Assessing teen smoking patterns: the weekend phenomenon.

BACKGROUND: Adolescent cigarette smokers may have more daily variability in their smoking patterns than adults. A better understanding of teen smoking patterns can inform the development of more effective adolescent smoking cessation interventions. METHODS: Teen smokers seeking cessation treatment (N=366) reported the number of cigarettes smoked on each day of a typical week. A paired t-test was used to examine differences between weekday (Sunday-Thursday) and weekend (Friday-Saturday) smoking. Main effects and interactions for race/ethnicity and gender were assessed using a 2-way ANOVA for the following variables: typical weekly smoking, average weekday smoking, average weekend smoking, and difference between weekday and weekend smoking. Scheffé post hoc tests were used to analyze any statistically significant differences. RESULTS: There was significantly more weekend smoking compared to weekday smoking, p<0.001. The difference in weekday versus weekend smoking levels was larger for females than for males, p<0.05. Hispanics reported less typical weekly smoking, p<0.001, less weekday smoking, p<0.001, and less weekend day smoking, p<0.01, compared to Caucasians and multi-racial teens. There was no difference in weekend day versus weekday smoking by race/ethnic background. CONCLUSIONS: Using a more detailed assessment of smoking quantity captures patterns of adolescent smoking that may lead to more effective smoking cessation interventions.

Using treatment process data to predict maintained smoking abstinence.

OBJECTIVES: To identify distinct subgroups of treatment responders and nonresponders to aid in the development of tailored smoking-cessation interventions for long-term maintenance using signal detection analysis (SDA). METHODS: The secondary analyses (n = 301) are based on data obtained in our randomized clinical trial designed to assess the efficacy of extended cognitive behavior therapy for cigarette smoking cessation. Model 1 included only pretreatment factors, demographic characteristics, and treatment assignment. Model 2 included all Model 1 variables, as well as clinical data measured during treatment. RESULTS: SDA was successfully able to identify smokers with varying probabilities of maintaining abstinence from end-of-treatment to 52-week follow-up; however, the inclusion of clinical data obtained over the course of treatment in Model 2 yielded very different partitioning parameters. CONCLUSIONS: The findings from this study may enable researchers to target underlying factors that may interact to promote maintenance of long-term smoking behavior change.