Mega-analysis on Neural Predictors of Message Effectiveness and Behavior Change
What are the most robust neural correlates of message effectiveness and behavior change across studies?
We are conducting three mega-analytic investigations to identify neural correlates of self-relevance, behavior change, and population-level message effectiveness. In the study, we are aggregating data from 17 different neuroimaging studies (with more studies currently being incorporated) across nine real-life contexts (alcohol use, smoking, physical activity, news sharing, sunscreen use, volunteering, TV ads, movie trailers, and YouTube videos). This work will define neural “signatures” of message effectiveness, which will be applied in future work to predict indicators of message effectiveness in new messages, populations, and cultures, and to inform message development efforts.
In addition to the main mega-analyses described above, we have developed a new fMRI analysis code using open source tools, and are using cutting edge tools such as multivoxel pattern analysis and network analysis methods to answer new questions using these datasets, including how the brain processes self- and other-related thought.
- Scholz, C., Chan, H.Y., Cooper, N., Doré, B.P., O’Donnell, M.B., Lieberman, M.D.,Coronel, J., Genevsky, A., Knutson, B., Venkatraman, V., Vo, K., Boksem, M., Smidts, A., Falk, E.B. (2021, May). Neural correlates of out-of-sample message effectiveness: A mega-analysis of 14 datasets. Annual conference of the International Communication Association, virtual.
- Victoria Romero (CACI International)
DARPA, SocialSim Program
Power of Ideas on the Internet (POINT)
Next Century (Prime) / Falk (Penn PI)
Award Number FA8650-17-C-7712
Photo Credit (top image): Linus Nylund / Unsplash
On This Study
These are the members of our lab involved in this study.