Multi-informant evaluation of Cognitive Disengagement Syndrome (formerly Slow Cognitive Tempo). Children's self-reported measures in relation to parents / Evaluación multi-informante del Síndrome de Desconexión Cognitiva (anteriormente Tempo Cognitivo Lento). Medidas autoinformadas de los niños con relación a padres

El objetivo fue examinar, desde una aproximación multi-informante, las medidas del Síndrome de Desconexión Cognitiva (SDC) de padres/madres e hijos/as y su relación con síntomas internalizantes y externalizantes. 279 niños/as (9-13 años), y sus padres/madres completaron las evaluaciones sobre SDC, la inatención del trastorno por déficit de atención e hiperactividad (TDAH) y otras medidas internalizadas y externalizadas. Los ítems de las tres medidas de SDC convergieron razonablemente bien en el factor SDC. Se aportaron pruebas discriminantes de la validez de las relaciones entre las puntuaciones de las pruebas y las medidas de los tres constructos diferentes (SDC, soledad y preferencia por la soledad). La asociación más estrecha estuvo entre la evaluación parental de las medidas de SDC con ansiedad y depresión, y entre inatención con hiperactividad/impulsividad y trastorno negativista desafiante. Se observó capacidad predictiva de la medida de SDC sobre la soledad y preferencia por estar solo autoinformadas. Se encontró una posible asociación entre la medida del SDC evaluado por padres/madres y sexo y edad de los niños. En conclusión, los datos apoyan la inclusión de medidas autoinformadas en la evaluación del SDC. Las medidas del SDC en niños se vinculan con medidas internalizantes y, la inatención con las externalizantes.(AU)

Multivariate brain-behaviour associations in psychiatric disorders.

Mapping brain-behaviour associations is paramount to understand and treat psychiatric disorders. Standard approaches involve investigating the association between one brain and one behavioural variable (univariate) or multiple variables against one brain/behaviour feature ('single' multivariate). Recently, large multimodal datasets have propelled a new wave of studies that leverage on 'doubly' multivariate approaches capable of parsing the multifaceted nature of both brain and behaviour simultaneously. Within this movement, canonical correlation analysis (CCA) and partial least squares (PLS) emerge as the most popular techniques. Both seek to capture shared information between brain and behaviour in the form of latent variables. We provide an overview of these methods, review the literature in psychiatric disorders, and discuss the main challenges from a predictive modelling perspective. We identified 39 studies across four diagnostic groups: attention deficit and hyperactive disorder (ADHD, k = 4, N = 569), autism spectrum disorders (ASD, k = 6, N = 1731), major depressive disorder (MDD, k = 5, N = 938), psychosis spectrum disorders (PSD, k = 13, N = 1150) and one transdiagnostic group (TD, k = 11, N = 5731). Most studies (67%) used CCA and focused on the association between either brain morphology, resting-state functional connectivity or fractional anisotropy against symptoms and/or cognition. There were three main findings. First, most diagnoses shared a link between clinical/cognitive symptoms and two brain measures, namely frontal morphology/brain activity and white matter association fibres (tracts between cortical areas in the same hemisphere). Second, typically less investigated behavioural variables in multivariate models such as physical health (e.g., BMI, drug use) and clinical history (e.g., childhood trauma) were identified as important features. Finally, most studies were at risk of bias due to low sample size/feature ratio and/or in-sample testing only. We highlight the importance of carefully mitigating these sources of bias with an exemplar application of CCA.

School closures and prescription medication use among children and adolescents before and during the COVID-19 pandemic in the USA, 2019-2022.

The impact of schools closing for in-person instruction in the USA during the COVID-19 pandemic on the use of prescription medications is not known. In this study, we examined changes in the total prescriptions filled, specifically for attention deficit hyperactivity disorder (ADHD) medications, among school-aged children and adolescents aged 10-19 years during periods before and after complete school closures between October 2019 and September 2022. Our findings indicate that complete school closures were associated with declines in the use of ADHD medications among younger populations in the USA. These findings suggest that the underuse of ADHD medications may be an overlooked contributor to declines in academic performance observed during periods of school closures during the COVID-19 pandemic.

How Do Mental Disorders and Combinations of Disorders Affect the Odds of Injuries and Poisoning?

ABSTRACT: Injuries and poisoning are associated with mental disorders. The association may be stronger if comorbid mental illness is involved. This study explores whether selected mental disorders (stress, anxiety, depression, attention deficit hyperactivity disorder [ADHD], bipolar, obsessive-compulsive disorder [OCD], schizophrenia) are associated with injuries and poisoning and if the presence and frequency of comorbid mental illness affect these associations. Analyses utilize medical claims data for adult employees of a large corporation during 2017-2021. Approximately half or more of the index mental disorders experience comorbid mental illness. Odds of injury and poisoning are significantly greater for each mental disorder and tend to be significantly greater when comorbid mental illness exists ( vs . the mental disorder alone), especially for the associations involving poisoning. Schizophrenia alone and in combination with other mental illness has the strongest associations with injury and poisoning. OCD is only associated with injury and poisoning, and ADHD is only associated with poisoning, if accompanied by comorbid mental illness.

Atopic Dermatitis: Disease Background and Risk Factors.

Multiple risk factors have been associated with the development of atopic dermatitis (AD). Recent advances in understanding the role of genetics in this disease have been made, with discovery of the filaggrin (FLG) gene as the most notable so far. In addition to FLG gene mutations as a risk factor for AD, a positive family history of atopic or allergic disease in either parent has been shown to confer a greater risk of developing AD. Atopic dermatitis usually presents early in life and is thought to represent the initial step in the "atopic march," which is characterized by the development of other atopic diseases later in life such as asthma, allergic rhinitis, and/or rhinoconjunctivitis, food allergies, and hay fever. Other comorbid diseases that have been associated with AD include increase risk of viral and bacterial skin infections, neuropsychiatric diseases such as attention-deficit hyperactivity disorders (ADHD), and autistic spectrum disorder (ASD). Patients with AD have also been found to have worse sleep quality overall compared to patients without AD. In this chapter, we will discuss the risk factors associated with development of atopic dermatitis as well as the most commonly reported comorbidities in patients with this disease.

Learning and Memory Impairments With Attention-Deficit/Hyperactivity Disorder.

ADHD is a common chronic neurodevelopmental disorder and is characterized by persistent inattention, hyperactivity, impulsivity and are often accompanied by learning and memory impairment. Great evidence has shown that learning and memory impairment of ADHD plays an important role in its executive function deficits, which seriously affects the development of academic, cognitive and daily social skills and will cause a serious burden on families and society. With the increasing attention paid to learning and memory impairment in ADHD, relevant research is gradually increasing. In this article, we will present the current research results of learning and memory impairment in ADHD from the following aspects. Firstly, the animal models of ADHD, which display the core symptoms of ADHD as well as with learning and memory impairment. Secondly, the molecular mechanism of has explored, including some neurotransmitters, receptors, RNAs, etc. Thirdly, the susceptibility gene of ADHD related to the learning and impairment in order to have a more comprehensive understanding of the pathogenesis. Key words: Learning and memory, ADHD, Review.

ADHD classification with cross-dataset feature selection for biomarker consistency detection.

Objective.Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children. While numerous intelligent methods are applied for its subjective diagnosis, they seldom consider the consistency problem of ADHD biomarkers. In practice, these data-driven approaches lead to varying learned features for ADHD classification across diverse ADHD datasets. This phenomenon significantly undermines the reliability of identified biomarkers and hampers the interpretability of these methods.Approach.In this study, we propose a cross-dataset feature selection (FS) module using a grouped SVM-based recursive feature elimination approach (G-SVM-RFE) to enhance biomarker consistency across multiple datasets. Additionally, we employ connectome gradient data for ADHD classification. In details, we introduce the G-SVM-RFE method to effectively concentrate gradient components within a few brain regions, thereby increasing the likelihood of identifying these regions as ADHD biomarkers. The cross-dataset FS module is integrated into an existing binary hypothesis testing (BHT) framework. This module utilizes external datasets to identify global regions that yield stable biomarkers. Meanwhile, given a dataset which waits for implementing the classification task as local dataset, we learn its own specific regions to further improve the performance of accuracy on this dataset.Main results.By employing this module, our experiments achieve an average accuracy of 96.7% on diverse datasets. Importantly, the discriminative gradient components primarily originate from the global regions, providing evidence for the significance of these regions. We further identify regions with the high appearance frequencies as biomarkers, where all the used global regions and one local region are recognized.Significance.These biomarkers align with existing research on impaired brain regions in children with ADHD. Thus, our method demonstrates its validity by providing enhanced biological explanations derived from ADHD mechanisms.

Inferring skin-brain-skin connections from infodemiology data using dynamic Bayesian networks.

The relationship between skin diseases and mental illnesses has been extensively studied using cross-sectional epidemiological data. Typically, such data can only measure association (rather than causation) and include only a subset of the diseases we may be interested in. In this paper, we complement the evidence from such analyses by learning an overarching causal network model over twelve health conditions from the Google Search Trends Symptoms public data set. We learned the causal network model using a dynamic Bayesian network, which can represent both cyclic and acyclic causal relationships, is easy to interpret and accounts for the spatio-temporal trends in the data in a probabilistically rigorous way. The causal network confirms a large number of cyclic relationships between the selected health conditions and the interplay between skin and mental diseases. For acne, we observe a cyclic relationship with anxiety and attention deficit hyperactivity disorder (ADHD) and an indirect relationship with depression through sleep disorders. For dermatitis, we observe directed links to anxiety, depression and sleep disorders and a cyclic relationship with ADHD. We also observe a link between dermatitis and ADHD and a cyclic relationship between acne and ADHD. Furthermore, the network includes several direct connections between sleep disorders and other health conditions, highlighting the impact of the former on the overall health and well-being of the patient. The average R 2 for a condition given the values of all conditions in the previous week is 0.67: in particular, 0.42 for acne, 0.85 for asthma, 0.58 for ADHD, 0.87 for burn, 0.76 for erectile dysfunction, 0.88 for scars, 0.57 for alcohol disorders, 0.57 for anxiety, 0.53 for depression, 0.74 for dermatitis, 0.60 for sleep disorders and 0.66 for obesity. Mapping disease interplay, indirect relationships, and the key role of mediators, such as sleep disorders, will allow healthcare professionals to address disease management holistically and more effectively. Even if we consider all skin and mental diseases jointly, each disease subnetwork is unique, allowing for more targeted interventions.

Barriers and facilitators to implementing a Canadian shared-care ADHD program in pediatric settings in Shanghai: a consolidated framework for implementation research approach.

OBJECTIVES: The vast majority of children with Attention-Deficit Hyperactivity Disorder (ADHD) do not have access to proper diagnosis and treatment in China. The goal of this project is to identify the challenges and facilitators in implementing a Canadian ADHD Shared Care Pathways program in pediatric settings in Shanghai region. METHODS: Purposive semi-structured focus groups were conducted on a total of 13 healthcare practitioners from the Shanghai Xinuha, Ninghai and Chongming hospitals. Two independent researchers conducted a thematic analysis of the data with themes emerging based on the Consolidated Framework for Implementation Research (CFIR). RESULTS: Notable barriers identified by participants included: (1) lack of knowledge in the management of ADHD, primarily among general practitioners; (2) lack of resources such as lack of staff, time, and medication for ADHD; (3) challenges in implementing an international multicentre intervention (such as communication difficulties between teams and integration of resources available in different hospitals); and (4) mental health stigma, difficulties in identifying ADHD patients, and logistical problems related to medication procurement rules put in place by provincial governments. Notable facilitators included: (1) the strong motivation of stakeholders and their confidence in their ability to learn and subsequently execute action plans to achieve the implementation goal; (2) the compatibility between the values and goals of the stakeholders and those of the program despite some cultural tension, a positive learning climate, strong tensions for change, and the high interest of organization leaders in engaging in the program (3) the perceived benefits of the program, such as standardization of the diagnostic and treatment process, and engaging primary care providers in ADHD management; and (4) the strong relationship between participating institutions and schools as well as provincial health initiatives available to support collaborative models of care. Mixed factors to implementation were also explored. CONCLUSIONS: Appropriate training of health care providers, cultural adaptation of the program, increase public awareness about ADHD to decrease stigma, as well as strong project management and guidelines that clearly describe the role and expectations of each team member appeared essential to successful implementation.

Identifying temporal pathways using biomarkers in the presence of latent non-Gaussian components.

Time-series data collected from a network of random variables are useful for identifying temporal pathways among the network nodes. Observed measurements may contain multiple sources of signals and noises, including Gaussian signals of interest and non-Gaussian noises, including artifacts, structured noise, and other unobserved factors (eg, genetic risk factors, disease susceptibility). Existing methods, including vector autoregression (VAR) and dynamic causal modeling do not account for unobserved non-Gaussian components. Furthermore, existing methods cannot effectively distinguish contemporaneous relationships from temporal relations. In this work, we propose a novel method to identify latent temporal pathways using time-series biomarker data collected from multiple subjects. The model adjusts for the non-Gaussian components and separates the temporal network from the contemporaneous network. Specifically, an independent component analysis (ICA) is used to extract the unobserved non-Gaussian components, and residuals are used to estimate the contemporaneous and temporal networks among the node variables based on method of moments. The algorithm is fast and can easily scale up. We derive the identifiability and the asymptotic properties of the temporal and contemporaneous networks. We demonstrate superior performance of our method by extensive simulations and an application to a study of attention-deficit/hyperactivity disorder (ADHD), where we analyze the temporal relationships between brain regional biomarkers. We find that temporal network edges were across different brain regions, while most contemporaneous network edges were bilateral between the same regions and belong to a subset of the functional connectivity network.

Functional Gastrointestinal Symptoms in Children with Autism and ADHD: Profiles of Hair and Salivary Cortisol, Serum Leptin Concentrations and Externalizing/Internalizing Problems.

BACKGROUND: Functional Gastrointestinal Disorders (FGIDs) present a higher prevalence in individuals with Neurodevelopmental Disorders (NDDs). The Stress System and the Gut-Brain axis (GBA) may mediate these relations. We aimed to assess the prevalence and profile of FGIDs in a clinical sample of children with Autism Spectrum Disorder (ASD) and Attention Deficit/Hyperactivity Disorder (ADHD) compared to typically developing children (TD) as well as to investigate possible relations between stress-related biomarkers and internalizing/externalizing problems in children with NDDS. METHODS: In total, 120 children, aged between 4 and 12 years old, formed three groups (N = 40, each): ADHD, ASD and TD. Salivary cortisol, hair cortisol and serum leptin were measured. RESULTS: The ASD group had more FGID problems than the TD group (p = 0.001). The ADHD and ASD groups had higher total internalizing/externalizing problems than the TD group (p < 0.0001, p < 0.0001, p = 0.005, respectively). Children with FGIDs showed more total, internalizing and externalizing problems compared to children without FGIDs (p < 0.0001, p < 0.0001, p = 0.041, respectively). The ADHD group showed lower AUCg values (p < 0.0001), while the hair cortisol was higher for the TD group (p < 0.0001). CONCLUSION: In conclusion, children with NDDs had more FGID symptoms and present higher internalizing and externalizing problems. Children with ADHD and FGIDs had more internalizing problems compared to those without FGIDs. No differences in stress-related biomarkers were shown to differentiate children with NDDs with and without FGIDs. Future prospective studies including a greater number of children may elucidate the biological pathways linking these comorbidities.

Prevalence and Clinical Profile of Adults with ADHD Attending a Tertiary Care Hospital for Five Years.

(1) Objectives: This study aimed to assess the 5-year prevalence and clinical profile of attention deficit hyperactive disorder (ADHD) among adult patients seeking care in a tertiary care hospital in Oman. (2) Methods: The data were analysed using descriptive and inferential statistics and standardised prevalence estimates were calculated. (3) Results: Of the 39,881 hospital visits, 1.77% were made by adults with ADHD. This is equivalent to 17.8 visits per 1000 outpatients. The year 2021 saw the highest prevalence among the five years considered, while 2020 had the lowest prevalence. Although the age distribution indicated that the age group 'under 20' had the highest prevalence, the gender distribution showed that ADHD was more common among adult men. Among the various subtypes of ADHD, inattention was the most common. (4) Conclusions: This study specifically compared the prevalence and associated factors between an adult cohort with ADHD and those other psychiatric clinic attendees during the same period. The study offers important information on the prevalence and clinical profile of adults with ADHD in the population under consideration.

Evolving Adult ADHD Care: Preparatory Evaluation of a Prototype Digital Service Model Innovation for ADHD Care.

BACKGROUND: Given the prevalence of ADHD and the gaps in ADHD care in Australia, this study investigates the critical barriers and driving forces for innovation. It does so by conducting a preparatory evaluation of an ADHD prototype digital service innovation designed to help streamline ADHD care and empower individual self-management. METHODS: Semi-structured interviews with ADHD care consumers/participants and practitioners explored their experiences and provided feedback on a mobile self-monitoring app and related service innovations. Interview transcripts were double coded to explore thematic barriers and the enablers for better ADHD care. RESULTS: Fifteen interviews (9 consumers, 6 practitioners) revealed barriers to better ADHD care for consumers (ignorance and prejudice, trust, impatience) and for practitioners (complexity, sustainability). Enablers for consumers included validation/empowerment, privacy, and security frameworks, tailoring, and access. Practitioners highlighted the value of transparency, privacy and security frameworks, streamlined content, connected care between services, and the tailoring of broader metrics. CONCLUSIONS: A consumer-centred approach to digital health service innovation, featuring streamlined, private, and secure solutions with enhanced mobile tools proves instrumental in bridging gaps in ADHD care in Australia. These innovations should help to address the gaps in ADHD care in Australia. These innovations should encompass integrated care, targeted treatment outcome data, and additional lifestyle support, whilst recognising the tensions between customised functionalities and streamlined displays.

Intrapartum exposure to synthetic oxytocin, maternal BMI, and neurodevelopmental outcomes in children within the ECHO consortium.

BACKGROUND: Synthetic oxytocin (sOT) is frequently administered during parturition. Studies have raised concerns that fetal exposure to sOT may be associated with altered brain development and risk of neurodevelopmental disorders. In a large and diverse sample of children with data about intrapartum sOT exposure and subsequent diagnoses of two prevalent neurodevelopmental disorders, i.e., attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), we tested the following hypotheses: (1) Intrapartum sOT exposure is associated with increased odds of child ADHD or ASD; (2) associations differ across sex; (3) associations between intrapartum sOT exposure and ADHD or ASD are accentuated in offspring of mothers with pre-pregnancy obesity. METHODS: The study sample comprised 12,503 participants from 44 cohort sites included in the Environmental Influences on Child Health Outcomes (ECHO) consortium. Mixed-effects logistic regression analyses were used to estimate the association between intrapartum sOT exposure and offspring ADHD or ASD (in separate models). Maternal obesity (pre-pregnancy BMI ≥ 30 kg/m2) and child sex were evaluated for effect modification. RESULTS: Intrapartum sOT exposure was present in 48% of participants. sOT exposure was not associated with increased odds of ASD (adjusted odds ratio [aOR] 0.86; 95% confidence interval [CI], 0.71-1.03) or ADHD (aOR 0.89; 95% CI, 0.76-1.04). Associations did not differ by child sex. Among mothers with pre-pregnancy obesity, sOT exposure was associated with lower odds of offspring ADHD (aOR 0.72; 95% CI, 0.55-0.96). No association was found among mothers without obesity (aOR 0.97; 95% CI, 0.80-1.18). CONCLUSIONS: In a large, diverse sample, we found no evidence of an association between intrapartum exposure to sOT and odds of ADHD or ASD in either male or female offspring. Contrary to our hypothesis, among mothers with pre-pregnancy obesity, sOT exposure was associated with lower odds of child ADHD diagnosis.

Maternal selenium deficiency during pregnancy in association with autism and ADHD traits in children: The Odense Child Cohort.

BACKGROUND: Selenoproteins regulate pathways controlling neurodevelopment, e.g., redox signaling and thyroid hormone metabolism. However, studies investigating maternal selenium in relation to child neurodevelopmental disorders are scarce. METHODS: 719 mother-child pairs from the prospective population-based Odense Child Cohort study in Denmark were included. Three selenium biomarkers, i.e. concentrations of serum selenium, selenoprotein P (SELENOP), and activity of glutathione peroxidase 3 (GPX3), along with serum copper, zinc and iron were measured in early third trimester (at 28.9+/-0.8 weeks of pregnancy). ADHD and ASD traits in children were assessed systematically using the established Child Behaviour Checklist at 5 years of age, based on a Danish reference cohort with cut-off at 90th percentile. Multivariable regression models adjusted for biologically relevant confounders were applied. RESULTS: 155 of 719 (21.6 %) children had ASD traits and 59 of 719 (8.2 %) children had traits of ADHD at 5 years of age. In crude and adjusted models, all three selenium biomarkers associated inversely with ADHD traits. For ADHD, fully adjusted OR for 10 µg/L increment in selenium was 0.76 (95 % CI 0.60, 0.94), for one mg/L increment in SELENOP was 0.73 (0.56, 0.95), and for 10 U/L increment in GPx3 was 0.93 (0.87,1.00). Maternal total selenium was inversely associated with child ASD traits, OR per 10 µg/L increment was 0.85 (0.74, 0,98). SELENOP and GPx3 were not associated with ASD traits. The associations were specific to selenium, as other trace elements such as copper, zinc, or iron were not associated with the outcomes. CONCLUSIONS: The results provide coherent evidence for selenium deficiency as a risk factor for ADHD and ASD traits in an environment with borderline supply, the causality of which should be elucidated in a randomized controlled trial.

A Digital Cognitive-Physical Intervention for Attention-Deficit/Hyperactivity Disorder: Randomized Controlled Trial.

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 (ß=-12.203, 95% CI -17.882 to -6.523; P<.001), owing to lower scores on the subscales Inattention (ß=-3.966, 95% CI -6.285 to -1.647; P<.001), Hyperactivity/Impulsivity (ß=-5.735, 95% CI -8.334 to -3.137; P<.001), and Oppositional Defiant Disorder (ß=-2.995, 95% CI -4.857 to -1.132; P=.002). The intervention was associated with significant reduction in the Metacognition Index (ß=-6.312, 95% CI -10.973 to -1.650; P=.006) and Global Executive Composite (ß=-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.