Smoking and stress: Exploring patterns among high school youth in Bulgaria
Bulgaria is a country with strikingly high death rates due to stroke, heart disease and different types of cancer. No serious attempt at dynamic analysis of the behavioral factors contributing to these high disease rates exists. These facts underline the importance of this study. ^ The project had three goals: (1) Measurement development and validation of smoking cessation, smoking prevention and stress measures for Bulgarian adolescents; (2) exploration of factors associated with smoking cessation and prevention in the same population; (3) applied comparison of logistic regression analysis and discriminant function analysis for models with binary outcomes. In the total sample recruited from 12 Bulgarian high schools (N = 673), 276 (41.0%) participants were smokers and quitters and 369 (54.8%) were nonsmokers. Measures with good psychometric properties were developed for decisional balance and self-efficacy for smoking cessation and prevention and the validity of these TTM constructs for Bulgarian adolescents was supported. Two stress measures were also validated. ^ A series of logistic regression and discriminant function analyses explored the factors associated with smoking behavior. Smoking status was operationalized in several ways in an attempt to differentiate between the factors related to smoking initiation, progression to regular smoking and smoking cessation. Attitude towards smoking bans was the single predictor retained across all models. In addition factors that differentiated between current smokers and ex-smokers were age, smoking status of family members and temptation to smoke. Nonsmokers at risk were differentiated from committed nonsmokers by scores on pros of staying smoke free, temptations and belief that smoking is harmful to health. Variables that distinguished between smokers and nonsmokers were age, GPA, smoking status of sibling and friends and beliefs that smoking is harmful to health. No support for relationship between levels of perceived stress and smoking was discovered, contrary to expectations. ^ Logistic regression and discriminant function analysis on data with binary outcomes resulted in models with comparable overall classification rates. For models with very different group sample sizes and equal prior probabilities the logistic regression models had lower sensitivity. The logistic regression procedure demonstrated more sensitivity to the choice of classification threshold than DFA did in these data. ^
Health Sciences, Public Health|Psychology, Clinical
Milena D Anatchkova,
"Smoking and stress: Exploring patterns among high school youth in Bulgaria"
Dissertations and Master's Theses (Campus Access).