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The Utility of Newborn Neurobehavioral Assessments for Early Prediction of Developmental Risk

Sat, March 25, 8:15 to 9:45am, Salt Palace Convention Center, Floor: 1, Meeting Room 151 A-C

Session Type: Paper Symposium

Abstract

Neurobehavioral dysregulation in infancy is associated with a host of maladaptive outcomes in childhood, including cognitive, behavioral, and socio-emotional difficulties (Lester et al., 2009; McGowan et al., 2022; Spinelli et al., 2018). Consequently, identifying patterns of dysregulation early in development (e.g., the neonatal period) is critical to identifying children at an increased risk of developmental disruptions and/or delays. The NICU Network Neurobehavioral Scale (NNNS; Lester & Tronick, 2004) offers valuable insight into newborns’ neurologic organization and behavioral functioning, thereby serving as a screening tool for neonatal neurobehavioral dysregulation. The current symposium demonstrates the utility of the NNNS in identifying both pre- and full-term infants at risk for adverse outcomes later in development and discusses pre- and perinatal antecedents of neonatal neurobehavior.
Paper 1 identifies two NNNS profiles that differentially predict infant social-emotional development at 18 months in combination with child sex and parenting stress. Paper 2 demonstrates that neonates’ neurobehavioral signs of stress interact with their mothers’ self-reported stress levels in predicting infant language outcomes at 18 months. Paper 3 reveals significant associations between dysregulated NNNS profiles, newborn medical morbidities, and risk for positive autism screenings at 2 years of age among a sample of very preterm infants. Finally, having established a link between newborn neurobehavior and infant development, Paper 4 identifies pre- and perinatal antecedents (e.g., maternal mental health and substance use) of dysregulated NNNS profiles. Collectively, these papers address important gaps in our understanding of the antecedents and consequences of neonatal neurobehavior across high and low-risk samples.

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