## 3 Results
### Statistical Analysis
A small proportion of this group (4.76%) reported no dependence, reflecting some variability in addiction levels within this cohort. Individuals who smoke both e-cigarettes and traditional cigarettes showed the highest prevalence of dependence, with 50.00% classified as highly dependent and 33.33% moderately dependent. Like e-cigarette users, no respondents in this group reported an absence of dependence, while 16.67% demonstrated low dependence. The average PSECDI scores further illustrate the differences in dependence levels among the groups. Dual users had the highest mean score of 13.50, indicating the most severe dependence on nicotine products. E-cigarette users followed closely with an average score of 13.11, suggesting a significant level of addiction within this group. Traditional cigarette smokers exhibited the lowest mean PSECDI score at 12.05, although this still reflects a considerable degree of dependence. Results showed significant differences in family support (\(p\) = 0.021) and family togetherness (\(p\) = 0.043) among smoking groups. Post hoc comparisons indicated that e-cigarette users reported significantly higher family support than traditional smokers, and significantly greater family togetherness than dual users. No significant differences were observed between dual users and traditional smokers in either dimension. PSECDI scores were highest among dual users (mean = 13.50), followed closely by e-cigarette users (13.11). Traditional smokers had the lowest average dependence (12.05). A one-way ANOVA test confirmed a statistically significant difference in dependence scores between e-cigarette users and traditional cigarette smokers (\(p\) = 0.037). No significant differences were observed between dual users and the other two groups. This study examined the influence of socio-demographic, familial, and behavioral factors on smoking behaviors and cessation attempts, yielding critical insights into underlying patterns and associations (Table 3). Age was found to have a statistically significant relationship with the type of smoking product used (F = 8.787, \(p\) = 0.0003). Additionally, age correlated positively with the age of smoking initiation (\(\rho\) = 0.22546, \(p\) = 0.0241), indicating that older participants tended to start smoking later in life. Gender was also significantly associated with the type of smoking product (\(\chi^{2}\) = 10.63, \(p\) = 0.031). In contrast, education level (\(\chi^{2}\) = 6.41, \(p\) = 0.60111), place of residence (\(\chi^{2}\) = 7.02, \(p\) = 0.53404), and a family history of smoking (\(\chi^{2}\) = 2, \(p\) = 0.36788) showed no significant associations with the type of smoking product used. Behavioral patterns demonstrated critical findings. Nocturnal smoking behavior was significantly correlated with higher smoking frequency (\(\chi^{2}\) = 14.2456, \(p\) = 0.014122). A strong positive Spearman correlation was observed between e-cigarette use and prior conventional smoking (\(\rho\) = 0.67921, \(p\) = 8.0027 \(\times\) 10\({}^{-15}\)), emphasizing a behavioral linkage between these habits. The time to the first cigarette after waking was negatively correlated with willingness to quit smoking (\(\rho=-0.30509\), \(p=0.002\)), indicating that individuals who smoked earlier in the day were less likely to exhibit cessation intent. However, smoking frequency itself showed no significant correlation with the willingness to quit (\(\rho=-0.07068\), \(p=0.4847\)). Familial dynamics were found to play a significant role in smoking behaviors. Family tension correlated positively with the number of cigarettes smoked (\(\rho=0.22\) to \(0.34\), \(p\)-values ranging from \(0.029\) to \(0.001\)).