OBJECTIVES: A key variable for the design of individual and public health interventions for smoking cessation is Stage of Change, a variable which employs past behavior and behavioral intention to characterize an individual's readiness to change. Reactively recruited samples distort estimates of the stage distribution in the population because such samples attract a disproportionate number of late-stage participants. Three representative samples are described which provide accurate estimates of the stage distribution in the population. These samples are of adequate size to permit within-sample comparisons with respect to sex, age, Hispanic or non-Hispanic origin, race, and education level. The implications of using stage distribution as a tool for planning intervention is discussed. METHOD: The first sample of 4,144 smokers was from the state of Rhode Island and involved a random-digit-dial survey. The second sample of 9,534 smokers was from the state of California and involved a stratified random-digit-dial survey. The third sample of 4,785 smokers was from a total of 114 worksites located in four different geographic locations. RESULTS: The stage distributions were approximately identical across the three samples, with approximately 40% of the sample in Precontemplation, 40% in Contemplation, and 20% in Preparation. The stage distribution was generally stable across age groups with the exception of the 65 years and older group. Education level did affect the stage distribution with the proportion of the sample in Precontemplation decreasing as education level increased. In all three samples, minor differences in stage distribution were related to Hispanic origin and race, but the pattern was not consistent across the samples. CONCLUSIONS: The pattern of stage distribution has important implications for the design of interventions. Existing interventions are most appropriate for the Preparation stage, but the majority of the three samples were in the first two stages, resulting in a likely mismatch between the smoker and the intervention. The stability of distribution across age suggests that interventions that are appropriately matched to stage can be applied across all age groups. The differences found with respect to education, Hispanic origin, and race can serve as a guide to the tailoring of intervention materials.
OBJECTIVES: A key variable for the design of individual and public health interventions for smoking cessation is Stage of Change, a variable which employs past behavior and behavioral intention to characterize an individual's readiness to change. Reactively recruited samples distort estimates of the stage distribution in the population because such samples attract a disproportionate number of late-stage participants. Three representative samples are described which provide accurate estimates of the stage distribution in the population. These samples are of adequate size to permit within-sample comparisons with respect to sex, age, Hispanic or non-Hispanic origin, race, and education level. The implications of using stage distribution as a tool for planning intervention is discussed. METHOD: The first sample of 4,144 smokers was from the state of Rhode Island and involved a random-digit-dial survey. The second sample of 9,534 smokers was from the state of California and involved a stratified random-digit-dial survey. The third sample of 4,785 smokers was from a total of 114 worksites located in four different geographic locations. RESULTS: The stage distributions were approximately identical across the three samples, with approximately 40% of the sample in Precontemplation, 40% in Contemplation, and 20% in Preparation. The stage distribution was generally stable across age groups with the exception of the 65 years and older group. Education level did affect the stage distribution with the proportion of the sample in Precontemplation decreasing as education level increased. In all three samples, minor differences in stage distribution were related to Hispanic origin and race, but the pattern was not consistent across the samples. CONCLUSIONS: The pattern of stage distribution has important implications for the design of interventions. Existing interventions are most appropriate for the Preparation stage, but the majority of the three samples were in the first two stages, resulting in a likely mismatch between the smoker and the intervention. The stability of distribution across age suggests that interventions that are appropriately matched to stage can be applied across all age groups. The differences found with respect to education, Hispanic origin, and race can serve as a guide to the tailoring of intervention materials.
Authors: Janice Y Tsoh; Elisa K Tong; Ginny Gildengorin; Tung T Nguyen; Mary V Modayil; Ching Wong; Stephen J McPhee Journal: Addict Behav Date: 2010-11-27 Impact factor: 3.913
Authors: J B McClure; H Derry; K R Riggs; E W Westbrook; J St John; S M Shortreed; A Bogart; L C An Journal: Contemp Clin Trials Date: 2012-07-04 Impact factor: 2.226