Modulating the neural bases of persuasion: why/how, gain/loss, and users/non-users

I Stephanie Vezich, Perri L Katzman, Daniel L Ames, Emily B Falk, Matthew D Lieberman, I Stephanie Vezich, Perri L Katzman, Daniel L Ames, Emily B Falk, Matthew D Lieberman

Abstract

Designing persuasive content is challenging, in part because people can be poor predictors of their actions. Medial prefrontal cortex (MPFC) activation during message exposure reliably predicts downstream behavior, but past work has been largely atheoretical. We replicated past results on this relationship and tested two additional framing effects known to alter message receptivity. First, we examined gain- vs. loss-framed reasons for a health behavior (sunscreen use). Consistent with predictions from prospect theory, we observed greater MPFC activity to gain- vs. loss-framed messages, and this activity was associated with behavior. This relationship was stronger for those who were not previously sunscreen users. Second, building on theories of action planning, we compared neural activity during messages regarding how vs. why to enact the behavior. We observed rostral inferior parietal lobule and posterior inferior frontal gyrus activity during action planning ("how" messages), and this activity was associated with behavior; this is in contrast to the relationship between MPFC activity during the "why" (i.e., gain and loss) messages and behavior. These results reinforce that persuasion occurs in part via self-value integration-seeing value and incorporating persuasive messages into one's self-concept-and extend this work to demonstrate how message framing and action planning may influence this process.

Keywords: MPFC; action planning; fMRI; message framing; persuasion.

© The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Figures

Fig. 1.
Fig. 1.
(a) MPFC ROI constructed from the region most strongly associated with behavior change in Falk et al. (2010) and used in subsequent studies (Falk et al., 2011, Falket al., 2012; Cooper et al., 2015; Falk et al., 2015) including this one, and (b) rIPL and (c) pIFG ROIs used in this study.
Fig. 2.
Fig. 2.
Sunscreen use increases pre-session to post-session for users and non-users. Note: † P < 0.1, *P < 0.05, **P < 0.01, ***P < 0.001.
Fig. 3.
Fig. 3.
MPFC activity during Whygain and Whyloss messages relative to Fact control messages for non-users vs users. Note: †P < 0.1, *P < 0.05, **P < 0.01, ***P < 0.001.
Fig. 4.
Fig. 4.
Correlation between activity in MPFC during (a) Whygain relative to Fact messages and behavior controlling for intentions, r(34) = 0.34, P = 0.021, and (b) Whygain relative to Whyloss messages and behavior controlling for intentions, r(34) = 0.30, P = 0.036.
Fig. 5.
Fig. 5.
Correlation between activity in MPFC during (a) Whygain relative to Fact messages and behavior controlling for intentions in users, r(16) = −0.070, P = 0.39, vs non-users, r(16) = 0.46, P = 0.027; Zdiff = 1.55, P = 0.061, and (b) Whygain relative to Whyloss messages and behavior controlling for intentions in users, r(16) = −0.23, P = 0.18, vs non-users, r(16) = 0.51, P = 0.015; Zdiff = 2.17, P = 0.015.
Fig. 6.
Fig. 6.
Activity in rIPL and pIFG during How relative to Fact control messages for users vs non-users. Note: † P < 0.1, *P < 0.05, **P < 0.01, ***P < 0.001.
Fig. 7.
Fig. 7.
Activity in MPFC, rIPL, and pIFG during Why relative to How messages.
Fig. 8.
Fig. 8.
Whole-brain activity in (a) MPFC during Why relative to How messages and in (b) rIPL, and pIFG during How relative to Why messages, P < 0.005, k = 78.
Fig. 9.
Fig. 9.
Correlation between (a) activity in rIPL, r(35) = 0.35, P = 0.016, and (b) pIFG, r(35) = 0.28, P = 0.047, during How relative to Fact messages and behavior controlling for intentions.

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