Faculty Bibliography

Determination of optimal individual treatment rules (ITR) is a rapidly growing area in precision medicine; various parametric and non-parametric methods have been proposed. Existing methods, however, focus on the mean outcome and thus are sensitive to outliers, skewed and heavy-tailed outcome distributions. In this paper, we propose an optimal ITR estimation framework using a weighted classifier with robust weights based on measures of similarity. Compared to previous methods in the literature, this two-stage nonparametric model is novel and enjoys several advantages. First, due to its non-parametric nature, it is more flexible than regression-based parametric and semi-parametric models. Second, the similarity-based confidence index is essentially a weighted sum of indicator functions depending on the sign of pairwise outcome differences; therefore, it is robust to outliers, skewed and heavy-tailed outcome distributions. The performance of the proposed approach is demonstrated via simulation studies and an analysis of data from a randomized clinical trial for depression.

OBJECTIVES/OBJECTIVE:Agitation and restraint among pediatric psychiatric patients are a frequent, yet little studied, source of morbidity and, rarely, mortality in the emergency department (ED). This study examined agitation and restraint among youth patients in a specialized pediatric psychiatric ED, considering clinical and sociodemographic characteristics of those who required restraint to determine the clinical correlates of agitation and restraint in this population. METHODS:This descriptive study was a 6-year retrospective chart review of all patients restrained for acute agitation. Demographics, clinical characteristics, diagnoses, and reasons for restraint were collected. Relationships between sociodemographic and clinical variables to types of restraints used were examined, along with change over the study period in rate of and mean time in restraint. RESULTS:The average restraint rate was 1.94%, which remained fairly consistent throughout study period, although average time in restraint decreased significantly. Restraints were more common in males. Adolescents were overrepresented in the ED population, and after controlling for this, restraint rates were similar in adolescents and younger children. Physical aggression was the most frequent precipitant, although among adolescents verbal aggression was also a precipitant (more so than in younger children). Disruptive behavior disorder diagnoses were most frequently associated with restraint. CONCLUSIONS:A lower rate of restraint is reported here than has been seen in programs where youths are treated in medical or adult psychiatric EDs. Hospitals without specialized pediatric psychiatric emergency programs should invest in staff training in deescalation techniques and in access to pediatric psychiatric treatment. The finding that, of youth restrained, a significant proportion were under 12 years old and/or carried diagnoses not typically associated with aggressive behavior, indicates that crisis prevention, management, and treatment should include younger populations and diverse diagnostic groups, rather than focusing narrowly on older patients with psychotic or substance use disorders.

There are mixed findings when examining if technology use is harmful for adolescent sleep and health. This study builds on these mixed findings by examining the association between technology use with sleep and health in a high-risk group of adolescents. Adolescents with an evening circadian preference (N = 176; 58% female, mean age = 14.77, age range = 10-18) completed measures over one week. Sleep was measured via actigraphy. Technology use and health were measured using ecological momentary assessment. Technology use was associated with an increase in sleep onset latency; with better emotional, social, cognitive, and physical health; and with worse behavioral health. This study offers support for technology use having some benefits and expands research on technology use to adolescents with an evening circadian preference.

Brain and cognitive development is a burgeoning area of scientific inquiry, with tremendous potential to better the lives of children. Large scale longitudinal neuroimaging studies offer opportunities for significant scientific advances in our understanding of developing brain structure and function. The proposed manuscript will focus on the scientific potential of the HEALthy Brain and Cognitive Development (HBCD) Study, highlighting what questions these data can and what they cannot answer about child development. Specifically, we caution against the misuse of these data for advancing de-contextualized and scientifically questionable narratives about the development of children from marginalized communities. We will focus on building and organizing a framework for interpreting HBCD data through the lens of sampling, cultural context, measurement, and developmental science theory. Our goal is to thoughtfully offer the scientific community opportunities to use the large scale and collaborative nature of HBCD to collectively revise practices in developmental science that to-date have not carefully considered their own role in perpetuating narratives that support systemic injustice.

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.

BACKGROUND:The prevalence of gestational diabetes mellitus (GDM) has rapidly increased, yet few prior studies have investigated parameters of early brain development in infants born to gestational diabetic mothers. The present study assessed visual evoked potentials (VEPs) in healthy infants born to gestational diabetic mothers and matched controls. METHODS:After exclusions, in this prospective study we examined VEPs in 73 neonates between 37 weeks and 41 weeks gestation at birth (n = 37 infants of gestational diabetic mothers). Stroboscopic flashes were presented through closed eyelids during passive electroencephalography (EEG) recording to derive VEP waveforms during natural sleep. RESULTS:There was a statistically significant moderate correlation between gestational age at birth and P2 latency of the flash VEP where P2 latency significantly decreased with increasing gestational age (Pearson's R(73) = -0.32, p < .01). There was also a significant moderate correlation between postnatal age (hours of life) and P2 latency of the flash VEP where P2 latency significantly decreased with increasing postnatal age (Pearson's R(73) = -0.23, p < .05). When controlling for gestational age at birth, postnatal age, and sex, there was a significant effect of group (GDM-exposed vs. control) on P2 latency of the flash VEP (p < .05). Infants of gestational diabetic mothers had a significantly longer P2 latency (M: 215.29 ± SD: 2.58 ms) than controls (M: 206.41 ± SD: 2.62 ms). CONCLUSION:Our findings suggest P2 flash VEP latency is a potential measure of cortical maturation and marker of immature development in infants of gestational diabetic mothers.

In response to the COVID-19 pandemic, research institutions across the globe have modified their operations in ways that have limited or eliminated the amount of permissible in-person research interaction. In order to prevent the loss of important developmentally-timed data during the pandemic, researchers have quickly pivoted and developed innovative methods for remote assessment of research participants. In this manuscript, we describe methods developed for remote assessment of a parent child cohort with a focus on examining the perinatal environment, behavioral and biological indicators of child neurobehavioral development, parent-child interaction, as well as parent and child mental and physical health. We include recommendations relevant to adapting in-laboratory assessments for remote data collection and conclude with a description of the successful dissemination of the methods to eight research sites across the United States, each of whom are involved in Phase 1 of the HEALthy Brain and Child Development (HBCD) Study. These remote methods were born out of pandemic-related necessity; however, they have much wider applicability and may offer advantages over in-laboratory neurodevelopmental assessments.

BACKGROUND:Climate change has important implications for the health and futures of children and young people, yet they have little power to limit its harm, making them vulnerable to climate anxiety. This is the first large-scale investigation of climate anxiety in children and young people globally and its relationship with perceived government response. METHODS:We surveyed 10 000 children and young people (aged 16-25 years) in ten countries (Australia, Brazil, Finland, France, India, Nigeria, Philippines, Portugal, the UK, and the USA; 1000 participants per country). Invitations to complete the survey were sent via the platform Kantar between May 18 and June 7, 2021. Data were collected on participants' thoughts and feelings about climate change, and government responses to climate change. Descriptive statistics were calculated for each aspect of climate anxiety, and Pearson's correlation analysis was done to evaluate whether climate-related distress, functioning, and negative beliefs about climate change were linked to thoughts and feelings about government response. FINDINGS/RESULTS:Respondents across all countries were worried about climate change (59% were very or extremely worried and 84% were at least moderately worried). More than 50% reported each of the following emotions: sad, anxious, angry, powerless, helpless, and guilty. More than 45% of respondents said their feelings about climate change negatively affected their daily life and functioning, and many reported a high number of negative thoughts about climate change (eg, 75% said that they think the future is frightening and 83% said that they think people have failed to take care of the planet). Respondents rated governmental responses to climate change negatively and reported greater feelings of betrayal than of reassurance. Climate anxiety and distress were correlated with perceived inadequate government response and associated feelings of betrayal. INTERPRETATION/CONCLUSIONS:Climate anxiety and dissatisfaction with government responses are widespread in children and young people in countries across the world and impact their daily functioning. A perceived failure by governments to respond to the climate crisis is associated with increased distress. There is an urgent need for further research into the emotional impact of climate change on children and young people and for governments to validate their distress by taking urgent action on climate change. FUNDING/BACKGROUND:AVAAZ.