Background: Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders among children. Pharmacotherapy has been the primary treatment for ADHD, supplemented by behavioral interventions. Digital and exercise interventions are promising nonpharmacologic approaches for enhancing the physical and psychological health of children with ADHD. However, the combined impact of digital and exercise therapies remains unclear. Objective: The aim of this study was to determine whether BrainFit, a novel digital intervention combining gamified cognitive and exercise training, is efficacious in reducing ADHD symptoms and executive function (EF) among school-aged children with ADHD. Methods: This 4-week prospective randomized controlled trial included 90 children (6-12 years old) who visited the ADHD outpatient clinic and met the diagnostic criteria for ADHD. The participants were randomized (1:1) to the BrainFit intervention (n=44) or a waitlist control (n=46) between March and August 2022. The intervention consisted of 12 30-minute sessions delivered on an iPad over 4 weeks with 3 sessions per week (Monday, Wednesday, and Friday after school) under the supervision of trained staff. The primary outcomes were parent-rated symptoms of attention and hyperactivity assessed according to the Swanson, Nolan, and Pelham questionnaire (SNAP-IV) rating scale and EF skills assessed by the Behavior Rating Inventory of Executive Function (BRIEF) scale, evaluated pre and post intervention. Intention-to-treat analysis was performed on 80 children after attrition. A nonparametric resampling-based permutation test was used for hypothesis testing of intervention effects. Results: Among the 145 children who met the inclusion criteria, 90 consented and were randomized; ultimately, 80 (88.9%) children completed the study and were included in the analysis. The participants’ average age was 8.4 (SD 1.3) years, including 63 (78.8%) male participants. The most common ADHD subtype was hyperactive/impulsive (54/80, 68%) and 23 (29%) children had severe symptoms. At the endpoint of the study, the BrainFit intervention group had a significantly larger improvement in total ADHD symptoms (SNAP-IV total score) as compared to those in the control group (β=–12.203, 95% CI –17.882 to –6.523; P<.001), owing to lower scores on the subscales Inattention (β=–3.966, 95% CI –6.285 to –1.647; P<.001), Hyperactivity/Impulsivity (β=–5.735, 95% CI –8.334 to –3.137; P<.001), and Oppositional Defiant Disorder (β=–2.995, 95% CI –4.857 to –1.132; P=.002). The intervention was associated with significant reduction in the Metacognition Index (β=–6.312, 95% CI –10.973 to –1.650; P=.006) and Global Executive Composite (β=–5.952, 95% CI –10.214 to –1.690; P=.003) on the BRIEF. No severe intervention-related adverse events were reported. Conclusions: This novel digital cognitive-physical intervention was efficacious in school-age children with ADHD. A larger multicenter effectiveness trial with longer follow-up is warranted to confirm these findings and to assess the durability of treatment effects. Trial Registration: Chinese Clinical Trial Register ChiCTR2300070521; https://www.chictr.org.cn/showproj.html?proj=177806

Background: Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder that commonly occurs in childhood. The aim of this meta-analysis was to summarize the available evidence for the efficacy of digital therapeutics in children and adolescents with ADHD.Methods: We searched the MEDLINE, EMBASE, Cochrane Library (Cochrane Database of Systematic Reviews), and Web of Science (science and social science citation index) databases for relevant studies and used Stata 15.0 software to carry out the meta-analysis.Results: A total of 31 studies involving 2169 participants (1665 boys and 504 girls) aged 4–17 years old were included in the final analysis. The meta-analysis results showed that digital interventions improved the symptoms of inattention with an effect value of −0.20 (95% confidence interval [CI] −0.36, −0.04) and decreased the continuous performance task (CPT) reaction time (effect, −0.40, 95% CI −0.73, −0.07) in ADHD patients. The score for impulsive hyperactivity was slightly decreased (effect, −0.07, 95% CI −0.23, 0.09). Moreover, executive function was improved (effect, 0.71, 95% CI 0.37, 1.04). The capability of working memory appeared to be increased (effect, 0.48, 95% CI 0.21, 0.76) between the two groups. Visual appraisal of the sensitivity analysis suggested the absence of heterogeneity, and no obvious publication bias was detected.Discussion: Based on the existing literature evidence, we conclude that digital therapy can be a promising therapeutic strategy for ADHD patients.

Background and Objective: Autism spectrum disorder (ASD) refers to a heterogeneous set of neurodevelopmental disorders with diverse symptom severity and comorbidities. Although alterations in gut microbiota have been reported in individuals with ASD, it remains unclear whether certain microbial pattern is linked to specific symptom or comorbidity in ASD. We aimed to investigate the associations between gut microbiota and the severity of social impairment and cognitive functioning in children with ASD.Methods: A total of 261 age-matched children, including 138 children diagnosed with ASD, 63 with developmental delay or intellectual disability (DD/ID), and 60 typically developing (TD) children, were enrolled from the Shanghai Xinhua Registry. The children with ASD were further classified into two subgroups: 76 children diagnosed with ASD and developmental disorder (ASD+DD) and 62 with ASD only (ASD-only). The gut microbiome of all children was profiled and evaluated by 16S ribosomal RNA sequencing.Results: The gut microbial analyses demonstrated an altered microbial community structure in children with ASD. The alpha diversity indices of the ASD+DD and ASD-only subgroups were significantly lower than the DD/ID or TD groups. At the genus level, we observed a decrease in the relative abundance of Prevotella. Simultaneously, Bacteroides and Faecalibacterium were significantly increased in ASD compared with DD/ID and TD participants. There was a clear correlation between alpha diversity and the Childhood Autism Rating Scale (CARS) total score for all participants, and this correlation was independent of IQ performance. Similar correlations with the CARS total score were observed for genera Bacteroides, Faecalibacterium, and Oscillospira. However, there was no single genus significantly associated with IQ in all participants.Conclusions: Specific alterations in bacterial taxonomic composition and associations with the severity of social impairment and IQ performance were observed in children with ASD or ASD subgroups, when compared with DD/ID or TD groups. These results illustrate that gut microbiota may serve as a promising biomarker for ASD symptoms. Nevertheless, further investigations are warranted.

This study aims to explore the psychosocial and behavioral problems of children and adolescents in the early stage of reopening schools. In this national cross-sectional study, a total of 11072 students from China were naturally divided into two groups based on their schooling status: reopened schools (RS) and home schooling (HS) group. The psychosocial and behavioral functioning were measured by Achenbach Child Behaviour Checklist (CBCL) and compared in these two groups. Multivariable logistic regression analyses were conducted to explore the independent predictors associated with the psychosocial and behavioral problems. Our results showed that the students in the RS group had more adverse behaviors than that of HS group. The RS group had the higher rates of parent-offspring conflict, prolonged homework time, increased sedentary time and sleep problems (all p < 0.001). When separate analyses were conducted in boys and girls, the RS group had the higher scores for (1) overall behavioral problems (p = 0.02 and p = 0.01), internalizing (p = 0.02 and p = 0.02) and externalizing (p = 0.02 and p = 0.004) behaviors in the 6–11 age group; (2) externalizing (p = 0.049 and p = 0.006) behaviors in the 12–16 age group. Multivariable regression showed parent-offspring conflict and increased sedentary time were the most common risk factors, while physical activity and number of close friends were protective factors for behavior problems in RS students (p < 0.01 or 0.05). The present study revealed that students’ psychosocial and behavioral problems increased in the early stage of schools reopened unexpectedly. These findings suggest that close attention must be paid and holistic strategies employed in the school reopening process of post-COVID-19 period.

The interactions between the microbiota and the human host can affect the physiological functions of organs (such as the brain, liver, gut, etc.). Accumulating investigations indicate that the imbalance of microbial community is closely related to the occurrence and development of diseases. Thus, the identification of potential links between microbes and diseases can provide insight into the pathogenesis of diseases. In this study, we propose a deep learning framework (MDAGCAN) based on graph convolutional attention network to identify potential microbe-disease associations. In MDAGCAN, we first construct a heterogeneous network consisting of the known microbe-disease associations and multi-similarity fusion networks of microbes and diseases. Then, the node embeddings considering the neighbor information of the heterogeneous network are learned by applying graph convolutional layers and graph attention layers. Finally, a bilinear decoder using node embedding representations reconstructs the unknown microbe-disease association. Experiments show that our method achieves reliable performance with average AUCs of 0.9778 and 0.9454 ± 0.0038 in the frameworks of Leave-one-out cross validation (LOOCV) and 5-fold cross validation (5-fold CV), respectively. Furthermore, we apply MDAGCAN to predict latent microbes for two high-risk human diseases, i.e., liver cirrhosis and epilepsy, and results illustrate that 16 and 17 out of the top 20 predicted microbes are verified by published literatures, respectively. In conclusion, our method displays effective and reliable prediction performance and can be expected to predict unknown microbe-disease associations facilitating disease diagnosis and prevention.

Background: Attention deficit/hyperactivity disorder (ADHD) has been identified as a risk factor for obesity in both children and adolescents. However, the mechanisms underlying the relationship between ADHD and obesity are still unclear. This study aimed to test a theoretical model of whether anxiety/depression is an intermediary factor in the ADHD-obesity relationship. Methods: Data were derived from the National Health Interview Survey (NHIS), a principal source of information on the health of the civilian noninstitutionalized population of the United States. A total of 35,108 adolescents aged 12-17 years old from 2010-2015 NHIS and 2016-2018 NHIS representing 46,550,729 individuals in the weighted population, had a parent-reported previous ADHD diagnosis, emotional problems, and height and weight data. Mediation analyses were used to explore whether anxiety/depression is an intermediary factor in the relationship between ever having ADHD and obesity. Mediation analyses were performed using multiple logistic regressions. Results: The findings showed that ADHD was a predictor of obesity. This relationship was partially mediated by depression(2010-2015: β=0.28, 95%CI:0.13-0.43; 2016-2018: β=0.26, 95%CI:0.03-0.49), as well as anxiety (2010-2015: β=0.28, 95%CI:0.18-0.38). Conclusions: Our study suggests the hypothetical role of depression and anxiety as underlying mechanisms in the association between ever having ADHD and obesity in adolescents. When treating children with ADHD, clinicians need to be particularly attentive to whether they show emotional problems and use interventions to eliminate anxiety/depression to protect against obesity.