4% and 30.3%, respectively). Similarly, higher prevalence of smoking in girls is detected in the majority (60%) of countries involved in the European School Survey Project on Alcohol and Other Drugs including Hungary www.selleckchem.com/products/Pazopanib-Hydrochloride.html (Hibell et al.), and this difference is also presented in the most recent National Report of Global Youth Tobacco Survey (Demj��n et al.). Confirmatory factor analysis Although CFA analysis resulted in a significant chi-square value ��2 = 1,417, df = 183, p < .0001, all of the other fit indices showed adequate fit: CFI: 0.954, TLI: 0.947, RMSEA: 0.051 (0.049�C0.054), and SRMR: 0.033. Inspection of the modification indices has revealed, however, that freeing the covariance between errors of two items would increase the degree of fit.
These items (��When I��m angry a cigarette can calm me down�� and ��Smoking calms me down when I feel nervous��) are strongly related in content, emphasizing the calming effect of smoking. After we freed the covariance, the fit indices indicated significantly better fit: ��2 = 1,041, df = 182, p < 0.0001; CFI: 0.968, TLI: 0.963, RMSEA: 0.043 (0.040�C0.045), and SRMR: 0.031. In this latter model, all of the items have factor loadings above 0.74, as presented in Table 1. We also performed a multigroup CFA in order to test the fit of the model in both smokers and nonsmokers. The fit indices show adequate fit ��2nonsmokers(398) = 943; ��2smokers(398) = 527; CFI: 0.954, TLI: 0.952, RMSEA: 0.046 (0.043�C0.048), and SRMR: 0.042. Table 1.
Short form of Smoking Consequences Questionnaire��Adolescent: Item and scale information Concurrent criterion validity of smoking outcome expectancies We also tested the concurrent validity of scales with multigroup structural equation modeling in which the outcome variable was the smoking status and the grouping variable was gender. The multigroup SEM revealed an adequate fit of the model in which factor loadings and regression coefficients were allowed to vary across the two groups ��2boys(474) = 687; ��2girls(474) = 588; CFI = 0.979, TLI = 0.977, RMSEA = 0.039. The estimated correlation between latent variables and smoking, and standardized regression coefficients predicting smoking status, are presented in Table 2. Negative and positive reinforcement predicts smoking status strongly in both boys and girls and the sizes of standardized regression coefficients are very similar in both groups.
There are, however, dissimilarities that deserve attention. On the one hand, negative consequences predict lower probability Dacomitinib of smoking in girls only. This result suggests that expectancies of negative consequences can be protective in girls but not in boys. On the other hand, appetite and weight control expectancies are negatively but weakly related with smoking in boys and unrelated to smoking in girls.