Individual Differences in Brain Responses: New Opportunities for Tailoring Health Communication Campaigns

Abstract

Prevention neuroscience investigates the brain basis of attitude and behavior change. Over the years, an increasingly structurally and functionally resolved “persuasion network” has emerged. However, current studies have only identified a small handful of neural structures that are commonly recruited during persuasive message processing, and the extent to which these (and other) structures are sensitive to numerous individual difference factors remains largely unknown. In this project we apply a multi-dimensional similarity-based individual differences analysis to explore which individual factors—including characteristics of messages and target audiences—drive patterns of brain activity to be more or less similar across individuals encountering the same anti-drug public service announcements (PSAs). We demonstrate that several ensembles of brain regions show response patterns that are driven by a variety of unique factors. These results are discussed in terms of their implications for neural models of persuasion, prevention neuroscience and message tailoring, and methodological implications for future research.

Artificial intelligence for health message generation: an empirical study using a large language model (LLM) and prompt engineering

“…As AI emerged into communication research, especially within the field of CMC, AI-mediated communication arose as a field (Hancock et al, 2020). Similarly, theory and methods from communication and neuroscience are converging, giving rise to the field of communication neuroscience (Huskey et al, 2020;Schmälzle and Meshi, 2020). Together, these three arguments underscore why the nexus of AI and communication is a theoretical wellspring: 3 DL-approaches for text generation help explain a henceforth mystic process and they provide us with a principled approach to generate thousands of novel messages, which we can analyze.…”