Using neural signatures to predict health behavior change: A mindful distancing intervention to reduce alcohol consumption as a proof of concept
PsyArXiv Preprints July 5, 2026 DOI: osf:7j4ey_v2 (opens in new tab) via PsyArXiv
Summary
AI-generated from the abstractMindful distancing reduced alcohol consumption among college students through two pathways: directly increasing mindful responses to alcohol and indirectly by reducing cravings. A brain-based predictive model (a "neural signature") of mindful distancing, developed using functional neuroimaging and machine learning, tracked moment-to-moment variation in strategy implementation. In the laboratory, mindful attention to alcohol cues decreased craving, especially among those with stronger neural signature expression. In a 28-day smartphone-based experience sampling intervention, individuals with stronger neural signature expression experienced the greatest benefits. The findings extend theoretical models of mindfulness-based emotion regulation for alcohol use in emerging adults without alcohol use disorders.
Study at a glance
| Characteristics | Translational neuroscience study combining fMRI and experience sampling intervention Peer reviewed |
|---|---|
| Population | College students |
| Intervention | mindful distancing intervention |
| Duration | 28-day intervention |
| Topics | Meditation |
| Keywords | Alcohol College Ema Emotion regulation Experience sampling |
| Key finding | Mindful distancing reduced alcohol consumption through direct and craving-mediated pathways, with greater benefits for individuals showing stronger neural signature expression. |
Abstract
Developing interventions to change health behaviors—especially those targeting cross-cutting health risk factors like alcohol use—is a public health priority. In this study, we used a translational neuroscience approach to evaluate the underlying mechanisms and individual differences in a mindful distancing intervention designed to reduce alcohol consumption among college students. We combined functional neuroimaging and machine learning to develop a brain-based predictive model (a “neural signature”) of mindful distancing. This model allowed us to track moment-to-moment variation in how participants implemented the strategy, as well as differences between individuals. Students completed a mindful distancing task involving alcohol cues during fMRI scanning. They then completed a 28-day, smartphone-based, experience sampling intervention. In the laboratory, mindfully attending to alcohol decreased craving, particularly among people who more strongly expressed the mindful distancing signature. In daily life, the mindful distancing intervention increased mindful responses to alcohol and decreased subsequent alcohol consumption through two distinct pathways: mindful responses directly influenced alcohol consumption and indirectly influenced it by reducing cravings for alcohol. Individuals with stronger expression of the neural signature experienced the greatest benefits from the intervention. These findings extend theoretical models of how mindfulness-based emotion regulation strategies impact alcohol use in emerging adults without alcohol use disorders. They also demonstrate the potential of using neural signatures to evaluate health behavior change interventions within a translational neuroscience framework.