Pubmed (TDAH) du 25/04/26
1. Adler R, Kozlov M, Mehta MD, Cowen E, Svigos K, Feig JL. Concurrent Asthma is Associated with Increased Risk of ADHD in Pediatric Atopic Dermatitis Patients: Response to Hu, et al. « The Mediating Role of Asthma in the Association Between Atopic Dermatitis and ADHD: A Population-Based Study in Children and Adolescents Using the NHANES Database ». J Am Acad Dermatol. 2026.
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2. Demirci B, Bıkmazer A, Görmez V. Irritability as a Mediator Between Sensory Processing Sensitivity, Theory of Mind, and Behavioral Problems in Children and Adolescents with ADHD. Psychiatr Q. 2026.
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3. Hu J, Ma J, Wang Y, Tang F, Xuan X, Chen J. Response to Adler et al.: « Concurrent Asthma is Associated with Increased Risk of ADHD in Pediatric Atopic Dermatitis Patients ». J Am Acad Dermatol. 2026.
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4. Ivkovic Smith A, Zhang W, Nisavic M, Carnduff A, Bethea E. Is ADHD Underrecognized in Liver Transplant Recipients with Alcohol-Associated Liver Disease?. J Acad Consult Liaison Psychiatry. 2026.
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5. Lin X, Wang Z, Yan H, Zeng S, Wang P, Wu Z, Yu X, Han J. [Research on weighted hypergraph attention neural network for the diagnosis of psychiatric disorders using brain functional connectivity networks]. Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2026; 43(2): 319-27.
The hypergraph neural network (HGNN) has demonstrated efficacy in modeling high-order interactions among brain regions, thus providing a promising framework for analyzing brain functional connectivity networks in the context of psychiatric research. The present study proposes a phase-amplitude coupling-weighted hypergraph attention neural network (PAC-HyperGAT) model for the diagnosis of psychiatric diseases. The proposed methodology first constructs a functional hypergraph using elastic net-based sparse regression and then assigns physiologically meaningful weights to hyperedges by quantifying the phase-amplitude coupling strength among nodes within each hyperedge. In light of these findings, the present study proposes a novel hypergraph attention convolution kernel. The efficacy of this approach is evidenced by its enhancement of the node-level message passing mechanism, a feat that facilitates the integration of hyperedge weight information. This phenomenon, in turn, results in an enhancement of the discriminative ability of brain functional connectivity network representations. The proposed model is systematically evaluated on publicly available electroencephalogram datasets for attention deficit hyperactivity disorder (ADHD) and major depressive disorder (MDD). The experimental results demonstrate that PAC-HyperGAT attains an accuracy of (72.14 ± 9.19) % in ADHD classification, surpassing the performance of existing brain functional connectivity network methods across a range of evaluation metrics. The model exhibits notable efficacy in MDD classification, signifying substantial cross-disorder generalization capabilities. Furthermore, PAC-HyperGAT has demonstrated efficacy in identifying brain regions associated with these disorders. In summary, the proposed model demonstrates excellent generalizability, robustness, and neurobiological interpretability, providing a reliable analytical framework for objective diagnosis and mechanistic investigation of psychiatric diseases.
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6. Thomas KS, Cooper K, Jones CRG. The Role of Self-Concept Clarity in the Relations Between Disordered Eating, Gender Diversity, and Autistic and ADHD Traits. Arch Sex Behav. 2026.
Self-concept clarity, the degree to which an individual has a well-defined and stable sense of self, is a well-documented factor in mental health conditions, particularly eating disorders. Difficulties with self-concept clarity are also reported among gender diverse and neurodivergent people, who are overrepresented in eating disorder populations. This cross-sectional study examined associations between self-concept clarity (Self-Concept Clarity Scale), autistic traits (Autism Spectrum Quotient), ADHD traits (Adult ADHD Self-Report Scale), gender diversity (Gender Self-Report), and disordered eating, a pattern of atypical eating behaviors and attitudes including food restriction and binge eating (Eating Disorder Examination Questionnaire). Gender diversity was assessed as binary (identity opposite to sex assigned at birth) and nonbinary traits (identity neither female nor male). Participants were 492 UK adults (324 assigned female at birth; 98.6% cisgender, 1.2% trans/gender diverse, 0.2% preferred not to say; M age = 41.44 years, SD = 13.11) recruited online. Correlational and path analysis investigated direct and indirect relations between gender diversity, neurodivergent traits, and disordered eating through self-concept clarity. Autistic traits were indirectly related to disordered eating through self-concept clarity, while ADHD traits showed both direct and indirect associations. Greater binary and nonbinary gender diverse traits were correlated with higher levels of disordered eating but were no longer significantly related once neurodivergent traits, age, and sex assigned at birth were controlled. Findings suggest low self-concept clarity may provide a mechanism for increased disordered eating in individuals with higher levels of neurodivergent traits, but not among those with gender diverse traits when covariates are considered.
