Search

Background and aimsThe 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.MethodsThis 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.ResultsParticipants 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 (β = -0.10 [95%CI: -0.16, -0.03], p = 0.004) and vice versa (β = -0.11 [95%CI: -0.18, -0.05], p < 0.001); 2) externalizing symptoms at age 10-11 predicting sleep problems (β = 0.11 [95%CI: 0.04, 0.19], p = 0.002), SMA (β = 0.07 [95%CI: 0.01, 0.13], p = 0.014), and internalizing symptoms (β = 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.ConclusionWe 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.

Youth screen media activity is a growing concern, though few studies include objective usage data. Through the longitudinal, U.S.-based Adolescent Brain Cognitive Development (ABCD) Study, youth (mage = 14; n = 1415) self-reported their typical smartphone use and passively recorded three weeks of smartphone use via the ABCD-specific Effortless Assessment Research System (EARS) application. Here we describe and validate passively-sensed smartphone keyboard and app use measures, provide code to harmonize measures across operating systems, and describe trends in adolescent smartphone use. Keyboard and app-use measures were reliable and positively correlated with one another (r = 0.33) and with self-reported use (rs = 0.21-0.35). Participants recorded a mean of 5 h of daily smartphone use, which is two more hours than they self-reported. Further, females logged more smartphone use than males. Smartphone use was recorded at all hours, peaking on average from 8 to 10 PM and lowest from 3 to 5 AM. Social media and texting apps comprised nearly half of all use. Data are openly available to approved investigators ( https://nda.nih.gov/abcd/ ). Information herein can inform use of the ABCD dataset to longitudinally study health and neurodevelopmental correlates of adolescent smartphone use.

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.

BackgroundSelf-reported physical activity is often inaccurate. Wearable devices utilizing multiple sensors are now widespread. The aim of this study was to determine acceptability of Fitbit Charge HR for children and their families, and to determine best practices for processing its objective data.MethodsData were collected via Fitbit Charge HR continuously over the course of 3 weeks. Questionnaires were given to each child and their parent/guardian to determine the perceived usability of the device. Patterns of data were evaluated and best practice inclusion criteria recommended.ResultsBest practices were established to extract, filter, and process data to evaluate device wear, r and establish minimum wear time to evaluate behavioral patterns. This resulted in usable data available from 137 (89%) of the sample.ConclusionsActivity trackers are highly acceptable in the target population and can provide objective data over longer periods of wear. Best practice inclusion protocols that reflect physical activity in youth are provided.

AimTo examine individual variability between perceived physical features and hormones of pubertal maturation in 9-10-year-old children as a function of sociodemographic characteristics.MethodsCross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study-a multi-site sample of 9-10 year-olds (n = 11,875)-and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels.ResultsPDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child's weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample.ConclusionsSociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9-10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes.

AimTo examine individual variability between perceived physical features and hormones of pubertal maturation in 9-10-year-old children as a function of sociodemographic characteristics.MethodsCross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study-a multi-site sample of 9-10 year-olds (n = 11,875)-and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels.ResultsPDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child's weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample.ConclusionsSociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9-10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes.

RationaleAdvancing marijuana prevention and intervention efforts are important given the decreasing perception of harm among adolescents and increasing marijuana legalization.ObjectivesThis study evaluates how a monitored abstinence protocol may contribute to emotional functioning and changes in marijuana problems that can enhance successful outcomes for non-treatment-seeking adolescent marijuana users.MethodsAdolescent marijuana users (n = 26) and demographically matched controls (n = 30) completed 28 days of monitored abstinence confirmed by biweekly urine toxicology. Participants were given measures of emotional functioning, marijuana use symptoms, and reward sensitivity during monitored abstinence.ResultsAll participants (n = 56) completed the protocol, and 69% of marijuana users (n = 18 of 26) were confirmed abstinent for 28 days, with all users showing decreasing marijuana use. Reductions in subsyndromal depression, positive marijuana use expectancies, and poor sleep quality were observed by the end of the monitored abstinence period (n = 26, p values

Spending time watching television, engrossed in a game on a tablet, glued to a gaming console, or messaging friends with a smartphone have become quintessential recreational activities of children and [...]

Background and Aims: Screen media activity (SMA) may impact neurodevelopment in youth. Cross-sectionally, SMA has been linked to brain structural patterns including cortical thinning in children. However, it remains unclear whether specific brain structural co-variation patterns are related to SMA and other clinically relevant measures such as psychopathology, cognition and sleep in children. Methods: Adolescent Brain Cognitive Development (ABCD) participants with useable baseline structural imaging (N = 10,691; 5,107 girls) were analyzed. We first used the Joint and Individual Variation Explained (JIVE) approach to identify cortical and subcortical covariation pattern(s) among a set of 221 brain features (i.e., surface area, thickness, or cortical and subcortical gray matter (GM) volumes). Then, the identified structural covariation pattern was used as a predictor in linear mixed-effect models to investigate its associations with SMA, psychopathology, and cognitive and sleep measures. Results: A thalamus-prefrontal cortex (PFC)- brainstem structural co-variation pattern (circuit) was identified. The pattern suggests brainstem and bilateral thalamus proper GM volumes covary more strongly with GM volume and/or surface area in bilateral superior frontal gyral, rostral middle frontal, inferior parietal, and inferior temporal regions. This covariation pattern highly resembled one previously linked to alcohol use initiation prior to adulthood and was consistent in girls and boys. Subsequent regression analyses showed that this co-variation pattern associated with SMA (β = 0.107, P = 0.002) and externalizing psychopathology (β = 0.117, P = 0.002), respectively. Discussion and Conclusions: Findings linking SMA-related structural covariation to externalizing psychopathology in youth resonate with prior studies of alcohol-use initiation and suggest a potential neurodevelopmental mechanism underlying addiction vulnerability. [ABSTRACT FROM AUTHOR]

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., (©Natasha Wade, Joseph M Ortigara, Ryan M Sullivan, Rachel L Tomko, Florence J Breslin, Fiona C Baker, Bernard F Fuemmeler, Katia Delrahim Howlett, Krista M Lisdahl, Andrew T Marshall, Michael J Mason, Michael C Neale, Lindsay M Squeglia, Dana L Wolff-Hughes, Susan F Tapert, Kara S Bagot, ABCD Novel Technologies Workgroup. Originally published in JMIR Mental Health (https://mental.jmir.org), 18.10.2021.)