Use of Tobacco Products and Suicide Attempts Among Elementary School-Aged Children.

Importance: The use of tobacco products, including e-cigarettes and vaping, has rapidly increased among children. However, despite consistent associations found between smoking cigarettes and suicidal behaviors among adolescents and adults, there are limited data on associations between emerging tobacco products and suicidal behaviors, especially among preadolescent children. Objective: To examine whether the use of tobacco products is associated with nonsuicidal self-injury (NSSI), suicidal ideation (SI), and suicide attempts (SAs) among preadolescent children. Design, Setting, and Participants: This cohort study, conducted from September 1, 2022, to September 5, 2023, included participants in the Adolescent Brain Cognitive Development study, a population-based cohort of 11 868 US children enrolled at 9 and 10 years of age. The cross-sectional investigation focused on 3-year periods starting from the baseline to year 2 of follow-up. Statistical analysis was performed from October 1, 2022, to June 30, 2023. Main Outcomes and Measures: Children's use of tobacco products was assessed based on youth reports, including lifetime experiences of various nicotine-related products, supplemented with hair toxicologic tests. Main outcomes were children's lifetime experiences of NSSI, SI, and SAs, assessed using the K-SADS-5 (Kiddie Schedule for Affective Disorders and Schizophrenia for the DSM-5). Multivariate logistic regression was conducted to examine the associations of the use of tobacco products with NSSI, SI, and SAs among the study participants. Sociodemographic, familial, and children's behavioral, temperamental, and clinical outcomes were adjusted in the analyses. Results: Of 8988 unrelated study participants (median age, 9.8 years [range, 8.9-11.0 years]; 4301 girls [47.9%]), 101 children (1.1%) and 151 children (1.7%) acknowledged lifetime use of tobacco products at baseline and at 18-month follow-up, respectively. After accounting for various suicide risk factors and potential confounders, children reporting use of tobacco products were at a 3 to 5 times increased risk of SAs (baseline: n = 153 [adjusted odds ratio (OR), 4.67; 95% CI, 2.35-9.28; false discovery rate (FDR)-corrected P < .001]; year 1: n = 227 [adjusted OR, 4.25; 95% CI, 2.33-7.74; FDR-corrected P < .001]; and year 2: n = 321 [adjusted OR, 2.85; 95% CI, 1.58-5.13; FDR-corrected P = .001]). Of all facets of impulsivity measures that were significant correlates of use of tobacco products, negative urgency was the only independent risk factor for SAs (adjusted OR, 1.52 [95% CI, 1.31-1.78]; FDR-corrected P < .001). In contrast, children's alcohol, cannabis, and prescription drug use were not associated with SAs. Conclusions and Relevance: This study of US children suggests that the increased risk of SAs, consistently reported for adolescents and adults who smoke cigarettes, extends to a range of emerging tobacco products and manifests among elementary school-aged children. Further investigations are imperative to clarify the underlying mechanisms and to implement effective preventive policies for children.

Substance Use, Suicidal Thoughts, and Psychiatric Comorbidities Among High School Students.

This cross-sectional study evaluates the dose-dependent association between alcohol, cannabis, and nicotine use and psychiatric symptoms among participants in the Substance Use and Risk Factor Survey and the Youth Risk Behavior Survey.

Heritability estimation of subcortical volumes in a multi-ethnic multi-site cohort study.

Heritability of regional subcortical brain volumes (rSBVs) describes the role of genetics in middle and inner brain development. rSBVs are highly heritable in adults but are not characterized well in adolescents. The Adolescent Brain Cognitive Development study (ABCD), taken over 22 US sites, provides data to characterize the heritability of subcortical structures in adolescence. In ABCD, site-specific effects co-occur with genetic effects which can bias heritability estimates. Existing methods adjusting for site effects require additional steps to adjust for site effects and can lead to inconsistent estimation. We propose a random-effect model-based method of moments approach that is a single step estimator and is a theoretically consistent estimator even when sites are imbalanced and performs well under simulations. We compare methods on rSBVs from ABCD. The proposed approach yielded heritability estimates similar to previous results derived from single-site studies. The cerebellum cortex and hippocampus were the most heritable regions (> 50%).

The Developmental Timing but Not Magnitude of Adolescent Risk-Taking Propensity Is Consistent Across Social, Environmental, and Psychological Factors.

PURPOSE: Risk-taking is thought to peak during adolescence, but most prior studies have relied on small convenience samples lacking participant diversity. This study tested the generalizability of adolescent self-reported risk-taking propensity across a comprehensive set of participant-level social, environmental, and psychological factors. METHODS: Data (N = 1,005,421) from the National Survey on Drug Use and Health were used to test the developmental timing and magnitude of risk-taking propensity and its link to alcohol and cannabis use across 19 subgroups defined via sex, race/ethnicity, socioeconomic status, population density, religious affiliation, and mental health. RESULTS: The developmental timing of a lifespan peak in risk-taking propensity during adolescence (15-18 years old) generalized across nearly all levels of social, environmental, and psychological factors, whereas the magnitude of this peak widely varied. Nearly all adolescents with regular substance use reported higher levels of risk-taking propensity. DISCUSSION: Results support a broad generalizability of adolescence as the peak lifespan period of self-reported risk-taking but emphasize the importance of participant-level factors in determining the specific magnitude of reported risk-taking.

Study design features that improve effect sizes in cross-sectional and longitudinal brain-wide association studies.

Brain-wide association studies (BWAS) are a fundamental tool in discovering brain-behavior associations. Several recent studies showed that thousands of study participants are required to improve the replicability of BWAS because actual effect sizes are much smaller than those reported in smaller studies. Here, we perform analyses and meta-analyses of a robust effect size index (RESI) using 63 longitudinal and cross-sectional magnetic resonance imaging studies from the Lifespan Brain Chart Consortium (77,695 total scans) to demonstrate that optimizing study design is critical for improving standardized effect sizes and replicability in BWAS. A meta-analysis of brain volume associations with age indicates that BWAS with larger covariate variance have larger effect size estimates and that the longitudinal studies we examined have systematically larger standardized effect sizes than cross-sectional studies. We propose a cross-sectional RESI to adjust for the systematic difference in effect sizes between cross-sectional and longitudinal studies that allows investigators to quantify the benefit of conducting their study longitudinally. Analyzing age effects on global and regional brain measures from the United Kingdom Biobank and the Alzheimer's Disease Neuroimaging Initiative, we show that modifying longitudinal study design through sampling schemes to increase between-subject variability and adding a single additional longitudinal measurement per subject can improve effect sizes. However, evaluating these longitudinal sampling schemes on cognitive, psychopathology, and demographic associations with structural and functional brain outcome measures in the Adolescent Brain and Cognitive Development dataset shows that commonly used longitudinal models can, counterintuitively, reduce effect sizes. We demonstrate that the benefit of conducting longitudinal studies depends on the strengths of the between- and within-subject associations of the brain and non-brain measures. Explicitly modeling between- and within-subject effects avoids conflating the effects and allows optimizing effect sizes for them separately. These findings underscore the importance of considering study design features to improve the replicability of BWAS.

Framewise multi-echo distortion correction for superior functional MRI.

Functional MRI (fMRI) data are severely distorted by magnetic field (B0) inhomogeneities which currently must be corrected using separately acquired field map data. However, changes in the head position of a scanning participant across fMRI frames can cause changes in the B0 field, preventing accurate correction of geometric distortions. Additionally, field maps can be corrupted by movement during their acquisition, preventing distortion correction altogether. In this study, we use phase information from multi-echo (ME) fMRI data to dynamically sample distortion due to fluctuating B0 field inhomogeneity across frames by acquiring multiple echoes during a single EPI readout. Our distortion correction approach, MEDIC (Multi-Echo DIstortion Correction), accurately estimates B0 related distortions for each frame of multi-echo fMRI data. Here, we demonstrate that MEDIC's framewise distortion correction produces improved alignment to anatomy and decreases the impact of head motion on resting-state functional connectivity (RSFC) maps, in higher motion data, when compared to the prior gold standard approach (i.e., TOPUP). Enhanced framewise distortion correction with MEDIC, without the requirement for field map collection, furthers the advantage of multi-echo over single-echo fMRI.

Future Directions in the Mental Health of Transgender Youth: Towards a Social-Affective Developmental Model of Health Disparity.

Mental health disparities in transgender and gender diverse (TGD) youth are well-documented. These disparities are often studied in the context of minority stress theory, and most of this research focuses on experiences of trauma and discrimination TGD youth experience after coming out. However, TGD youth may be targets of violence and victimization due to perceived gender nonconformity before coming out. In this Future Directions, we integrate research on attachment, developmental trauma, and effects of racism and homophobia on mental health to propose a social-affective developmental framework for TGD youth. We provide a clinical vignette to highlight limitations in current approaches to mental health assessment in TGD youth and to illustrate how using a social-affective developmental framework can improve clinical assessment and treatment approaches and deepen our understanding of mental health disparities in TGD people.

A canonical trajectory of executive function maturation from adolescence to adulthood.

Theories of human neurobehavioral development suggest executive functions mature from childhood through adolescence, underlying adolescent risk-taking and the emergence of psychopathology. Investigations with relatively small datasets or narrow subsets of measures have identified general executive function development, but the specific maturational timing and independence of potential executive function subcomponents remain unknown. Integrating four independent datasets (N = 10,766; 8-35 years old) with twenty-three measures from seventeen tasks, we provide a precise charting, multi-assessment investigation, and replication of executive function development from adolescence to adulthood. Across assessments and datasets, executive functions follow a canonical non-linear trajectory, with rapid and statistically significant development in late childhood to mid-adolescence (10-15 years old), before stabilizing to adult-levels in late adolescence (18-20 years old). Age effects are well captured by domain-general processes that generate reproducible developmental templates across assessments and datasets. Results provide a canonical trajectory of executive function maturation that demarcates the boundaries of adolescence and can be integrated into future studies.

Brain tissue iron neurophysiology and its relationship with the cognitive effects of dopaminergic modulation in children with and without ADHD.

Children with attention-deficit/hyperactivity disorder (ADHD) exhibit impairments in response inhibition. These impairments are ameliorated by modulating dopamine (DA) via the administration of rewards or stimulant medication like methylphenidate (MPH). It is currently unclear whether intrinsic DA availability impacts these effects of dopaminergic modulation on response inhibition. Thus, we estimated intrinsic DA availability using magnetic resonance-based assessments of basal ganglia and thalamic tissue iron in 36 medication-naïve children with ADHD and 29 typically developing (TD) children (8-12 y) who underwent fMRI scans and completed standard and rewarded go/no-go tasks. Children with ADHD additionally participated in a double-blind, randomized, placebo-controlled, crossover MPH challenge. Using linear regressions covarying for age and sex, we determined there were no group differences in brain tissue iron. We additionally found that higher putamen tissue iron was associated with worse response inhibition performance in all participants. Crucially, we observed that higher putamen and caudate tissue iron was associated with greater responsivity to MPH, as measured by improved task performance, in participants with ADHD. These results begin to clarify the role of subcortical brain tissue iron, a measure associated with intrinsic DA availability, in the cognitive effects of reward- and MPH-related dopaminergic modulation in children with ADHD and TD children.

The Cannabis Effects Expectancy Questionnaire-Medical (CEEQ-M): Preliminary psychometric properties and longitudinal validation within a clinical trial.

The use of cannabis for medical symptoms is increasing despite limited evidence for its efficacy. Expectancies-prior beliefs about a substance or medicine-can modulate use patterns and effects of medicines on target symptoms. To our knowledge, cannabis expectancies have not been studied for their predictive value for symptom relief. The 21-item Cannabis Effects Expectancy Questionnaire-Medical (CEEQ-M) is the first longitudinally validated measure of expectancies for cannabis used for medical symptoms. The questionnaire was developed for a randomized clinical trial of the effect of state cannabis registration (SCR) card ownership on symptoms of pain, insomnia, anxiety, and depression in adults (N = 269 across six questionnaire administrations). Item-level analyses (n = 188) demonstrated between-person stability of expectancies and no aggregate, within-person expectancy changes 3 months after individuals gained access to SCR cards. Exploratory factor analysis (n = 269) indicated a two-factor structure. Confirmatory factor analysis at a later timepoint (n = 193) demonstrated good fit and scalar invariance of the measurement model. Cross-lagged panel models across 3 and 12 months (n = 187 and 161, respectively) indicated that CEEQ-M-measured expectancies did not predict changes in self-reported cannabis use; symptoms of pain, insomnia, anxiety, and depression; and well-being. However, greater baseline cannabis use predicted more positive expectancy changes. The findings suggest that the CEEQ-M is psychometrically sound. Future work should clarify at what timescales cannabis expectancies have predictive value and how cannabis expectancies for medical symptoms are maintained and diverge from other substance use expectancies. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Tailoring Psychiatric Neuroimaging to Translational Goals.

This Viewpoint discusses tailoring psychiatric neuroimaging paradigms toward clear translational and practical end goals in an effort to focus resources, improve reproducibility, and accelerate neuroimaging's clinical utility.

Exploring the multiverse: the impact of researchers' analytic decisions on relationships between depression and inflammatory markers.

In recent years, a replication crisis in psychiatry has led to a growing focus on the impact of researchers' analytic decisions on the results from studies. Multiverse analyses involve examining results across a wide array of possible analytic decisions (e.g., log-transforming variables, number of covariates, or treatment of outliers) and identifying if study results are robust to researchers' analytic decisions. Studies have begun to use multiverse analysis for well-studied relationships that have some heterogeneity in results/conclusions across studies.We examine the well-studied relationship between peripheral inflammatory markers (PIMs; e.g., white blood cell count (WBC) and C-reactive protein (CRP)) and depression severity in the large NHANES dataset (n = 25,962). Specification curve analyses tested the impact of 9 common analytic decisions (comprising of 58,000+ possible combinations) on the association of PIMs and depression severity. Relationships of PIMs and total depression severity are robust to analytic decisions (based on tests of inference jointly examining effect sizes and p-values). However, moderate/large differences are noted in effect sizes based on analytic decisions and the majority of analyses do not result in significant findings, with the percentage of analyses with statistically significant results being 46.1% for WBC and 43.8% for CRP. For associations of PIMs with specific symptoms of depression, some associations (e.g., sleep, appetite) in males (but not females) were robust to analytic decisions. We discuss how multiverse analyses can be used to guide research and also the need for authors, reviewers, and editors to incorporate multiverse analyses to enhance replicability of research findings.

Development of cannabis use disorder in medical cannabis users: A 9-month follow-up of a randomized clinical trial testing effects of medical cannabis card ownership.

Background: Evidence for long-term effectiveness of commercial cannabis products used to treat medical symptoms is inconsistent, despite increasingly widespread use. Objective: To prospectively evaluate the effects of using cannabis on self-reported symptoms of pain, insomnia, anxiety, depression, and cannabis use disorder (CUD) after 12 months of use. Methods: This observational cohort study describes outcomes over 9 months following a 12-week randomized, waitlist-controlled trial (RCT: NCT03224468) in which adults (N = 163) who wished to use cannabis to alleviate insomnia, pain, depression, or anxiety symptoms were randomly assigned to obtain a medical marijuana card immediately (immediate card acquisition group) or to delay obtaining a card for 12 weeks delay (delayed card acquisition group). During the 9-month post-randomization period, all participants could use cannabis as they wished and choose their cannabis products, doses, and frequency of use. Insomnia, pain, depression, anxiety, and CUD symptoms were assessed over the 9-month post-randomization period. Results: After 12 months of using cannabis for medical symptoms, 11.7% of all participants (n = 19), and 17.1% of those using cannabis daily or near-daily (n = 6) developed CUD. Frequency of cannabis use was positively correlated with pain severity and number of CUD symptoms, but not significantly associated with severity of self-reported insomnia, depression, or anxiety symptoms. Depression scores improved throughout the 9 months in all participants, regardless of cannabis use frequency. Conclusions: Frequency of cannabis use was not associated with improved pain, anxiety, or depression symptoms but was associated with new-onset cannabis use disorder in a significant minority of participants. Daily or near-daily cannabis use appears to have little benefit for these symptoms after 12 months of use.

Uncovering and mitigating bias in large, automated MRI analyses of brain development.

Large, population-based MRI studies of adolescents promise transformational insights into neurodevelopment and mental illness risk 1,2. However, MRI studies of youth are especially susceptible to motion and other artifacts 3,4. These artifacts may go undetected by automated quality control (QC) methods that are preferred in high-throughput imaging studies, 5 and can potentially introduce non-random noise into clinical association analyses. Here we demonstrate bias in structural MRI analyses of children due to inclusion of lower quality images, as identified through rigorous visual quality control of 11,263 T1 MRI scans obtained at age 9-10 through the Adolescent Brain Cognitive Development (ABCD) Study6. Compared to the best-rated images (44.9% of the sample), lower-quality images generally associated with decreased cortical thickness and increased cortical surface area measures (Cohen's d 0.14-2.84). Variable image quality led to counterintuitive patterns in analyses that associated structural MRI and clinical measures, as inclusion of lower-quality scans altered apparent effect sizes in ways that increased risk for both false positives and negatives. Quality-related biases were partially mitigated by controlling for surface hole number, an automated index of topological complexity that differentiated lower-quality scans with good specificity at Baseline (0.81-0.93) and in 1,000 Year 2 scans (0.88-1.00). However, even among the highest-rated images, subtle topological errors occurred during image preprocessing, and their correction through manual edits significantly and reproducibly changed thickness measurements across much of the cortex (d 0.15-0.92). These findings demonstrate that inadequate QC of youth structural MRI scans can undermine advantages of large sample size to detect meaningful associations.

Multivariate brain-based dimensions of child psychiatric problems: degrees of generalizability.

Multivariate machine learning techniques are a promising set of tools for identifying complex brain-behavior associations. However, failure to replicate results from these methods across samples has hampered their clinical relevance. This study aimed to delineate dimensions of brain functional connectivity that are associated with child psychiatric symptoms in two large and independent cohorts: the Adolescent Brain Cognitive Development (ABCD) Study and the Generation R Study (total n =8,605). Using sparse canonical correlations analysis, we identified three brain-behavior dimensions in ABCD: attention problems, aggression and rule-breaking behaviors, and withdrawn behaviors. Importantly, out-of-sample generalizability of these dimensions was consistently observed in ABCD, suggesting robust multivariate brain-behavior associations. Despite this, out-of-study generalizability in Generation R was limited. These results highlight that the degree of generalizability can vary depending on the external validation methods employed as well as the datasets used, emphasizing that biomarkers will remain elusive until models generalize better in true external settings.

Cannabis use and sleep quality in daily life: An electronic daily diary study of adults starting cannabis for health concerns.

BACKGROUND: Real world patterns of cannabis use for health concerns are highly variable and rarely overseen by a physician. Pragmatic effectiveness studies with electronic daily diaries that capture person-specific patterns of cannabis use and health symptoms may help clarify risks and benefits. METHODS: As part of a larger, randomized trial (NCT03224468), adults (N = 181) seeking cannabis for insomnia, pain, or anxiety or depressive symptoms were randomized to obtain a medical cannabis card immediately (MCC) or a waitlist control (WLC) and completed 12-weeks of daily web-based surveys on cannabis use and sleep, pain, and depressive symptoms. RESULTS: Completion rates of daily surveys were moderate to high (median completed: 72 out of 90 days). Daily reports of cannabis use were consistent with monthly interview assessments and urinalysis. The MCC group increased cannabis use frequency in the 12 weeks following randomization, while WLC did not. Among the MCC group, self-reported sleep quality was significantly higher on cannabis use days, compared to nonuse days. The MCC group displayed long-term sleep improvements, consistent with increasing cannabis frequency. No improvements were found for pain or depressive symptoms. CONCLUSION: Cannabis use is associated with same day improvements in self-reported sleep quality, but not pain or depressive symptoms, although sleep improvements occurred in the context of increased frequency of cannabis use, raising the risk for cannabis use disorder. Daily web-based assessments of cannabis appear valid and feasible in adults seeking cannabis for health concerns, providing a flexible, complementary method for future real-world effectiveness studies with expanded and objective measures.

State-Level Recreational Cannabis Legalization Is Not Differentially Associated with Cannabis Risk Perception Among Children: A Multilevel Regression Analysis.

Introduction: As more states pass recreational cannabis laws (RCLs) for adults, there is concern that increasing (and state-sanctioned) cannabis acceptance will result in a reduced perception of risk of harm from cannabis among children. We aimed to discover whether children in states with RCLs had decreased perception of risk from cannabis compared with children in states with illicit cannabis. Methods: We analyzed data from the multisite multistate Adolescent Brain and Cognitive Development Study to determine how the perception of cannabis harm among children (age at baseline: 9-10; N=10,395) changes over time in states with and without RCLs. Using multilevel modeling, we assessed survey responses from children longitudinally across 3 years, adjusting for state-, family-, and participant-level clustering and child-level factors, including demographics (sex, race, and socioeconomic status), religiosity, and trait impulsivity. Results: There was no significant main effect of state RCLs on perceived risk of cannabis use, and no differences in change over time by state RCLs, even after controlling for demographic factors and other risk (e.g., impulsivity) and protective (e.g., religiosity) factors. Conclusions: This analysis indicates that state-level RCLs are not associated with differential perception of cannabis risk among children, even after controlling for demographics, trait impulsivity, and religiosity. Future studies could assess how perception of risk from cannabis changes as children and adolescents continue to mature in states with and without RCLs.

Development of frontal GABA and glutamate supports excitation/inhibition balance from adolescence into adulthood.

Animal and human postmortem studies provide evidence for changes in gamma-aminobutyric acid (GABA) and glutamate in prefrontal cortex (PFC) during adolescence, suggesting shifts in excitation and inhibition balance consistent with critical period plasticity. However, how GABA and glutamate change through adolescence and how the balance of these inhibitory and excitatory neurotransmitters changes is not well understood in vivo in humans. High field (7 Tesla) Magnetic Resonance Spectroscopic Imaging was used to investigate age-related changes in the balance of GABA/creatine (Cr) and glutamate/Cr in multiple developmentally-relevant regions of frontal cortex in 144 10-30-year-olds. Results indicated a homogenous pattern of age-related Glu/Cr decreases across regions, while age-related changes in GABA/Cr were heterogenous, with a mix of stable and decreasing age effects. Importantly, balance between glutamate/Cr and GABA/Cr in areas of frontal cortex increased through adolescence, suggesting the presence of critical period plasticity in frontal cortex at this significant time of development when adult trajectories are established.