Faculty Bibliography

PURPOSE/OBJECTIVE:performed with autistic youth with varying presentations. METHODS:administration and results were analyzed and compared across relevant clinical characteristics, including age, language level, and autism severity. RESULTS:results were highly correlated with existing measures, parent-child agreement was relatively low and variable across subgroups of autistic youth. CONCLUSIONS:adaptations are likely necessary to improve accessibility, linguistic clarity, and diagnostic specificity and will be important to promote scalable, equitable MH screening for autistic youth.

There is limited understanding of modifiable factors influencing health-related quality of life (HRQoL) among children living with type 1 diabetes (T1D). Executive function skills may be a relevant factor because they underpin the ability to successfully orchestrate T1D self-management. We examined the association between executive functioning and HRQoL among 10-17 year old children living with T1D for more than six months. Caregivers and children (n = 41) completed assessments to measure the child's executive function skills and child and caregiver HRQoL. Linear regression models estimated adjusted betas and 95% confidence intervals (CI) for associations between child executive functioning and child and caregiver HRQoL. In adjusted models, worse executive functioning skills were associated with worse HRQoL. This pattern was consistent across caregiver and child report of the child's executive functioning, caregiver and child report of the child's HRQoL, and caregiver report of their own HRQoL. Further investigation is needed to understand how executive functioning and HRQoL are related in this population, as well as whether educating families on the role of executive functioning in diabetes self-management could improve HRQoL within the family ecosystem.

BACKGROUND:Autism is most often diagnosed after the age of 3, despite evidence that neurodevelopmental differences emerge within the first 2 years of life and that genetic and familial risk can be identified at birth. METHODS:Established in September 2022 (anticipated duration of 5-7 years), the Prospective Genetic Risk Evaluation and Assessment (PROGRESS) in Autism Center is an ongoing longitudinal cohort study designed to characterize early developmental trajectories associated with autism and evaluate the impact of providing genetic information to families. RESULTS:Infants who undergo genomic newborn screening and enroll in PROGRESS are followed from 3 to 24 months of age and categorized into three groups: identified genetic probability (IGP), familial likelihood without identified genetic probability (Baby Siblings), and no identified genetic probability (NGP). Assessments include electroencephalography, electrocardiography, auditory, eye tracking, developmental testing, caregiver-infant interaction, and caregiver-reported measures. Autism screening is conducted at 18 months, with comprehensive diagnostic evaluation at 24 months. Caregiver psychosocial experiences of receiving early genetic information are assessed through surveys and interviews. CONCLUSION/CONCLUSIONS:By integrating genomic probability with early neurobehavioral development and family experiences, PROGRESS provides a framework to inform ethical genomic screening, developmental monitoring, and timely access to early intervention supported by a family navigator. IMPACT/CONCLUSIONS:This study presents the rationale and methods of the ongoing Prospective Genetic Risk Evaluation and Assessment (PROGRESS) in Autism Center at Columbia University, which began in September 2022 (anticipated duration of 5-7 years). PROGRESS is a prospective longitudinal cohort assessing infants with identified genetic probability, familial likelihood, or no identified genetic probability for autism from 3 to 24 months of age. By linking early genetic probability with brain-behavioral trajectories, PROGRESS advances understanding of autism-related differences before clinical diagnosis and provides an empirically grounded foundation for ethical genomic newborn screening and optimized early developmental monitoring and intervention.

INTRODUCTION/BACKGROUND:Historical disparities in maternal and infant health, exacerbated over the COVID-19 pandemic, necessitate investment in a systematic and community-based approach to dyadic care. NewYork-Presbyterian sought to build an innovative, 2-generation program integrating obstetric, pediatric, behavioral health, and community services. METHOD/METHODS:This report outlines the development of the Maternal and Child Integrated Mental Health Program (MAC-IMP) from 2020 to 2024, utilizing the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework, informed by deidentified patient data collected during this period. RESULTS:Through multidisciplinary collaboration, data and health record optimization, risk stratification, and comprehensive service alignment, an equitable and patient-centered model was developed. DISCUSSION/CONCLUSIONS:Lessons learned include methods for multisystem clinical and administrative coordination, communication, and community-partnership building. These lessons can be adapted for multispecialty health care systems across the country to build a more patient-centered, preventative, and holistic model of maternal and infant care. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

In several European countries, national clinical guidelines for the management of ADHD are lacking. In others, guidelines are outdated or do not address more detailed aspects of care, such as medication titration procedures or specific recommendations for school adjustments. Perceptions of the appropriateness of treatment, which influence the delivery of care for ADHD, are shaped by sociocultural aspects. Consequently, practices in the management of ADHD are expected to substantially vary across Europe. To better understand current practices in both pharmacological and non-pharmacological management of ADHD, as well as clinicians' perceptions of treatment appropriateness, we conducted an online survey among European qualified child and adolescent (neuro)psychiatrists and general psychiatrists or trainees involved in the care of children and adolescents with ADHD. The survey was developed and implemented by the European Society for Child and Adolescent Psychiatry (ESCAP) Research Academy, with input from the European ADHD Guidelines Group (EAGG). It was completed by 1,441 clinicians of varying seniority from 23 European countries. The findings provide updated insights into ADHD management across Europe and highlight three key unmet needs. First, several clinically relevant areas lack sufficient evidence, including how to personalise treatment and identify practical predictors of treatment response. Second, some existing evidence has not yet been adequately translated into clinical guidelines or routine practice, particularly regarding comparative treatment effects and dose-response relationships relevant to medication titration. Third, some respondents reported needs that are already addressed in existing international guidelines, suggesting that language barriers may limit access to guidance and underscoring the importance of developing country-specific recommendations in local languages. Overall, this survey - to our knowledge the largest of its kind conducted in Europe - provides valuable information to inform future clinical guidelines, research priorities, and health policy. It also informs future training programmes aimed at reducing bias in the perception and delivery of ADHD treatment.

More than 100 prediction models have been developed to support the diagnosis, prognosis, or treatment of ADHD, yet none has reached routine clinical practice. In this Personal View, we argue that an important reason for this implementation gap is the absence of clearly defined prediction-based decision rules-formalised mappings from a model's output to specific clinical actions. Most published models report discrimination metrics such as the area under the receiver-operating-characteristic curve, but do not specify what a clinician should do differently for a patient classified as at high risk versus low risk. Without this link to action, even an accurate model remains clinically inert. We describe how prediction-based decision rules, combined with target trial emulation of their clinical utility in large observational datasets, offer a feasible path forward. We illustrate the approach with two worked ADHD examples (treatment intensity guided by predicted persistence and medication selection guided by predicted treatment response) and propose four priorities to shift the field from model development towards decision-oriented evaluation and implementation.

OBJECTIVE:Prenatal maternal depression (PMD) is a common public health concern, affecting up to 20% of pregnancies worldwide. Children exposed to PMD exhibit early self-regulatory and emotional difficulties, although its impact on the developing fetal brain remains largely unexplored. The amygdala and cerebellum are both implicated in emotion regulation and psychiatric vulnerability, are densely interconnected, and undergo rapid maturation in utero. Characterizing the relationship of PMD symptoms to amygdala-cerebellar connectivity before birth offers a unique opportunity to isolate in utero mechanisms of risk. METHOD/METHODS:In a sample of 123 pregnant participants (61% male fetuses, n = 75), PMD symptoms were assessed between the second to third trimester using the Center for Epidemiologic Studies-Depression Scale. Fetuses underwent functional MRI, and region-to-voxel analyses examined amygdala-cerebellar functional connectivity. Statistical tests focused on an emerging hypothesis regarding fetal amygdala-cerebellar connectivity, while also addressing potential amygdala connectivity effects across the full fetal cerebrum. RESULTS:Higher PMD symptoms were associated with significantly increased functional connectivity between the fetal amygdala and cerebellum. This effect remained significant following small volume correction within the cerebellum and after adjusting for covariates. CONCLUSION/CONCLUSIONS:This is the first study to demonstrate altered amygdala-cerebellum connectivity in the human fetal brain in relation to prenatal maternal depression. These findings extend models of prenatal programming by addressing the earliest stages of human brain development and by highlighting the cerebellum's role in emotional network development. Enhanced amygdala-cerebellar coupling in utero may represent an early neural marker of risk for later emotional dysregulation.

Decades of research on the developmental origins of health and disease highlight how prenatal and perinatal conditions are associated with long-term neurocognitive development. Exposures such as maternal stress, substance use, metabolic disorders, obstetric complications, low birthweight, and preterm birth have been linked to differences in brain, cognition, and mental health. Yet, most prior studies have been limited by small sample sizes, narrow exposure measures, or isolated outcomes. The Adolescent Brain Cognitive Development (ABCD) Study provides an unparalleled opportunity to overcome these limitations with nearly 12,000 children recruited at ages 9-10 across the United States, followed longitudinally with harmonized multimodal MRI, cognitive and behavioral testing, biospecimens, genetic data, and rich environmental measures in a diverse cohort. Retrospective caregiver reports provide key prenatal and perinatal information, which can be prospectively related to neurodevelopmental outcomes across adolescence. This review synthesizes findings from 111 ABCD-based studies published from 2017 to 2026. Results implicate maternal health conditions, substance use, birth outcomes, and cumulative adversity as being associated with variation in brain, cognitive, and behavioral development. Leveraging its size and diversity, ABCD has fostered advanced analytic approaches, such as multimodal integration of imaging and behavioral data, and longitudinal tracking of developmental trajectories, rarely possible elsewhere. While methodological challenges remain, including retrospective reporting and imaging site variability, ABCD offers unique opportunities to clarify pathways of vulnerability and resilience within an observational framework. Insights from this work can inform public health strategies and guide policies to reduce prenatal risks and strengthening early-life environments to optimize developmental outcomes.

BACKGROUND AND OBJECTIVE/OBJECTIVE:Randomised controlled trials (RCTs) have demonstrated that pharmacotherapy reduces symptoms of attention-deficit/hyperactivity disorder (ADHD) at a group level, but efficacy and tolerability vary across individuals. Clinico-demographic characteristics may act as predictors and/or moderators of treatment efficacy and tolerability, but systematic evidence remains limited. Therefore, we systematically analysed RCTs of ADHD medications to identify potential demographic and clinical predictors/moderators of efficacy and tolerability across the lifespan. METHODS:Randomised controlled trials were identified from the MED-ADHD database ( https://med-adhd.org/ ), a repository of RCTs of medications for ADHD in children, adolescents and adults. The database is based on systematic searches of multiple electronic sources, including PubMed, BIOSIS Previews, CINAHL, the Cochrane Central Registry of Controlled Trials and EMBASE, and is also complemented by unpublished data obtained from manufacturers and study authors. We used the most recent (2026) version of MED-ADHD. The risk of bias was assessed using the revised Cochrane risk-of-bias tool (RoB 2). RESULTS:Among the 171 RCTs screened, 62 assessed clinico-demographic factors as possible predictors or moderators of treatment efficacy and tolerability. Age was the most examined characteristic (56.4%) followed by, among the top five, psychiatric comorbidities (53.2%), sex (46.8%), baseline ADHD symptom severity (27.4%), and ADHD presentation (24.2%). Most RCTs reported no significant findings although there was preliminary evidence of associations with age (17.7%), psychiatric comorbidities (17.7%), baseline ADHD symptom severity (16.1%), sex (11.3%), and ADHD presentation (4.8%). Risk of bias was rated high in 37% of RCTs. CONCLUSIONS:Stringent sample selection and reliance on group-level analyses may limit the power to detect predictors and moderators of treatment efficacy and tolerability in classical RCTs. Consequently, the current evidence provides limited and inconsistent guidance on clinically meaningful predictors/moderators. However, variables such as age, psychiatric comorbidities, sex, baseline severity and ADHD presentation have been the most frequently examined with positive findings and may hold promise. Future research should prioritise individual participant data meta-analyses of RCTs, alongside well-powered analyses of a comprehensive observational dataset, to more robustly investigate these associations and support treatment stratification through predictive models.

Prior studies suggest fluoride exposure in drinking water above 1500 μg/L is associated with lower child cognition, but evidence is limited at lower exposure levels and in U.S. populations. We evaluated whether prenatal exposure to fluoride in regulated public drinking water was associated with cognition in a pooled U.S. cohort. We analyzed observational data from the Environmental influences on Child Health Outcomes (ECHO) Cohort, including 2514 children born 2006-2019 across 17 sites in 23 states. Individual prenatal time-weighted average public water fluoride concentrations were estimated by linking census tract-level concentrations to residential addresses across pregnancy. Fluid and crystallized cognition were assessed using NIH Toolbox scores. Generalized estimating equation models estimated adjusted mean differences using restricted cubic spline and linear change-point models. Individual prenatal time-weighted average water fluoride concentrations ranged from < 1.0-1940.0 μg/L (mean = 396.9 μg/L). Cubic spline models showed significant inverse associations for fluid cognition above 1107.0 μg/L. Linear change-point models identified 675 μg/L as the best-fitting change-point for fluid cognition; above this value, fluid scores were 0.67 points lower (95% CI, -0.92, -0.42) per 100 μg/L higher fluoride. These findings indicate that prenatal fluoride exposure in regulated public water is nonlinearly associated with lower fluid cognition scores in U.S. children at concentrations below current WHO and U.S. EPA thresholds.