Recruiting the ABCD sample: Design considerations and procedures

The ABCD study is a new and ongoing project of very substantial size and scale involving 21 data acquisition sites. It aims to recruit 11,500 children and follow them for ten years with extensive assessments at multiple timepoints. To deliver on its potential to adequately describe adolescent development, it is essential that it adopt recruitment procedures that are efficient and effective and will yield a sample that reflects the nation’s diversity in an epidemiologically informed manner. Here, we describe the sampling plans and recruitment procedures of this study. Participants are largely recruited through the school systems with school selection informed by gender, race and ethnicity, socioeconomic status, and urbanicity. Procedures for school selection designed to mitigate selection biases, dynamic monitoring of the accumulating sample to correct deviations from recruitment targets, and a description of the recruitment procedures designed to foster a collaborative attitude between the researchers, the schools and the local communities, are provided.

[1]  Megan E. Patrick,et al.  What is a representative brain? Neuroscience meets population science , 2013, Proceedings of the National Academy of Sciences.

[2]  K. Merikangas,et al.  Association of Lifetime Mental Disorders and Subsequent Alcohol and Illicit Drug Use: Results From the National Comorbidity Survey-Adolescent Supplement. , 2016, Journal of the American Academy of Child and Adolescent Psychiatry.

[3]  Jody Tanabe,et al.  Sex disparities in substance abuse research: Evaluating 23 years of structural neuroimaging studies. , 2017, Drug and alcohol dependence.

[4]  Roger Tourangeau,et al.  Summary Report of the AAPOR Task Force on Non-probability Sampling , 2013 .

[5]  Michael R. Elliott,et al.  Inference for Nonprobability Samples , 2017 .

[6]  Jesper Andersson,et al.  A multi-modal parcellation of human cerebral cortex , 2016, Nature.

[7]  Michael C. Neale,et al.  The utility of twins in developmental cognitive neuroscience research: How twins strengthen the ABCD research design , 2017, Developmental Cognitive Neuroscience.

[8]  T. Paus Population neuroscience. , 2016, Handbook of clinical neurology.

[9]  Megan S. Schuler,et al.  Generalizing observational study results: applying propensity score methods to complex surveys. , 2014, Health services research.

[10]  B. J. Casey,et al.  Family Income, Parental Education and Brain Structure in Children and Adolescents , 2015, Nature Neuroscience.

[11]  Mark A. Elliott,et al.  The Philadelphia Neurodevelopmental Cohort: A publicly available resource for the study of normal and abnormal brain development in youth , 2016, NeuroImage.

[12]  Henrik Toft Sørensen,et al.  Comment on "Perils and potentials of self-selected entry to epidemiological studies and surveys" , 2016 .

[13]  Thomas E. Nichols,et al.  The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data , 2014, Brain Imaging and Behavior.

[14]  W. Thompson,et al.  Design considerations for characterizing psychiatric trajectories across the lifespan: application to effects of APOE-ε4 on cerebral cortical thickness in Alzheimer's disease. , 2011, The American journal of psychiatry.

[15]  A. Hofman,et al.  The Generation R Study: design and cohort update until the age of 4 years , 2008, European Journal of Epidemiology.

[16]  Kathleen Mullan Harris,et al.  National Longitudinal Study of Adolescent Health, Wave IV, 2007-2008 (Add Health): (527532012-001) , 2008 .

[17]  Patricia A. Berglund,et al.  Applied Survey Data Analysis , 2010 .

[18]  Catherine P. Bradshaw,et al.  Assessing the Generalizability of Randomized Trial Results to Target Populations , 2015, Prevention Science.

[19]  D. Rubin,et al.  The central role of the propensity score in observational studies for causal effects , 1983 .

[20]  P. Elliott,et al.  UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age , 2015, PLoS medicine.

[21]  Torsten Rohlfing,et al.  The National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA): A Multisite Study of Adolescent Development and Substance Use. , 2015, Journal of studies on alcohol and drugs.

[22]  L. Hedges,et al.  Generalizing from unrepresentative experiments: a stratified propensity score approach , 2014 .

[23]  Laurie Drapela National Education Longitudinal Survey of 1988 (NELS:88) , 2005 .

[24]  Sarah W. Feldstein Ewing,et al.  Approaching Retention within the ABCD Study , 2017, Developmental Cognitive Neuroscience.

[25]  A. Hofman,et al.  The Generation R Study: design and cohort update 2010 , 2010, European Journal of Epidemiology.

[26]  P. Gluckman,et al.  Insights from the Growing Up in Singapore Towards Healthy Outcomes (GUSTO) Cohort Study , 2014, Annals of Nutrition and Metabolism.

[27]  Tal Kenet,et al.  The Pediatric Imaging, Neurocognition, and Genetics (PING) Data Repository , 2016, NeuroImage.