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Interplay of Depression, Smoking Intention, and Smoking Behavior in Chinese Dai Adolescents.

Xiang ZhaoGareth DaveyXiangxing Wan
Published in: Journal of addictions nursing (2023)
Tobacco smoking and depression are important contributors to the burden of disease in China, and their onset typically occurs in adolescence. However, there is no consensus on the nature and underlying mechanisms of their interplay, and related studies on Chinese adolescents and ethnic minorities are limited. This study tested the mediation role of depression in the link between smoking intention and behavior in relation to sex. A secondary analysis was conducted on data from a survey of 1,322 Chinese Dai middle school students aged 15-19 years (M = 17.02 years; 773 female students and 542 male students) in Xishuangbanna, China. We found that the mediation role of depression between smoking intention and smoking behavior was nonsignificant, although smoking intention and depression both had significant associations with smoking behavior. Therefore, depression might be better theorized as an underlying predictor of smoking intention or that other volitional factors may link smoking intention and smoking behavior more closely. Nevertheless, depression was a significant independent variable for smoking behavior even when smoking intention was adjusted. Women perceived more depression than men with similar smoking intention levels, yet the relationship between smoking intention and smoking behavior was stronger in men. Although it seems that men were abler to translate their smoking intention into actual smoking, the high level of depression among young women who reported higher levels of smoking intention is noteworthy. Tobacco control for Chinese adolescents could incorporate sex-specific psychological therapies for negative emotions and for the internalization of problems by children.
Keyphrases
  • smoking cessation
  • depressive symptoms
  • physical activity
  • mental health
  • pregnant women
  • metabolic syndrome
  • social support
  • machine learning
  • polycystic ovary syndrome
  • insulin resistance
  • artificial intelligence