Predicting the rate of cigarette smoking based on resilience and cognitive emotion regulation in the non-clinical population of Shiraz, Iran, 2016

Background: Cigarette smoking is considered a public health problem. Much research has been conducted on smoking and respective factors, but little research has addressed the prediction of the smoking rate based on various psychological variables. The present study was conducted aimed at predicting the smoking rate in the non-clinical population of Shiraz, Iran, in 2016, based on resilience and cognitive emotion regulation. Materials and methods: In the present descriptive study, 250 female and male smokers of the non-clinical population of Shiraz, Iran, in 2016, were selected through random sampling. The research instruments included a demographic scale and smoking patterns, the Connor-Davidson Resilience Scale (CD-RISC), and the Cognitive Emotion Regulation Scale. The obtained data were analyzed by the Pearson correlation and linear regression, using SPSS (Version 20(. Results: The results showed a negative correlation between the subscales of resilience and cognitive emotion regulation, age, and education with the cigarette smoking rate (P<0.01). In addition, the values of R and R2 were 0.39 and 0.15, respectively. The daily smoking rates can be predictable with resiliency, cognitive-emotional regulation sub-scales, age, and education variables (0/015). Conclusion: Some psychological variables, such as resilience and cognitive emotion regulation probably affect the tendency to cigarette smoking, so considering these variables could be efficient in the interventions for preventing and stopping cigarette smoking.