Search

Objective: While the U.S. adult smoking rate has declined, Black smokers disproportionately face more barriers to accessing brief effective tobacco cessation treatments compared with other racial groups. This study developed and tested the effects of a novel, evidence-based, brief smoking intervention culturally targeted for disadvantaged Black smokers (ClinicalTrials.gov ID: NCT04460417). Method: In this randomized controlled trial, primarily low-income Black non-treatment-seeking smokers ( N = 204, 51% female) were randomized to enhanced care (EC) or treatment as usual (TAU). The EC group received a 30-min session with personal feedback on smoking, education on health outcomes and tobacco advertising targeting Black smokers, and nicotine replacement therapy (NRT) starter kits. TAU included provision of self-help materials. Primary outcome was motivation to change smoking behavior, and secondary outcomes included NRT knowledge and use, quit attempts, and number of cigarettes smoked per day. Data were collected at baseline, 1- and 6-month follow-ups. Results: Compared with TAU, EC increased motivation to change ( p = .02), accuracy in NRT knowledge, ( p < .001), NRT use ( p = .01), and likelihood of making a serious quit attempt as well as reduced cigarettes smoked per day ( p < .01) through 6-month follow-up. Conclusions: A brief motivational intervention for Black non-treatment-seeking smokers increased motivation to change smoking and resulted in improvements in NRT knowledge, use, and quit-relevant behaviors. Findings support cultural-targeting and provision of NRT to enhance motivation in Black smokers to reduce cultural and institutional barriers to tobacco cessation. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Objective: To examine cognitive and affective mechanisms underlying mindfulness-based addiction treatment (MBAT) versus cognitive-behavioral therapy (CBT) and usual care (UC) for smoking cessation., Method: Participants in the parent study from which data were drawn (N = 412; 54.9% female; 48.2% African American, 41.5% non-Latino White, 5.4% Latino, 4.9% other; 57.6% annual income <$30,000) were randomized to MBAT (n = 154), CBT (n = 155), or UC (n = 103). From quit date through 26 weeks postquit, participants completed measures of emotions, craving, dependence, withdrawal, self-efficacy, and attentional bias. Biochemically confirmed 7-day smoking abstinence was assessed at 4 and 26 weeks postquit. Although the parent study did not find a significant treatment effect on abstinence, mixed-effects regression models were conducted to examine treatment effects on hypothesized mechanisms, and indirect effects of treatments on abstinence were tested., Results: Participants receiving MBAT perceived greater volitional control over smoking and evidenced lower volatility of anger than participants in both other treatments. However, there were no other significant differences between MBAT and CBT. Compared with those receiving UC, MBAT participants reported lower anxiety, concentration difficulties, craving, and dependence, as well as higher self-efficacy for managing negative affect without smoking. Indirect effects of MBAT versus UC on abstinence occurred through each of these mechanisms., Conclusions: Whereas several differences emerged between MBAT and UC, MBAT and CBT had similar effects on several of the psychosocial mechanisms implicated in tobacco dependence. Results help to shed light on similarities and differences between mindfulness-based and other active smoking cessation treatments. (PsycINFO Database Record, ((c) 2017 APA, all rights reserved).)

The study was a randomized placebo-controlled trial testing whether fluoxetine selectively enhances cessation for smokers with a history of depression. Euthymic smokers with (H+, n = 109) or without (H-, n = 138) a history of major depression received 60 mg fluoxetine or placebo plus group behavioral quit-smoking treatment for 12 weeks. Fluoxetine initially enhanced cessation for H+ smokers (p = .02) but subsequently impaired cessation regardless of depressive history. Six months after quit date, fluoxetine-treated participants were 3.3 times more likely to be smoking (p = .02). Further research is warranted to determine why high-dose fluoxetine produces continuing effects that oppose tobacco abstinence., (Copyright 2007 APA, all rights reserved.)

The authors compared simultaneous versus sequential approaches to multiple health behavior change in diet, exercise, and cigarette smoking. Female regular smokers (N = 315) randomized to 3 conditions received 16 weeks of behavioral smoking treatment, quit smoking at Week 5, and were followed for 9 months after quit date. Weight management was omitted for control and was added to the 1st 8 weeks for early diet (ED) and the final 8 weeks for late diet (LD). ED lacked lasting effect on weight gain, whereas LD initially lacked but gradually acquired a weight-suppression effect that stabilized (p = .004). Behavioral weight control did not undermine smoking cessation and, when initiated after the smoking quit date, slowed the rate of weight gain, supporting a sequential approach.

Telephone counseling is a popular modality for smoking cessation treatment; however, little attention has been paid to evaluating the efficacy of different contents of calls. This study compared 2 types of proactive telephone calls following a group program. Participants were randomized to receive either: (a) basic content, consisting primarily of support; or (b) enhanced content, tailored to the stage of cessation (still smoking, abstinent, or relapsed) and targeting factors hypothesized to be related to success (motivation, self-efficacy, and negative mood). There was a significant interaction between treatment condition and gender. For men, the enhanced condition produced better abstinence rates through 15 months and lower relapse rates. For women, the basic condition was better. History of depression did not interact with condition.

The authors evaluated the efficacy of fluoxetine hydrochloride (Prozac; Eli Lilly and Company, Indianapolis, IN) as an adjunct to behavioral treatment for smoking cessation. Sixteen sites randomized 989 smokers to 3 dose conditions: 10 weeks of placebo, 30 mg, or 60 mg fluoxetine per day. Smokers received 9 sessions of individualized cognitive-behavioral therapy, and biologically verified 7-day self-reported abstinence follow-ups were conducted at 1, 3, and 6 months posttreatment. Analyses assuming missing data counted as smoking observed no treatment difference in outcomes. Pattern-mixture analysis that estimates treatment effects in the presence of missing data observed enhanced quit rates associated with both the 60-mg and 30-mg doses. Results support a modest, short-term effect of fluoxetine on smoking cessation and consideration of alternative models for handling missing data.

Methods are proposed and described for estimating the degree to which relations among variables vary at the individual level. As an example of the methods, M. Fishbein and I. Ajzen's (1975; I. Ajzen & M. Fishbein, 1980) theory of reasoned action is examined, which posits first that an individual's behavioral intentions are a function of 2 components: the individual's attitudes toward the behavior and the subjective norms as perceived by the individual. A second component of their theory is that individuals may weight these 2 components differently in assessing their behavioral intentions. This article illustrates the use of empirical Bayes methods based on a random-effects regression model to estimate these individual influences, estimating an individual's weighting of both of these components (attitudes toward the behavior and subjective norms) in relation to their behavioral intentions. This method can be used when an individual's behavioral intentions, subjective norms, and attitudes toward the behavior are all repeatedly measured. In this case, the empirical Bayes estimates are derived as a function of the data from the individual, strengthened by the overall sample data.

Random regression models (RRMs) were used to investigate the role of initial severity in the outcome of 4 treatments (cognitive-behavior therapy [CBT], interpersonal psychotherapy [IPT], imipramine plus clinical management [IMI-CM], and placebo plus clinical management [PLA-CM]) for outpatients with major depressive disorder seen in the National Institute of Mental Health Treatment of Depression Collaborative Research Program. Initial severity of depression and impairment of functioning significantly predicted differential treatment effects. A larger number of differences than previously reported were found among the active treatments for the more severely ill patients; this was due, in large part, to the greater power of the present statistical analyses.

A random-effects regression model is proposed for analysis of clustered data. Unlike ordinary regression analysis of clustered data, random-effects regression models do not assume that each observation is independent but do assume that data within clusters are dependent to some degree. The degree of this dependency is estimated along with estimates of the usual model parameters, thus adjusting these effects for the dependency resulting from the clustering of the data. A maximum marginal likelihood solution is described, and available statistical software for the model is discussed. An analysis of a dataset in which students are clustered within classrooms and schools is used to illustrate features of random-effects regression analysis, relative to both individual-level analysis that ignores the clustering of the data, and classroom-level analysis that aggregates the individual data.

A random-effects probit model is developed for the case in which the outcome of interest is a series of correlated binary responses. These responses can be obtained as the product of a longitudinal response process where an individual is repeatedly classified on a binary outcome variable (e.g., sick or well on occasion t), or in "multilevel" or "clustered" problems in which individuals within groups (e.g., firms, classes, families, or clinics) are considered to share characteristics that produce similar responses. Both examples produce potentially correlated binary responses and modeling these person- or cluster-specific effects is required. The general model permits analysis at both the level of the individual and cluster and at the level at which experimental manipulations are applied (e.g., treatment group). The model provides maximum likelihood estimates for time-varying and time-invariant covariates in the longitudinal case and covariates which vary at the level of the individual and at the cluster level for multilevel problems. A similar number of individuals within clusters or number of measurement occasions within individuals is not required. Empirical Bayesian estimates of person-specific trends or cluster-specific effects are provided. Models are illustrated with data from mental health research.

Smokers registering for a televised cessation program who also expressed interest in joining a support group and who had a nonsmoking buddy were randomly assigned to 3 conditions: no-contact control, discussion, and social support. All Ss received a self-help manual and were encouraged to watch the daily TV program. Ss in the discussion and social support conditions were scheduled to attend 3 group meetings (one with a buddy). Social support Ss and buddies received training in support and relapse prevention. A 4th analysis group was composed of Ss who failed to attend any of the scheduled meetings (no shows). There were strong group effects at the end of treatment. Abstinence rates were highest in the social support group, followed, in order, by the discussion group, no shows, and no-contact controls. The social support group improved outcome by increasing both the level of support and program material use (reading the manual and watching TV).