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Identifying attendance patterns in a smoking cessation treatment and their relationships with quit success.

ABSTRACT: While important for substance use outcomes, knowledge about treatment attendance patterns, and their relation with clinical outcomes is limited. We examined the association between attendance patterns and smoking outcomes in a randomized, controlled smoking cessation intervention trial.In addition to standard smoking cessation treatment, participants were randomized to 15 weeks of an exercise intervention (n=72) or an education control condition (n=64). Latent class growth analysis (LCGA) tested whether intervention attendance would be better modeled as qualitatively distinct attendance patterns rather than as a single mean pattern. Multivariate generalized linear mixed modeling (GLMM) was used to evaluate associations between the attendance patterns and abstinence at the end of treatment and at 6-month follow-up.The LCGA solution with three patterns characterized by high probability of attendance throughout (Completers, 46.3%), gradual decreasing probability of attendance (Titrators, 23.5%), and high probability of dropout within the first few weeks (Droppers, 30.1%) provided the best fit. The GLMM analysis indicated an interaction of attendance pattern by treatment condition, such that titration was associated with lower probability of quit success for those in the control condition. Probability of quit success was not significantly different between Titrators and Completers in the exercise condition.These findings underscore the importance of examining how treatment efficacy may vary as a function of attendance patterns. Importantly, treatment discontinuation is not necessarily indicative of poorer abstinence outcome.

SUBMITTER: Jacquart J

PROVIDER: S-EPMC5423398 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Identifying attendance patterns in a smoking cessation treatment and their relationships with quit success.

Jacquart Jolene J Papini Santiago S Davis Michelle L ML Rosenfield David D Powers Mark B MB Frierson Georita M GM Hopkins Lindsey B LB Baird Scarlett O SO Marcus Bess H BH Church Timothy S TS Otto Michael W MW Zvolensky Michael J MJ Smits Jasper A J JAJ

Drug and alcohol dependence 20170306

<h4>Background</h4>While important for substance use outcomes, knowledge about treatment attendance patterns, and their relation with clinical outcomes is limited. We examined the association between attendance patterns and smoking outcomes in a randomized, controlled smoking cessation intervention trial.<h4>Methods</h4>In addition to standard smoking cessation treatment, participants were randomized to 15 weeks of an exercise intervention (n=72) or an education control condition (n=64). Latent ...[more]

PMID: 28315809

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Project description:IntroductionMost people who smoke cigarettes are not willing (ie, not ready) to make a quit attempt (QA) at any given time. Unfortunately, interventions intended to increase QAs and the success of QAs are only modestly effective. Identifying processes leading to QAs and quitting success could guide intervention development.Aims and methodsThis is a secondary analysis of a randomized factorial trial of 6 weeks of motivation-phase interventions among primary care patients (N = 517) who were initially unwilling to quit but were willing to reduce their smoking. Using logistic regression, we controlled for treatment condition and tested whether baseline or change in smoking-related constructs after 6 weeks of treatment predicted (1) making an at least 24 h QA between weeks 6 and 26 and (2) quitting success at week 26 (7-day point-prevalence abstinence among those who made a QA). Predictors included cigarettes/day, time to first cigarette, motivation to quit, quitting self-efficacy, anticipated urges to smoke if quit, positive affect, negative affect, and time spent around others who smoke.ResultsIn multivariable models that included all smoking-related constructs, changes in the following variables predicted initiating a QA above and beyond other variables: greater baseline time to first cigarette (odds ratio [OR] = 1.60), increases in time to first cigarette (OR = 1.27), and increases in quitting self-efficacy (OR = 1.14). Increased motivation to quit predicted conversion of a QA into quitting success at 26 weeks (OR = 1.36).ConclusionPredictors of making a QA differed from predictors of quitting success. Predictors of QAs and success could each serve as important treatment targets of motivation-phase interventions.ImplicationsMotivation-phase interventions for people initially unwilling to quit smoking cigarettes may be improved by striving to increase their (1) time to first cigarette and quitting self-efficacy to promote QAs and (2) motivation to quit to promote quit success. Future experimental tests of such interventions are needed to identify causal determinants of QAs and quitting success.

Project description:BackgroundSetting a target quit date (TQD) is often an important component in smoking cessation treatment, but ambiguity remains concerning the optimal timing (ie, quitting spontaneously versus delaying to prepare).ObjectiveWe examined four questions about the timing of TQDs and smoking outcomes in secondary analyses of The iQUITT Study, a randomized trial of Internet and telephone treatment for cessation: (1) What are the characteristics of TQDs set using an online interactive quit date tool?, (2) What are the characteristics of individuals who use a quit date tool and do they differ from those who do not?, (3) Are there differences in smoker characteristics, treatment utilization, and cessation outcomes based TQD timing?, and (4) Is maintenance of an initial TQD predictive of abstinence or do changes to TQDs lead to cessation?MethodsA total of 825 adult current cigarette smokers were randomized to enhanced Internet or enhanced Internet plus telephone counseling. Latency to TQD in days was calculated as the date difference between the initial TQD and enhanced Internet registration; prospective TQD setters were stratified into four latency groups (0, 1-14, 15-28, 29+ days). Baseline variables, website utilization, and 3-month cessation outcomes were examined between prospective TQD groups. Desire and confidence to quit, number of TQDs, and website logins were tested as predictors of 30-day point prevalence abstinence (ppa) at 3 months (responder-only analyses). Classification and regression tree (CART) analysis explored interactions among baseline variables, website utilization, and latency to TQD as predictors of 30-day ppa.ResultsThere were few baseline differences between individuals who used the quit date tool and those who did not. Prospective TQDs were set as follows: registration day was 17.1% (73/427), 1-14 days was 37.7% (161/427), 15-28 days was 18.5% (79/427), and 29+ days was 26.7% (114/427). Participants with a TQD within 2 weeks had higher baseline self-efficacy scores but did not differ on smoking variables. Individuals whose TQD was the same day as registration had the highest logins, page views, number of TQDs set using the tool, and messages sent to other members. Logistic regression revealed a significant interaction between number of TQDs and website logins for 30-day ppa (P=.005). Among those with high logins, 41.8% (33/79) with 1 TQD were abstinent versus 25.9% (35/135) with 2+TQDs. Logins and self-efficacy predicted 30-day ppa in the CART model.ConclusionsTQD timing did not predict cessation outcomes in standard or exploratory analyses. Self-efficacy and an apparent commitment to an initial TQD were the components most highly related to abstinence but only via interactions with website utilization. Findings highlight the importance of feeling efficacious about handling specific smoking situations and engaging with treatment. Additional research focused on increasing engagement in Web-based cessation studies is needed.Trial registrationClinicalTrials.gov: NCT00282009; http://clinicaltrials.gov/show/NCT00282009 (Archived by WebCite at http://www.webcitation.org/6Kt7NrXDl).

Project description:BackgroundSmoking continues to be a leading cause of preventable chronic disease-related morbidity and mortality, excess healthcare expenditure, and lost work productivity. Tobacco users are disproportionately more likely to be engaging in other modifiable risk behaviours such as excess alcohol consumption, physical inactivity, and poor diet. While hundreds of interventions addressing the clustering of smoking and other modifiable risk behaviours have been conducted worldwide, there is insufficient information available about the context and mechanisms in these interventions that promote successful smoking cessation. The aim of this rapid realist review was to identify possible contexts and mechanisms used in multiple health behaviour change interventions (targeting tobacco and two or more additional risk behaviours) that are associated with improving smoking cessation outcome.MethodsThis realist review method incorporated the following steps: (1) clarifying the scope, (2) searching for relevant evidence, (3) relevance confirmation, data extraction, and quality assessment, (4) data analysis and synthesis.ResultsOf the 20,423 articles screened, 138 articles were included in this realist review. Following Michie et al.'s behavior change model (the COM-B model), capability, opportunity, and motivation were used to identify the mechanisms of behaviour change. Universally, increasing opportunities (i.e. factors that lie outside the individual that prompt the behaviour or make it possible) for participants to engage in healthy behaviours was associated with smoking cessation success. However, increasing participant's capability or motivation to make a behaviour change was only successful within certain contexts.ConclusionIn order to address multiple health behaviours and assist individuals in quitting smoking, public health promotion interventions need to shift away from 'individualistic epidemiology' and invest resources into modifying factors that are external from the individual (i.e. creating a supportive environment).Trial registrationPROSPERO registration number: CRD42017064430.

Project description:IntroductionGenetic variation in Cytochrome P450 2A6 (CYP2A6), the major nicotine metabolizing enzyme, is associated with nicotine dependence and smoking cessation. Nicotine dependence severity also predicts smoking cessation. Our goals were to determine how CYP2A6 variation and nicotine dependence alter smoking cessation, and whether dependence could refine CYP2A6-based treatment recommendations.Aims and methodsAdult smokers treated for 12 weeks with placebo, nicotine patch, or varenicline (NCT01314001) were grouped as CYP2A6 normal (n = 567) or slow (n = 432) nicotine metabolizers based on a CYP2A6 weighted genetic risk score. Fagerström test for nicotine dependence scores were measured at baseline and biochemically verified smoking cessation was assessed at end of treatment.ResultsDependence neither mediated nor moderated an association between CYP2A6 variation and smoking cessation overall, within any treatment arm, or after stratifying by ancestry (n = 591 European, n = 408 African ancestry) or sex (n = 444 women, n = 555 men). In within-treatment analyses, the mediation effect odds ratio (OR) ranged from 0.95 to 1.00 and the bias-corrected 95% confidence interval contained 1. Moderation (i.e. interaction) effect ORs ranged from 0.88 to 1.61 (p = .397-.828). For CYP2A6 normal metabolizers, quit rates on varenicline were similar for those with high (41.1%) and low (43.4%) dependence, while quit rates were lower for those with high versus low dependence on both patch (16.5 vs. 29.7%) and placebo (8.9 vs. 18.5%). CYP2A6 slow metabolizers with high versus low dependence had lower quit rates in all three treatment arms.ConclusionsAlthough nicotine dependence severity neither mediated nor moderated CYP2A6 associations with smoking cessation, incorporating information on dependence may optimize the choice of smoking cessation treatment aid in CYP2A6 normal and slow metabolizers.ImplicationsVariation in CYP2A6 and nicotine dependence severity alter smoking cessation success. Our findings suggest that while nicotine dependence severity is unlikely to mediate or moderate CYP2A6 associations with cessation, incorporating patient information on both CYP2A6 and nicotine dependence severity may lead to improved smoking cessation strategies.

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Identifying attendance patterns in a smoking cessation treatment and their relationships with quit success.

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Identifying attendance patterns in a smoking cessation treatment and their relationships with quit success.

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