Research Publications

Abstract

Background
Binge eating symptoms emerge in early adolescence and are clinically meaningful below diagnostic thresholds. Digital media engagement may be relevant, yet most studies rely on aggregate screen time and rarely separate patterns of use from addiction-like features. This study tested whether screen use profiles and social media addiction risk were associated with binge eating symptom indicators in a large longitudinal cohort.

Methods
Data were drawn from the Adolescent Brain Cognitive Development (ABCD) Study at Time 3 (T3; n = 10,465; ages 10–13 years) and Time 5 (T5; n = 9257; ages 12–16 years). Latent profile analysis of six screen modalities derived screen use profiles. Social media addiction risk was classified using the Social Media Addiction Questionnaire. Four binge eating symptom indicators were assessed at each wave using item-level data from the Kiddie Schedule for Affective Disorders and Schizophrenia. Binomial logistic regression models tested associations, adjusting for sex, family conflict, and school environment.

Results
Two profiles were supported: High Screen Usage (44.5%) and Low Screen Usage (55.5%). At T3, High Screen Usage and higher social media addiction risk were each associated with higher odds of all symptom indicators after adjustment. At T5, High Screen Usage remained associated with binge-related distress, binge eating behaviour, and recurrent binge eating, while social media addiction risk differentiated all four symptoms. Family conflict showed the strongest associations, whereas a more positive school environment was associated with lower odds of symptoms.

Conclusions
Higher overall screen engagement and addiction-like social media use were independently associated with binge eating symptoms across early to mid-adolescence. Social media addiction risk showed more consistent symptom differentiation than screen use profiles, suggesting engagement quality may be more clinically informative than duration.

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Multisite pain is common during adolescence and is influenced by sex-related neurobiological and developmental factors, but its developmental neural mechanisms are unclear.

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Rates of suicidal thoughts and behaviors are increasing among preadolescent children, yet there is a paucity of longitudinal research among this developmental group. This study evaluated prospective associations between current and lifetime psychiatric disorders and first-onset suicidal ideation (SI), first-onset suicide attempts (SA), and the transition from SI to SA over the course of preadolescence, and estimated the prevalence of psychiatric treatment utilization among preadolescents with SI and SA. Data were drawn from the Adolescent Brain Cognitive Development study. Preadolescents ages 9-10 from 21 sites across the country completed follow-up assessments every 12 months. The sample was restricted to preadolescents under age 13 at their two-year follow-up (n = 9940). In multivariate models, current major depressive disorder (MDD OR = 2.14, [95% CI = 1.10-4.15]), obsessive-compulsive disorder (OCD OR = 1.42, 95%CI = [1.12-1.81]), attention-deficit/hyperactivity disorder (ADHD OR = 1.88, [95%CI = 1.49-2.36]), and binge eating disorder (BED OR = 2.42 [95% CI = 1.25-4.72]) were most robustly predictive of first-onset SI. Only lifetime depression predicted first-onset SA (OR = 2.52, [OR = 1.58-4.00]). No disorders predicted the transition from SI to SA. Rates of psychiatric treatment utilization were 29.38% and 53.91% for first-onset SI and SA, respectively. Based on their small effect sizes, MDD, OCD, ADHD and BED may offer modest value in ascertaining risk for SI. Clinicians and researchers may benefit from looking beyond psychiatric disorders to understand risk for SA. Many preadolescents with SI and SA do not present in psychiatric care settings. Widespread risk screenings in other settings (e.g., primary care) may facilitate early detection and reduce the treatment gap for children at risk for SI and SA.

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Precursors of alcohol and cannabis use, such as friend (dis)approval, have rarely been examined in person-centered analyses that can inform tailored prevention, particularly among Black and Latino youth. This study aimed to identify person-centered patterns (classes) of precursors of alcohol and cannabis use in Black and Latino youth, examine correlates across classes, and determine whether the classes predicted positive anticipated effects (expectancies) of alcohol and cannabis one year later.

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Childhood experiences with pain and discrimination can have lasting negative impacts on short- and long-term health outcomes, yet the association between pain and discrimination remains incompletely understood.

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Adolescence is a key period of neurocognitive maturation. Exposure to high levels of air pollutants has been associated with brain differences in youth, though the relevance of these brain findings to behavioral outcomes such as cognitive development is less clear. In this study, we used the US Environmental Protection Agency’s thresholds for unhealthy levels of fine particulate matter (PM), Ozone (O), and NO pollutants to compare youth exclusively exposed to high levels of each pollutant to their respective socioeconomically-matched low-pollution peers over a two-year period in the Adolescent Brain Cognitive Development (ABCD) Study. No youth in the ABCD study were found to be at or above the unhealthy threshold for NO. Multivariate analyses showed a consistent neurocognitive latent variable loading positively on cortical functional maturation and task performance, and negatively on cortical grey matter thickness from 9 to 10-11-12 years of age. We found a significant difference in this neurocognitive maturation latent variable over time between the high-pollution (PM: N = 348, O: N = 355) and control groups (PM2.5: N=279; O3: N=324), such that maturation of cortical networks, increase in task performance, and cortical thinning were significantly higher in the control groups. These results were adjusted for parental income and education and youth’s age, sex, race/ethnicity, site, head-motion, scanner, general factor of psychopathology, pubertal status, and area deprivation index, in addition to the socioeconomic matching between high-pollution and control groups. In conclusion, exposure to high levels of PM and O is associated with lags in normative neurocognitive maturation in early adolescence.

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Early alcohol sipping with permission, here defined as tasting alcohol without necessarily taking a full drink by late childhood with parental permission, is an early marker of future problematic alcohol use. This study aimed to generate an initial data-driven causal model of the potential risk factors underlying early alcohol sipping and probe gender differences in this model.

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Objective
Recreational activities are considered vital for youths’ emotional and cognitive health, yet empirical research examining the specific associations between recreational activities and youth behavioral and cognitive outcomes is limited.

Method
In this cohort study, we applied interpretable machine learning methods, specifically Random Forest paired with SHAP (Shapley additive explanation) analysis, to quantify each activity’s contribution to behavioral and cognitive outcomes in the Adolescent Brain Cognitive Development baseline data (aged 9-10-year-olds). Data-driven activity groups were defined by SHAP contribution patterns for behavioral and cognitive outcomes. Engagement in these groups was then tested for association with the corresponding outcomes using linear mixed-effects models in the hold-out sample, both cross-sectionally and longitudinally.

Results
We identified 14 activities with more favorable and eight with less favorable behavioral patterns, and 13 with more favorable and two with less favorable cognitive patterns. Activities with more favorable behavioral patterns (e.g., skiing/snowboarding) were linked to fewer problems (β = −1.12, p < 0.001), whereas those with less favorable patterns (e.g., martial arts) were linked to more problems (β = 1.75, p < 0.001). For cognition, activities with less favorable patterns (e.g., football) were associated with lower cognitive scores (β=-1.34, p<0.001). While those with more favorable patterns (e.g., musical instruments) were associated with higher scores (β=0.98, p<0.001), and family income moderated this relationship (p<0.001).

Conclusion
Recreational activities exhibit distinct patterns of association with cognitive and mental health outcomes. These data-driven findings highlight the importance of considering individual differences and contextual factors when investigating youth engagement in recreational activities.

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This study aimed to prospectively identify the independent, mutually adjusted, and interactive associations of screen time and physical activity with BMI and overweight/obesity risk in adolescents.

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This study investigates the association between screen time and cognitive function and examines whether putamen volume, which decreases with increased screen time, mediates this relationship.

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Objectives
To characterize cardiovascular health (CVH) among U.S. early adolescents using the American Heart Association’s Life’s Essential 8 (LE8) metric in a large national cohort.

Methods
A cross-sectional analysis of children aged 10–13 years in the Adolescent Brain Cognitive Development (ABCD) Study was conducted, primarily using data from the Year 2 follow-up (2018–2020), with supplemental Year 3 (2019–2021) data to improve completeness of cardiometabolic measures. LE8 behavioral factors scores (diet, physical activity, nicotine exposure, sleep) and health factors scores (body mass index, blood pressure, blood glucose, blood lipids), as well as overall LE8 scores, were calculated. Descriptive statistics were generated, and sex differences were assessed using Mann-Whitney U tests.

Results
Among participants with complete LE8 data (N=1,235; mean age 12.0±0.7 years), the mean overall LE8 score was 78.1±10.4. Most adolescents had moderate (52.9%) or high (46.4%) CVH, while very few had low (0.4%) or optimal (0.3%) CVH. The mean behavioral factors score was 66.8±15.9, and the mean health factors score was 88.1±11.8. Overall LE8 scores did not significantly differ by sex; however, males had higher (better) physical activity and body mass index scores but lower (worse) diet, nicotine exposure, sleep, and blood pressure scores compared with females.

Conclusions
In this national sample of early adolescents, fewer than half demonstrated high CVH based on LE8, and optimal CVH was rare. Poor diet and low physical activity were prominent contributors to suboptimal CVH. These findings highlight early adolescence as a critical window for interventions to improve long-term CVH.

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Sleep plays a foundational role in adolescent development, supporting emotional regulation, cognition and brain maturation. However, adolescents today face increasing challenges to healthy sleep partly due to widespread social media use and heightened reward sensitivity. While each factor has been studied independently, less is known about how they interact, especially whether brain activation shapes how social media influences sleep. We examined prospective associations between self-reported sleep duration, social media use and brain activation in 1985 adolescents (mean age, Year 2 = 11.91 years) from the Adolescent Brain Cognitive Development (ABCD) Study. Sleep duration was measured via the Munich Chronotype Questionnaire; social media use via the Youth Screen Time Survey and brain activity using fMRI during the Monetary Incentive Delay task. We tested three sets of prospective models to examine how sleep, social media use, executive control and reward-related brain activation influence each other over two years, controlling sociodemographics. Greater social media use at Year 2 predicted shorter sleep duration at Year 4, particularly among adolescents with lower activation in the nucleus accumbens, cingulate gyrus, insula and putamen. Shorter sleep also predicted increased social media use two years later, with effects moderated by activation in the insula and middle frontal gyrus. Longer sleep at Year 2 predicted higher caudate activation at Year 4. Brain activation in reward and executive control-related regions moderated associations between sleep and social media use, suggesting that lower neural engagement may reflect increased susceptibility to the sleep-disrupting effects of social media.

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Attention abilities can be represented within the population as a spectrum from low to high ability. Attention deficits are present in a number of neurodevelopmental disorders, including as a primary symptom of ADHD. When evaluating the relationship between brain networks and attention abilities, it is important to know whether this relationship is mediated by diagnosis to understand processes that contribute to disability and to determine if attention can appropriately be studied transdiagnostically. Functional connectivity (FC) within the brain has been studied in association with inhibitory attention and ADHD diagnosis separately, but it is unclear whether the relationship between inhibitory attention and FC is altered in individuals with ADHD.

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Normative modeling of brain development has gained traction for quantifying individual deviations in maturation. The brain age gap (BAG), the difference between predicted age from MRI features and chronological age, offers a potential individualized normative metric of neurodevelopment. However, consistent patterns across psychiatric disorders remain elusive, and no studies have examined whether BAG can predict developmental trajectories within an inclusive continuous model of youth’s cognition and behavior.

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Addictive screen use (ASU), above and beyond screen time, has been linked to significant mental health risks. Yet, little is known about the neural risk factors that may associate with ASU. We examined two neurodevelopmental factors-cognitive control and reward-highlighted in substance use research and their links to ASU.

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There is limited evidence regarding the relationship between the severity of ADHD symptoms and the level of sleep disruption in early adolescent children. This study aimed to better understand this relationship by studying early adolescents from the Adolescent Brain Cognitive Development (ABCD) Study at the 2-year follow-up visit (mean age 12.0,  = 4,414).

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Understand how pubertal progression is associated with physical activity behaviors in adolescent girls.

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Cannabis legalization in the U.S. has introduced an ongoing public health challenge. Among adults, cannabis legalization is associated with increased cannabis use and shifting attitudes toward cannabis use. These expectancies, or personal beliefs about the outcomes of a behavior, are both positive (e.g., increased relaxation) and negative (e.g., cognitive impairment). With rapid shifts in state-level cannabis legislation, the associations of these policies with adolescent cannabis expectancies are unknown.

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Individual differences in neural circuits underlying emotional regulation, motivation, and decision-making are implicated in many psychiatric illnesses. Interindividual variability in these circuits may manifest, at least in part, as individual differences in impulsivity. Impulsivity reflects a tendency towards rapid, unplanned reactions to internal or external stimuli without considering potential negative consequences, coupled with difficulty inhibiting responses. Here, we use multivariate machine learning approaches (brain-based predictive models) to explore the neural bases of impulsivity. We consider multiple impulsivity measures, neuroanatomical features (cortical thickness, surface area, and gray matter volume, as well as non-cortical gray matter volume), and sexes (females and males) in a large sample of youth from the Adolescent Brain Cognitive Development (ABCD) Study at baseline (n = 8630), two-year follow-up (n = 5998), four-year follow-up (n = 4844), and six-year follow-up (n = 3100). Using brain-based predictive models, we demonstrate that regional variations in cortical thickness, surface area, and gray matter volume significantly predict self-reported impulsivity measures, with associations varying across impulsivity dimensions and developmental timepoints. Impulsivity broadly maps onto default mode, limbic, ventral attention, and visual networks, as well as cerebellar and brain stem structures. While many relationships are stable across sexes and developmental time points, others exhibit sex effects and dynamic changes. These results suggest that neuroanatomy is linked to self-reported impulsivity in youth and highlight the complexity of these relationships across measures, features, sexes, and time points. This work also emphasizes the importance of adopting a multivariate and sex-specific approach in neuroimaging and behavioral research.

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Suicidal ideation (SI) significantly increases during the transition from childhood to adolescence, serving as a key predictor of future suicidal behaviors. Despite this, research focusing on preadolescents is scarce and often overlooks immediate risk factors, which hampers the predictive accuracy regarding future suicidality. We examine the dynamic impact of late childhood factors on SI during the transition to early adolescence.

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Sleep behavior markedly shifts in adolescence, increasing vulnerability to mental health disorders. Although sleep health is understood to be multidimensional, adolescent-specific sleep health dimensions have not been empirically validated and their relevance to transdiagnostic mental health outcomes is unknown.

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Executive functioning in children has been linked to intrinsic brain network organization assessed during the resting state, as well as to brain network organization during the performance of cognitive tasks. Prior work has established that task-based brain networks are stronger predictors of behavior than resting state networks, yet it is unclear if tasks only strengthen relationships that exist weakly at rest or if tasks also evoke unique relationships. A lack of discernment regarding how tasks and the resting state commonly and uniquely support executive functions precludes a holistic understanding of the neurobiological basis of executive functions. This project investigated differences in brain network organization and relationships with executive function ability between the resting state and two executive function tasks, a stop signal task and an emotional n-back task, using the Adolescent Brain and Cognitive Development Study dataset. Both executive function tasks evoked a more integrated network organization than the resting state, and executive function ability was related to different aspects of brain network organization during the resting state and during the tasks. Further, task-related shifts in brain network organization evoked several new relationships with executive function that were not detectable during the resting state and strengthened a relationship with executive function that existed weakly during the resting state. Overall, this study establishes a distinction between common and unique features of intrinsic and task-evoked brain function that facilitate executive function in children.

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Evidence on screen time and cognition is mixed, with few longitudinal studies on social media patterns and memory. This study aimed to examine how social media trajectories relate to cognitive performance in early adolescence.

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In recent years longitudinal, multi-site imaging studies have emerged as key tools for investigating brain function. These studies follow a large number of participants for an extended period, offering exciting opportunities to uncover brain functional network changes over time as a function of clinical and demographic covariates. However, these studies also introduce many statistical challenges such as site-effects and accounting for the heterogeneous nature of network differences between subjects. Robust statistical methods are highly needed to address these issues, but to date there has been little methods development addressing these problems in the context of data-driven brain network estimation. This work addresses this gap in the literature, introducing a general Bayesian framework, REMBRAiNDT, incorporating site- and subject-effects into the network decomposition, while also enabling covariate effect estimation and efficient information pooling across brain locations. We use our procedure to conduct a novel analysis of neurodevelopment among adolescents in the longitudinal, multi-site ABCD study. We find extensive evidence of increasing functional integration with age in networks associated with higher order cognitive processes. Our study is one of the first to examine neurodevelopment using blind source separation in the longitudinal ABCD study data, and the findings enrich earlier cross-sectional results on neurodevelopment.

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Child irritability (CI) is a transdiagnostic symptom of multiple psychopathologies, is prospectively associated with negative psychosocial outcomes, and may influence or be influenced by family functioning. The current study assessed bidirectional relations between CI and family conflict (FC) among youth (N = 10,608, M = 9.48 years, 47% female, 49.5% White) and one parent (85.3% mothers) across five years in the Adolescent Brain Cognitive Development study. In latent growth curve models with structured residuals, both boys and girls demonstrated curvilinear changes in FC and CI over time, with increasing and subsequently decreasing CI and the reverse trajectory for FC. Significant bidirectional, prospective associations between FC and CI, however, were only present for girls. Early CI was associated with FC one year later, while girls’ reports of FC were associated with later CI across all timepoints. Findings highlight biological sex as a critical factor influencing associations between family functioning and children’s symptoms.

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This study examined whether the Youth E-cigarette Outcome Expectancies Questionnaire (YEOEQ) measures e-cigarette beliefs consistently with respect to sex, race/ethnicity, and intersectional identity among Black, Latino, and White youth. Inconsistent measurement, or non-invariance, can lead to misleading conclusions about which groups are at higher risk of e-cigarette use. By identifying and adjusting for this bias, we aimed to improve the accuracy of group comparisons.

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Adverse experiences during early life can disrupt gut-brain axis development, but the mechanisms linking early life stress (ELS) to long-term gastrointestinal (GI) dysmotility and pain remain unclear.

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Background
Risks for internalizing behaviors may be moderated by attentional mechanisms such as inhibitory control and attention shifting. However, research is mixed on whether these dimensions are always favorable. Inhibitory control may exacerbate internalizing behaviors through behavioral rigidity, while data suggest that attention shifting is universally protective.

Methods
In a registered report using the Adolescent Brain Cognitive Development Study dataset, Subgrouping Group Iterative Multiple Model Estimation (S-GIMME) was applied to identify data-driven subgroups based on resting state functional connectivity among frontoparietal network (FPN) regions of interest and the amygdala. We then examined subgroup differences and the interaction between subgroup membership and executive functioning (EF) in association with longitudinal changes in internalizing symptoms through adolescence.

Results
Four network-based subgroups were identified. Subgroups with more overall FPN-FPN connections and dorsolateral prefrontal-intraparietal sulcus (dlPFC-IPS) connections showed the highest EF performance relative to subgroups with more amygdala-FPN and inferior temporal gyrus-IPS (ITG-IPS) connections, though only select pairwise comparisons were statistically significant. There were no subgroup differences in internalizing symptoms or interactions with EF. Exploratory analysis found that subgroup differences in inhibitory control were sustained across time, whereby the high FPN-FPN subgroup showed greater improvement across development compared to the ITG-IPS subgroup.

Conclusions
FPN connectivity, particularly involving coupling between the dlPFC and IPS, functions to promote higher inhibitory control and attention shifting across development. However, the mechanistic link between EF and internalizing symptoms remains unclear, underscoring the need for future work that more precisely examines how specific attentional processes can confer risk or resilience for internalizing symptoms.

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Youth with diabetes are at a higher risk for mental health challenges. Despite this awareness, there is much to learn how factors of a child’s environment, such as pet ownership, may promote better diabetes-related health outcomes. This study assessed if pet ownership in diabetic youth was associated with anxiety/depression, parental stress, and A1C, as well as if geographic prevalence of diabetes differed by pet ownership status.

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Pediatric mild traumatic brain injury (mTBI) is a major public health concern. New psychiatric disorders (NPDs) can arise after mTBI, yet postinjury NPDs in nonclinical samples remain poorly understood.

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The current study aims to determine heterogenous latent profiles of substance use perceived harm and examine the concurrent associations between profiles and substance use experimentation.

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ObjectivePrevious research has yielded mixed findings regarding the validity of the Child Behavior Checklist (CBCL) DSM-Oriented Scales (DOSs) in identifying DSM diagnoses. The present study evaluates the concurrent validity of the DOSs by comparing scale classifications with a gold-standard clinical interview.MethodsParticipants ( = 11,851) were children in the NIH Adolescent Brain Cognitive Development (ABCD) study whose caregivers completed the CBCL and the Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS) semi-structured interview at baseline (9.92 years, SD = 0.63), two-year follow-up (12.03 years, SD = 0.67), or both.Results2,321 (19.59%) children at baseline and 1,708 (15.57%) participants at two-year follow-up met criteria for one or more KSADS disorders. Sensitivity of the CBCL relative to KSADS diagnoses was generally low (10.36% – 75.00%), with only two scales above 50%. Specificity was high (92.47% – 97.07%). Positive predictive values were low (0.71% – 48.20%), and negative predictive values were high (89.84% – 99.90%). Area under the curve (AUC) ranged from 0.55 to 0.84.DiscussionIn the present sample, the DOSs showed poor concurrent validity with a gold standard clinical interview. Caution should be exercised when using the CBCL due to the high rates of false negatives.

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Early neurodevelopmental manifestations of genetic vulnerabilities to psychopathology are crucial for understanding disease onset and informing early intervention. However, the timing of when genetic risks begin to manifest in the brain remains unclear.

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Mild traumatic brain injury (mTBI) disproportionately affects children and adolescents and has been associated with poorer neurocognitive performance, but the biological mechanisms driving symptom variability and severity remain understudied. In accordance with the omnigenic disease model, we integrated gene-by-mTBI interaction genome-wide association studies on neurocognition from the Adolescent Brain Cognitive Development (ABCD) cohort with single-cell RNA sequencing gene regulatory networks to elucidate the cell type-specific key regulators and molecular mechanisms governing neurocognitive outcome of mTBI, specifically learning and memory performance. Our analysis revealed distinct network regulators in neuronal and glial cell types across hippocampal and cortical brain regions to orchestrate key neurodevelopmental pathways. Examples include APP for synaptic signaling in excitatory neurons, COX5A for mitochondrial function in inhibitory neurons, MOG for myelination in oligodendrocytes in the hippocampus; GRM7 for synaptic signaling in excitatory neurons, SV2A for synaptic signaling in inhibitory neurons, and MOG for myelination in oligodendrocytes in the cortex. These mechanisms also associate with learning and memory through pathway-based polygenic risk score modeling in ABCD. Our findings provide brain region- and cell type-specific insights into the complex regulatory network landscape of mTBI pathology and potential therapeutic candidates at the pathway and network levels.

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Participation in sports contributes substantially to children’s physical health, psychological well-being, and cognitive development. Despite national initiatives to increase youth sports participation, inequities remain. Socioeconomic disadvantage, racial and ethnic minority status, and other social determinants of health (SDOH) are associated with lower engagement. However, most research addresses isolated factors rather than cumulative neighborhood-level SDOH. This study identified neighborhood SDOH profiles and examined their associations with sports participation.

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Adolescent pain complaints may be related to genetic risk for chronic pain across the life course. Identifying whether adolescent pain is genetically linked to chronic pain in adulthood can advance understanding of pain etiology and inform early intervention. Two waves of pain assessments were used from the Adolescent Brain Cognitive Development (ABCD) study, a population-based sample of 11,876 adolescents with 94.0% retention across waves. The analyses included 6,387 adolescents of European-like ancestry (mean ages = 12.03 and 12.93 at waves 2 and 3; 52% males). Two polygenic scores (PGSs) were constructed using genome-wide association study summary statistics from up to 435,917 adults in the UK Biobank. One PGS captured shared genetic risk across 24 pain conditions (General Chronic Pain), while the second captured additional musculoskeletal-specific genetic risk across 11 conditions after adjusting for general pain (Musculoskeletal-specific Pain). Mixed-effects models were used to examine associations between these PGSs and adolescent self-reported pain presence, intensity, recurrence, and multi-site pain. Across both waves, 36.0%-37.0% adolescents reported pain. The General Pain PGS was associated with pain presence (b=0.07, OR=1.07, 95%CI=1.02-1.13, FDR-corrected p=0.023) and intensity (b=0.14, 95%CI=0.07-0.21, FDR-corrected p<0.001); but not recurrent pain (b=0.08, OR=1.08, 95%CI=1.01-1.16, FDR-corrected p=0.091) or multi-site pain (b=0.01, OR=1.00, 95%CI=0.94-1.07, FDR-corrected p=0.958). The Musculoskeletal-specific Pain PGS was not significantly associated with the outcomes. Genetic risk for chronic pain in adulthood, as measured by PGSs, is associated with adolescent pain complaints. Adolescent pain signals early vulnerability for chronic pain, highlighting adolescence for early intervention. PERSPECTIVE: This study links adolescent pain to polygenic risk for adult chronic pain, suggesting that early pain reflects enduring genetic liability and reflects central pain processes. These results provide mechanistic insight into chronic pain across the lifespan and highlight adolescence as a period for intervention.

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Significant changes occur in brain structure and cognition during adolescence. Investigating their association can provide insight into brain-based cognitive development, yet previous studies are limited by narrow measures, small samples, and lacking focus on age-dependence. Using a large cohort (n = 8534, age 9-15) with structural MRI and diffusion imaging, we derive 16 regional metrics and integrate them via morphometric similarity networks to characterize 16,563 brain features. We apply large-scale models to investigate their associations with seven cognitive subtests and general intelligence (g), as well as age-dependence. Brain areas most strongly associated with cognition also show the greatest age-dependence of the associations, primarily in the frontal, temporal, and occipital lobes. Stronger and more age-dependent associations with cognition are observed for structural MRI measures and global hub measures, compared with diffusion-derived metrics and local measures, respectively. Overall, our study provides a comprehensive and reliable characterization of adolescent brain structure-cognition associations.

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Potentially traumatic events (PTEs) and substance use (SU) are commonly endorsed in early adolescence, a crucial period for neurodevelopment. PTEs and SU are precipitating events in the etiological development of comorbid posttraumatic stress disorder (PTSD) and substance use disorder (SUD). Separately, they have been shown to alter within- and between-network connectivity in the three brain networks posited by Menon’s Theory of Psychopathology: the default mode network (DMN), fronto-parietal network (FPN), and salience network (SN). While comorbid PTSD+SUD in adulthood shows shared neural underpinnings, this is less clear in adolescence. We analyzed the effects of PTEs and SU on resting state functional connectivity (rsFC) in 9-15 year olds from the Adolescent Brain Cognitive Development (ABCD) Study. Fixed effects panel models were fit to assess the effects of PTEs and SU on between-network (FPN-SN rsFC, DMN-SN rsFC, and FPN-DMN rsFC) and within-network (FPN rsFC, SN rsFC, and DMN rsFC) connectivity measured across three timepoints spanning two years. PTEs, SU, and their interaction was not significantly associated with between- and within-network rsFC two years later. No sex specific interactions were observed. Results suggest rsFC changes observed in older adolescents and adults with comorbid PTSD+SUD do not developmentally translate to early adolescents endorsing PTEs+SU. Lack of impact on rsFC may indicate a potential buffer period in which PTEs and SU do not affect rsFC until later in development or after symptom onset following PTEs+SU.

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Many adolescents initiate social media use during early adolescence, but the associations of early social media use with neurodevelopment have not been extensively studied. We utilized neuroimaging data from the U.S. Adolescent Brain and Cognitive Development (ABCD) Study to investigate the association of social media usage (hours per day) or social media addiction (Social Media Addiction Questionnaire) with brain morphology in early adolescence. We analyzed data from 7,614 participants with high-quality structural MRI and complete covariate data at Year 2 (2018-2020, ages 10-13). In addition to pre-defined cortical regions, we performed vertexwise analysis using Fast and Efficient Mixed Effects Algorithm (FEMA), which is unbiased by arbitrary borders between atlas-based brain regions and provides higher spatial resolution. After adjusting for demographics, socioeconomic factors, genetic ancestry, and scanner features, higher average daily social media use was significantly associated with lower total cortical thickness and volume. Region-of-interest (ROI) and vertexwise analysis identified broad regions with lower cortical thickness across the prefrontal cortices, temporal lobe, occipital lobe, and parietal lobe associated with both social media use and social media addiction, which overlap with key nodes of the default mode network, prefrontal executive control networks, and visual processing and attention networks. Social media addiction was not significantly associated with differences in brain morphology in ROI analysis. Our findings in a large nationwide population demonstrate that higher social media usage is associated with variation in cortical morphology, but future studies are required to establish the directionality of this association.

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Accurate brain parcellation from structural MRI across the human lifespan is essential for advancing neuroimaging and neuroscience studies. However, existing methods often struggle to generalize owing to intensity and contrast variations across brain maturation, aging and differences in MRI acquisition protocols, limiting their clinical and research utility. Here we present BrainParc, a unified parcellation framework that leverages anatomical information invariant to intensity and contrast, enabling accurate, robust and longitudinally consistent parcellation across a heterogeneous dataset without the need for fine-tuning. Extensive experiments on both internal and external datasets demonstrate that BrainParc substantially outperforms state-of-the-art methods in delineating 106 brain regions. BrainParc consistently shows better performance across diverse populations and imaging conditions, both quantitatively and qualitatively. Beyond anatomical segmentation, we show that BrainParc enables reliable tracking of brain development and facilitates early diagnosis of neurological disorders, underscoring its potential as a robust and generalizable tool for large-scale neuroimaging studies and clinical translation.

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Attention-deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder characterised by inattention, hyperactivity and impulsivity, resulting in impaired functioning in multiple settings, including home, school and in social settings. Disparities exist in ADHD care among children, with White male children experiencing increased access to diagnosis and treatment. Other children remain underdiagnosed, undertreated and subject to poorer functional outcomes. Factors that impact equitable ADHD treatment include gender, race, ethnicity and social determinants of health (SDOH), including household income, parental education, insurance status, neighbourhood deprivation and discrimination. Medication is effective, yet little is known regarding the impact of medication type and trajectories of use on functional outcomes.

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Insufficient sleep (less than 8 hours for adolescents) has heterogeneous neurobiological underpinnings. Using the SuStaIn model on brain MRI from ABCD Study, we identified three distinct subtypes with reduced cortical thickness, starting from the postcentral, pericalcarine, and entorhinal cortices. The subtypes diverged in sleep-related determinants. The postcentral subtype mirrored the controls of sufficient sleep in sleep behavior and sleep environment and showed no psychiatric comorbidities, which aligned with natural short sleepers (phenotypically normal despite short sleep). Notably, this subtype displayed significantly advanced brain age, and polygenetic score analysis revealed a genetic predisposition for short sleep. The pericalcarine subtype was linked to environmental factors (e.g., light/noise pollution), with sleep duration mediating environmental effects on cortical thinning. The entorhinal subtype showed elevated psychiatric risk, younger brain age, and larger spatial correlations with psychosis-related neurotransmitter systems. This work deciphers the heterogeneous neurobiology of insufficient sleep and offers a framework for stratified interventions.

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Children with ADHD are at increased risk for developing gaming addiction, but the psychosocial mechanisms underlying this relationship remain poorly understood. This study aimed to identify factors that mediate this risk.

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Adolescent e-cigarette use remains an important public health challenge, and evidence on its neurocognitive effects at an early age is limited. This study examined associations between exclusive e-cigarette use and cognitive performance in adolescents.

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Emotion dysregulation (ED) is the inability to modulate the intensity and quality of emotional responses. It is strongly associated with psychopathology among youth, carries significant morbidity and predicts long-term impairments. Data on ED are limited among nonclinical populations. This study aims to estimate the prevalence of ED and to identify its demographic and clinical correlates in children.

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Delay discounting, or the propensity to devalue rewards as the time to reward receipt increases, is a robust predictor of psychiatric and neurodevelopmental outcomes across the life course. However, less is known about environmental antecedents that may be associated with delay discounting tendencies during adolescence, a developmental period during which delay discounting behaviors are still developing. Here, we examined the relation between delay discounting and the exposome—multi-level environmental exposures experienced from conception onwards. Participants included 9,848 children (Mage = 10.94 years, SD = 0.64; 53.2% female; 72% White) from the Adolescent Brain Cognitive Development Study who completed the Adjusting Delay Discounting Task at the 1-year follow-up. Predictors included six exposome factors that captured aspects of proximal and distal environments including: positive day-to-day experiences, family values, household adversity, neighborhood poverty, birth/pregnancy complications, and state-level conservatism/rurality. Greater household adversity, lower positive day-to-day experiences, and greater birth/pregnancy complications were associated with greater delay discounting, after adjusting for age, sex, race, household income and parent education. These findings highlight potential intervention and policy targets aimed at modifying delay discounting preferences in adolescence and reducing risk for negative sequelae across development.

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Sleep disturbances are increasingly recognized as a modifiable factor associated with poor outcomes after mild traumatic brain injury (mTBI) in adults, yet their prevalence, mechanisms, and clinical impact in children remain largely unknown. Identifying whether sleep problems contribute to behavioral, cognitive, and neurobiological outcomes after pediatric mTBI could inform targeted interventions.

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Prenatal alcohol exposure (PAE) is a risk factor for early-onset psychopathology. Low birthweight (LBW), one potential consequence of PAE, increases the vulnerability of children for externalizing disorders. This study investigates potential sex-specific indirect pathways linking PAE to behavioral symptoms in offspring, focusing on LBW as a mediating and moderating factor.

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This study examined sources of heterogeneity in antisocial behaviors in a large-scale and nationally representative sample of n = 7655 youth from the Adolescent Brain and Cognitive Development Study. Separate latent profile analyses were conducted for males and females using indicators of physical aggression, relational aggression, callous-unemotional (CU) traits, and conduct symptom severity. Distinct profiles emerged within each sex. Among females, profiles were primarily differentiated by levels of CU traits, whereas among males, physical aggression played a more central role in distinguishing groups. In both sexes, a higher-risk profile characterized by elevated aggression and/or CU traits was identified alongside a lower-severity marked by minimal conduct problems and aggression. Profiles also differed significantly in overall distress, with the higher-risk male profile demonstrating the greatest distress and the lower-risk female profile the least. Findings highlight meaningful sex-specific configurations of aggression and CU traits and underscore the importance of person-centered, sex-informed approaches to developmental models, assessment, and intervention in youth with antisocial behavior.

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Background
In May 2021, COVID-19 vaccines became available for adolescents aged 12–15. However, safety concerns, misinformation, and politicization surrounding the vaccine left some parents hesitant to vaccinate their children. This study analyzes how media sources and religious affiliation were associated with parental COVID-19 vaccination intent.

Methods
We conducted a cross-sectional analysis of 5552 parents in the May 2021 COVID-19 Rapid Research Response Survey of the Adolescent Brain Cognitive Development (ABCD) study, which collected data on parental intention to vaccinate their children against COVID-19 just before the FDA approved the first vaccine for children aged 12–15. Parental vaccination intent was analyzed by media sources, religious affiliation, and other sociodemographic factors. We also fit a log-binomial regression model to examine the impact of media sources and religious affiliation on parental vaccination intent, controlling for sociodemographic factors.

Results
We found that, compared to parents consuming balanced media sources, parents consuming right-leaning media sources were less likely to plan to vaccinate their children [PR = 0.53 (0.47, 0.6)], while parents consuming left-leaning media sources were not significantly different from parents consuming balanced media [PR = 1.06 (0.99, 1.12)]. We also found differences in vaccination intent by religious affiliation. Compared to Christian parents, Agnostic/Atheist parents were more likely to plan to vaccinate their children [PR = 1.41 (1.35, 1.47)], as were Jewish parents [PR = 1.32 (1.22, 1.43)], and parents with no religious affiliation [(PR = 1.18 (1.14, 1.23)].

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Our study highlights the multifaceted factors influencing vaccine hesitancy among parents of adolescents during the COVID-19 pandemic. To create effective public health strategies for future outbreaks, it is crucial to better understand the complex interplay of religious affiliation and media bias with vaccine hesitancy.

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Adolescent alcohol experimentation is a rising concern given its links to future problematic drug use. Difficulty with inhibitory control (i.e., the ability to suppress unwanted behaviors) is a well-known risk factor for early alcohol use onset. Nevertheless, little is known about the neurobiology of inhibitory control during early development (i.e., preadolescence), especially in relation to minimal early low-level alcohol use. The current study will reveal neural and behavioral differences in inhibitory control that differentiate youth will go on to engage in low-level alcohol experimentation compared with youth who remain alcohol naïve.

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Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by diverse presentations, which complicates the identification of consistent biological markers. This study examined whether integrating multimodal neuroimaging and physical-health measures from a population-based cohort can improve ASD classification and reveal interpretable markers that reflect both clinical and community variation.

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Numerous publications utilize data from the Adolescent Brain and Cognitive Development (ABCD) Study. This review aimed to evaluate how data from the ABCD cohort contributes to understanding the pathophysiology of incipient eating disorders.

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Problematic use of social media (PUSM) is a major public health concern estimated to affect 35% of adolescents. However, data-driven research to identify neural networks predictive of PUSM in adolescents remains limited. The aim of this study was to utilize connectome-based predictive modelling (CPM), a machine-learning approach that employs whole-brain functional connectivity data, to predict PUSM severity and identify underlying neural networks in adolescents. We included 2294 participants from the Adolescent Brain Cognitive Development study (M = 10.03, 50.6% female) who had resting-state functional magnetic resonance imaging (fMRI) data at baseline and PUSM scores at the four-year follow-up. CPM with 10-fold cross-validation was applied to resting-state fMRI data and PUSM scores. CPM successfully predicted PUSM scores and identified connectivity within and between multiple large-scale neural networks predictive of PUSM severity, which could be categorized into two key systems: (i) a cognitive control and self-regulation system consisting of the default mode, frontoparietal, and medial frontal networks, and (ii) a perceptual-motor integration system consisting of the visual area 1 and sensorimotor networks. The large-scale networks identified in the present study provide mechanistic insight into PUSM vulnerability and represent potential targets for personalized interventions. Future research should aim to replicate and extend the current results to refine prevention and treatment approaches.

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Family factors, such as parental symptomatology and parenting behaviors, are related to adolescent internalizing symptoms. Yet fewer studies have evaluated how family factors relate to the emergence of internalizing symptoms during the pubertal transition with large-scale longitudinal data. The present study addressed this issue using data from the Adolescent Brain Cognitive Development Study in adolescents who were prepubertal at baseline and had manifested puberty at 4-year follow-up (N = 2,276). Participants completed the Child Behavior Checklist (CBCL), Adult Self Report (ASR), Child Report of Parenting Behavior Inventory (CRPBI), Parental Monitoring Survey (PMQ), and Family Environment Scale (FES). Structural equation modeling revealed that higher levels of parent internalizing symptoms and parent-reported family conflict at baseline were associated with higher levels of adolescent internalizing symptoms at the 4-year follow-up. Higher baseline parental monitoring was associated with lower adolescent internalizing symptoms at the 4-year follow-up. Baseline parental acceptance and youth-reported family conflict were not related to adolescent internalizing symptoms. Adolescent sex did not moderate any associations in our models. Our results offer insights into how research, prevention, and intervention strategies can be developed to address the development of adolescent internalizing psychopathology.

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Objective
Despite increasing social media use among adolescents, few studies have investigated social media use patterns associated with the social media addiction (SMA) scale. SMA is characterized in terms of social media platforms, engagement patterns, and account settings.

Method
Cross-sectional data on youth ages 10-13 years from the Adolescent Brain Cognitive DevelopmentSM Study (n = 5,639) were used. The majority of the sample was female, White, and from families living above poverty. SMA was assessed via an adapted scale. Regression models assessed links between SMA and hours spent per day on social media, most-used platform, public and secret accounts, and follower and following counts.

Results
SMA was higher among youth whose most-used platforms were TikTok (b = 1.52, 95% CI 1.12, 1.93), Instagram (b = 0.92, 95% CI 0.51, 1.34), and Snapchat (b = 0.60, 95% CI 0.16, 1.03). Those with a public account (b = 0.85, 95% CI 0.56, 1.13), a secret account (b = 2.27, 95% CI 1.65, 2.89), or reporting more social media hours (b = 0.66, 95% CI 0.61, 0.71) had higher SMA scores. Weak interactions between social media hours and platforms were observed.

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Higher SMA scores were most associated with TikTok, Instagram, and Snapchat use as well as using a public account, a secret account, and spending more time on social media. The relationship between social media hours and SMA confirms previous findings. This is the first study to investigate the relationship between account settings and SMA.

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Many psychiatric disorders begin during adolescence, coinciding with the rapid development of brain white matter (WM). However, it remains unclear whether deviations from normal WM development during this period contribute to psychopathology. In this study, we developed normative models of brain age based on specific WM tracts using three large-scale developmental datasets ( ~ 10,000 subjects). We found that tract-specific deviations in WM development of association and limbic/subcortical systems were linked to concurrent and future cognition and psychopathology. The spatial pattern of the association system aligned closely with high-order brain networks and mitochondrial maps. Importantly, delayed brain-age especially in dorsal association tracts predicted psychiatric disorders across diagnoses and disorder onset over a 2-year follow-up. By identifying tract-specific WM development during preadolescence as a predictor of cognitive capacity and psychiatric risks, this study provides a framework for tracking individualized brain development and understanding the neurobiological underpinnings of cognition and transdiagnostic psychopathology.

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Cyberbullying victimization is prevalent and closely linked to mental health problems. However, existing research, often limited by cross-sectional designs and a focus on direct relationships, has yielded inconsistent results. Furthermore, the biological mechanisms underlying the relationship between cyberbullying victimization and psychopathological outcomes remain largely unclear at present.

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Irritability, a form of emotion dysregulation, is a transdiagnostic symptom cutting across internalizing and externalizing problems. Clinical practitioners and parents have expressed concerns about the potential negative impact of screen use on irritability in youth. Despite the significant concerns, no studies have examined the association between screen usage and irritability and its directionality. Using a novel temporal network approach, this study investigated bidirectional associations between irritability and screen time across different activities in preadolescents.

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To investigate sex differences in prospective associations between eating disorder (ED) symptoms and changes in body mass index (BMI) percentile in early adolescence.

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This study examines the association between parental mental health and children’s socioeconomic status (SES) across both home and school environments, using nationally representative data from the Adolescent Brain Cognitive Development (ABCD) Study. Traditional childhood SES markers often focus on parental income, occupational prestige, and maternal education; however, they may not fully capture how children’s proximal experiences of SES differ across daily contexts due to parents’ personal challenges. Employing latent variable path analyses (LVPA), we explored whether parents’ mental health, often a critical aspect of childhood adversity, shapes both home-based and school-based SES. Our findings revealed that poorer parental mental health is significantly linked to more disadvantaged SES in home and school settings. This suggests that parental mental health may affect not only the resources families possess but also the degree to which children benefit from those resources across critical developmental settings. These findings highlight the importance of addressing parental mental health as a key mechanism in understanding and reducing invisible developmental inequality.

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Adolescence is a sensitive period of brain development marked by rapid cortical thinning and increased risk for psychiatric disorders, yet the biological drivers of atypical trajectories remain unclear. Here, using longitudinal data from the Adolescent Brain Cognitive Development Study, we examined whether genetic predisposition to systemic inflammation, indexed by polygenic scores for C-reactive protein (PGS-CRP), influences brain development and psychopathology. Higher PGS-CRP was associated with accelerated cortical thinning, particularly in medial temporal and insular regions, and with increased externalizing symptoms. Early-life infections independently predicted greater depressive and externalizing symptoms but did not interact with genetic risk. Mediation analyses indicated that cortical thinning partially accounted for the association between PGS-CRP and externalizing psychopathology. Biological annotation further identified the regional similarity between cortical effects of PGS-CRP and several neurotransmitter systems. Together, these findings suggest that genetic susceptibility to inflammation may shape adolescent brain maturation and contribute to mental health vulnerability via neuroimmune pathways.

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There is an urgent need to advance understanding of the neural underpinnings of depression, especially early in the life span. Examination of neural dynamics using resting-state functional magnetic resonance imaging (fMRI) data can provide indices of neural flexibility, which may provide important new insights for the neurobiology of pediatric depression. Here we applied Hidden Markov Modeling (HMM) to resting-state fMRI data to investigate neural flexibility in relation to depression and suicidal thinking in children. We utilized data from the Adolescent Brain Cognitive Development℠ Study (ABCD Study), and included data from 10,763 children (9-10 years) who completed two 5-min resting state fMRI scans at the baseline visit. After applying the NeuroMark framework to the data, HMM was applied with a varying number of states; a six-state model was selected from candidate models based on between-scan reliability. We applied linear mixed-effect modeling to test the relationship between two clinical predictors: current major depressive disorder (MDD) diagnosis and presence of suicidal ideation (SI) with our primary outcome for neural flexibility: the frequency of transitions between HMM-derived states (“state-switching”), while including sex, age, and other socio-demographic variables as covariates. Analyses were conducted both with and without correction for head motion. We also explored relationships with total time and dwell time in each state of the six states. Lower state-switching during rest was associated with both MDD and SI, although these findings were no longer significant after correcting for head motion. Notably, state-switching was inversely related to head motion and was higher in females than males. Exploratory analysis showed that MDD was associated with shorter dwell time in one state and longer dwell time in another, suggesting altered temporal persistence of specific neural configurations. Tentative evidence supported our hypothesis that lower state-switching in children with MDD and SI may reflect a reduction in brain flexibility, potentially contributing to a tendency to become “stuck” in negative patterns of thinking and feeling. However, the relatively low frequency of these problems in late childhood reduced statistical power after correcting for motion. Future research is needed to assess these relationships at later adolescent time points, when higher prevalence of depression and SI and lower prevalence of head motion will allow more powerful tests of these associations.

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Emerging evidence suggests regional neuroanatomical variability may be predictive of early alcohol use (before age 15). However, the relationship between whole-brain network organization and early alcohol initiation remains unknown. Using data from the Adolescent Brain Cognitive Development (ABCD) study, we conducted a structural covariance network (SCN) analysis to examine brain network features preceding early alcohol initiation. Structural MRI data collected at baseline (ages 9-10) were used to generate SCNs based on regional cortical thickness measurements. Early alcohol initiation was defined as consuming a full drink between baseline and 4-year follow-up ( ≤ age 15). Participants who reported a full drink of alcohol at baseline, did not participate in the 4-year follow-up, or did not meet imaging quality control criteria were excluded. The remaining participants were compared to a subsample matched at a 1:1 ratio (n = 160 per group). SCN properties, including network segregation (modularity, clustering coefficient), integration (characteristic path length, global efficiency), and resilience (degree assortativity), were compared between groups. While no differences in regional cortical thickness between groups were identified, early initiators demonstrated lower segregation and higher integration compared to non-initiators. These findings suggest that cortical thickness network topology at ages 9-10 may serve as a neuroanatomical risk marker for early adolescent alcohol initiation, independent of prior alcohol exposure, sociodemographic differences, and regional neuroanatomical variability.

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Deviant peer association is a robust risk factor for offending, that is, any behavior that violates a criminal law. This can include behaviors like drug use, violence, and theft; among others. Autism is a neurodivergent condition characterized by both atypical cognitive development and challenges with social interaction and communication. Despite these impairments, there is a dearth of research focused on the relationship between autism and deviant peer association. Relatedly, there exists no research examining the role that dual systems model constructs (sensation-seeking and impulse control) as mediators of this relationship. This study sought to address these gaps in the literature by examining autism as a predictor of deviant peer association in childhood and whether either or both impulse control or sensation-seeking significantly mediate this relationship.

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Characterizing associations between individual differences in brain activity and behavior remains a primary challenge in functional neuroimaging research. A growing literature supports the use of formal computational models to represent the mechanistic processes underlying behavior during cognitive tasks. This study applies one such model to the Adolescent Brain Cognitive Development Study stop-signal task (SST) and quantifies relationships between mechanistic model parameters and task-related brain activation using a machine-learning-based predictive modeling approach. With a large sample of task performance and task-related neuroimaging data from 9- to 11-year-olds (n = 6469), we found that SST formal model parameters showed relatively strong relationships with fMRI task-related activation (average variance explained as high as R2 = 26.86 ± 1.69%) compared with empirically derived performance measures (largest R2 = 20.89 ± 1.41%). Our approach suggests that neuroimaging data are most closely associated with evidence accumulation for the go choice process and with attentional lapses that prevent the initiation of the stop process (“trigger failure”). Increased salience network (i.e., insula and anterior cingulate) activity on correct go trials was associated with worse evidence accumulation, and greater visual cortex activity on error trials was associated with fewer attentional lapses. In addition, through relationships with phenotypic measures of inhibition, impulsivity, and cognition, we provide evidence supporting the formal model’s construct validity. We demonstrate the utility of computational cognitive modeling for revealing stronger, and more meaningful, associations between brain function and behavior.

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Preclinical evidence suggests that intrauterine exposures can impact hypothalamic structure at birth and future disease risk, yet early human data are limited. Because the hypothalamus regulates critical early life processes including sleep, growth, stress regulation, and metabolic control, characterizing its structural maturation and how it relates to developmental conditions and exposures is essential for understanding links to later health.

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There are limited large-scale, prospective analyses examining problematic (addiction-like) screen use and mental and behavioral health outcomes in early adolescents. This study aimed to determine the associations between problematic screen use and mental and behavioral health outcomes-such as depressive symptoms, suicidal behaviors, sleep disturbance, and substance use initiation-1 year later in a national cohort of children aged 11-12 years in the U.S.

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Physical activity and sedentary behavior are associated with adolescent mental health. However, prior studies have not assessed whether these associations differ across varying levels of mental health severity. This study uses objectively measured physical activity and sedentary behavior to examine their associations with adolescent mental health and to determine how these associations vary across the distribution of mental health symptoms.

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Objective
Impulsivity, a key symptom in attention-deficit/hyperactivity disorder (ADHD), is related to maladaptive outcomes longitudinally. Yet relatively little is known about how impulsivity manifests among children with the ADHD primarily inattentive presentation. We sought to address this gap by investigating impulsivity symptoms across all ADHD subtypes and in youth without ADHD. We also examined the association between ADHD symptoms at baseline and maladaptive outcomes measured cumulatively over 4 years.

Method
We examined impulsivity symptoms and maladaptive outcomes measured longitudinally among 5059 youth with complete diagnostic and symptom data, age 9-10 from the Adolescent Brain Cognitive Development℠ (ABCD) Study.

Results
Youth with the ADHD inattentive presentation demonstrated elevated impulsivity relative to typically developing youth across self (Cohen’s d=0.489, 95% confidence interval (CI) [0.40, 0.58], p<0.00001) and parent reports (d=1.40, 95% CI [1.31, 1.50], 95% p<0.00001) as well as decreased performance relative to typically developing youth on measures of impulsivity control (flanker: d=-0.251, 95% CI [-0.35, -0.16], p<0.0001; stop signal task: d=-0.276, 95% CI [-0.38, -0.17], p<0.00001). Among youth with the inattentive presentation, impulsivity measured at study baseline was associated with increased risk for maladaptive outcomes after controlling for hyperactivity and inattentive symptoms.

Conclusion
Impulsivity symptoms among youth with the inattentive ADHD presentation are higher than traditionally conceived. Longitudinal associations between impulsivity and maladaptive outcomes underscores the clinical import of elevated impulsivity symptoms in youth with the inattentive presentations. We highlight the importance of classifying impulsivity symptoms independently of hyperactivity symptoms to facilitate accurate identification of individualized symptom profiles for the purpose of personalized treatment planning and risk evaluation, and to advance future research.

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Low socioeconomic status (SES) is linked to pubertal development, mental health issues, and academic performance. However, the role of early pubertal development in the link between low SES and mental health and academic outcomes is unclear. Using longitudinal data from the ABCD Study (9-10 years at baseline, = 9,848, 52.2% males) across four time points, we examined associations between household and neighborhood disadvantage, pubertal development, and mental health and academic achievement. Greater household and neighborhood disadvantage were associated with more advanced pubertal status at baseline in both males and females. Among females, higher pubertal status at baseline mediated the association between lower household income and neighborhood disadvantage with greater mental health problems and poorer school performance. Additionally, slower pubertal tempo attenuated the relationship between neighborhood disadvantage and these outcomes in females. These findings underscore the importance of considering both household and neighborhood contexts in shaping adolescent development and highlight pubertal development as a potential pathway underlying socioeconomic disparities in mental health and academic achievement.

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Adolescent depression has risen sharply, especially among racial-ethnic minority youth. While racial-ethnic discrimination is known to be linked with depression, there is limited understanding of how individual differences in brain development contribute to this process. Drawing on the framework of adolescent neurobiological susceptibility, this study examined the moderating role of hippocampal volume in the longitudinal association between racial-ethnic discrimination and adolescent depression. Using longitudinal data of racial-ethnic minority youth from the Adolescent Brain Cognitive Development study (n = 5,061, M = 9.93 years; 52% female), we found that racial-ethnic discrimination was associated with adolescents’ increased depression two years later. Notably, a larger left hippocampal volume amplified the link between discrimination and depression. These findings highlight the detrimental role of racial-ethnic discrimination on adolescents’ psychological well-being and suggest that hippocampal volume may serve as a neurobiological marker of susceptibility, amplifying the negative impact of racialethnic discrimination among racial-ethnic minority youth.

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The World Health Organization ranks depression as the leading non-fatal contributor to the global burden of disease. Research shows that early intervention before clinical onset leads to better outcomes. To study depression at this pre-onset stage, risk can be evaluated through depressive prodromal behaviors and associated brain biomarkers. Both environmental and genetic factors independently contribute to depression vulnerability, yet little work has examined how they interact. We therefore examined whether the socioeconomic status (SES) predictor of family income-to-needs ratio (INR) has independent and/or interactive effects with a depression polygenic risk score (D-PRS) on youth behavior and brain structure and function.

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Normative modeling has been applied to study how brain measures, such as gray matter thickness or volume, change across development. These models help identify how an individual’s brain may differ from what is typical for their age or sex, which could eventually support more personalized treatments. However, most existing models use only one-time (cross-sectional) data, meaning they cannot capture how the brain changes over time. Longitudinal data, tracking the same individuals across multiple time points, is more informative but harder and more expensive to collect. We analyzed brain scans from over 6000 young people in the Adolescent Brain Cognitive Development (ABCD) study, about half of whom were girls. Each participant had brain scans at the start of the study, two and four years later. We deployed Baseline-Conditioned Norms (B-Norms) that used cortical thickness derived from each person’s first scan and their ages at baseline and follow-up timepoint to predict cortical thickness at follow-up. We compared this to Cross-Sectional Norms (C-Norm), which only used age to predict thickness at follow-up. As expected, B-Norms predicted cortical thickness more accurately. Importantly, they were also better at detecting brain differences linked to puberty, especially in girls. Our findings suggest that our here proposed B-Norms may capture more developmental variance and may be more sensitive to sex-specific brain development over time during puberty. Therefore, B-norms may constitute a valuable complement to established C-norms.

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Social media exposure may influence early nicotine experimentation, a behavior linked to later nicotine dependence and health risks. Few studies have examined the role of smoking expectancies (i.e., beliefs about the anticipated positive or negative effects of nicotine) as a pathway underlying this association, especially in early adolescence. The objective of this study is to examine the prospective association between social media use and nicotine experimentation in early adolescence, and whether smoking expectancies mediate this relationship.

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The cultural value of familism describes prioritizing family over the individual. Previous evidence supports relations between familism and health behaviors, including sleep. Using data from the Adolescent Brain Cognitive Development Study, this investigation explored associations of parent and adolescent familism and adolescent sleep. The sample included 438 Latino/a parent-adolescent dyads, with youth averaging 11.87 ( = 0.67) years old (assigned female at birth: 49.78%) and parents averaging 40.51 ( = 6.50) years old (female: 90.38%) with a majority identifying as Mexican or Mexican American (parents: 53.83%; youth: 54.51%). Most adolescents were born in the United States or its territories (94.28%). Parents and adolescents independently reported on multiple dimensions of familism, including familism support, familism obligation, and familism referent, which were combined to create an overall familism score. Adolescents wore Fitbit devices that measured objective parameters of sleep including minutes, efficiency, wake after sleep onset, latency, midpoint, and variability in minutes and midpoint. Multiple regression models were fit to determine associations of parent and adolescent familism dimensions with adolescent sleep. Youth obligation and parent support familism were related to more ideal sleep, while youth referent and parent obligation familism were related to less ideal sleep. While some dimensions of familism may pose a risk for poor sleep, others support ideal sleep and should be emphasized within the parent-adolescent relationship. As practitioners and clinicians incorporate cultural sensitivity into their practices and recommendations and families cultivate a supportive environment through familism values, Latino/a youth will be more likely to experience optimal sleep outcomes. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

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Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder. Studies indicate that 20-55 % of individuals with ADHD experience comorbid sleep disturbances, among which, sleep initiation difficulty (SID) is highly correlated with hyperactivity behaviors. However, the underlying neuroimaging mechanisms common to ADHD and sleep initiation difficulty remain poorly understood.

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Neurodevelopmental models regard impulsivity as a central risk factor for adolescent substance use. However, the practical utility of impulsivity in predicting substance use is complicated by variability among measures that encompass multiple methods and theoretical domains. Prior research has been constrained by cross-sectional designs, small sample sizes, and/or the use of a narrow subset of impulsivity measures.

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Depression is shaped by both genetic and environmental factors, but genome-wide interaction studies (GWIS) often lack power to detect complex gene-environment (G × E) interactions. We applied a forest-based machine learning approach to 38,018 UK Biobank (UKB) participants, examining interactions between 285,677 single-nucleotide polymorphisms (SNPs) and three trauma types (childhood, adult, and catastrophic trauma). While GWIS detected no significant interactions, we identified 8,225 potentially important SNP-environment pairs across 1,732 genes, with childhood trauma contributing most prominently. Stratified heritability was higher among childhood trauma-exposed individuals (13.3%) versus those unexposed (6.0%). Many identified genes overlapped with known psychiatric risk loci and accounted for most of the SNP-based heritability. Thirteen top genes were replicated in the Adolescent Brain Cognitive Development Study. Our findings highlight the polygenic G × E nature of depression and the critical role of childhood trauma in modulating genetic risk, demonstrating the value of forest-based methods in detecting complex gene-environment interactions.

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This study relied on previously established factor scores of environmental, education, and socioeconomic-related variables in the Adolescent Brain Cognitive Development Study (ABCD) and their associations with cognitive functioning in youth.

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Social health, having an adequate quantity and quality of social relationships, is essential for well-being but understudied during adolescence compared to adulthood. We sought to identify patterns and predictors of social health by characterizing peer relationships among 10,050 adolescents (10-13 years old, 4,815 girls, 53.68% non-Hispanic White) in Year 2 of the Adolescent Brain Cognitive Development Study. To characterize social health profiles, we applied latent profile analysis on peer variables collected in Year 2: number of friends (close, general), aggression, victimization, relationships with prosocial and rule-breaking peers, and support. We then assessed whether loneliness (baseline, Year 2), family conflict (baseline, Year 2), and participant sex predicted profile membership. Fit indices supported a three-class solution: a “selective” class (∼60% of the sample) characterized by values below sample means but within population norms across variables (e.g., number of friends), a “robust” class (∼30%) characterized by high numbers of friends, and a “concerning” class (∼10%) characterized by high levels of peer aggression and victimization. Lonely adolescents were more likely to be in the concerning group and less likely to be in the robust group. Youth with more family conflict and boys were more likely to be in the concerning group; girls were more likely to be in the selective group. These findings reveal profiles of peer relationships in a large representative sample, providing a template for characterizing social health as adolescents begin to build intimate peer relationships. The results also highlight individual differences in social health profiles, which can inform targets to improve adolescent social health. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

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Household cannabis use is a risk factor for adolescents’ mental health problems. However, little is known about the association of the cessation and psychological impairments in affected adolescents. This study examined the associations of household cannabis cessation and adolescents’ mental health outcomes and potential pathways.

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The environment, especially social features, plays a key role in shaping the development of the brain, notably during adolescence. To better understand variation in brain-environment coupling and its associated outcomes, we identified ”social envirotypes,” or different patterns of social environment experience, in the Adolescent Brain Cognitive Development Study by hierarchically clustering subjects. Two focal clusters, which accounted for 89.3% of all participants, differed significantly on eight out of nine youth-report social environment quality measures, representing almost perfect complements. We then applied tools from network neuroscience to show different social envirotypes are associated with different patterns of whole brain functional connectivity. Differences were distributed across the brain but were especially prominent in Default and Somatomotor Hand systems for these focal clusters. Finally, we examined how social envirotypes change over development and how these patterns of change are associated with a suite of outcomes. The resulting dynamic social envirotypes differed along dimensions of stability and quality, but outcomes diverged based on stability. Altogether, our findings represent significant contributions to both social developmental neuroscience and network neuroscience, emphasizing the variability and dynamicity of brain-environment coupling and its consequences.

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