Abstract
INTRODUCTION: Lung cancer screening (LCS) combined with smoking cessation intervention is currently recommended for older individuals with a history of heavy smoking. Tailoring tobacco treatment for this patient population of older, people who smoke (PWS) may improve cessation rates while efficiently using limited smoking cessation resources. Although some older people who smoke will need more intensive treatment to achieve sustained abstinence, others may be successful with less intensive treatment. A framework to identify them a priori would be helpful to distribute smoking cessation resources accordingly. METHODS: Baseline demographic, smoking, and health data are reported from a randomized clinical trial of longitudinal smoking cessation interventions delivered in the setting of LCS. Candidate variables were factor analyzed to identify latent factors, or constructs, to identify subgroups of older participants among the heterogenous population of older people who smoke. RESULTS: We identified three factor-derived constructs: self-reported health status, heaviness of smoking, and nicotine dependence. Nicotine dependence was moderately correlated with both of the other two factors. CONCLUSIONS: This factor analysis of baseline participant characteristics identified a set of latent constructs - based on a few practical clinical variables -- that can be used to classify the heterogenous population of older people who smoke to identify. We propose this framework to identify subgroups of people who smoke who might successfully quit with less intense treatment at the time of lung cancer screening.