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Modifying behaviors, such as alcohol consumption, is difficult. Creating psychological distance between unhealthy triggers and one’s present experience can make it easier to change. Using two multisite, randomized experiments, we examine whether theory-driven strategies to create psychological distance—mindfulness and perspective-taking—can change drinking among two samples of young adults without alcohol dependence via a 28-day smartphone intervention (Study 1, N = 108 participants, 5492 observations; Study 2, N=218 participants, 9994 observations). Study 2 presents a close replication with a fully remote delivery during the onset of the COVID-19 pandemic. During weeks when they received daily smartphone reminders, individuals in the psychological distance interventions drank less frequently than control weeks, and less than control participants. Reminders reduced drinking frequency but did not impact amount. Smartphone-based mindfulness and perspective-taking interventions to create psychological distance, can change behavior. However, this approach requires frequent reminders, which can be delivered successfully via mobile phones.

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Mindful attention is characterized by acknowledging the present experience as a transient mental event. Early stages of mindfulness practice may require greater neural effort for later efficiency. Early effort may self-regulate behavior and focalize the present, but this understanding lacks a computational explanation. Here we used network control theory as a model of how external control inputs—operationalizing effort—distribute changes in neural activity evoked during mindful attention across the white matter network. We hypothesized that individuals with greater network controllability, thereby efficiently distributing control inputs, effectively self-regulate behavior. We further hypothesized that brain regions that utilize greater control input exhibit shorter intrinsic timescales of neural activity. Shorter timescales characterize quickly discontinuing past processing to focalize the present. We tested these hypotheses in a randomized controlled study that primed participants to either mindfully respond or naturally react to alcohol cues during fMRI and administered text reminders and measurements of alcohol consumption during 4 wk postscan. We found that participants with greater network controllability moderated alcohol consumption. Mindful regulation of alcohol cues, compared to one’s own natural reactions, reduced craving, but craving did not differ from the baseline group. Mindful regulation of alcohol cues, compared to the natural reactions of the baseline group, involved more-effortful control of neural dynamics across cognitive control and attention subnetworks. This effort persisted in the natural reactions of the mindful group compared to the baseline group. More-effortful neural states had shorter timescales than less effortful states, offering an explanation for how mindful attention promotes being present.

Humans are a fundamentally social species whose well-being depends on how we connect with and relate to one another. As such, scientific understanding of factors that promote health and well-being requires insight into causal factors present at multiple levels of analysis, ranging from brain networks that dynamically reconfigure across situations to social networks that allow behaviors to spread from person to person. The Social Health Impacts of Network Effects (SHINE) study takes a multilevel approach to investigate how interactions between the mind, brain, and community give rise to well-being. The SHINE protocol assesses multiple health and psychological variables, with particular emphasis on alcohol use, how alcohol-related behavior can be modified via self-regulation, and how thoughts, feelings, and behaviors unfold in the context of social networks. An overarching aim is to derive generalizable principles about relationships that promote well-being by applying multilayer mathematical models and explanatory approaches such as network control theory. The SHINE study includes data from 711 college students recruited from social groups at two universities in the northeastern United States of America, prior to and during the COVID-19 pandemic. Participants completed at least one of the following study components: baseline self-reported questionnaires and social network characterization, self-regulation intervention assignment (mindful attention or perspective taking), functional and structural neuroimaging, ecological momentary assessment, and longitudinal follow-ups including questionnaires and social network characterization. The SHINE dataset enables integration across modalities, levels of analysis, and timescales to understand young adults’ well-being and health-related decision making. Our goal is to further our understanding of how individuals can change their thoughts, feelings, and behaviors, and of how these changes unfold in the context of social networks.