Faculty Bibliography

INTRODUCTION/BACKGROUND:Females with disabilities have greater preconception health risks and adverse perinatal outcomes than those without disabilities. Characterization of reproductive health care utilization among females with disabilities in the United States is limited. We examined health care receipt before, during, and after pregnancy by extent of disability among U.S. females with recent live births. METHODS:This cross-sectional study used Pregnancy Risk Assessment Monitoring System data (collected 2018-2020 and analyzed in 2025) from 24 states that included the Washington Group Short Set of Questions on Disability. Participants self-reported health care visits in the year prior to pregnancy; receipt and timing of prenatal care; and receipt of a postpartum checkup. Disability was assessed as extent of difficulty (none, some, and a lot of difficulty). Associations between extent of disability and health care utilization were estimated using multivariable modified Poisson regression (adjusted prevalence ratios, aPR, and 95% confidence intervals, CI). RESULTS:trimester initiation of prenatal care, but they had a 171% (aPR=2.71, 95% CI: 1.49-4.94) and 63% (aPR=1.63, 95% CI: 1.40-1.91) higher prevalence of not having any prenatal care and not having a postpartum checkup, respectively, than females with no difficulty. CONCLUSIONS:Females with some and a lot of difficulty reported lower receipt of reproductive, prenatal, and postpartum care than those with no difficulty. Strategies are needed to establish and coordinate comprehensive reproductive health care among females with disabilities.

This dataset, Collab-CXR, provides a unique resource to study human-AI collaboration in chest X-ray interpretation. We present experimentally generated data from 227 professional radiologists who assessed 324 historical cases under varying information conditions: with and without AI assistance, and with and without clinical history. Using a custom-designed interface, we collected probabilistic assessments for 104 thoracic pathologies using a comprehensive hierarchical reporting structure. This dataset is the largest known comparison of human-AI collaborative performance to either AI or humans alone in radiology, offering assessments across an extensive range of pathologies with rich metadata on radiologist characteristics and decision-making processes. Multiple experimental designs enable both within-subject and between-subject analyses. Researchers can leverage this dataset to investigate how radiologists incorporate AI assistance, factors influencing collaborative effectiveness, and impacts on diagnostic accuracy, speed, and confidence across different cases and pathologies. By enabling rigorous study of human-AI integration in clinical workflows, this dataset can inform AI tool development, implementation strategies, and ultimately improve patient care through optimized collaboration in medical imaging.

OBJECTIVE:To evaluate the association between attention-deficit/hyperactivity disorder (ADHD) and atypical sensory processing patterns. METHOD/METHODS:For this systematic review and meta-analysis, PubMed, Embase, and Web of Science were searched from their inception until June 30, 2024. Studies examining sensory processing patterns using questionnaires in participants with a diagnosis of ADHD compared with healthy controls were included. The study risk of bias was assessed using a modified Newcastle-Ottawa Scale. A random-effects meta-analysis was conducted using R Version 4.3.1 software, considering sensory modulation severity atypicities as the primary outcome. The risk of publication bias was explored, and sensitivity analyses were conducted to test the robustness of findings. RESULTS:= 97%). Heterogeneity was high in all analyses. Only 9 studies were deemed at overall low risk of bias. CONCLUSION/CONCLUSIONS:Even though available ADHD clinical guidelines do not specifically mention the need to assess sensory processing in ADHD, this meta-analysis suggests that this should be systematically explored in the evaluation of children and adults referred for ADHD. PLAIN LANGUAGE SUMMARY/CONCLUSIONS:This systematic review and meta-analysis examined 30 studies including over 5,000 participants to assess the link between attention-deficit/hyperactivity disorder (ADHD) and atypical sensory processing. Findings show that individuals with ADHD experience significantly higher sensory sensitivity, sensory avoidance, sensory seeking, and low sensory registration compared to controls. Given their impact on daily functioning, assessing sensory processing could improve clinical evaluations for both children and adults with ADHD. STUDY REGISTRATION INFORMATION/UNASSIGNED:Association between ADHD and sensory processing disorder: A systematic review and meta-analysis; https://www.crd.york.ac.uk/PROSPERO/view/CRD42022325271. DIVERSITY & INCLUSION STATEMENT/UNASSIGNED:We actively worked to promote sex and gender balance in our author group. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science.

BACKGROUND:Children from migrant families with absent parents are more likely to have poorer physical and mental health than children from non-migrant families. The impact of labor migration on left-behind family members in South Asian countries is not well-known. This study aimed to examine the patterns of labor migration and its impact on the health and development of children and their caregivers in rural Nepal. METHODS:Baseline family data collected from a school-based violence prevention program were utilized. Parents/caregivers (N = 346) with school-aged children (aged 3 to 15 years attending nursery to primary grades) from the rural Arghakhanchi district of Nepal were included in the study. A series of descriptive and chi-square analyses were carried out to explore the pattern of labor migration and differences between labor-migrant and non-labor-migrant families. Multivariate linear and logistic regression analyses were applied to explore the correlates and moderators involved. RESULTS:Labor migration has been a common practice in rural Nepal, with an estimated 49% of families having parents working overseas, mostly in India (57%) and Gulf countries (39%) on low-skill labor jobs. Labor migration was significantly associated with left-behind caregivers' and children's mental health. Left-behind caregivers in father-only labor-migrant families reported higher levels of depression than did parents in non-labor migrant families and left-behind children from labor-migrant families reported greater anger than did children from non-labor migrant families. The impact of labor migration on families was moderated by social class. For low social-class father migrant families, left-behind children were at greater risk for developmental delay and behavioral problems, but there seems to be a protective effect for high social-class father migrant families (with lower risk of developmental delay and problem behaviors compared to all other groups). CONCLUSIONS:Labor migration has a substantial impact on the mental health of left-behind families and children. The impact of labor migration may vary by living social-cultural context. Understanding the complex dynamics of labor migration has important implications for local and global migration-related health service planning.

Suicide remains a leading cause of death among US youth. The emergency department (ED) is a critical access point for identifying suicide risk and initiating interventions to reduce that risk. Key strategies include developing individualized safety plans and counseling on reducing access to lethal means. This article reviews the current evidence supporting ED safety planning for youth at risk of suicide and presents a practical framework for its delivery. It also explores strategies to enhance the implementation of safety planning and lethal means counseling, including using clinical pathways, training of staff, optimizing reimbursement, and integrating resources into the electronic medical record system. Finally, the article highlights emerging innovations aimed at improving the reach of safety plan interventions in the ED setting.

BACKGROUND:Depression rates are higher in women, especially during periods of hormonal fluctuation. Reproductive system disorders (RSDs), which often disrupt hormonal balance, may contribute to this mental health burden. Despite their prevalence and significant health implications, the link between RSDs and depression remains underexplored, leaving a gap in understanding these women's mental health risks. METHODS:Using Danish nationwide health registers (2005-2018), we conducted a cohort study of 2,295,824 women aged 15-49, examining depression outcomes in 265,891 women diagnosed with 24 RSDs, including endometriosis, polycystic ovary syndrome, and pain-related diagnoses. For each RSD, age-matched controls were selected. We calculated incidence rates, incidence rate ratios, and prevalence proportions of depression diagnoses or antidepressant use around RSD diagnosis. RESULTS:Across all RSD subtypes, women demonstrated higher rates of depression both before and after diagnosis, with a peak within the year following diagnosis. Incidence rate ratios within 1 year of RSD diagnosis ranged from 1.15 (95% confidence interval [CI] 1.06-1.25) to 2.09 (95% CI 1.98-2.21), depending on RSD subtype. Elevated depression prevalence was observed 3 years before diagnosis, suggesting mental health impacts may have preceded clinical RSD identification. CONCLUSIONS:This study reveals a striking association between RSDs and depression. Women with RSDs are more likely to suffer from depression, before and after RSD diagnosis, highlighting the need for integrated mental health screening and intervention. With over 10% of women affected by RSDs, addressing this overlooked mental health burden is imperative for improving well-being in a significant portion of the population.

Mental disorders are increasingly understood as disorders of brain development. Large and heterogeneous samples are required to define generalizable links between brain development and psychopathology. To this end, we introduce Reproducible Brain Charts (RBC), an open resource that integrates data from 5 large studies of brain development in youth from three continents (N = 6,346). Bifactor models were used to create harmonized psychiatric phenotypes, capturing major dimensions of psychopathology. Following rigorous quality assurance, neuroimaging data were carefully curated and processed using consistent pipelines in a reproducible manner. Initial analyses of RBC emphasize the benefit of careful quality assurance and data harmonization in delineating developmental effects and associations with psychopathology. Critically, all RBC data-including harmonized psychiatric phenotypes, unprocessed images, and fully processed imaging derivatives-are openly shared without a data use agreement via the International Neuroimaging Data-sharing Initiative. Together, RBC facilitates large-scale, reproducible, and generalizable research in developmental and psychiatric neuroscience.