ArticleAddictive behaviors2018
Predictors of reduced smoking quantity among recovering alcohol dependent men in a smoking cessation trial.
Article in Addictive behaviors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Topiramate for smoking cessation: Systematic review and meta-analysis.Tobacco prevention & cessation · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
introductionAdults 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.
methodsThe 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.
resultsOverall, 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.
conclusionsSmokers 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.