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Demographic variables, smoking variables, and outcome across five studies.
Authors:Wayne F Velicer  Colleen A Redding  Xiaowu Sun  James O Prochaska
Affiliation:Cancer Prevention Research Center, University of Rhode Island, Kingston, RI 02881, USA. velicer@uri.edu
Abstract:OBJECTIVE: Intervention effectiveness can potentially be affected by membership in different demographic subgroups (race, ethnicity, gender, age, and education level) or smoking behavior variables (time to first cigarette, longest previous quit attempt, number of attempts in the past year, number of cigarettes, and stage of change). Previous research on these 2 sets of variables has produced mixed results. DESIGN: This secondary data analysis combined data from 5 effectiveness trials (a random-digit-dial sample [N=1,358], members of an HMO [N=207], parents of students recruited for a school-based study [N=347], patients from an insurance provider list [N=535], and employees [N=175]) in which smokers were all proactively recruited from a defined population and all received the same expert system intervention. The intervention produced a consistent 22% to 26% point prevalence cessation rate across the 5 studies. MAIN OUTCOME MEASURES: The main outcome measures were 24-hr point prevalence, 7-day point prevalence, 30-day prolonged abstinence, and 6-month prolonged abstinence. RESULTS: There were no significant differences in outcome across gender, race, and ethnicity subgroups. There were significant differences and small effect sizes for age and education subgroups. There were significant differences and large effect sizes for all 5 smoking behavior variables. DISCUSSION: Demographic variables are static variables, whereas the smoking variables are more dynamic, that is, open to change. Given the dynamic nature of the smoking variables and the large effect sizes, interventions tailored on the smoking variables should be more successful.
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