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Background While campus food pantries have been important safety net programs for alleviating food insecurity among college students, factors related to accessing these vital resources have not been fully researched and summarized. This study systematically synthesized peer-reviewed literature on the predictors, barriers to, and facilitators of using campus food pantries among college students. Methods A search was conducted on PubMed, CINAHL Complete, PsychInfo, PsycARTICLES, and ScienceDirect in April 2023. Included studies needed to be peer-reviewed, written in English, and focused on college or university students. Three authors independently screened all articles retrieved from the five databases based on titles, titles and abstracts, and a full article review. The Study Quality Assessment Tool from the National Heart, Lung, and Blood Institute was used to assess the risk of bias in the included cross-sectional studies. The risk of bias and quality of mixed methods or qualitative studies were assessed as well. Results Eight studies were included in the systematic review. Students likely to use a college food pantry were food-insecure, who most often identified as Asian, Hispanic/Latino, Filipino or Pacific Islander; were first-generation to college; international students; sophomores and juniors; had student loans; were living off-campus; and were without stable housing. Stigma was the most frequently mentioned barrier to using a food pantry. Participants mentioned facilitators such as convenient location and hours of operation, access to fresh produce and nutritious and safe foods, availability of a variety of foods, friendly and helpful service, social support, and awareness of a pantry through fellow students and other members of the university such as staff and faculty. Conclusions Continued research must address students' systemic barriers to accessing food pantries. Campus food pantry leaders, university administrators, and policymakers need to work together to create cost-effective and sustainable solutions that will alleviate the stigma and burden of food-insecure students and provide them with safe, nutritious, and culturally acceptable foods.

As legalization of cannabis products continues, cannabis use becomes more prevalent, and concerns regarding cannabis use disorder (CUD) rise, improving CUD treatment has become increasingly important. Techniques used to regulate emotions, such as cognitive reappraisal, may help manage cravings for cannabis in individuals with CUD. Transcranial direct current stimulation (tDCS), a noninvasive brain stimulation technique, may improve regulation of emotions and reduce substance use. This study aims to determine whether the addition of tDCS to training in cognitive reappraisal leads to greater reductions in cravings and cannabis use than cognitive reappraisal without active stimulation. This longitudinal between-subjects study will recruit 60 participants who will each be randomly assigned to receive either active or sham tDCS. Participants will undergo 5 sessions, each spaced approximately one week apart. In session, they will receive 20 minutes of (active/sham) 1.5mA anodal stimulation over the right dorsolateral prefrontal cortex while receiving training in cognitive reappraisal. Primary outcomes include changes in cannabis use during the study, changes in electroencephalogram brain activity when viewing cannabis cues, and changes in cannabis craving intensity. The results of this study will inform a full-scale randomized controlled trial designed to assess the effectiveness of this intervention. More broadly, these results will add to the literature on the role of tDCS in enhancing CUD treatment. ClinicalTrials.gov NCT06369311.

Binge drinking is associated with numerous negative consequences. The prevalence and intensity of binge drinking is highest among young adults. This randomized trial tested the efficacy of a 12-week interactive text message intervention to reduce binge drinking up to 6 months after intervention completion among young adults. Young adult participants (18-25 y; n = 765) drinking above the low-risk limits (AUDIT-C score >3/4 women/men), but not seeking alcohol treatment, were enrolled from 4 Emergency Departments (EDs) in Pittsburgh, PA. Participants were randomized to one of three conditions in a 2:1:1 allocation ratio: SMS Assessments + Feedback (SA+F), SMS Assessments (SA), or control. For 12 weeks, SA+F participants received texts each Thursday querying weekend drinking plans and prompting drinking limit goal commitment and each Sunday querying weekend drinking quantity. SA+F participants received tailored feedback based on their text responses. To contrast the effects of SA+F with self-monitoring, SA participants received texts on Sundays querying drinking quantity, but did not receive alcohol-specific feedback. The control arm received standard care. Follow-up outcome data collected through web-based surveys were provided by 78% of participants at 3- months, 63% at 6-months and 55% at 9-months. Multiple imputation-derived, intent-to-treat models were used for primary analysis. At 9-months, participants in the SA+F group reported greater reductions in the number of binge drinking days than participants in the control group (incident rate ratio [IRR] 0.69; 95% CI .59 to.79), lower binge drinking prevalence (odds ratio [OR] 0.52; 95% CI 0.26 to 0.98]), less drinks per drinking day (beta -.62; 95% CI -1.10 to -0.15) and lower alcohol-related injury prevalence (OR 0.42; 95% CI 0.21 to 0.88). Participants in the SA group did not reduce drinking or alcohol-related injury relative to controls. Findings were similar using complete case analyses. An interactive text-message intervention was more effective than self-monitoring or controls in reducing alcohol consumption and alcohol-related injury prevalence up to 6 months after intervention completion. These findings, if replicated, suggest a scalable approach to help achieve sustained reductions in binge drinking and accompanying injuries among young adults. ClinicalTrials.gov NCT01688245.

Impairments in gait occur after alcohol consumption, and, if detected in real-time, could guide the delivery of “just-in-time” injury prevention interventions. We aimed to identify the salient features of gait that could be used for estimating blood alcohol content (BAC) level in a typical drinking environment. We recruited 10 young adults with a history of heavy drinking to test our research app. During four consecutive Fridays and Saturdays, every hour from 8 p.m. to 12 a.m., they were prompted to use the app to report alcohol consumption and complete a 5-step straight-line walking task, during which 3-axis acceleration and angular velocity data was sampled at a frequency of 100 Hz. BAC for each subject was calculated. From sensor signals, 24 features were calculated using a sliding window technique, including energy, mean, and standard deviation. Using an artificial neural network (ANN), we performed regression analysis to define a model determining association between gait features and BACs. Part (70%) of the data was then used as a training dataset, and the results tested and validated using the rest of the samples. We evaluated different training algorithms for the neural network and the result showed that a Bayesian regularization neural network (BRNN) was the most efficient and accurate. Analyses support the use of the tandem gait task paired with our approach to reliably estimate BAC based on gait features. Results from this work could be useful in designing effective prevention interventions to reduce risky behaviors during periods of alcohol consumption.

Solitary drinking is a risk marker for alcohol use disorder; thus, it is important to identify why individuals drink alone and for whom this association is particularly relevant. Evidence suggests the desire to ameliorate negative affect (NA) motivates solitary drinking, with some individuals particularly likely to drink alone to cope, but all past studies are cross-sectional. The present study therefore aimed to determine whether 1) experimentally induced NA increased preferences to drink alcohol alone, and 2) whether the relationship between NA and choosing to drink alcohol alone was moderated by neuroticism, drinking to cope motives, and social anxiety. Current drinkers (ages 21-29) with a solitary drinking history (N=126) were randomly assigned to either NA, positive affect [PA], or no affect change (control) conditions via differing cognitive task feedback. After the mood manipulation, participants chose between drinking alcoholic or nonalcoholic beverages in one of two contexts: alone or socially. Evidence regarding effectiveness of the mood manipulation was mixed, and few chose non-alcoholic beverages in either context. Condition did not influence outcome choice. Across conditions, increases in NA and the importance placed on receiving one’s context choice were associated with solitary (versus social) alcohol preference. Neuroticism and its interaction with NA change also influenced choice; individuals high in neuroticism chose more solitary (versus social) drinking contexts while the opposite was true for those low in neuroticism, and among the latter, the preference difference was more pronounced with relatively smaller NA increases. Findings are discussed based on the existing solitary drinking literature.

Digital just-in-time adaptive interventions can reduce binge-drinking events (BDEs; consuming ≥4 drinks for women and ≥5 drinks for men per occasion) in young adults but need to be optimized for timing and content. Delivering just-in-time support messages in the hours prior to BDEs could improve intervention impact. We aimed to determine the feasibility of developing a machine learning (ML) model to accurately predict future, that is, same-day BDEs 1 to 6 hours prior BDEs, using smartphone sensor data and to identify the most informative phone sensor features associated with BDEs on weekends and weekdays to determine the key features that explain prediction model performance. We collected phone sensor data from 75 young adults (aged 21 to 25 years; mean 22.4, SD 1.9 years) with risky drinking behavior who reported their drinking behavior over 14 weeks. The participants in this secondary analysis were enrolled in a clinical trial. We developed ML models testing different algorithms (eg, extreme gradient boosting [XGBoost] and decision tree) to predict same-day BDEs (vs low-risk drinking events and non-drinking periods) using smartphone sensor data (eg, accelerometer and GPS). We tested various \"prediction distance\" time windows (more proximal: 1 hour; distant: 6 hours) from drinking onset. We also tested various analysis time windows (ie, the amount of data to be analyzed), ranging from 1 to 12 hours prior to drinking onset, because this determines the amount of data that needs to be stored on the phone to compute the model. Explainable artificial intelligence was used to explore interactions among the most informative phone sensor features contributing to the prediction of BDEs. The XGBoost model performed the best in predicting imminent same-day BDEs, with 95% accuracy on weekends and 94.3% accuracy on weekdays (F -score=0.95 and 0.94, respectively). This XGBoost model needed 12 and 9 hours of phone sensor data at 3- and 6-hour prediction distance from the onset of drinking on weekends and weekdays, respectively, prior to predicting same-day BDEs. The most informative phone sensor features for BDE prediction were time (eg, time of day) and GPS-derived features, such as the radius of gyration (an indicator of travel). Interactions among key features (eg, time of day and GPS-derived features) contributed to the prediction of same-day BDEs. We demonstrated the feasibility and potential use of smartphone sensor data and ML for accurately predicting imminent (same-day) BDEs in young adults. The prediction model provides \"windows of opportunity,\" and with the adoption of explainable artificial intelligence, we identified \"key contributing features\" to trigger just-in-time adaptive intervention prior to the onset of BDEs, which has the potential to reduce the likelihood of BDEs in young adults. ClinicalTrials.gov NCT02918565; https://clinicaltrials.gov/ct2/show/NCT02918565.

An increasing number of studies have implicated the role of network functional connectivity in addiction. Yet, none have examined functional connectivity as a potential mechanism of adolescent behavior change. We examined the underlying neural mechanism of a promising treatment for adolescents, motivational interviewing (MI). We began by employing psychophysiological interaction (PPI) to evaluate network response in a sample of adolescent cannabis users (N=30). Next, we examined correlations between network connectivity and clinical metrics of treatment outcome. PPI analyses seeded on the orbitofrontal cortex (OFC) showed significant increases in functional connectivity across the inferior frontal gyrus (IFG), precentral gyrus, anterior and posterior cingulate gyrus, supplementary motor area (SMA), superior frontal gyrus, pallidus, caudate, and parahippocampal gyrus. Further, greater functional connectivity between the OFC and anterior cingulate/medial frontal gyrus was associated with less behavior change (e.g., greater post-treatment cannabis problems). These data support the role of the OFC network as a mechanism of adolescent treatment response. •Functional connectivity has been associated with addiction.•We examined functional connectivity as a mechanism of treatment response.•We found network cohesion seeded on the OFC.•OFC functional connectivity was associated with behavior change.

Risk for substance use disorder (SUD) is associated with poor response inhibition and heightened reward sensitivity. During adolescence, incentives improve performance on response inhibition tasks and increase recruitment of cortical control areas (Geier et al., 2010) associated with SUD (Chung et al., 2011). However, it is unknown whether incentives moderate the relationship between response inhibition and trait-level psychopathology and personality features of substance use risk. We examined these associations in the current project using a rewarded antisaccade (AS) task (Geier et al., 2010) in youth at risk for substance use. Participants were 116 adolescents and young adults (ages 12-21) from the University of Pittsburgh site of the National Consortium on Adolescent Neurodevelopment and Alcohol [NCANDA] study, with neuroimaging data collected at baseline and 1 year follow up visits. Building upon previous work using this task in normative developmental samples (Geier et al., 2010) and adolescents with SUD (Chung et al., 2011), we examined both trial-wise BOLD responses and those associated with individual task-epochs (cue presentation, response preparation, and response) and associated them with multiple substance use risk factors (externalizing and internalizing psychopathology, family history of substance use, and trait impulsivity). Results showed that externalizing psychopathology and high levels of trait impulsivity (positive urgency, SUPPS-P) were associated with general decreases in antisaccade performance. Accompanying this main effect of poor performance, positive urgency was associated with reduced recruitment of the frontal eye fields (FEF) and inferior frontal gyrus (IFG) in both a priori regions of interest and at the voxelwise level. Consistent with previous work, monetary incentive improved antisaccade behavioral performance and was associated with increased activation in the striatum and cortical control areas. However, incentives did not moderate the association between response inhibition behavioral performance and any trait-level psychopathology and personality factor of substance use risk. Reward interactions were observed for BOLD responses at the task-epoch level, however, they were inconsistent across substance use risk types. The results from this study may suggest poor response inhibition and heightened reward sensitivity are not overlapping neurocognitive features of substance use risk. Alternatively, more subtle, common longitudinal processes might jointly explain reward sensitivity and response inhibition deficits in substance use risk.

The novel coronavirus pandemic that emerged in late 2019 (COVID-19) has created challenges not previously experienced in human research. This paper discusses two large-scale NIH-funded multi-site longitudinal studies of adolescents and young adults – the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) and the Adolescent Brain Cognitive Development (ABCD) Study – and valuable approaches to learn about adaptive processes for conducting developmentally sensitive research with neuroimaging and neurocognitive testing across consortia during a global pandemic. We focus on challenges experienced during the pandemic and modifications that may guide other projects, such as implementing adapted protocols that protect the safety of participants and research staff, and addressing assessment challenges through the use of strategies such as remote and mobile assessments. Given the pandemic’s disproportionate impacts on participants typically underrepresented in research, we describe efforts to retain these individuals. The pandemic provides an opportunity to develop adaptive processes that can facilitate future studies’ ability to mobilize effectively and rapidly.

Executive functions (EF) are a complex set of neurodevelopmental, higher-ordered processes that are especially salient during adolescence. Disruptions to these processes are predictive of psychiatric problems in later adolescence and adulthood. The objectives of the current study were to characterize the latent structure of EF using bifactor analysis and to investigate the independent and interactive effects of genes and environments on EF during adolescence. Using a representative young adolescent sample, we tested the interaction of a polymorphism in the serotonin transporter gene (5-HTTLPR) and parental supervision for EF through hierarchical linear regression. To account for the possibility of a hierarchical factor structure for EF, a bifactor analysis was conducted on the eight subtests of the Delis-Kaplan Executive Functions System (D-KEFS). The bifactor analysis revealed the presence of a general EF construct and three EF subdomains (i.e., conceptual flexibility, inhibition, and fluency). A significant 5-HTTLPR by parental supervision interaction was found for conceptual flexibility, but not for general EF, fluency or inhibition. Specifically, youth with the L/L genotype had significantly lower conceptual flexibility scores compared to youth with S/S or S/L genotypes given low levels of parental supervision. Our findings indicate that adolescents with the L/L genotype were especially vulnerable to poor parental supervision on EF. This vulnerability may be amenable to preventive interventions. (JINS, 2014, 20, 62–73)