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Abstract
This dissertation aims to identify neural correlates of anti-vaping message processing and examine the potential moderating influence of depression and anxiety symptoms on the relationship between neural activity and subsequent vaping behavior in young adults. Using functional magnetic resonance imaging, regions of interest implicated in visual processing, emotion regulation, and memory formation were functionally identified during exposure to anti-vaping messages. These potential neural markers were then linked to self-report vaping behavior one month following the scan. The dissertation revealed that neural activity in limbic and default mode networks, particularly during cognitive message exposure, was predictive of lower vaping frequency one month later. Moreover, depression symptoms emerged as a significant moderator, indicating that neural activity in the identified regions of interest correlated positively with subsequent vaping frequency among individuals with higher depression symptom scores, while showing a negative correlation among those with lower levels of depression symptoms. Anxiety symptoms did not yield significant moderation results. These findings contribute to our understanding of anti-vaping message processing and underscore the importance of considering individual differences in mental health symptoms in developing targeted interventions for young adult vapers. Moving forward, this study provides a foundation for the development of more effective anti-vaping interventions tailored to the needs of individuals with varying levels of depression symptoms.