Using the Stages of Change Model to Choose an Optimal Health Marketing Target

Background: In the transtheoretical model of behavior change, “stages of change” are defined as Precontemplation (not even thinking about changing), Contemplation, Preparation, Action, and Maintenance (maintaining the behavior change). Marketing principles suggest that efforts should be targeted at persons most likely to “buy the product.” Objectives: To examine the effect of intervening at different stages in populations of smokers, with various numbers of people in each “stage of change.” One type of intervention would increase by 10% the probability of a person moving to the next higher stage of change, such as from Precontemplation to Contemplation. The second type would decrease by 10% the probability of relapsing to the next lower stage, such as from Maintenance to Action, and also of changing from Never Smoker to Smoker. Nine hypothetical interventions were compared with the status quo, to determine which type of intervention would provide the most improvement in population smoking. Methods: Three datasets were used to estimate the probability of moving among the stages of change for smoking. Those probabilities were used to create multi-state life tables, which yielded estimates of the expected number of years the population would spend in each stage of change starting at age 40. We estimated the effect of each hypothetical intervention, and compared the intervention effects. Several initial conditions, time horizons, and criteria for success were examined. Results: A population of 40-year-olds in Precontemplation had a further life expectancy of 36 years, of which 26 would be spent in the Maintenance stage. In a population of former and current smokers, moving more persons from the Action to the Maintenance stage (a form of relapse prevention) decreased the number of years spent smoking more than the any other intervention. In a population of 40-year-olds that included Never Smokers, primary smoking prevention was the most effective. The results varied somewhat by the choice of criterion, the length of follow-up, the initial stage distribution, the data, and the sensitivity analyses. Conclusions: In a population of 40-year-olds, smokers were likely to achieve Maintenance without an intervention. On the population basis, targeting quitters and never-smokers was more effective than targeting current smokers. This finding is supported by some principles of health marketing. Additional research should target younger ages as well as other health behaviors

Predictors of Childhood Exposure to Parental Secondhand Smoke in the House and Family Car

Childhood exposure to secondhand smoke (SHS) is a serious threat to public health and can be influenced by parental lifestyle habits and beliefs. Taking the above into account we aimed at locating predictors of parental induced exposure to SHS in the house and family car among 614 children who visited the emergency department of two large pediatric hospitals in Athens, Greece. The multivariate analysis revealed that the factors found to mediate household exposure to paternal SHS were the number of cigarettes smoked per day (O.R 1.13, p<0.001) while, having a non-smoking spouse had a protective effect (O.R 0.44, p=0.026). Maternally induced household SHS exposure was related to cigarette consumption. For both parents, child exposure to SHS in the family car was related to higher numbers of cigarettes smoked (p<0.001), and for fathers was also more often found in larger families. Additionally, lower educated fathers were more likely to have a spouse that exposes their children to SHS inside the family car (O.R 1.38 95%C.I: 1.04–1.84, p=0.026). Conclusively, efforts must be made to educate parents on the effects of home and household car exposure to SHS, where smoke free legislation may be difficult to apply

Peer Pressure, Psychological Distress and the Urge to Smoke

Background: Psychology and addiction research have found that cigarette smokers react with subjective and automatic responses to stimuli associated with smoking. This study examines the association between the number of cigarettes smokers consume per month and their response to cues derived from peer and psychological distress. Methods: We studied 1,220 adult past and current smokers drawn from a national face-to-face interview survey administered in 2004. We defined two types of cues possibly triggering a smoker to have a cigarette: peer cues and psychological cues. We used ordinary least square linear regressions to analyze smoking amount and response to peer and psychological distress cues. Results: We found a positive association between amount smoked and cue response: peer cues (1.06, 95%CI: 0.74-1.38) and psychological cues (0.44, 95%CI = 0.17-0.70). Response to psychological cues was lower among male smokers (–1.62, 95%CI = –2.26- –0.98), but response to psychological cues were higher among those who had senior high school level educations (0.96, 95%CI = 0.40-1.53) and who began smoking as a response to their moods (1.25, 95%CI = 0.68-1.82). Conclusions: These results suggest that both peer cues and psychological cues increase the possibility of contingent smoking, and should, therefore, be addressed by anti-smoking policies and anti-smoking programs. More specifically, special attention can be paid to help smokers avoid or counter social pressure to smoke and to help smokers resist the use of cigarettes to relieve distress

LGBT community, social network characteristics, and smoking behaviors in young sexual minority women.

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106605/1/LGBT community, social network characteristics, and smoking behaviors in young sexual minority women.pd

Smoking cessation patterns by socioeconomic status in Alaska

The ongoing disparity in smoking prevalence across levels of socioeconomic status (SES) is a significant concern in the tobacco control field, and surveillance of cessation-related activity is key to understanding progress. Historically, lower SES smokers have had much lower quit ratios but this measure can be insensitive to recent quit-related behavior. It is therefore important to examine recent quit-related behavior to assess progress toward addressing this disparity, especially in states with tobacco control programs that focus on this priority population.We compared recent quit attempts and successes among non-Native lower SES Alaska smokers to those of higher SES using data from the 2012–2013 Alaska Behavioral Risk Factor Surveillance System (BRFSS). We assessed quit ratios, one-year and five-year quit rates, and six-month abstinence between the two groups.Cessation-related measures restricted to those who smoked in the previous one year did not significantly vary by SES. However, five year quit rates were significantly lower for persons of lower SES vs. higher SES (14% vs. 32% respectively, p < .001). Results were consistent after adjustment for age, sex, and other factors.Results showed that in the previous year, smokers of lower SES in Alaska were trying to quit and succeeding at similar rates as their higher SES counterparts. However, the equivalent pattern of quit success was not reflected in the five-year time frame. Tobacco control programs should monitor cessation trends using both recent and longer-term time frames for this population. More research is needed on reasons for fewer long-term quits among lower SES smokers. Keywords: Smoking/epidemiology, Smoking/prevention and control, Smoking cessation, Social class, Socioeconomic factor