BACKGROUND: Sex differences in the symptomatology of adults with attention-deficit/hyperactivity disorder (ADHD) have often been overlooked when studying behavioral abnormalities. However, it is known that women exhibit considerably more stronger symptoms related to emotional competence than men. Since affective functions significantly influence the processing of risky decision-making and risk-engagement, we assume that risky behavior in ADHD is affected by sex differences. Therefore, we specifically investigated sex-specific effects on the interaction between emotionally induced changes in physiology and behavioral performance on a decision-making task.
METHODS: Skin conductance responses of twenty-nine adults with ADHD (n = 16 male; n = 13 female) and thirty-three adults in the control group (n = 14 male; n = 19 female) were recorded during the performance in a modified version of the Balloon Analogue Risk Task (BART). Additional questionnaires were used to reveal insights in the self-assessment of emotional competence, risk perception, and feedback sensitivity. Emotional arousal and decision-making behavior were analyzed using linear mixed-effects models.
RESULTS: Results showed different effects of sex on risk behaviors in controls and ADHD. In contrast to healthy controls, female adults with ADHD showed a significantly greater risk engagement in the BART compared to males with ADHD. This contrary sex relation was not observed in skin conductance responses and revealed a significantly different sex-dependent correlation of body response and behavioral task performance in ADHD. Comparisons with results from self-assessments furthermore indicate a reduced behavioral self-perception in women with ADHD, but not in men.
CONCLUSIONS: In summary, we found an altered interaction between physiological activity and risky behavior in women with ADHD. Thus, the present study indicates a reduced sensitivity towards the own bodily responses in women with ADHD, which could consequently cause increased risky DM behavior in daily life. The current results suggest that more consideration needs to be given to sex-specific effects on physiological processes and behavior in adults with ADHD.

Attention-Deficit/Hyperactivity Disorder (ADHD), a prevalent childhood neurodevelopmental disorder with complex etiology involving genetic and environmental factors, causes impairments across various life domains and substantial social and economic burden. Identifying correlates to prevent its onset and decrease its incidence is crucial. To our knowledge, our study represents the first case-control investigation of Lebanese ADHD patients to explore potential correlations between familial, maternal, and child health variables and ADHD to enhance understanding of its etiology and aid in prevention efforts. We recruited 61 Lebanese ADHD patients and 58 matched controls aged 6-24 years from all districts of Lebanon. The data to analyze were collected using a questionnaire. We employed statistical tests, including the independent samples t-test and the Chi-square test or Fisher\'s exact test. We conducted a multivariate logistic regression analysis to identify the statistically significant factors explaining ADHD likelihood. We observed male predominance (68.9%) among patients. Maternal anemia during pregnancy (OR = 3.654; 95% CI [1.158-11.529]), maternal self-reported stress during pregnancy (OR = 3.268; 95% CI [1.263-8.456]), neonatal jaundice (OR = 5.020; 95% CI [1.438-17.532]), and familial history of ADHD (OR = 12.033; 95% CI [2.950-49.072]) were significantly associated with increased odds of the disorder. On the other hand, breastfeeding (OR = 0.263; 95% CI [0.092-0.757]) was identified as a protective factor against ADHD. This pilot study shed light on risk and protective factors associated with ADHD in the Lebanese population. The results are relevant, as some identified correlates could be avoidable. Further rigorous investigation is required to expand upon the observed correlations and to assist in early detection, prevention, and intervention strategies targeting ADHD.

BACKGROUND: In attention-deficit/hyperactivity disorder (ADHD), poor inhibitory control is one of the main characteristics, with oculomotor inhibition impairments being considered a potential biomarker of the disorder. While auditory white noise has demonstrated the ability to enhance working memory in this group, visual white noise is still unexplored and so are the effects of both types of white noise stimulation on oculomotor inhibition.
OBJECTIVE: This crossover study aims to explore the impact of auditory and visual white noise on oculomotor inhibition in children with ADHD and typically developing (TD) children. The study will investigate the impact of different noise levels (25% and 50% visual, 78 dB auditory), and performance will be evaluated both with and without noise stimulation. We hypothesize that exposure to white noise will improve performance in children with ADHD and impair the performance for TD children.
METHODS: Memory-guided saccades and prolonged fixations, known for their sensitivity in detecting oculomotor disinhibition in ADHD, will be used to assess performance. Children diagnosed with ADHD, withdrawing from medication for 24 hours, and TD children without psychiatric disorders were recruited for the study.
RESULTS: Data collection was initiated in October 2023 and ended in February 2024. A total of 97 participants were enrolled, and the first results are expected between September and November 2024.
CONCLUSIONS: This study will examine whether cross-modal sensory stimulation can enhance executive function, specifically eye movement control, in children with ADHD. In addition, the study will explore potential differences between auditory and visual noise effects in both groups. Our goal is to identify implications for understanding how noise can be used to improve cognitive performance.
BACKGROUND: ClinicalTrials.gov NCT06057441; https://clinicaltrials.gov/study/NCT06057441.
UNASSIGNED: DERR1-10.2196/56388.

Aim: To compare long-term safety and efficacy outcomes of centanafadine versus lisdexamfetamine dimesylate (lisdexamfetamine), methylphenidate hydrochloride (methylphenidate) and atomoxetine hydrochloride (atomoxetine), respectively, in adults with attention-deficit/hyperactivity disorder (ADHD) using matching-adjusted indirect comparisons (MAICs). Patients & methods: Patient-level data from a centanafadine trial (NCT03605849) and published aggregate data from a lisdexamfetamine trial (NCT00337285), a methylphenidate trial (NCT00326300) and an atomoxetine trial (NCT00190736) were used. Patient characteristics were matched in each comparison using propensity score weighting. Study outcomes were assessed up to 52 weeks and included safety (rates of adverse events [AEs]) and efficacy (mean change from baseline in the Adult ADHD Investigator Symptom Rating Scale [AISRS] or ADHD Rating Scale [ADHD-RS] score). Results: In all comparisons of matched populations, risks of AEs were statistically significantly lower with centanafadine or non-different between centanafadine and comparator; the largest differences in AE rates included upper respiratory tract infection (risk difference in percentage points: 18.75), insomnia (12.47) and dry mouth (12.33) versus lisdexamfetamine; decreased appetite (20.25), headache (18.53) and insomnia (12.65) versus methylphenidate; and nausea (26.18), dry mouth (25.07) and fatigue (13.95) versus atomoxetine (all p < 0.05). Centanafadine had a smaller reduction in the AISRS/ADHD-RS score versus lisdexamfetamine (6.15-point difference; p < 0.05) and no statistically significant difference in the change in AISRS score versus methylphenidate (1.75-point difference; p = 0.13) and versus atomoxetine (1.60-point difference; p = 0.21). Conclusion: At up to 52 weeks, centanafadine showed significantly lower incidence of several AEs than lisdexamfetamine, methylphenidate and atomoxetine; efficacy was lower than lisdexamfetamine and non-different from methylphenidate and atomoxetine.

Background: Alterations in the serum lipid profile have been suspected in many psychiatric disorders, such as schizophrenia and depression. However, studies on lipid status in attention-deficit/hyperactivity disorder (ADHD) are sparse and inconsistent. Methods: Using the nationwide, population-based IQVIA Disease Analyzer database, this retrospective cohort study included 5367 outpatients from general practices in Germany aged ≥18 years with a documented first diagnosis of ADHD between January 2005 and December 2021 and 26,835 propensity score-matched individuals without ADHD. Study outcomes were the first diagnosis of lipid metabolism disorders as a function of ADHD within up to 10 years of the index date. The cumulative 10-year incidence was analyzed using Kaplan-Meier curves and compared using the log-rank test. In addition, univariate Cox regression analyses were performed. Results: In the regression analysis, there was no significant association between ADHD and subsequent lipid metabolism disorders in the total population (HR: 0.94; 95% CI: 0.83-1.08), among women (HR: 1.04; 95% CI: 0.84-1.28), and among men (HR: 0.89; 95% CI: 0.74-1.06). In addition, no significant association was observed in the disease-stratified analyses. Conclusions: The findings of this study indicate that ADHD does not exert an influence on lipid metabolism. However, further investigation is warranted, particularly with respect to pharmacological interventions.

BACKGROUND: Sotos syndrome is an autosomal dominant disorder, whereas attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition. This report aimed to summarize the clinical and genetic features of a pediatric case of Soros syndrome and ADHD in a child exhibiting precocious puberty.
METHODS: The patient presented with accelerated growth and advanced skeletal maturation; however, she lacked any distinct facial characteristics related to specific genetic disorders. Genetic analyses revealed a paternally inherited heterozygous synonymous mutation [c.4605C>T (p.Arg1535Arg)]. Functional analyses suggested that this mutation may disrupt splicing, and bioinformatics analyses predicted that this mutation was likely pathogenic. After an initial diagnosis of Sotos syndrome, the patient was diagnosed with ADHD during the follow-up period at the age of 8 years and 7 months.
CONCLUSIONS: The potential for comorbid ADHD in Sotos syndrome patients should be considered to avoid the risk of a missed diagnosis.

BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental psychiatric condition that typically emerges during childhood but often persists into adulthood, significantly impacting individuals\' functioning, relationships, productivity, and overall quality of life. However, the current diagnostic process exhibits limitations that can significantly affect its overall effectiveness. Notably, its face-to-face and time-consuming nature, coupled with the reliance on subjective recall of historical information and clinician subjectivity, stand out as key challenges. To address these limitations, objective measures such as neuropsychological evaluations, imaging techniques and physiological monitoring of the Autonomic Nervous System functioning, have been explored.
METHODS: The main aim of this study was to investigate whether physiological data (i.e., Electrodermal Activity, Heart Rate Variability, and Skin Temperature) can serve as meaningful indicators of ADHD, evaluating its utility in distinguishing adult ADHD patients. This observational, case-control study included a total of 76 adult participants (32 ADHD patients and 44 healthy controls) who underwent a series of Stroop tests, while their physiological data was passively collected using a multi-sensor wearable device. Univariate feature analysis was employed to identify the tests that triggered significant signal responses, while the Informative k-Nearest Neighbors (KNN) algorithm was used to filter out less informative data points. Finally, a machine-learning decision pipeline incorporating various classification algorithms, including Logistic Regression, KNN, Random Forests, and Support Vector Machines (SVM), was utilized for ADHD patient detection.
RESULTS: Results indicate that the SVM-based model yielded the optimal performance, achieving 81.6% accuracy, maintaining a balance between the experimental and control groups, with sensitivity and specificity of 81.4% and 81.9%, respectively. Additionally, integration of data from all physiological signals yielded the best results, suggesting that each modality captures unique aspects of ADHD.
CONCLUSIONS: This study underscores the potential of physiological signals as valuable diagnostic indicators of adult ADHD. For the first time, to the best of our knowledge, our findings demonstrate that multimodal physiological data collected via wearable devices can complement traditional diagnostic approaches. Further research is warranted to explore the clinical applications and long-term implications of utilizing physiological markers in ADHD diagnosis and management.

BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a recognized neurodevelopmental disorder with a complex, multifactorial origin. Lead (Pb) and mercury (Hg) are highly toxic substances that can potentially impair brain development and have been implicated in the development of ADHD. This systematic review aims to analyze the epidemiological literature regarding the association between Pb and Hg exposure and the diagnosis of ADHD.
METHODS: From November 1983 to June 2, 2023, a comprehensive search was conducted in multiple databases and search engines, including PubMed, Web of Science, Scopus, and Google Scholar. Observational studies (case-control, cohort, and cross-sectional) measuring Pb and Hg levels in various biological samples (blood, hair, urine, nail, saliva, teeth, and bone) of children with ADHD or their parents and their association with ADHD symptoms were included.
RESULTS: Out of 2059 studies, 87 met the inclusion criteria and were included in this systematic review. Approximately two-thirds of the 74 studies investigating Pb levels in different biological samples reported associations with at least one subtype of ADHD. However, most studies examining Hg levels in various biological samples found no significant association with any ADHD subtype, although there were variations in exposure periods and diagnostic criteria.
CONCLUSIONS: The evidence gathered from the included studies supports an association between Pb exposure and the diagnosis of ADHD, while no significant association was found with Hg exposure. Importantly, even low levels of Pb were found to elevate the risk of ADHD. Further research is needed to explore the comprehensive range of risk factors for ADHD in children, considering its significance as a neurodevelopmental disorder.

UNASSIGNED: Studies have found maternal smoking during pregnancy was linked to attention-deficit/hyperactivity disorder (ADHD) risk. It is unclear if maternal smoking cessation during pregnancy lowers ADHD and learning disability (LD) risk in offspring. This study aimed to explore the associations between maternal smoking cessation during pregnancy and ADHD and LD risk in offspring.
UNASSIGNED: Data from the National Health and Nutrition Examination Survey 1999-2004 (8,068 participants) were used. Logistic regression was used to analyze the associations between maternal smoking and smoking cessation during pregnancy and ADHD and LD risk in offspring.
UNASSIGNED: Compared to non-smokers\' offspring, maternal smoking during pregnancy increased the risk of ADHD (odds ratios [OR] = 2.07, 95% confidence interval [CI]: 1.67-2.56) and LD (OR = 1.93, 95% CI: 1.61-2.31) in offspring, even if mothers quit smoking later (ORADHD = 1.91, 95%CIADHD: 1.38-2.65, ORLD = 1.65, 95%CILD: 1.24-2.19). Further analysis of the timing of initiation of smoking cessation during pregnancy revealed that, compared to non-smokers\' offspring, maternal quitting smoking in the first trimester still posed an increased risk of ADHD (OR = 1.72, 95% CI: 1.41-2.61) and LD (OR = 1.52, 95% CI: 1.06-2.17) in offspring. Maternal quitting smoking in the second or third trimester also had a significantly increased risk of ADHD (OR = 2.13, 95% CI: 1.26-3.61) and LD (OR = 1.82, 95% CI: 1.16-2.87) in offspring. Furthermore, maternal smoking but never quitting during pregnancy had the highest risk of ADHD (OR = 2.17, 95% CI: 1.69-2.79) and LD (OR = 2.10, 95% CI: 1.70-2.58) in offspring. Interestingly, a trend toward a gradual increase in the risk-adjusted OR for ADHD and LD risk was observed among the three groups: maternal quitting smoking in the first trimester, maternal quitting smoking in the second or third trimester, and maternal smoking but never quitting.
UNASSIGNED: Maternal smoking cessation in the first trimester still poses an increased risk of ADHD and LD in offspring. Furthermore, it seems that the later the mothers quit smoking during pregnancy, the higher the risk of ADHD and LD in their offspring. Therefore, early intervention of maternal smoking in preconception and prenatal care is vital for offspring neurodevelopment.

BACKGROUND: Diagnosis of child and adolescent psychopathologies involves a multifaceted approach, integrating clinical observations, behavioral assessments, medical history, cognitive testing, and familial context information. Digital technologies, especially internet-based platforms for administering caregiver-rated questionnaires, are increasingly used in this field, particularly during the screening phase. The ascent of digital platforms for data collection has propelled advanced psychopathology classification methods such as supervised machine learning (ML) into the forefront of both research and clinical environments. This shift, recently called psycho-informatics, has been facilitated by gradually incorporating computational devices into clinical workflows. However, an actual integration between telemedicine and the ML approach has yet to be fulfilled.
OBJECTIVE: Under these premises, exploring the potential of ML applications for analyzing digitally collected data may have significant implications for supporting the clinical practice of diagnosing early psychopathology. The purpose of this study was, therefore, to exploit ML models for the classification of attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) using internet-based parent-reported socio-anamnestic data, aiming at obtaining accurate predictive models for new help-seeking families.
METHODS: In this retrospective, single-center observational study, socio-anamnestic data were collected from 1688 children and adolescents referred for suspected neurodevelopmental conditions. The data included sociodemographic, clinical, environmental, and developmental factors, collected remotely through the first Italian internet-based screening tool for neurodevelopmental disorders, the Medea Information and Clinical Assessment On-Line (MedicalBIT). Random forest (RF), decision tree, and logistic regression models were developed and evaluated using classification accuracy, sensitivity, specificity, and importance of independent variables.
RESULTS: The RF model demonstrated robust accuracy, achieving 84% (95% CI 82-85; P<.001) for ADHD and 86% (95% CI 84-87; P<.001) for ASD classifications. Sensitivities were also high, with 93% for ADHD and 95% for ASD. In contrast, the DT and LR models exhibited lower accuracy (DT 74%, 95% CI 71-77; P<.001 for ADHD; DT 79%, 95% CI 77-82; P<.001 for ASD; LR 61%, 95% CI 57-64; P<.001 for ADHD; LR 63%, 95% CI 60-67; P<.001 for ASD) and sensitivities (DT: 82% for ADHD and 88% for ASD; LR: 62% for ADHD and 68% for ASD). The independent variables considered for classification differed in importance between the 2 models, reflecting the distinct characteristics of the 3 ML approaches.
CONCLUSIONS: This study highlights the potential of ML models, particularly RF, in enhancing the diagnostic process of child and adolescent psychopathology. Altogether, the current findings underscore the significance of leveraging digital platforms and computational techniques in the diagnostic process. While interpretability remains crucial, the developed approach might provide valuable screening tools for clinicians, highlighting the significance of embedding computational techniques in the diagnostic process.