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      Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description

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          Abstract

          The Adolescent Brain and Cognitive Development (ABCD) Study incorporates a comprehensive range of measures assessing predictors and outcomes related to both mental and physical health across childhood and adolescence. The workgroup developed a battery that would assess a comprehensive range of domains that address study aims while minimizing participant and family burden. We review the major considerations that went into deciding what constructs to cover in the demographics, physical health and mental health domains, as well as the process of selecting measures, piloting and refining the originally proposed battery. We present a description of the baseline battery, as well as the six-month interim assessments and the one-year follow-up assessments. This battery includes assessments from the perspectives of both the parent and the target youth, as well as teacher reports. This battery will provide a foundational baseline assessment of the youth’s current function so as to permit characterization of stability and change in key domains over time. The findings from this battery will also be utilized to identify both resilience markers that predict healthy development and risk factors for later adverse outcomes in physical health, mental health, and substance use and abuse.

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          Most cited references119

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          A self-report measure of pubertal status: Reliability, validity, and initial norms.

          Puberty is a central process in the complex set of changes that constitutes the transition from childhood to adolescence. Research on the role of pubertal change in this transition has been impeded by the difficulty of assessing puberty in ways acceptable to young adolescents and others involved. Addressing this problem, this paper describes and presents norms for a selfreport measure of pubertal status. The measure was used twice annually over a period of three years in a longitudinal study of 335 young adolescent boys and girls. Data on a longitudinal subsample of 253 subjects are reported. The scale shows good reliability, as indicated by coefficient alpha. In addition, several sources of data suggest that these reports are valid. The availability of such a measure is important for studies, such as those based in schools, in which more direct measures of puberty may not be possible.
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            The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: A large-scale cross-sectional study.

            Over the last decade, research into "addictive technological behaviors" has substantially increased. Research has also demonstrated strong associations between addictive use of technology and comorbid psychiatric disorders. In the present study, 23,533 adults (mean age 35.8 years, ranging from 16 to 88 years) participated in an online cross-sectional survey examining whether demographic variables, symptoms of attention-deficit/hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), anxiety, and depression could explain variance in addictive use (i.e., compulsive and excessive use associated with negative outcomes) of two types of modern online technologies: social media and video games. Correlations between symptoms of addictive technology use and mental disorder symptoms were all positive and significant, including the weak interrelationship between the two addictive technological behaviors. Age appeared to be inversely related to the addictive use of these technologies. Being male was significantly associated with addictive use of video games, whereas being female was significantly associated with addictive use of social media. Being single was positively related to both addictive social networking and video gaming. Hierarchical regression analyses showed that demographic factors explained between 11 and 12% of the variance in addictive technology use. The mental health variables explained between 7 and 15% of the variance. The study significantly adds to our understanding of mental health symptoms and their role in addictive use of modern technology, and suggests that the concept of Internet use disorder (i.e., "Internet addiction") as a unified construct is not warranted.
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              Socioeconomic disadvantage and child development.

              V C McLoyd (1998)
              Recent research consistently reports that persistent poverty has more detrimental effects on IQ, school achievement, and socioemotional functioning than transitory poverty, with children experiencing both types of poverty generally doing less well than never-poor children. Higher rates of perinatal complications, reduced access to resources that buffer the negative effects of perinatal complications, increased exposure to lead, and less home-based cognitive stimulation partly account for diminished cognitive functioning in poor children. These factors, along with lower teacher expectancies and poorer academic-readiness skills, also appear to contribute to lower levels of school achievement among poor children. The link between socioeconomic disadvantage and children's socioemotional functioning appears to be mediated partly by harsh, inconsistent parenting and elevated exposure to acute and chronic stressors. The implications of research findings for practice and policy are considered.
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                Author and article information

                Contributors
                Journal
                Dev Cogn Neurosci
                Dev Cogn Neurosci
                Developmental Cognitive Neuroscience
                Elsevier
                1878-9293
                1878-9307
                03 November 2017
                August 2018
                03 November 2017
                : 32
                : 55-66
                Affiliations
                [a ]Departments of Psychological & Brain Sciences and Psychiatry, Washington University, Box 1125, One Brookings Drive, St. Louis, MO 63130, United States
                [b ]Department of Psychiatry, University of Vermont College of Medicine, Mail Stop 446 AR6, 1 South Prospect Street, Burlington, VT 05401, United States
                [c ]National Institute of Mental Health, National Institutes of Health, 6001 Executive Blvd, Bethesda, MD 20892, United States
                [d ]Chang Department of Radiology, University of Maryland School of Medicine, 419 W. Redwood Street, Suite 225, Baltimore, MD 21201, United States
                [e ]Department of Psychiatry, University of Pittsburgh, 3811 O’Hara Street, Pittsburgh, PA 15215, United States
                [f ]Department of Epidemiology, Services, and Prevention Research, National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD 20892, United States
                [g ]Department of Psychiatry, University of Vermont College of Medicine, St. Joe’s Room 3213, Box 364SJ, 1 South Prospect, Burlington, VT 05401, United States
                [h ]Departments of Cognitive Science, Psychiatry & Radiology, University of California at San Diego,9500 Gilman Drive(0603), La Jolla, CA 92093-0603, United States
                [i ]Department of Psychiatry, University of California at San Diego,9500 Gilman Drive(0603), La Jolla, CA 92093-0603, United States
                [j ]Department of Psychiatry, University of Utah School of Medicine, 501 Chipeta Way, Salt Lake City, UT 84108, United States
                [k ]Department of Psychiatry, Icahn School of Medicine at Mount Sinai, Friedman Brain Institute, 1470 Madison Avenue, New York, NY 10029, United States
                [l ]Department of Psychiatry, University of Vermont College of Medicine, 1 South Prospect Street Arnold 6, Burlington, VT 05401, United States
                [m ]Laureate Institute for Brain Research, 6655 South Yale Ave, Tulsa, OK 74136-3326, United States
                [n ]Center for Health Sciences, SRI International, 333 Ravenswood Avenue, Menlo Park, CA 94025, United States
                [o ]Department of Psychiatry & Addiction Center, University of Michigan, Rachel UpJohn Building, 4250 Plymouth Road, Ann Arbor, MI 48109-2700, United States
                [p ]Department of Psychological Sciences, University of Missouri, 200 South Seventh Street, Columbia, MO 65211, United States
                Author notes
                [* ]Corresponding author at: Couch Chair of Psychiatry, Washington University in St. Louis., Box 1125, One Brookings Drive, St. Louis, MO, 63130, United States. dbarch@ 123456wustl.edu
                Article
                S1878-9293(17)30068-3
                10.1016/j.dcn.2017.10.010
                5934320
                29113758
                f8cad399-376e-4416-8544-ad91500798ca
                © 2017 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 18 March 2017
                : 10 September 2017
                : 30 October 2017
                Categories
                Article

                Neurosciences
                psychopathology,assessment,physical health,mental health
                Neurosciences
                psychopathology, assessment, physical health, mental health

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