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|Title:||The persuasion network is modulated by drug-use risk and predicts anti-drug message effectiveness||Authors:||Huskey, Richard
Mangus, J. Michael
Turner, Benjamin O.
|Issue Date:||2017||Source:||Huskey, R., Mangus, J. M., Turner, B. O., & Weber, R. (2017). The persuasion network is modulated by drug-use risk and predicts anti-drug message effectiveness. Social Cognitive and Affective Neuroscience, 12(12), 1902-1915. doi:10.1093/scan/nsx126||Series/Report no.:||Social Cognitive and Affective Neuroscience||Abstract:||While a persuasion network has been proposed, little is known about how network connections between brain regions contribute to attitude change. Two possible mechanisms have been advanced. One hypothesis predicts that attitude change results from increased connectivity between structures implicated in affective and executive processing in response to increases in argument strength. A second functional perspective suggests that highly arousing messages reduce connectivity between structures implicated in the encoding of sensory information, which disrupts message processing and thereby inhibits attitude change. However, persuasion is a multi-determined construct that results from both message features and audience characteristics. Therefore, persuasive messages should lead to specific functional connectivity patterns among a priori defined structures within the persuasion network. The present study exposed 28 subjects to anti-drug public service announcements where arousal, argument strength, and subject drug-use risk were systematically varied. Psychophysiological interaction analyses provide support for the affective-executive hypothesis but not for the encoding-disruption hypothesis. Secondary analyses show that video-level connectivity patterns among structures within the persuasion network predict audience responses in independent samples (one college-aged, one nationally representative). We propose that persuasion neuroscience research is best advanced by considering network-level effects while accounting for interactions between message features and target audience characteristics.||URI:||https://hdl.handle.net/10356/106396
|ISSN:||1749-5016||DOI:||http://dx.doi.org/10.1093/scan/nsx126||Rights:||© 2017 The Author(s). Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact email@example.com||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||WKWSCI Journal Articles|
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