Faculty Bibliography

Objectives: The risk for psychopathology increases with the number of adverse childhood experiences. Summing a number of experiences, however, assumes that all adversity equitably confers risk and operates through complementary mechanisms. To disentangle neurobiological pathways between disparate events and mental health, we examined how threat and deprivation-2 common dimensions of adversity-relate to early childhood psychopathology. Threat or the presence of experiences involving harm or threat of harm affects emotional control. Deprivation or absence of expected environmental inputs affects higher-order cognitive function. If threat and deprivation differentially affect brain development, then they may differentially relate to psychopathology, especially among young children.
Method(s): To examine these patterns, we used the Duke Preschool Anxiety Study, a cross-sectional study of youth ages 2-6 years enrolled through primary care from 2007 to 2011, weighted to reflect a screened population of 3433. Threat and deprivation were operationalized using questions from the Conflict Tactics Scale-2, Conflict Tactics Scale for Parent and Child, and Preschool Age Psychiatric Assessment. Threat measured physical or sexual abuse, domestic violence, and violent neighborhood. Deprivation measured neglect and lack of cognitive stimulation. Poisson regression with robust standard errors estimated adjusted prevalence ratios (PR) jointly for deprivation and threat in relation to counts for total symptoms and symptoms for specific disorders, such as anxiety, depression, and ADHD, in 760 children.
Result(s): Threat (47%) and deprivation (18%) were common; 36 percent of children had at least one disorder, and the total number of symptoms ranged from 0 to 46. Threat-exposed children had 40 percent more total symptoms (95% CI 1.2-1.6) than unexposed children after adjusting for deprivation and demographic covariates. Deprivation was not meaningfully associated with total symptom count (PR 1.1, 95% CI 0.9-1.5) after adjusting for threat and demographic covariates.
Conclusion(s): These disparate associations among threat, deprivation, and mental health symptomatology may reflect the young age of these children or our approach designed to distinguish the unique contributions of deprivation and threat, lending support to the dimensional model of adversity and psychopathology. CAN, PSP, PSC
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Objectives: We will: 1) describe the WonderLab, a digital health initiative within the New York University Langone Health Department of Child and Adolescent Psychiatry; 2) introduce When to Wonder: Picky Eating, which is the WonderLab's first early childhood mental health digital study; and 3) present preliminary data from this study. Our first objective is to demonstrate how smartphone-based tools developed to assess children in their homes and the use of advanced data analytics can transform how, when, and where we assess young children's development and mental health. Our second objective is to share how our multidisciplinary team and agile development methodology enable us to build and launch a consumer-facing pediatric health app within an academic medical center.
Method(s): The WonderLab creates scalable mobile digital health tools to collect multimodal data in children's homes at the individual, family, and population levels. In December 2018, we released When to Wonder: Picky Eating, a national study with consent, enrollment, study activities, and feedback fully integrated in iOS and Android apps that parents download from the app stores. When to Wonder: Picky Eating focuses on the emotions and behaviors related to picky eating in children under the age of 7 years. Data sources include parent-report, video, audio, and an active task that children and parents play independently to quantify children's food preferences.
Result(s): We will present preliminary data from When to Wonder: Picky Eating to characterize normative and clinically significant emotions and behaviors related to picky eating. We will also share data on recruitment and engagement using social media, app performance, and "lessons learned" about digital pediatric health.
Conclusion(s): We create clinically and scientifically valid digital tools that parents and children want to use. We integrate clinical, scientific, engineering, design, data science, and bioethics expertise with collaborative user engagement and a "build, measure, learn" agile development culture. Our app-based study demonstrates how to build digital health tools that collect and analyze population-level and individual-level, multimodal data about children and families in the home. These new tools and approaches have the potential to transform our engagement with families and our delivery of care. EA, EC, MED
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Objectives: Digital innovation has the potential to transform both the science and practice of child mental health. Creation of pediatric digital health tools requires that bioethics, human-centered design, and clinical and scientific expertise are integrated with digital tool development, digital data collection, and data analytics. In this talk, we will describe the opportunities for innovations in pediatric digital mental health and the concurrent ethical and security risks. We will then present a framework and design methodology for creating ethical, human-centered, clinically informed, and evidence-based digital tools for children's mental health.
Method(s): The data presented will come from our experience founding and leading the New York University Langone Department of Child and Adolescent Psychiatry's WonderLab, which creates pediatric digital mental health tools that are evidence based, scalable, and ethical, as well as beautiful and fun so that parents and children would want to use them. The WonderLab brings clinical, scientific, digital engineering, digital design, data science, and bioethics expertise together with user engagement and a "build, measure, learn" agile development culture and methodology. We will use the WonderLab team's development and launch of our first app-based study, "When to Wonder: Picky Eating," to illustrate our framework and methodology.
Result(s): We will describe the innovation opportunities in pediatric digital mental health, including innovation in measurement, engagement, access, and collaborative methodologies. We will then present the ethical, privacy, security, and safety risks related to digital health applications and app-based data collection with children and their families. Finally, we will describe how the WonderLab team, methodology, and products innovate across multiple domains within an explicit ethical and clinically informed framework.
Conclusion(s): Digital innovation and data science have great potential to address the challenges facing our patients and our field. To build ethical and useful digital health tools for children's mental health requires multidisciplinary teams, user engagement, collaborative agile methodology, and a framework that ensures that innovations are integrated with and reflect our ethics and commitment to children. R, COMP, DAM
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Anxiety disorders are prevalent and significantly impact young children and their families. One hypothesized risk factor for anxiety is heightened responses to sensory input. Few studies have explored this hypothesis prospectively. This study had two goals: (1) examine whether sensory over-responsivity is predictive of the development of anxiety in a large prospective sample of children, and (2) identify whether anxiety mediates the relationship between sensory over-responsivity and behavioral challenges. Children's sensory and anxiety symptoms were assessed in a community sample of 917 at 2-5 and again in 191 of these children at 6 years old. Parents also reported on a number of additional behavioral challenges previously found to be associated with both sensory over-responsivity and anxiety separately: irritability, food selectivity, sleep problems, and gastrointestinal problems. Forty three percent of preschool children with sensory over-responsivity also had a concurrent impairing anxiety disorder. Preschool sensory over-responsivity symptoms significantly and positively predicted anxiety symptoms at age six. This relationship was both specific and unidirectional. Finally, school-age anxiety symptoms mediated the relationship between preschool sensory over-responsivity symptoms and both irritability and sleep problems at school-age. These results suggest sensory over-responsivity is a risk factor for anxiety disorders. Furthermore, children who have symptoms of sensory over-responsivity as preschoolers have higher levels of anxiety symptoms at school-age, which in turn is associated with increased levels of school-age behavioral challenges.

This study examines interactions of heritable influences, prenatal substance use, and postnatal parental warmth and hostility on the development of conduct problems in middle childhood for boys and girls. Participants are 561 linked families, collected in 2 cohorts, including birth parents, adoptive parents, and adopted children. Heritable influences on internalizing and externalizing (including substance use) problems were derived from birth mothers' and fathers' symptoms, diagnoses, and age of onset from diagnostic interviews, and the proportion of first-degree relatives with the same type of problems. Smoking during pregnancy (SDP) and alcohol use during pregnancy were assessed retrospectively from birth mothers at 5 months postpartum. Earlier externalizing problems and parental warmth and hostility and were assessed at 1 assessment prior to the outcome (Cohort II: 4.5 years; Cohort I: 7 years). Conduct problems were symptoms from a diagnostic interview assessed at age 6 (Cohort II) or 8 (Cohort I). Findings from regression analyses suggest that (a) SDP plays an important role for the development of conduct problems, (b) some relatively well-accepted effects (e.g., parental hostility) were less important when simultaneously considering multiple factors influencing the development of conduct problems, and (c) main effects of genetic risk and SDP, and interactions among genetic risk and postnatal warmth, SDP and postnatal warmth, and genetic risk, SDP, and postnatal hostility for conduct problems were important for boys' but not girls' conduct problems. Replication is needed, but the current results provide preliminary but empirically grounded hypotheses for future research testing complex developmental models of conduct problems. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

To demonstrate the capability of computer vision analysis to detect atypical orienting and attention behaviors in toddlers with autism spectrum disorder. One hundered and four toddlers of 16-31 months old (mean = 22) participated in this study. Twenty-two of the toddlers had autism spectrum disorder and 82 had typical development or developmental delay. Toddlers watched video stimuli on a tablet while the built-in camera recorded their head movement. Computer vision analysis measured participants' attention and orienting in response to name calls. Reliability of the computer vision analysis algorithm was tested against a human rater. Differences in behavior were analyzed between the autism spectrum disorder group and the comparison group. Reliability between computer vision analysis and human coding for orienting to name was excellent (intra-class coefficient 0.84, 95% confidence interval 0.67-0.91). Only 8% of toddlers with autism spectrum disorder oriented to name calling on >1 trial, compared to 63% of toddlers in the comparison group (p = 0.002). Mean latency to orient was significantly longer for toddlers with autism spectrum disorder (2.02 vs 1.06 s, p = 0.04). Sensitivity for autism spectrum disorder of atypical orienting was 96% and specificity was 38%. Older toddlers with autism spectrum disorder showed less attention to the videos overall (p = 0.03). Automated coding offers a reliable, quantitative method for detecting atypical social orienting and reduced sustained attention in toddlers with autism spectrum disorder.

Academic medical centers (AMCs) today prioritize digital innovation. In efforts to develop and disseminate the best technology for their institutions, challenges arise in organizational structure, cross-disciplinary collaboration, and creative and agile problem solving that are essential for successful implementation. To address these challenges, the Digital DesignLab was created at NYU Langone Health to provide structured processes for assessing and supporting the capacity for innovative digital development in our research and clinical community. Digital DesignLab is an enterprise level, multidisciplinary, digital development team that guides faculty and student innovators through a digital development "pipeline", which consists of intake, discovery, bootcamp, development. It also provides a framework for digital health innovation and dissemination at the institution. This paper describes the Digital DesignLab's creation and processes, and highlights key lessons learned to support digital health innovation at AMCs.