Nicotine effects on affective response in depression-prone smokers
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Comorbidity between cigarette smoking and depression is thought to arise because depression-prone smokers self-administer nicotine to improve mood. Yet little evidence supports this view, and nicotine’s effect on positive affect deficiency in depression remains largely unstudied.
We hypothesized that (1) nicotine would dispel negative affect and enhance positive affect and (2) effects would be stronger for smokers vulnerable to depression, particularly during a depressed state.
Materials and methods
Regular smokers (N = 165) were recruited from the community: 63 with no history of major depressive disorder (MDD), 61 with recurrent past but no current MDD, and 41 with both current and past MDD. During four sessions, participants smoked either a nicotinized (NIC+) or denicotinized (NIC−) cigarette double blind after experiencing a negative mood induction or while undergoing a positive mood induction. Positive and negative affects were measured at baseline and at two time points after smoking.
Previously depressed smokers showed a heightened positive mood response to positive mood induction when smoking a nicotinized cigarette. Nicotine also increased the degree to which positive mood induction dispelled negative mood in depression-vulnerable smokers. Finally, nicotine worsened the negative affect response to negative mood induction for all groups.
Self-administering nicotine appears to improve depression-prone smokers’ emotional response to a pleasant stimulus.
KeywordsNicotine Depression Tobacco smoking Affect Tobacco use
Supported by a VA Medical Research Merit Review grant to Dr. Spring and by NIH grants P30 CA060553 and R25 CA100600. Portions of this paper were presented at the Annual Meeting of the Society for Research in Nicotine and Tobacco, Austin, Texas, February, 2007. We express appreciation to Dennis McChargue and Neal Doran for discussions during the conduct of the research and an anonymous reviewer for noting the relevance of attentional allocation models to our findings.
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