Advancing high quality longitudinal data collection: Implications for the HEALthy Brain and Child Development (HBCD) Study design and recruitment

Autor: Yajuan Si, Gretchen Bandoli, Katherine M. Cole, M. Daniele Fallin, Elizabeth A. Stuart, Kelly K. Gurka, Keri N. Althoff, Wesley K. Thompson
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Developmental Cognitive Neuroscience, Vol 69, Iss , Pp 101432- (2024)
Druh dokumentu: article
ISSN: 1878-9293
DOI: 10.1016/j.dcn.2024.101432
Popis: The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The HBCD Study aims to reflect the sociodemographic diversity of pregnant individuals in the U.S. The study will also oversample individuals who use substances during pregnancy and enroll similar individuals who do not use to allow for generalizable inferences of the impact of prenatal substance use on trajectories of child development. Without probability sampling or a randomization-based design, the study requires innovation during enrollment, close monitoring of group differences, and rigorous evaluation of external and internal validity across the enrollment period. In this article, we discuss the HBCD Study recruitment and enrollment data collection processes and potential analytic strategies to account for sources of heterogeneity and potential bias. First, we introduce the adaptive design and enrollment monitoring indices to assess and enhance external and internal validity. Second, we describe the visit schedule for in-person and remote data collection where dyads are randomly assigned to visit windows based on a jittered design to optimize longitudinal trajectory estimation. Lastly, we provide an overview of analytic procedures planned for estimating trajectories.
Databáze: Directory of Open Access Journals