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Machine learning analysis of vaping dependence (HHS)
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Description: This project consists of three main components. The overarching goal is to develop and validate a machine learning algorithm that is capable of predicting American adolescents’ risk of becoming dependent on e-cigarettes (i.e., vaping) at 6-, 12- and 24-month using routinely collected person-level survey data (Component 1). Using the finalized machine learning algorithm, we will identify and rank the importance of individual risk factors on vaping dependence (Component 2) and demonstrate intersectionality of vaping dependence that points to adolescent subgroups that are particularly susceptible (Component 3).
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