Functional brain imaging predicts public health campaign success

Emily B Falk, Matthew Brook O'Donnell, Steven Tompson, Richard Gonzalez, Sonya Dal Cin, Victor Strecher, Kenneth Michael Cummings, Lawrence An, Emily B Falk, Matthew Brook O'Donnell, Steven Tompson, Richard Gonzalez, Sonya Dal Cin, Victor Strecher, Kenneth Michael Cummings, Lawrence An

Abstract

Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a 'self-localizer' defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400,000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R(2) up to 0.65) and (ii) this relationship depends on message content-self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns.

Keywords: MPFC; fMRI; health communication; media effects; self; smoking.

© The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Figures

Fig. 1.
Fig. 1.
Overview of methods: (a) message design; (b) self-localizer task; (c) ROI identified using the self-localizer task; (d) population-level assessment of messages.
Fig. 2.
Fig. 2.
Neural activity in response to negative images predicts population-level email c through rates. (a) RANK success in the email campaign. Red = negative images; Blue = neutral images; (b) Relationship between MPFC activity and population-level CTR.
Fig. 3.
Fig. 3.
Recruitment diagram. Participants were initially screened via telephone. Of the 77 deemed eligible, 21 were unable to be scheduled. An additional two participants were deemed ineligible by the study team after more detailed screening at appointment 1 and 4 participants failed to attend their scheduled fMRI appointment.
Fig. 4.
Fig. 4.
Neural activity associated with CTR for negative > neutral images. Note: These results correspond to Table 3e. Image thresholded at P < 0.005, k = 36, corresponding to P < 0.05, corrected.

Source: PubMed

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