Commercial Cannabidiol for Community-Based Young Adolescents: Predicting Medicinal Use.

Objectives: Cannabidiol (CBD) is rising in popularity, including as a potential medicinal product. Yet data on use of commercial CBD for medicinal or health reasons in adolescents are lacking. In this study we aim to detail characteristics of adolescents given commercial CBD for health reasons (health CBD [hCBD]) and to investigate predictors of use. Materials and Methods: The Adolescent Brain Cognitive Development (ABCD) Study is a population-based cohort study following U.S. healthy, community-based adolescents annually, with data from 2018 to 2022 (11- to 15-year-olds; N=11,189). Participants and caregivers completed questionnaires, including whether adolescents were given CBD with parent or doctor's permission. Participants reported past-month pain, attention problems, externalizing symptoms, internalizing symptoms, and total mental health problems. Caregivers reported youth sociodemographics, sleep problems, whether the youth had mental health treatment or sought medical treatment, and rules about recreational cannabis use. We describe youth given hCBD, and run generalized estimating equations predicting odd ratios (ORs) and 95% confidence intervals of adolescents given hCBD by mental health, physical health, or sociodemographics of factors. Results: Of the 11,189 participants across up to three waves of data, 48% were female. Mean age across waves was 12.8 years old (SD=1). In total, 307 (2.8%) were given hCBD. Common administration methods were oil (42%), topical (31%), and edibles (29%). Increased hCBD odds were associated with being older (OR=1.32 [1.17-1.49]), White (relative to Black, OR=05.97 [2.81-12.65] or Hispanic, OR=1.82 [1.17-2.82]), parents with some college (relative to no high school diploma, OR=3.55 [1.09-11.6]), internalizing symptoms (OR=1.81 [1.13-2.91]), mental health treatment (OR=1.76 [1.3-2.38]), pain (OR=1.38 [1.09-1.76]), medical treatment (OR=1.39 [1.08-1.79]), and sleep problems (OR=1.69 [1.27-2.25]). Rules against recreational cannabis decreased odds of hCBD (OR=1.75 [1.30-2.36]). Conclusions: Findings indicate some healthy adolescents are given hCBD, and predictors of use include mental and physical health concerns, being White, older, and parents with some college education. Providers should ask if their youth patients are being given CBD medicinally, and transparently discuss potential benefits, consequences, and unknowns of CBD.

Greater social jetlag predicts poorer NIH Toolbox crystallized cognitive and academic performance in the Adolescent Brain Cognitive Development (ABCD) study.

Academic performance plays a crucial role in long-term educational attainment and occupational function. Chronotype refers to an individual's daily tendencies for times for waking, activity, and sleep. Social jetlag reflects the mismatch between an individual's chronotype and their social schedule. Because school typically starts early in the morning, later chronotype is often associated with daytime sleepiness, insufficient sleep, and poor academic performance. However, the relationship between academic performance, chronotype, and social jetlag has not been extensively examined in large samples like the Adolescent Brain Cognitive Development (ABCD) study. We hypothesized that greater social jetlag would predict poorer cognitive and academic performance. Year 2 (ages 11-14) cross-sectional data from the ABCD cohort (n = 6,890 adolescents) were used to evaluate academic performance (i.e. self-reported past year grades), NIH Toolbox cognitive performance measures, chronotype, and social jetlag from the Munich Chronotype Questionnaire. We found that later chronotype and greater social jetlag predicted poorer cognitive and academic performance with small effect sizes. Our findings emphasize the importance of individual differences in chronotype and social jetlag when designing class schedules, as aligning school activities with student optimal sleep-wake times may contribute to improved academic performance.

Screen time, sleep, brain structural neurobiology, and sequential associations with child and adolescent psychopathology: Insights from the ABCD study.

Background and Aims: The precise roles of screen media activity (SMA) and sleep problems in relation to child/adolescent psychopathology remain ambiguous. We investigated temporal relationships among sleep problems, SMA, and psychopathology and potential involvement of thalamus-prefrontal-cortex (PFC)-brainstem structural covariation. Methods: This study utilized data from the Adolescent Brain Cognitive Development study (n = 4,641 ages 9-12) at baseline, Year1, and Year2 follow-up. Cross-Lagged Panel Models (CLPMs) investigated reciprocal predictive relationships between sleep duration/problems, SMA, and psychopathology symptoms. A potential mediating role of baseline Thalamus-PFC-brainstem covariation on SMA-externalizing relationships was examined. Results: Participants were divided into discovery (n = 2,359, 1,054 girls) and replication (n = 2,282, 997 girls) sets. CLPMs showed 1) bidirectional associations between sleep duration and SMA in late childhood, with higher frequency SMA predicting shorter sleep duration (ß = -0.10 [95%CI: -0.16, -0.03], p = 0.004) and vice versa (ß = -0.11 [95%CI: -0.18, -0.05], p < 0.001); 2) externalizing symptoms at age 10-11 predicting sleep problems (ß = 0.11 [95%CI: 0.04, 0.19], p = 0.002), SMA (ß = 0.07 [95%CI: 0.01, 0.13], p = 0.014), and internalizing symptoms (ß = 0.09 [95%CI: 0.05, 0.13], p < 0.001) at age 11-12; and 3) externalizing behavior at age 10-11 partially mediating the relationship between baseline thalamus-PFC-brainstem covariation and SMA at age 11-12 (indirect effect = 0.032 [95%CI: 0.003, 0.067], p-value = 0.030). Findings were replicable. Conclusion: We found bi-directional SMA-sleep-duration associations in late childhood. Externalizing symptoms preceded future SMA and sleep disturbances and partially mediated relationships between structural brain covariation and SMA. The findings emphasize the need for understanding individual differences and developing and implementing integrated strategies addressing both sleep concerns and screen time to mitigate potential impacts on psychopathology.

Imaging of brain electric field networks.

We present a method for direct imaging of the electric field networks in the human brain from electroencephalography (EEG) data with much higher temporal and spatial resolution than functional MRI (fMRI), without the concomitant distortions. The method is validated using simultaneous EEG/fMRI data in healthy subjects, intracranial EEG data in epilepsy patients, and in a direct comparison with standard EEG analysis in a well-established attention paradigm. The method is then demonstrated on a very large cohort of subjects performing a standard gambling task designed to activate the brain's 'reward circuit'. The technique uses the output from standard EEG systems and thus has potential for immediate benefit to a broad range of important basic scientific and clinical questions concerning brain electrical activity, but also provides an inexpensive and portable alternative to function MRI (fMRI).

Do traumatic events and substance use co-occur during adolescence? Testing three causal etiologic hypotheses.

BACKGROUND: Why do potentially traumatic events (PTEs) and substance use (SU) so commonly co-occur during adolescence? Causal hypotheses developed from the study of posttraumatic stress disorder (PTSD) and substance use disorder (SUD) among adults have not yet been subject to rigorous theoretical analysis or empirical tests among adolescents with the precursors to these disorders: PTEs and SU. Establishing causality demands accounting for various factors (e.g. genetics, parent education, race/ethnicity) that distinguish youth endorsing PTEs and SU from those who do not, a step often overlooked in previous research. METHODS: We leveraged nationwide data from a sociodemographically diverse sample of youth (N = 11,468) in the Adolescent Brain and Cognitive Development Study. PTEs and substance use prevalence were assessed annually. To account for the many pre-existing differences between youth with and without PTE/SU (i.e. confounding bias) and provide rigorous tests of causal hypotheses, we linked within-person changes in PTEs and SU (alcohol, cannabis, nicotine) across repeated measurements and adjusted for time-varying factors (e.g. age, internalizing symptoms, externalizing symptoms, and friends' use of substances). RESULTS: Before adjusting for confounding using within-person modeling, PTEs and SU exhibited significant concurrent associations (ßs = .46-1.26, ps < .05) and PTEs prospectively predicted greater SU (ßs = .55-1.43, ps < .05) but not vice versa. After adjustment for confounding, the PTEs exhibited significant concurrent associations for alcohol (ßs = .14-.23, ps < .05) and nicotine (ßs = .16, ps < .05) but not cannabis (ßs = -.01, ps > .05) and PTEs prospectively predicted greater SU (ßs = .28-.55, ps > .05) but not vice versa. CONCLUSIONS: When tested rigorously in a nationwide sample of adolescents, we find support for a model in which PTEs are followed by SU but not for a model in which SU is followed by PTEs. Explanations for why PTSD and SUD co-occur in adults may need further theoretical analysis and adaptation before extension to adolescents.

How Do Anger and Impulsivity Impact Fast-Food Consumption in Transitional Age Youth?

Introduction: Consumption of fast food has been linked to psychiatric distress, violent behaviors, and impulsivity in adolescents. The relationship between eating fast food, anger, and impulsivity has not been widely investigated. The National Consortium on Alcohol and Neurodevelopment in Adolescence community-based cohort consists of 831 youth, half at elevated risk factors for substance use disorders during adolescence, followed annually. Methods: Impulsivity using Urgency, Premeditation, Perseverance, and Sensation Seeking Impulsive Behavior scale from annual assessments was examined in relation to self-reported fast-food consumption frequency and mobile application questions of anger. This study tested the hypotheses that youth anger may be predicted by fast-food consumption frequency and impulsivity using multiple regression, in addition to whether adolescent fast-food consumption frequency may be predicted by anger and impulsivity. Results: Among youth, higher anger levels and impulsivity predicted greater frequency of fast-food consumption, and greater fast-food consumption frequency and impulsivity predicted higher anger levels. Conclusions: This study's longitudinal findings are consistent with those of other studies that have found fast-food consumption and anger associated with impulsivity and also reveal a bidirectional link between anger and fast-food consumption. These results may point attention to food selection considerations for those at risk of anger and poorer psychiatric outcomes.

Neuroanatomical variability associated with early substance use initiation: Results from the ABCD Study.

The extent to which neuroanatomical variability associated with substance involvement reflects pre-existing risk and/or consequences of substance exposure remains poorly understood. In the Adolescent Brain Cognitive DevelopmentSM (ABCD®) Study, we identify associations between global and regional differences in brain structure and early substance use initiation (i.e., occurring <15 years of age; nsanalytic=6,556-9,804), with evidence that associations precede initiation. Neurodevelopmental variability in brain structure may confer risk for substance involvement.

How Does Parental Monitoring Reduce Adolescent Substance Use? Preliminary Tests of Two Potential Mechanisms.

OBJECTIVE: The purpose of this study was to test two non-exclusive mechanisms by which parental monitoring might reduce teen substance use. The first mechanism (M1) is that monitoring increases punishment for substance use since parents who monitor more are more likely to find out when substance use occurs. The second mechanism (M2) is that monitoring directly prevents/averts teens from using substances in the first place for fear that parents would find out. METHOD: A total of 4,503 teens ages 11-15 years old in 21 communities across the United States completed a survey reporting on parents' monitoring/knowledge and teens' substance use. RESULTS: We found no support for M1: Parents with greater parental monitoring were not more likely to be aware when the teen had used substances (odds ratios = 0.79-0.93, ps = .34-.85), so they could not have increased the rate of punishment. We found support for M2: When asked directly, teens identified instances in which they planned to or had a chance to use substances but did not because their parents got in the way or would have found out (p < .01). Had all those opportunities for substance use occurred rather than been averted by parents, the prevalence of substance use in the sample would have been 1.4 times higher. CONCLUSIONS: In this community-based sample of teens, we failed to support prior punishment-centric theories of how monitoring might reduce teen substance use. Rather, monitoring may directly discourage teens from using substances regardless of whether it increases parents' awareness of substance use or results in more punishment. Replication in other samples and contexts is needed.

Traumatic brain injury, working memory-related neural processing, and alcohol experimentation behaviors in youth from the ABCD cohort.

Adolescent traumatic brain injury (TBI) has long-term effects on brain functioning and behavior, impacting neural activity under cognitive load, especially in the reward network. Adolescent TBI is also linked to risk-taking behaviors including alcohol misuse. It remains unclear how TBI and neural functioning interact to predict alcohol experimentation during adolescence. Using Adolescent Brain Cognitive Development (ABCD) study data, this project examined if TBI at ages 9-10 predicts increased odds of alcohol sipping at ages 11-13 and if this association is moderated by neural activity during the Emotional EN-Back working memory task at ages 11-13. Logistic regression analyses showed that neural activity in regions of the fronto-basal ganglia network predicted increased odds of sipping alcohol by ages 11-13 (p < .05). TBI and left frontal pole activity interacted to predict alcohol sipping (OR = 0.507, 95% CI [0.303 - 0.846], p = .009) - increased activity predicted decreased odds of alcohol sipping for those with a TBI (OR = 0.516, 95% CI [0.314 - 0.850], p = .009), but not for those without (OR = 0.971, 95% CI [0.931 -1.012], p = .159). These findings suggest that for youth with a TBI, increased BOLD activity in the frontal pole, underlying working memory, may be uniquely protective against the early initiation of alcohol experimentation. Future work will examine TBI and alcohol misuse in the ABCD cohort across more time points and the impact of personality traits such as impulsivity on these associations.

Cannabis use and neurocognitive performance at 13-14 Years-Old: Optimizing assessment with hair toxicology in the Adolescent brain cognitive development (ABCD) study.

OBJECTIVE: Cannabis is widely used, including in early adolescence, with prevalence rates varying by measurement method (e.g., toxicology vs. self-report). Critical neurocognitive development occurs throughout adolescence. Given conflicting prior brain-behavior results in cannabis research, improved measurement of cannabis use in younger adolescents is needed. METHODS: Data from the Adolescent Brain Cognitive Development (ABCD) Study Year 4 follow-up (participant age: 13-14 years-old) included hair samples assessed by LC-MS/MS and GC-MS/MS, quantifying THCCOOH (THC metabolite), THC, and cannabidiol concentrations, and the NIH Toolbox Cognitive Battery. Youth whose hair was positive for cannabinoids or reported past-year cannabis use were included in a Cannabis Use (CU) group (n = 123) and matched with non-using Controls on sociodemographics (n = 123). Standard and nested ANCOVAs assessed group status predicting cognitive performance, controlling for family relationships. Follow-up correlations assessed cannabinoid hair concentration, self-reported cannabis use, and neurocognition. RESULTS: CU scored lower on Picture Memory (p = .03) than Controls. Within the CU group, THCCOOH negatively correlated with Picture Vocabulary (r = -0.20, p = .03) and Flanker Inhibitory Control and Attention (r = -0.19, p = .04), and past-year cannabis use was negatively associated with List Sorting Working Memory (r = -0.33, p = .0002) and Picture Sequence Memory (r = -0.19, p = .04) performances. CONCLUSIONS: Youth who had used cannabis showed lower scores on an episodic memory task, and more cannabis use was linked to poorer performances on verbal, inhibitory, working memory, and episodic memory tasks. Combining hair toxicology with self-report revealed more brain-behavior relationships than self-report data alone. These youth will be followed to determine long-term substance use and neurocognition trajectories.

Brain structural covariance network features are robust markers of early heavy alcohol use.

BACKGROUND AND AIMS: Recently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)-derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies. DESIGN AND SETTING: Cross-sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14-22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17-22 years) and the Human Connectome Project (HCP) (n = 375, age range = 22-37 years). CASES: Cases were defined based on heavy alcohol use patterns or former alcohol use disorder (AUD) diagnoses: 50, 68 and 61 cases were identified. Controls had none or low alcohol use or absence of AUD: 350, 204 and 314 controls were selected. MEASUREMENTS: Graph theory metrics of segregation and integration were used to summarize SCN. FINDINGS: Mirroring our prior findings, and across the three data sets, cases had a lower clustering coefficient [area under the curve (AUC) = -0.029, P = 0.002], lower modularity (AUC = -0.14, P = 0.004), lower average shortest path length (AUC = -0.078, P = 0.017) and higher global efficiency (AUC = 0.007, P = 0.010). Local efficiency differences were marginal (AUC = -0.017, P = 0.052). That is, cases exhibited lower network segregation and higher integration, suggesting that adjacent nodes (i.e. brain regions) were less similar in thickness whereas spatially distant nodes were more similar. CONCLUSION: Structural covariance network (SCN) differences in the brain appear to constitute an early marker of heavy alcohol use in three new data sets and, more generally, demonstrate the utility of SCN-derived metrics to detect brain-related psychopathology.

Imputing Brain Measurements Across Data Sets via Graph Neural Networks.

Publicly available data sets of structural MRIs might not contain specific measurements of brain Regions of Interests (ROIs) that are important for training machine learning models. For example, the curvature scores computed by Freesurfer are not released by the Adolescent Brain Cognitive Development (ABCD) Study. One can address this issue by simply reapplying Freesurfer to the data set. However, this approach is generally computationally and labor intensive (e.g., requiring quality control). An alternative is to impute the missing measurements via a deep learning approach. However, the state-of-the-art is designed to estimate randomly missing values rather than entire measurements. We therefore propose to re-frame the imputation problem as a prediction task on another (public) data set that contains the missing measurements and shares some ROI measurements with the data sets of interest. A deep learning model is then trained to predict the missing measurements from the shared ones and afterwards is applied to the other data sets. Our proposed algorithm models the dependencies between ROI measurements via a graph neural network (GNN) and accounts for demographic differences in brain measurements (e.g. sex) by feeding the graph encoding into a parallel architecture. The architecture simultaneously optimizes a graph decoder to impute values and a classifier in predicting demographic factors. We test the approach, called Demographic Aware Graph-based Imputation (DAGI), on imputing those missing Freesurfer measurements of ABCD (N=3760; minimum age 12 years) by training the predictor on those publicly released by the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA, N=540). 5-fold cross-validation on NCANDA reveals that the imputed scores are more accurate than those generated by linear regressors and deep learning models. Adding them also to a classifier trained in identifying sex results in higher accuracy than only using those Freesurfer scores provided by ABCD.

Neural correlates of negative life events and their relationships with alcohol and cannabis use initiation.

OBJECTIVE: Negative life events (NLEs), e.g., poor academic performance (controllable) or being the victim of a crime (uncontrollable), can profoundly affect the trajectory of one's life. Yet, their impact on how the brain develops is still not well understood. This investigation examined the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) dataset for the impact of NLEs on the initiation of alcohol and cannabis use, as well as underlying neural mechanisms. METHODS: This study evaluated the impact of controllable and uncontrollable NLEs on substance use initiation in 207 youth who initiated alcohol use, 168 who initiated cannabis use, and compared it to 128 youth who remained substance-naïve, using generalised linear regression models. Mediation analyses were conducted to determine neural pathways of NLE impacting substance use trajectories. RESULTS: Dose-response relationships between controllable NLEs and substance use initiation were observed. Having one controllable NLE increased the odds of alcohol initiation by 50% (95%CI [1.18, 1.93]) and cannabis initiation by 73% (95%CI [1.36, 2.24]), respectively. Greater cortical thickness in left banks of the superior temporal sulcus mediated effects of controllable NLEs on alcohol and cannabis initiations. Greater left caudate gray-matter volumes mediated effects of controllable NLEs on cannabis initiation. CONCLUSIONS: Controllable but not uncontrollable NLEs increased the odds of alcohol and cannabis initiation. Moreover, those individuals with less mature brain structures at the time of the NLEs experienced a greater impact of NLEs on subsequent initiation of alcohol or cannabis use. Targeting youth experiencing controllable NLEs may help mitigate alcohol and cannabis initiation.

Screen media activity in youth: A critical review of mental health and neuroscience findings.

This review has two primary objectives: (1) to offer a balanced examination of recent findings on the relationship between screen media activity (SMA) in young individuals and outcomes such as sleep patterns, mood disturbances, anxiety-related concerns, and cognitive processes; and (2) to introduce a novel multi-level system model that integrates these findings, resolves contradictions in the literature, and guides future studies in examining key covariates affecting the SMA-mental health relationship. Key findings include: (1) Several meta-analyses reveal a significant association between SMA and mental health issues, particularly anxiety and depression, including specific negative effects linked to prolonged screen time; (2) substantial evidence indicates that SMA has both immediate and long-term impacts on sleep duration and quality; (3) the relationship between SMA and cognitive functioning is complex, with mixed findings showing both positive and negative associations; and (4) the multifaceted relationship between SMA and various aspects of adolescent life is influenced by a wide range of environmental and contextual factors. SMA in youth is best understood within a complex system encompassing individual, caregiver, school, peer, and environmental factors, as framed by Bronfenbrenner's ecological systems theory, which identifies five interrelated systems (microsystem, mesosystem, exosystem, macrosystem, and chronosystem) that influence development across both proximal and distal levels of the environment. This model provides a framework for future research to examine these interactions, considering moderating factors, and to develop targeted interventions that can mitigate potential adverse effects of SMA on mental well-being.

Associations between alcohol use and sex-specific maturation of subcortical gray matter morphometry from adolescence to adulthood: Replication across two longitudinal samples.

Subcortical brain morphometry matures across adolescence and young adulthood, a time when many youth engage in escalating levels of alcohol use. Initial cross-sectional studies have shown alcohol use is associated with altered subcortical morphometry. However, longitudinal evidence of sex-specific neuromaturation and associations with alcohol use remains limited. This project used generalized additive mixed models to examine sex-specific development of subcortical volumes and associations with recent alcohol use, using 7 longitudinal waves (n = 804, 51% female, ages 12-21 at baseline) from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA). A second, independent, longitudinal dataset, with up to four waves of data (n = 467, 43% female, ages 10-18 at baseline), was used to assess replicability. Significant, replicable non-linear normative volumetric changes with age were evident in the caudate, putamen, thalamus, pallidum, amygdala and hippocampus. Significant, replicable negative associations between subcortical volume and alcohol use were found in the hippocampus in all youth, and the caudate and thalamus in female but not male youth, with significant interactions present in the caudate, thalamus and putamen. Findings suggest a structural vulnerability to alcohol use, or a predisposition to drink alcohol based on brain structure, with female youth potentially showing heightened risk, compared to male youth.

Pandemic-Related Changes in the Prevalence of Early Adolescent Alcohol and Drug Use, 2020-2021: Data From a Multisite Cohort Study.

PURPOSE: Evaluate changes in early adolescent substance use from May 2020 to May 2021 during the coronavirus disease 2019 pandemic using data from a prospective nationwide cohort: the Adolescent Brain Cognitive Development Study. METHODS: In 2018-2019, 9,270 youth aged 11.5-13.0 completed a prepandemic assessment of past-month alcohol and drug use, then up to seven during-pandemic assessments between May 2020 and May 2021. We compared the prevalence of substance use among same-age youth across these eight timepoints. RESULTS: Pandemic-related decreases in the past-month prevalence of alcohol use were detectable in May 2020, grew larger over time, and remained substantial in May 2021 (0.3% vs. 3.2% prepandemic, p <.001). Pandemic-related increases in inhalant use (p = .04) and prescription drug misuse (p < .001) were detectable in May 2020, shrunk over time, and were smaller but still detectable in May 2021(0.1%-0.2% vs. 0% pre-pandemic). Pandemic-related increases in nicotine use were detectable between May 2020 and March 2021 and no longer significantly different from prepandemic levels in May 2021 (0.5% vs. 0.2% prepandemic, p = .09). There was significant heterogeneity in pandemic-related change in substance use at some timepoints, with increased rates among youth identified as Black or Hispanic or in lower-income families versus stable or decreased rates among youth identified as White or in higher-income families. DISCUSSION: Among youth ages 11.5-13.0 years old, rates of alcohol use remained dramatically reduced in May 2021 relative to prepandemic and rates of prescription drug misuse and inhalant use remained modestly increased. Differences remained despite the partial restoration of prepandemic life, raising questions about whether youth who spent early adolescence under pandemic conditions may exhibit persistently different patterns of substance use.

Effects of emerging alcohol use on developmental trajectories of functional sleep measures in adolescents.

STUDY OBJECTIVES: Adolescence is characterized by significant brain development, accompanied by changes in sleep timing and architecture. It also is a period of profound psychosocial changes, including the initiation of alcohol use; however, it is unknown how alcohol use affects sleep architecture in the context of adolescent development. We tracked developmental changes in polysomnographic (PSG) and electroencephalographic (EEG) sleep measures and their relationship with emergent alcohol use in adolescents considering confounding effects (e.g. cannabis use). METHODS: Adolescents (n = 94, 43% female, age: 12-21 years) in the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study had annual laboratory PSG recordings across 4-years. Participants were no/low drinkers at baseline. RESULTS: Linear mixed effect models showed developmental changes in sleep macrostructure and EEG, including a decrease in slow wave sleep and slow wave (delta) EEG activity with advancing age. Emergent moderate/heavy alcohol use across three follow-up years was associated with a decline in percentage rapid eye movement (REM) sleep over time, a longer sleep onset latency (SOL) and shorter total sleep time (TST) in older adolescents, and lower non-REM delta and theta power in males. CONCLUSIONS: These longitudinal data show substantial developmental changes in sleep architecture. Emergent alcohol use during this period was associated with altered sleep continuity, architecture, and EEG measures, with some effects dependent on age and sex. These effects, in part, could be attributed to the effects of alcohol on underlying brain maturation processes involved in sleep-wake regulation.

Effects of the COVID-19 pandemic on screen time and sleep in early adolescents.

OBJECTIVE: During the COVID-19 pandemic, adolescents and families have turned to online activities and social platforms more than ever to maintain well-being, connect remotely with friends and family, and online schooling. However, excessive screen use can have negative effects on health (e.g., sleep). This study examined changes in sleep habits and recreational screen time (social media, video gaming), and their relationship, before and across the first year of the pandemic in adolescents in the Adolescent Brain Cognitive Development (ABCD) Study. METHOD: Mixed-effect models were used to examine associations between self-reported sleep and screen time using longitudinal data of 5,027 adolescents in the ABCD Study, assessed before the pandemic (10-13 years) and across six time points between May 2020 and March 2021 (pandemic). RESULTS: Time in bed varied, being higher during May-August 2020 relative to pre-pandemic, partially related to the school summer break, before declining in October 2020 to levels lower than pre-pandemic. Screen time steeply increased and remained high across all pandemic time points relative to pre-pandemic. Higher social media use and video gaming were associated with shorter time in bed, later bedtimes, and longer sleep onset latency. CONCLUSIONS: Sleep behavior and screen time changed during the pandemic in early adolescents. More screen time was associated with poorer sleep behavior, before and during the pandemic. While recreational screen usage is an integral component of adolescent's activities, especially during the pandemic, excessive use can have negative effects on essential health behaviors, highlighting the need to promote balanced screen usage. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The beneficial effect of sleep on behavioral health problems in youth is disrupted by prenatal cannabis exposure: A causal random forest analysis of Adolescent Brain Cognitive Development data.

Studies suggest prenatal cannabis exposure is associated with mood/behavioral problems in children. However, it is unclear if targeting modifiable domains like sleep behaviors would improve outcomes in exposed youth. Using a causal inference framework, the effect of changing sleep-hours on changing internalizing/externalizing problems in children was examined using the Adolescent Brain Cognitive Development™ study baseline (ages 9-10; collected during 2016-2018) and year-1 follow-up data (N = 9825; 4663 female; 5196 white). Average treatment effects (ATE) indicated that more sleep predicted less internalizing (ATE = -.34, SE = .08, p < .001) and externalizing (ATE = -.29, SE = .07, p < .001) problems over time. However, prenatal cannabis exposure moderated the ATE on internalizing (conditional-ATE = .91, SE = .39, p = .019), whereby participants with exposure (n = 605) did not show any effect of changing sleep-hours on mood (B = .09, SE = .24).

Concordance between substance use self-report and hair analysis in community-based adolescents.

Background: Accurate drug use identification through subjective self-report and toxicological biosample (hair) analysis are necessary to determine substance use sequelae in youth. Yet consistency between self-reported substance use and robust, toxicological analysis in a large sample of youth is understudied.Objectives: We aim to assess concordance between self-reported substance use and hair toxicological analysis in community-based adolescents.Methods: Hair results by LC-MS/MS and GC-MS/MS and self-reported past-year substance use from an Adolescent Brain Cognitive Development (ABCD) Study subsample (N = 1,390; ages 9-13; 48% female) were compared. The participants were selected for hair selection through two methods: high scores on a substance risk algorithm selected 93%; 7% were low-risk, randomly selected participants. Kappa coefficients the examined concordance between self-report and hair results.Results: 10% of youth self-reported any past-year substance use (e.g. alcohol, cannabis, nicotine, and opiates), while a mostly non-overlapping 10% had hair results indicating recent substance use (cannabis, alcohol, non-prescription amphetamines, cocaine, nicotine, opiates, and fentanyl). In randomly selected low-risk cases, 7% were confirmed positive in hair. Combining methods, 19% of the sample self-reported substance use and/or had a positive hair sample. Kappa coefficient of concordance between self-report and hair results was low (kappa = 0.07; p = .007).Conclusions: Hair toxicology identified substance use in high-risk and low-risk ABCD cohort subsamples. Given low concordance between hair results and self-report, reliance on either method alone would incorrectly categorize 9% as non-users. Multiple methods for characterizing substance use history in youth improves accuracy. Larger representative samples are needed to assess the prevalence of substance use in youth.