Pacific Treatment and Research Center (Pac-TARC), 3350 La Jolla Village Drive, 116A, San Diego, CA 92161, United States; Department of Psychiatry, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0821, United States.
Pacific Treatment and Research Center (Pac-TARC), 3350 La Jolla Village Drive, 116A, San Diego, CA 92161, United States; Department of Psychiatry, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0821, United States.
Addict Behav. 2018 Sep;84:263-270. doi: 10.1016/j.addbeh.2018.05.004. Epub 2018 May 9.
Adults with alcohol dependence (AD) have exceptionally high smoking rates and poor smoking cessation outcomes. Discovery of factors that predict reduced smoking among AD smokers may help improve treatment. This study examined baseline predictors of smoking quantity among AD smokers in a pharmacotherapy trial for smoking cessation.
The sample includes male, AD smokers (N = 129) with 1-32 months of alcohol abstinence who participated in a 12-week trial of medication (topiramate vs. placebo) and adjunct counseling with 6 months of follow-up. Baseline measures of nicotine dependence, AD severity, psychopathology, motivation to quit smoking, and smoking-related cognitions were used to predict smoking quantity (cigarettes per day) at post-treatment and follow-up.
Overall, the sample had statistically significant reductions in smoking quantity. Greater nicotine dependence (Incidence rate ratios (IRRs) = 0.82-0.90), motivation to quit (IRRs = 0.65-0.85), and intrinsic reasons for quitting (IRRs = 0.96-0.98) predicted fewer cigarettes/day. Conversely, greater lifetime AD severity (IRR = 1.02), depression severity (IRRs = 1.05-1.07), impulsivity (IRRs = 1.01-1.03), weight-control expectancies (IRRs = 1.10-1.15), and childhood sexual abuse (IRRs = 1.03-1.07) predicted more cigarettes/day.
Smokers with AD can achieve large reductions in smoking quantity during treatment, and factors that predict smoking outcomes in the general population also predict greater smoking reductions in AD smokers. Treatment providers can use severity of nicotine dependence and AD, motivation to quit, smoking-related cognitions, and severity of depression to guide treatment and improve outcomes among AD smokers.
患有酒精依赖症(AD)的成年人吸烟率极高,戒烟效果不佳。发现能预测 AD 吸烟者吸烟量减少的因素可能有助于改善治疗效果。本研究在一项针对戒烟的药物治疗试验中,检查了 AD 吸烟者的基线预测因子。
该样本包括 129 名男性 AD 吸烟者,他们在 1-32 个月的酒精戒断期内参与了一项为期 12 周的药物(托吡酯与安慰剂)治疗试验,并在 6 个月的随访期内接受了辅助咨询。使用基线尼古丁依赖程度、AD 严重程度、心理病理学、戒烟动机以及与吸烟有关的认知等指标,来预测治疗后和随访时的吸烟量(每天吸烟量)。
总体而言,该样本的吸烟量有显著统计学减少。更高的尼古丁依赖(发生率比(IRR)=0.82-0.90)、戒烟动机(IRR=0.65-0.85)和戒烟的内在原因(IRR=0.96-0.98)预测每天吸烟量较少。相反,更高的终生 AD 严重程度(IRR=1.02)、抑郁严重程度(IRR=1.05-1.07)、冲动性(IRR=1.01-1.03)、体重控制预期(IRR=1.10-1.15)和儿童期性虐待(IRR=1.03-1.07)预测每天吸烟量更多。
AD 吸烟者在治疗期间可以大幅减少吸烟量,而在普通人群中预测吸烟结果的因素也可以预测 AD 吸烟者的吸烟量减少更多。治疗提供者可以使用尼古丁依赖和 AD 的严重程度、戒烟动机、与吸烟有关的认知以及抑郁的严重程度来指导治疗并改善 AD 吸烟者的治疗效果。