Applying the tripartite model of anxiety and depression to cigarette smoking: an integrative review
- PMID: 21036959
- PMCID: PMC2991624
- DOI: 10.1093/ntr/ntq174
Applying the tripartite model of anxiety and depression to cigarette smoking: an integrative review
Abstract
Introduction: Research on the relationship between emotional disorders and smoking often characterizes anxiety and depression at the broad syndrome level. Because of the complex concordance and discordance across and within anxiety and depressive symptoms, research using this approach may be limited. Watson and Clark developed the tripartite model of anxiety and depression, which identifies negative affect (NA), anhedonia and low positive affect (PA), and anxious arousal (AA) as traits that characterize the underlying heterogeneity in emotional symptoms. An emerging literature has examined the relation between the affective constructs in the tripartite model and smoking; however, these findings have not been summarized and integrated. The aim of this report reviews the literature on the association between tripartite affective dimensions (anhedonia and low PA, NA, and AA) and smoking variables (smoking status, heaviness, chronicity, dependence, cessation, craving/urge).
Methods: Qualitative summarization and integration of findings.
Results: All three dimensions were consistently associated with smoking status but demonstrated mixed or no relationship with smoking heaviness, chronicity, and dependence. Low PA and anhedonia consistently associated with craving and relapse, even in studies that controlled for other dimensions. Emotional disturbance on multiple dimensions (e.g., low PA + high NA) was associated with disproportionate increases in smoking risk in several studies.
Conclusions: Tripartite dimensions may each have differential effects on smoking. Anhedonic and low PA individuals (especially those with concurrent NA or AA) may be a high-risk group worthy of targeting for interventions. Continued research of the affective dimensions linked with smoking could inform the etiology of tobacco dependence and lead to more effective smoking interventions that target affect.
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