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A machine learning approach to identify drivers of e-cigarette dependence Nominated Principal Investigator Michael Chaiton Independent Scientist, Centre for Addiction and Mental Health [email protected] Knowledge User Peter Selby Centre for Addiction and Mental Health Co-investigators Susan J Bondy Adam G Cole Tara E Elton-Marshall Hayley A Hamilton Sean Hill Scott Leatherdale Nikolaos Mitsakakis Robert M Schwartz Wei Wang Project Summary Understanding person-level drivers of current e-cigarette use (vaping) is crucial to guide tobacco policy, but prior studies have not fully identified these drivers due to the reliance on cross-sectional data, small sample sizes in many studies, lack of generalizability, and limitations of traditional data analyses

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Its a different world for filmmakers and cinemagoers alike, with on-screen puffing the exception instead of the rule

While most people are aware of the health risks involved in smoking, few seem to realise that cigarettes are also bad for the environment

Stephanie agrees, drawn to Sofias genuine kindness and warmth