Background: Concerns abound regarding childhood smartphone use, but studies to date have largely relied on self-reported screen use. Self-reporting of screen use is known to be misreported by pediatric samples and their parents, limiting the accurate determination of the impact of screen use on social, emotional, and cognitive development. Thus, a more passive, objective measurement of smartphone screen use among children is needed. Objective: This study aims to passively sense smartphone screen use by time and types of apps used in a pilot sample of children and to assess the feasibility of passive sensing in a larger longitudinal sample. Methods: The Adolescent Brain Cognitive Development (ABCD) study used passive, objective phone app methods for assessing smartphone screen use over 4 weeks in 2019-2020 in a subsample of 67 participants (aged 11-12 years; 31/67, 46% female; 23/67, 34% White). Children and their parents both reported average smartphone screen use before and after the study period, and they completed a questionnaire regarding the acceptability of the study protocol. Descriptive statistics for smartphone screen use, app use, and protocol feasibility and acceptability were reviewed. Analyses of variance were run to assess differences in categorical app use by demographics. Self-report and parent report were correlated with passive sensing data. Results: Self-report of smartphone screen use was partly consistent with objective measurement (r=0.49), although objective data indicated that children used their phones more than they reported. Passive sensing revealed the most common types of apps used were for streaming (mean 1 hour 57 minutes per day, SD 1 hour 32 minutes), communication (mean 48 minutes per day, SD 1 hour 17 minutes), gaming (mean 41 minutes per day, SD 41 minutes), and social media (mean 36 minutes per day, SD 1 hour 7 minutes). Passive sensing of smartphone screen use was generally acceptable to children (43/62, 69%) and parents (53/62, 85%). Conclusions: The results of passive, objective sensing suggest that children use their phones more than they self-report. Therefore, use of more robust methods for objective data collection is necessary and feasible in pediatric samples. These data may then more accurately reflect the impact of smartphone screen use on behavioral and emotional functioning. Accordingly, the ABCD study is implementing a passive sensing protocol in the full ABCD cohort. Taken together, passive assessment with a phone app provided objective, low-burden, novel, informative data about preteen smartphone screen use.

Though largely substance-naïve at enrollment, a proportion of the youth in the Adolescent Brain Cognitive Development (ABCD) Study are expected to initiate substance use (SU) as they transition into later adolescence. With annual data from youth 9-13 years-old, this study aims to describe their SU patterns over time. Here, prevalence rates of use are reported, along with predicted odds of use while analyzing common risk-factors associated with youth SU. The ABCD Study^® enrolled 11,876 participants at Baseline (ages 9-10) and has followed them annually. Data through half of the third follow-up visit are available (ages 12-13; n = 6,251). SU descriptives for al psychoactive substances over time are outlined. General estimating equations (GEEs) assessed whether sociodemographic factors, internalizing and externalizing symptoms, and parental SU problems were associated with SU between Baseline and Y2 follow-up. Across time, alcohol and nicotine remain the most used substances. Yearly rates of any SU increased (past year use: 13.9% in Y1; 14% Y2, 18.4% Y3). Cumulatively, by Y3, 39.7% of the cohort reported experimenting (e.g., sipping alcohol) with SU within their lifetime, while 7.4% reported a "full use" (a full alcohol drink, nicotine use, cannabis use, or any other SU) in their lifetime (past-year: 1.9% alcohol, 2.1% nicotine, 1.1% cannabis, 1.2% other substances). GEEs revealed ongoing longitudinal associations between sociodemographic factors, greater externalizing symptoms, and parental drug problems with increased odds of initiating SU. As ABCD participants transition into their teenage years, the cohort is initiating SU at increasing (though still low) rates.

Objective: Research has demonstrated comorbidity between Attention-Deficit Hyperactivity Disorder (ADHD) and cannabis use, and some have proposed that subclinical ADHD symptoms may explain attentional deficits in cannabis users. Here we investigated whether subclinical ADHD symptoms and cannabis use independently or interactively predict performance on attention tasks in adolescents and young adults. Method: Seventy-two participants (cannabis users (MJ) = 34, Controls = 38) completed neuropsychological tasks of inhibition and attention. Parent report on the Child Behaviors Checklist reflected current ADHD symptoms. Multiple regression analyses examined whether ADHD symptoms and cannabis use independently or interactively predicted cognitive outcomes. Results: Cannabis use was significantly associated with slower CPT hit rate response. Subclinical ADHD symptoms did not independently predict or moderate cannabis effects. Conclusions: Cannabis users demonstrated slower response rate during an attentional task. Subclinical ADHD symptoms did not predict any deficits. As such, attention deficits seen in cannabis users are more related to substance use than ADHD symptomatology.

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.

Objectives: The high rate of cannabis (CAN) use in emerging adults is concerning given prior research suggesting neurocognitive deficits associated with CAN use in youth. Regular CAN use downregulates endocannabinoid activity, while aerobic exercise upregulates cannabinoid receptor 1 activity and releases endocannabinoids. Here we investigate the influence of regular CAN use on neuropsychological performance, and whether aerobic fitness moderates these effects. Methods: Seventy-nine young adults (37 CAN users) aged 16–26 participated. Groups were balanced for aerobic fitness level. Exclusion criteria included: left-handedness, past-year independent Axis-I disorders, major medical/neurologic disorders, prenatal issues, or prenatal alcohol/illicit drug exposure. After 3 weeks of abstinence, participants completed a neuropsychological battery and a maximal oxygen consumption test (VO₂ max). Multiple regressions tested whether past-year CAN use, VO₂ max, and CAN*VO₂ max interaction predicted neuropsychological performance, controlling for past-year alcohol use, cotinine, gender, and depression symptoms. Results: Increased CAN use was associated with decreased performance on working memory and psychomotor tasks. High aerobic fitness level was related to better performance on visual memory, verbal fluency, and sequencing ability. CAN*VO₂ max predicted performance of psychomotor speed, visual memory, and sequencing ability. Conclusions: Following monitored abstinence, increased CAN use was associated with poorer performance in working memory and psychomotor speed. Higher aerobic fitness level moderated the impact of CAN on visual memory, executive function and psychomotor speed, as more aerobically fit CAN users demonstrated better performance relative to low-fit users. Therefore, aerobic fitness may present an affordable and efficacious method to improve cognitive functioning in CAN users. (JINS, 2019, 25, 134–145)