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• W2789510119 abstract "Worldwide, tobacco use is the leading cause of preventable death and illness. One common strategy for reducing the prevalence of cigarette smoking and other health risk behaviors is the use of graphic warning labels (GWLs). This has led to widespread interest from the perspective of health psychology in understanding the mechanisms of GWL effectiveness. Here we investigated differences in how the brain responds to negative, graphic warning label-inspired antismoking ads and neutral control ads, and we probed how this response related to future behavior.A group of smokers (N = 45) viewed GWL-inspired and control antismoking ads while undergoing fMRI, and their smoking behavior was assessed before and one month after the scan. We examined neural coherence between two regions in the brain's valuation network, the medial prefrontal cortex (MPFC) and ventral striatum (VS).We found that greater neural coherence in the brain's valuation network during GWL ads (relative to control ads) preceded later smoking reduction.Our results suggest that the integration of information about message value may be key for message influence. Understanding how the brain responds to health messaging and relates to future behavior could ultimately contribute to the design of effective messaging campaigns, as well as more broadly to theories of message effects and persuasion across domains. (PsycINFO Database Record" @default.
• W2789510119 created "2018-03-29" @default.
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• W2789510119 creator A5089866395 @default.
• W2789510119 date "2018-04-01" @default.
• W2789510119 modified "2023-10-10" @default.
• W2789510119 title "Associations between coherent neural activity in the brain’s value system during antismoking messages and reductions in smoking." @default.
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• W2789510119 doi "https://doi.org/10.1037/hea0000574" @default.
• W2789510119 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5880700" @default.
• W2789510119 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29446965" @default.
• W2789510119 hasPublicationYear "2018" @default.
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