettes, respectively. The number of prior quit attempts, r = 0.17, 95% CI [0.14, 0.20], concentration problems, r = -0.04, 95% CI [-0.027, -0.01], showed the strongest positive and negative associations, respectively, with current motivation to quit. Nodes with significant links to current smoking and motivation to quit were also among the most influential in the overall network.
conclusionsFindings suggest prior quit experiences and consequences associated with withdrawal symptoms may differentially relate to maintenance of smoking behavior and motivation to quit in treatment-seeking smokers. Interventions targeting key withdrawal symptoms may enhance motivation to quit.
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