Tailoring Tobacco Control: CHAID Decision-Tree Profiles of Ever Quit Attempts Among Current Smokers

Self-reported lifetime quit-attempt history among current smokers may differ across groups defined by psychosocial, economic, motivational, and perceptual characteristics. We aimed to identify cross-sectional profiles associated with ever having made a quit attempt among current smokers and to demonstrate the use of CHAID for transparent exploratory segmentation.

We secondarily analyzed a 2024 interviewer-administered survey of 1,018 current smokers drawn from a sex-stratified non-probability household sample in three Turkish metropolitan areas. Chi-squared Automatic Interaction Detection (CHAID) was applied to measures of sociodemographics, nicotine dependence, motivation, perceived consequences, financial burden, beliefs, and cessation methods; terminal nodes reported quit-attempt prevalence, gain, and index.

Overall, 41.0% had made at least one quit attempt. The CHAID model revealed interpretable exploratory profiles. The highest quit-attempt prevalence appeared among smokers with strong quit motivation and strong financial burden (Node 21 = 89.9%; Gain 19.2%). The largest share of quit attempts clustered among smokers who recognized the need to quit yet endorsed perceived cognitive benefits of smoking (Node 11 = 70.0%; Gain 43.2%), indicating a prominent "motivated cognitive-benefit belief" pattern. Additional subgroups included those who had used herbal remedies (Node 13 = 76.5%) and those with high motivation but low perceived financial burden (Node 20 = 60.9%).

Quit attempts clustered around motivation, perceived financial burden, and co-occurring smoking-related misperceptions. Interpretable decision-tree segmentation may help identify candidate domains for future research on better-aligned brief advice and linkage to evidence-based cessation support, including cost-salient messaging and targeted myth correction.