Neural Predictors of Vaping: Covert Emotional Engagement Versus Reactance to Overt Emotional Appeals in Vaping Prevention Message Processing.

Abstract

Vaping products are the most widely used tobacco products among young adults in the U.S., driven partly by added flavors that are palatable and misperceived as safe. Vaping prevention public service announcements often use cognitive, emotional, and social appeals, yet little is known about the neurobehavioral mechanisms driving their effectiveness. This study employed functional magnetic resonance imaging to determine whether neural responses to vaping prevention public service announcements in the salience, emotional, cognitive control, and default mode networks predict subsequent vaping and whether these effects vary by message type. Forty-six young adult nonsmokers who vaped ≥15 days during the past month viewed vaping prevention public service announcements during functional magnetic resonance imaging. Public service announcements were adapted from existing campaigns with cognitive, emotional, and social appeals. Subsequent vaping behavior was tracked weekly for 1 month. Data were collected between 2019 and 2022, with formal analyses conducted in 2024. Greater reactivity in the emotional network during public service announcement exposure predicted reduced vaping 1 month later, especially when viewing cognitive and social public service announcement. In contrast, heightened cognitive control network reactivity was linked to increased vaping, driven primarily by responses to emotional public service announcements. Emotional network responses to cognitive and social public service announcements and cognitive control responses to emotional public service announcements may serve as useful and possibly differential neuromarkers of future vaping behavior. Specifically, public service announcements that elicit reflective emotional processing may be more effective than those relying on overt emotional intensity. These findings suggest the utility of functional magnetic resonance imaging in informing optimization of health message design in the evolving nicotine product landscape.