Skilled social interactions require knowledge about others' intentions and the ability to implement this knowledge in real-time to generate appropriate responses to one's partner. Young infants demonstrate an understanding of other people's intentions (e.g. Woodward, Sommerville, Gerson, Henderson & Buresh, 2009), yet it is not until the second year that infants seem to master the real-time implementation of their knowledge during social interactions (e.g. Warneken & Tomasello, 2007). The current study investigates the possibility that developments in social competence during the second year are related to increases in the speed with which infants can employ their understanding of others' intentions. Twenty- to 22-month-old infants (N = 23) viewed videos of goal-directed actions on a Tobii eye-tracker and then engaged in an interactive perspective-taking task. Infants who quickly and accurately anticipated another person's future behavior in the eye-tracking task were more successful at taking their partner's perspective in the social interaction. Success on the perspective-taking task was specifically related to the ability to correctly predict another person's intentions. These findings highlight the importance of not only being a 'smart' social partner but also a 'fast' social thinker.

While attention dysregulation is a promising early indicator of neurodevelopmental risk, in particular attention-deficit/hyperactivity disorder (ADHD), it is difficult to characterize clinical concern due to its developmental expectability at the transition to toddlerhood. Thus, explicating the typical:atypical continuum of risk indicators is among the key future directions for research to promote early identification and intervention, and prevent decrements in the attainment of developmental milestones into early childhood. In this paper, we present the Multidimensional Assessment Profiles-Attention Regulation Infant-Toddler (MAPS-AR-IT) Scale, a novel parent-report survey of dimensional, developmentally specified indicators of attention (dys)regulation. Item Response Theory was employed to characterize the typical:atypical spectrum of both normative and more concerning dysregulation (including the contexts in which behavior occurs). We provide evidence of the validity of this measure in capturing the full typical:atypical spectrum via a longitudinal sample of typically developing children at 12-18 months of age (baseline) via concurrent scores on well-validated temperament and clinical measures. We also examine longitudinal stability and predictive validity if the MAPS-AR-IT via a clinical interview of ADHD symptoms at 24-30 months (follow-up). While not diagnostic, we present evidence of the utility of the MAPS-AR-IT in explicating individual neurodevelopmental risk and elucidating the broader typicality of behaviors related to attention (dys)regulation.

Abstract

Objective: Approximately 50% of children with autism exhibit severe tantrums, defiance, and/or aggression. We propose that the Disruptive Behavior Diagnostic Observation Schedule (DB-DOS)-a standardized clinical observation modeled after, and complementary to, the Autism Diagnostic Observation Schedule (ADOS)-could enhance earlier identification of disruptive behavior (DB) in autism populations and inform treatment planning. Methods: We adapted the DB-DOS for children with autism based on expert input and preliminary feasibility testing to accommodate varying cognitive and social communication capacities and increase the likelihood of observing DB in this population. Thereafter, we concurrently administered the modified DB-DOS and the ADOS to 12 children with autism aged 36 to 50 months. Results: Overall, children exhibited greater DB, especially behavioral regulation challenges, during the DB-DOS than during the ADOS. Conclusion: The use of a developmentally sensitive standardized observation tool that presses for DB to complement standardized observations such as the ADOS shows promise for enabling more precise research on targeted DB interventions. Such a tool holds promise as a reliable and efficient method of identifying comorbid DB disorders in the autism population.

Early identification of atypical infant movement behaviors consistent with underlying neuromotor pathologies can expedite timely enrollment in therapeutic interventions that exploit inherent neuroplasticity to promote recovery. Traditional neuromotor assessments rely on qualitative evaluations performed by specially trained personnel, mostly available in tertiary medical centers or specialized facilities. Such approaches are high in cost, require geographic proximity to advanced healthcare resources, and yield mostly qualitative insight. This paper introduces a simple, low-cost alternative in the form of a technology customized for quantitatively capturing continuous, full-body kinematics of infants during free living conditions at home or in clinical settings while simultaneously recording essential vital signs data. The system consists of a wireless network of small, flexible inertial sensors placed at strategic locations across the body and operated in a wide-bandwidth and time-synchronized fashion. The data serve as the basis for reconstructing three-dimensional motions in avatar form without the need for video recordings and associated privacy concerns, for remote visual assessments by experts. These quantitative measurements can also be presented in graphical format and analyzed with machine-learning techniques, with potential to automate and systematize traditional motor assessments. Clinical implementations with infants at low and at elevated risks for atypical neuromotor development illustrates application of this system in quantitative and semiquantitative assessments of patterns of gross motor skills, along with body temperature, heart rate, and respiratory rate, from long-term and follow-up measurements over a 3-mo period following birth. The engineering aspects are compatible for scaled deployment, with the potential to improve health outcomes for children worldwide via early, pragmatic detection methods.