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Objective: The health consequences of tobacco smoking disproportionately affect African Americans, but research on whether efficacious interventions can be generalized to this population is limited. This study examined the efficacy of group-based cognitive-behavioral therapy (CBT) for smoking cessation among African Americans. Method: Participants (N = 154; 65% female, M = 44 years old, mean cigarettes/day = 13) were randomly assigned to either (a) group CBT or (b) group general health education (GHE). Participants in both conditions received 6 sessions of counseling and 8 weeks of transdermal nicotine patches. The primary outcome variable was 7-day point prevalence abstinence (ppa), assessed at the end of counseling (2 weeks) and at 3- and 6-month follow-ups. Secondary outcomes included 24-hr ppa and 28-day continuous abstinence (assessed at 3 and 6 months). Results: Intent-to-treat analyses demonstrated the hypothesized effects, such that 7-day ppa was significantly greater in the CBT than the GHE condition at the end of counseling (51% vs. 27%), at 3 months (34% vs. 20%), and at 6 months (31% vs. 14%). Results of a generalized linear mixed model demonstrated a significant effect of CBT versus GHE on 7-day ppa (odds ratio = 2.57, 95% CI [1.40, 4.71] and also an effect of time (p less than 0.002). The Condition x Time interaction was not significant. Similar patterns of results emerged for 24-hour ppa and 28-day continuous abstinence. Results from per protocol analyses (i.e., participants who completed all aspects of the study) corroborate the intent-to-treat findings. Conclusions: These results demonstrate that intensive, group CBT smoking cessation interventions are efficacious among African American smokers. (Contains 1 figure, 2 tables, and 2 footnotes.)

Researchers suggest that culturally specific (CS) interventions are important in addressing smoking-related health disparities. Yet. little research has examined the perspectives of African American smokers regarding these efforts. This qualitative study sought to gain insight into perceptions related to (a) the smoking prevalence among African Americans, (b) smoking-related health disparities, (c) expectancies for CS interventions. (d) methods of recruiting research participants, and (e) key intervention components. Six focus groups were conducted with 41 African American smokers (aged 21-64) at a community health center. Content analyses revealed several themes, including the perception that smoking is normative among African Americans, limited knowledge of racial health disparities, mixed perceptions regarding race as a risk factor for illness, and mixed expectancies for the efficacy of CS interventions. In conclusion, individual differences, such as smoking norms, knowledge of health disparities, and intervention expectations may influence receptivity to CS treatments. Implications for tobacco interventions among African Americans are discussed. Keywords: African American smokers; health disparities; culturally specific interventions; expectancies; qualitative research; focus groups

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.addbeh.2006.03.030 Byline: Ji-Hyun Lee, Thaddeus A. Herzog, Cathy D. Meade, Monica S. Webb, Thomas H. Brandon Keywords: Statistical analysis; Binary longitudinal data; GEE; Tobacco relapse; Relapse-prevention-intervention Abstract: Longitudinal study designs in addictive behaviors research are common as researchers have focused increasingly on how various explanatory variables affect responses over time. In particular, such designs are used in intervention studies that have multiple follow-up points. These designs typically involve repeated measurement of participants' responses, and thus correlation within each participant is expected. Correct inferences can only be obtained by taking into account this within-participant correlation between repeated measurements, which can complicate the analysis of longitudinal data. In recent years, generalized estimating equations (GEE) has become a standard method for analyzing non-normal longitudinal data, yet it often is not utilized by addiction researchers. The goal of this article is to provide an overview of the GEE approach for analyzing correlated binary data for behavioral researchers, using data from an intervention study on the prevention of relapse to tobacco smoking. Author Affiliation: H. Lee Moffitt Cancer Center and Research Institute, The University of South Florida, Tampa, Florida, USA

Relapse prevention remains a major challenge to smoking cessation efforts. T. H. Brandon, B. N. Collins, L. M. Juliano, and A. B. Lazev (2000) found that a series of 8 empirically based relapse-prevention booklets mailed to ex-smokers over 1 year significantly reduced relapse. This study dismantled 2 components of that intervention: the amount of content (number of booklets) and the frequency of contact. Content and contact were crossed in a 2 x 2 factorial design. The criteria of at least 1 week of abstinence at baseline was met by 431 participants, 75%-85% of whom returned 12-, 18-, and 24-month follow-up questionnaires. Eight booklets produced consistently higher point-prevalence abstinence rates than did a single booklet, but frequency of contact did not affect outcome. Moreover, the high-content interventions were highly cost-effective.

A study was conducted to determine whether experimental learning intervention that was based on cognitive dissonance theory would increase the intentions to quit smoking in college students. Manipulation as well as brief experimental intervention could be responsible for increasing the intention to quit smoking among the college students.