Associations between coherent neural activity in the brain's value system during antismoking messages and reductions in smoking

Face Value: Remote facial expression analysis adds predictive power to perceived effectiveness for selecting anti-tobacco PSAs

Perceived effectiveness (PE) is a validated tool for predicting the potential impact of anti-tobacco public service announcements (PSAs). We set out to evaluate the added predictive value of facial expression analysis when combined with PE in a remote (online) survey. Each of 302 tobacco users watched 3 PSAs and allowed transmission of webcam videos from which metrics for "attention" (head position) and "facial action units" (FAU) were computed. The participants completed scales for their subjective emotions, willingness to share on social media, and intention to quit smoking using the Tobacco Free Florida website. Based on PE, both ready to quit (RTQ) and not ready (NR) respondents favored the same PSAs but RTQs assigned higher PE scores. Negative PSAs ("sad" or "frightening") were more compelling overall but RTQs also favored surprising ads and were more willing to share them on social media. Logistic regression showed that the combination of Attention + FAU+ PE (AUC = .816, p < .0001) outperformed single factors or factor combinations in distinguishing RTQ from NR. This study demonstrates that on-line assessment of facial expressions enhances the predictive value of PE and can be deployed on large remote samples.

Neural activity in self-related brain regions in response to tailored nutritional messages predicts dietary change

Overweight and obesity have become international public health problems, so there is an urgent need to implement effective interventions that prevent these concerning health issues. Designing personalized (tailored) dietary communications has become one of the most effective tools in reducing unhealthy eating behavior, when compared with one-size-fits-all messages (untailored). However, more research is required to gain a complete understanding of the underlying mechanisms by which tailored nutritional messages elicit reductions in unhealthy dietary behavior. To the best of our knowledge, our study may be the first to use neuroimaging, namely functional magnetic resonance imaging (fMRI), aiming to evaluate the neural basis of tailored and untailored nutritional messages and assess how these neural responses predict unhealthy food intake reduction after a month receiving tailored nutritional messages. To that goal, 30 participants were scanned while reading tailored and untailored nutritional messages. Subsequently, for a month, they received tailored interventions encouraging healthy food intake. The neural findings reveal that when compared to untailored communications, tailored messages elicit brain networks associated with self-relevance, such as the precuneus, the middle temporal gyrus, the hippocampus, the inferior orbitofrontal cortex (OBC), the dorsomedial prefrontal cortex (dMPFC), and the angular gyrus. Interestingly, among these self-related brain areas, the dMPFC, OFC, angular gyrus, and hippocampus forecast reductions in unhealthy food intake after a one-month tailored intervention for the cessation of unhealthy eating. These results may offer implications for clinicians, practitioners, and/or policymakers who should implement substantial efforts in creating individualized campaigns focused on their target's perceived needs, goals, and drivers in relation to eating healthy to reduce overweight issues. This research therefore constitutes a step forward in showing a direct association between the neural responses to tailored nutritional messages and changes in real-life healthy eating behavior.

Time-evolving dynamics in brain networks forecast responses to health messaging

Neuroimaging measures have been used to forecast complex behaviors, including how individuals change decisions about their health in response to persuasive communications, but have rarely incorporated metrics of brain network dynamics. How do functional dynamics within and between brain networks relate to the processes of persuasion and behavior change? To address this question, we scanned 45 adult smokers by using functional magnetic resonance imaging while they viewed anti-smoking images. Participants reported their smoking behavior and intentions to quit smoking before the scan and 1 month later. We focused on regions within four atlas-defined networks and examined whether they formed consistent network communities during this task (measured as allegiance). Smokers who showed reduced allegiance among regions within the default mode and fronto-parietal networks also demonstrated larger increases in their intentions to quit smoking 1 month later. We further examined dynamics of the ventromedial prefrontal cortex (vmPFC), as activation in this region has been frequently related to behavior change. The degree to which vmPFC changed its community assignment over time (measured as flexibility) was positively associated with smoking reduction. These data highlight the value in considering brain network dynamics for understanding message effectiveness and social processes more broadly.