A grassroots initiative dedicated to accelerating the scientific community''''s understanding of the neural basis of ADHD through the implementation of open data-sharing and discovery-based science. They believe that a community-wide effort focused on advancing functional and structural imaging examinations of the developing brain will accelerate the rate at which neuroscience can inform clinical practice. The ADHD-200 Global Competition invited participants to develop diagnostic classification tools for ADHD diagnosis based on functional and structural magnetic resonance imaging (MRI) of the brain. Applying their tools, participants provided diagnostic labels for previously unlabeled datasets. The competition assessed diagnostic accuracy of each submission and invited research papers describing novel, neuroscientific ideas related to ADHD diagnosis. Twenty-one international teams, from a mix of disciplines, including statistics, mathematics, and computer science, submitted diagnostic labels, with some trying their hand at imaging analysis and psychiatric diagnosis for the first time. The data for the competition was provided by the ADHD-200 Consortium. Consortium members from institutions around the world provided de-identified, HIPAA compliant imaging datasets from almost 800 children with and without ADHD. A phenotypic file including all of the test set subjects and their diagnostic codes can be downloaded. Winner is presented. The ADHD-200 consortium included: * Brown University, Providence, RI, USA (Brown) * The Kennedy Krieger Institute, Baltimore, MD, USA (KKI) * The Donders Institute, Nijmegen, The Netherlands (NeuroImage) * New York University Medical Center, New York, NY, USA (NYU) * Oregon Health and Science University, Portland, OR, USA (OHSU) * Peking University, Beijing, P.R.China (Peking 1-3) * The University of Pittsburgh, Pittsburgh, PA, USA (Pittsburgh) * Washington University in St. Louis, St. Louis, MO, USA (WashU)

Purpose: We aim to determine the prevalence and characteristics of developmental disabilities among the clinical population of children who receive hearing health care in the United States.Method: Using electronic health records of 131,709 children (0–18 years), we identified those with a diagnosis of attention deficit/hyperactivity disorder, autism spectrum disorder, vision differences, cerebral palsy, chromosomal abnormalities, delayed milestones, Down syndrome, or intellectual disability. We determined prevalence, age of first audiology encounter, age of diagnosis for the developmental disability, and hearing status based on the specific disability and the number of diagnoses. Binomial and multinomial logistic regressions were performed.Results: One in four children had a diagnosed developmental disability. The most common disabilities were delayed milestones (11.3%), vision differences (7.4%), attention-deficit/hyperactivity disorder (6.6%), and autism spectrum disorder (6.2%). Half of the children with developmental disabilities had at least one diagnosis before their first audiology encounter. Children with developmental disabilities were more likely to have a reduced hearing or an unknown hearing status than children without developmental diagnoses. For children with reduced hearing, those with developmental disabilities had higher rates of bilateral configurations and poorer hearing severity levels.Conclusions: Developmental disabilities are common among children who seek hearing health care. Moreover, developmental disabilities often co-occur with reduced hearing. Further research and advocacy efforts are critical for creating clinical practices that are inclusive of, and equitable for, children with complex and diverse developmental profiles.Supplemental Material S1. ICD-9/10 umbrella mappings for the specific developmental disabilities used in the study.Supplemental Material S2. Binomial logistic regression results for if a diagnosis of attention deficit/hyperactivity disorder (ADHD) was known at the time of the first audiology encounter.Supplemental Material S3. Binomial logistic regression results for if a diagnosis of autism spectrum disorder was known at the time of the first audiology encounter.Supplemental Material S4. Binomial logistic regression results for if a diagnosis of cerebral palsy was known at the time of the first audiology encounter.Supplemental Material S5. Binomial logistic regression results for if a diagnosis of a chromosomal abnormality was known at the time of the first audiology encounter.Supplemental Material S6. Binomial logistic regression results for if a diagnosis of delayed milestones was known at the time of the first audiology encounter.Supplemental Material S7. Binomial logistic regression results for if a diagnosis of Down syndrome was known at the time of the first audiology encounter.Supplemental Material S8. Binomial logistic regression results for if a diagnosis of an intellectual disability was known at the time of the first audiology encounter.Supplemental Material S9. Binomial logistic regression results for if a diagnosis of a vision difference was known at the time of the first audiology encounter.Bonino, A. Y., Goodwich, S. F., & Mood, D. (2025). Prevalence and characteristics of developmental disabilities among children who receive hearing health care. American Journal of Audiology, 34(1), 60–71. https://doi.org/10.1044/2024_AJA-24-00118

Background: Several studies have revealed significant associations between single nucleotide polymorphisms (SNPs) in the cannabinoid receptor 1 (CNR1) gene and a broad spectrum of psychiatric disorders such as major depressive disorder (MDD), attention deficit hyperactivity disorder (ADHD), and schizophrenia. Personality traits that are highly related to susceptibility to these conditions have been associated with the CNR1 variants in subjects of Caucasian origin. However, there are no reported studies regarding the effects of CNR1 polymorphisms on personality traits in the African-American (AA) population.Methods: We performed an imputation-based association analysis for 26 CNR1 variants with five dimensions of personality in 3,046 AAs.Results: SNPs rs806372 and rs2180619 showed a significant association with extraversion after Bonferroni correction for multiple testing (p < 0.0019). Further, several extraversion-associated SNPs were significantly associated with conscientiousness, agreeableness, and openness. SNP priority score analysis indicated that SNPs rs806368, rs806371, and rs2180619 play a role in the modulation of personality and psychiatric conditions.Conclusion:CNR1 is important in determining personality traits in the AA population.

ObjectiveAttention-deficit/hyperactivity disorder (ADHD) is a common condition that often persists into adulthood, although data suggest that the current diagnostic criteria may not represent how the condition presents in adults. We aimed to use qualitative methods to better understand ADHD symptomatology in young adults, especially regarding attentional and emotional dysregulation.MethodsNine focus groups involving young adults (aged 18–35 years; N = 43; 84% female; 86% US and Canada) with diagnoses of ADHD were conducted. Participants were asked about their perceptions of the current diagnostic criteria and how their symptoms have presented and changed over time. Data were analyzed using an interpretive phenomenological analysis framework.ResultsMost participants reported that the diagnostic criteria did not accurately capture their experiences with ADHD. They reported struggling with attention dysregulation, including hyperfocusing, and emotional dysregulation, including rejection-sensitive dysphoria. Many participants believed that their changing environments and behavioral adaptations influenced how their symptoms presented into adulthood.ConclusionCurrent diagnostic criteria for ADHD may not capture the range of symptoms present in young adults. More research is needed to characterize attentional and emotional dysregulation in this population.