Negative affect subtypes and craving differentially predict long-term cessation success among smokers achieving initial abstinence.

Published

Journal Article

OBJECTIVE:This study aimed to examine the associations of individual trajectories of three types of negative affect (NA: anxiety, depression, and anger) and craving during a 44-day period of incentivized smoking abstinence period with cessation outcome at 3 months and at 1 year. METHODS:Adult smokers (N = 140) completed questionnaire assessments of NA and craving during pre-quit baseline sessions and 15 postquit sessions over the 45 days of biochemically verified abstinence while on nicotine or placebo patch treatment. Growth curve and logistic regression analyses were used to examine the associations of trajectory parameters of the individual NA states and craving with the abstinence outcomes at 3 months and 1 year postquit. RESULTS:Greater declines in anxiety, depression, and anger symptoms over the first 44 days of smoking cessation were predictive of higher odds of abstinence at both 3 months and 1 year. Moreover, the greater declines in anxiety and anger remained as significant predictors of abstinence at both time points, independent of the predictive ability of the trajectory profiles of craving. CONCLUSIONS:The findings suggest that slower dissipation of NA, especially anxiety and anger, represents a greater risk for relapse to smoking beyond that predicted by craving during early abstinence. Thus, temporal profiles of the affective symptoms convey unique motivational significance in relapse. Reduction in NA during early abstinence may be a valid target for interventions to increase long-term cessation success rates particularly among individuals with refractory affective symptoms.

Full Text

Duke Authors

Cited Authors

  • Zuo, Y; Rabinovich, NE; Gilbert, DG

Published Date

  • March 2017

Published In

Volume / Issue

  • 234 / 5

Start / End Page

  • 761 - 771

PubMed ID

  • 28028602

Pubmed Central ID

  • 28028602

Electronic International Standard Serial Number (EISSN)

  • 1432-2072

International Standard Serial Number (ISSN)

  • 0033-3158

Digital Object Identifier (DOI)

  • 10.1007/s00213-016-4509-1

Language

  • eng