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Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by repeated patterns of hyperactivity, impulsivity, and inattention that limit daily functioning and development. Electroencephalography (EEG) anomalies correspond to changes in brain connection and activity. The authors propose utilizing empirical mode decomposition (EMD) and discrete wavelet transform (DWT) for feature extraction and machine learning (ML) algorithms to categorize ADHD and control subjects. For this study, the authors considered freely accessible ADHD data obtained from the IEEE data site. Studies have demonstrated a range of EEG anomalies in ADHD patients, such as variations in power spectra, coherence patterns, and event-related potentials (ERPs). Some of the studies claimed that the brain's prefrontal cortex and frontal regions collaborate in intricate networks, and disorders in either of them exacerbate the symptoms of ADHD. , Based on the research that claimed the brain's prefrontal cortex and frontal regions collaborate in intricate networks, and disorders in either of them exacerbate the symptoms of ADHD, the proposed study examines the optimal position of EEG electrode for identifying ADHD and in addition to monitoring accuracy on frontal/ prefrontal and other regions of brain our study also investigates the position groupings that have the highest effect on accurateness in identification of ADHD. The results demonstrate that the dataset classified with AdaBoost provided values for accuracy, precision, specificity, sensitivity, and F1-score as 1.00, 0.70, 0.70, 0.75, and 0.71, respectively, whereas using random forest (RF) it is 0.98, 0.64, 0.60, 0.81, and 0.71, respectively, in detecting ADHD. After detailed analysis, it is observed that the most accurate results included all electrodes. The authors believe the processes can detect various neurodevelopmental problems in children utilizing EEG signals.
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BACKGROUND: Literature emphasises the importance of identifying and intervening in the adoption of unhealthy lifestyle behaviours (ULBs) during adolescence at an early stage, to mitigate their long-term detrimental effects. Among the possible associated factors contributing to ULBs, attention-deficit hyperactivity disorder (ADHD) has been shown to play an important role. However, little is known about ADHD subclinical manifestations. AIMS: The present study aimed to bridge the gap in the literature and shed light on the relationship between subclinical ADHD and early adoption of ULBs during adolescence. Through a clinimetric approach, prevalence of ULBs, severity of ADHD symptoms and psychosocial factors (i.e. allostatic overload, abnormal illness behaviour, quality of life, psychological well-being) were investigated among adolescents. The associations between different degrees of ADHD, ULBs and psychosocial factors were also explored. METHOD: This multicentre cross-sectional study involved 440 adolescents (54.5% females; mean age 14.21 years) from six upper secondary schools. Participants completed self-report questionnaires on sociodemographic characteristics, ULBs, ADHD symptoms and psychosocial factors. RESULTS: The most common ULBs were energy drinks/alcohol consumption and problematic smartphone use. Of the sample, 22% showed subclinical ADHD and 20.2% showed clinical ADHD. The subclinical ADHD group showed several ULBs (i.e. altered mindful eating, impaired quality of sleep, problematic technology use) and psychosocial factors, akin to those of ADHD group and different from peers without ADHD symptoms. CONCLUSIONS: Since subclinical ADHD manifestation is associated with ULBs, similarly to clinical ADHD, identifying subthreshold symptoms during adolescence is crucial, as it could improve health-related outcomes in adulthood across different domains.
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BACKGROUND: Neurodivergent individuals often face unique challenges during the perinatal period, which can significantly impact their experiences of pregnancy, childbirth, and early parenting. Despite growing awareness of neurodiversity, there remains a gap in perinatal care that fully addresses the lived experiences and needs of those with neurodivergent conditions such as Autism (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD). OBJECTIVE: To compile and analyse recent literature on the perinatal experiences of neurodivergent parturients. To provide an overview of current knowledge, identify prevalent challenges, and suggest opportunities for improving perinatal services. Additionally, we aim to highlight research gaps that guide future studies and enhance care quality for neurodivergent individuals during the perinatal period. METHODS: The Systematic Reviews methodological process was utilised to search relevant scientific databases to gather current research articles on neurodivergent perinatal experiences. Eleven studies met the inclusion criteria and were appraised using a rigorous quality checklist. Thematic analysis identified recurring themes across the selected papers. RESULTS: Three major themes emerged: Care provider support, Perinatal mental health needs, and Resilience and growth of neurodivergent parturients. These themes highlight significant differences in perinatal experiences between neurodivergent and neurotypical individuals, underscoring the need for tailored care approaches. CONCLUSION: The findings reveal that current perinatal care practices do not adequately address the specific challenges faced by perinatal neurodivergent individuals. There is a critical need for perinatal care systems to integrate neurodiversity-affirming practices. Future research should consider intersectionality to include marginalised and underrepresented neurodivergent voices.
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Background: Attention-deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder, with a chronic, and potentially debilitating course if untreated. Medication adherence is poor - negatively affecting emotional, social, educational and employment outcomes. The current Schedule 6 status of methylphenidate (MPH) drives healthcare resource utilisation and costs - a potential barrier to care. Aim: This study explored stakeholders' understanding and perceptions of the potential impact of a regulatory shift in the scheduling of MPH on treatment accessibility and adherence for ADHD. Setting: Participants from multiple stakeholder groups, involved in ADHD management in South Africa, were recruited via professional networks. Methods: A qualitative analysis of semi-structured interviews with 23 stakeholders was conducted to explore their views on the utility, benefits and risks associated with rescheduling MPH. Results: Six key themes emerged from the interviews: 'adherence', 'accessibility', 'affordability', 'stigma', 'rescheduling of MPH' and 'risk mitigation'. Core to these themes is the role of the scheduling of MPH - which can have a protective societal role, but also acts as a barrier to care for individuals with ADHD. Conclusion: The current Schedule 6 status of MPH is not an effective strategy to prevent misuse and diversion but negatively impacts on treatment adherence. The positive outlook from stakeholders on rescheduling MPH holds significant implications for the ADHD landscape in South Africa. Contribution: It is crucial to address stigma, facilitate fundamental change in service delivery and remove structural and practical barriers to care to improve outcomes for individuals with ADHD. A framework for ADHD treatment adherence is provided.
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Background: This study used functional near-infrared spectroscopy (fNIRS) to investigate brain activation patterns in children with attention deficit hyperactivity disorder (ADHD) with and without additional comorbidities to identify disease-related biomarkers by the neuroimaging that will facilitate to make a diagnosis decision. Methods: In this study, 165 medication-naive children aged 7 to 15 years were recruited and categorized into four groups: ADHD, ADHD with learning disabilities (ADHD&LD), ADHD with oppositional defiant disorder (ADHD&ODD), and healthy controls. A multichannel fNIRS system was used to monitor hemodynamic changes at rest state in the prefrontal and temporal lobes of the brain. The amplitude of a low-frequency fluctuation (ALFF) matrix was calculated by summation and averaging of the square root of the signal power spectrum. One-way analysis of variance was used to identify statistical differences between channels. Results: All ADHD children presented significantly higher ALFF values in different brain regions when compared with the healthy controls. Patients with ADHD&LD exhibited higher ALFF values in the medial prefrontal cortex (P Ch38 = .01, P Ch48 = .01), temporal cortex (P Ch22 = .04, P Ch41 = .002, P Ch51 = .001), and the left ventrolateral prefrontal cortex (P Ch39 = .0009, P Ch50 = .001), whereas ADHD&ODD children were not significantly different to those diagnosed with ADHD. Conclusions: ADHD with learning disabilities (LD) possessed a different pathogenesis from ADHD, manifested as lower functional brain activity in the medial prefrontal cortex, temporal cortex, and the left ventrolateral prefrontal cortex, while ADHD&ODD did not present significant changes compared with ADHD. ODD-related symptoms may be part of ADHD symptoms rather than being an independent disorder.
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Background Neurodevelopmental disorders (NDDs) encompass intricate interactions among genetic, brain, cognitive, emotional, and behavioral processes. These disorders, which are influenced by hereditary and environmental factors, impair personal, social, intellectual, or occupational functioning. Typically emerging early in life, NDDs include conditions such as attention deficit hyperactivity disorder (ADHD), intellectual disability, autism spectrum disorders (ASDs), vision and hearing impairments, motor disorders, and specific learning disabilities. Children from impoverished and low-income neighborhoods are particularly vulnerable. The lack of comprehensive health data and public awareness about these conditions results in limited information regarding the prevalence of neurological illnesses in developing countries. India, with its large and ethnically diverse population, exemplifies this gap. Methods It is a prospective study to detect the prevalence and risk factors of neurodevelopmental disorders in children aged six months to nine years at a tertiary care center. Patient details, clinical findings, and relevant history were recorded on a pre-designed pro forma and analyzed statistically. Results Among the 1000 children in the study, 91 (9.1%) tested positive for NDDs. Among the 91 children who tested positive for NDD, the highest frequency is in the three to four years age group (17.6%), males were found to be in a higher ratio with 75.82%, with the male: female ratio being 3:1. Among the 91 children with NDD, intellectual disability was the most common disorder (20.9%), followed by ADHD (17.6%) and vision impairment (14.3%). Autism spectrum disorders, including autism and Asperger syndrome, and communication disorders, including stuttering and speech disorders, accounted for 13.2% each. Hearing loss was seen in 9.9% of children and multiple disorders were seen in 8.8% of the children from among 91 children. Conclusion Neurodevelopmental disorders are common and often coexist with other conditions. Children from low-income backgrounds are more affected. This study provides valuable insights into the prevalence and characteristics of NDDs in a specific population.
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Objective: To evaluate the comparative efficacy of pharmacological interventions for children and adolescents with a dual diagnosis of persistent tic disorders or Tourette disorder and attention-deficit/hyperactivity disorder (TD + ADHD). Methods: We searched CENTRAL, Embase, PubMed, PsycInfo, Web of Sciences, ClinicalTrials.gov, and WHO ICTRP up to September 2023 to identify double-blinded randomized controlled trials (RCTs) assessing pharmacological interventions for children and adolescents with TD + ADHD. Outcomes were change in ADHD symptoms (primary) and tics (secondary) severity. Standardized mean difference (SMD) was calculated and pooled in random-effects network meta-analysis. The Confidence in Network Meta-Analysis framework was adopted to determine certainty of evidence. Results: We included 8 RCTs involving 575 participants. Network meta-analyses demonstrated that α2 agonists (SMD, 95% confidence interval [CI] ADHD: -0.72 [-1.13 to -0.31]; TD: -0.70 [-0.96 to -0.45]) and stimulants + α2 agonists (ADHD: -0.84 [-1.54 to -0.13]; TD: -0.60 [-1.04 to -0.17]) were more efficacious than placebo for ADHD symptoms and tics severity. Stimulants alone were more efficacious than placebo for ADHD symptoms severity only, but they did not worsen tics (ADHD: -0.54 [-1.05 to -0.03]; TD: -0.22 [-0.49 to 0.05]). There were no significant differences between any pairs of medications that were found efficacious against placebo for ADHD symptoms or tics severity. Certainty in the evidence varied from low to very low. Conclusions: Stimulants are efficacious for ADHD symptoms severity and do not increase tics severity in TD + ADHD. α2 agonists are efficacious for both ADHD symptoms and tics severity in TD + ADHD. These findings should inform guidelines and help guide shared decision-making to choose a medication for children with TD + ADHD.
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INTRODUCTION: Numerous studies have linked deficits in Theory of Mind (ToM) with language problems. We aimed to explore the similarities and differences between children's patterns of performance on a ToM task that requires minimal linguistic skill and a pragmatic inference task that relies on both ToM and language. We assessed variability in pragmatic inference skills and ToM across populations of children (8-14 years) displaying varying cognitive profiles. We further compared the sensitivity of ToM versus pragmatic ability to core language skills, memory and executive functioning (EF). METHOD: ToM was tested using the Social Attribution Task (SAT-MC-II). Pragmatic ability was assessed in an implicature comprehension task. Receptive vocabulary, grammar comprehension, short-term and working memory (STM and WM) capacity and EF were measured using Hungarian adaptations of standard tasks and tests developed by the authors' lab. In addition to typically developing (TD) children (n = 33), we included children with neurodevelopmental disorders where ToM and/or language abilities are vulnerable: autism spectrum disorder (ASD, n = 26), attention deficit hyperactivity disorder (ADHD, n = 25) and developmental language disorder (DLD, n = 18). RESULTS: Results revealed a significant but only moderate positive correlation between pragmatic inference and ToM indicating that the two abilities are related but distinct. The ASD group showed impairments in both ToM and pragmatic inference ability but no significant deficit was observed in ADHD or DLD relative to TD children in either skill. However, while SAT-MC-II results were only affected by verbal WM and vocabulary measures, pragmatic performance was associated with STM, verbal WM, EF, grammatical skills and vocabulary. CONCLUSION: Our findings indicate that disentangling the contributions of different cognitive skills to ToM tasks may help clarify the role of ToM in language skills and identify distinct patterns of ToM and pragmatic skills in developmental disorders.
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Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by persistent patterns of inattention, hyperactivity, and impulsivity that significantly impair daily functioning and quality of life. Although often diagnosed in childhood, ADHD symptoms frequently persist into adolescence and adulthood. Heat stroke, a severe medical condition characterized by central nervous system dysfunction, seizures, and extreme hyperthermia, can result in mortality even with medical intervention. Notably, exertional heat stroke remains a leading cause of sudden death among young athletes and individuals engaged in strenuous physical activity. We present a case of a young athlete diagnosed with ADHD and prescribed amphetamine and dextroamphetamine (Adderall), who presented with heat stroke, partly due to his medication.
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Attention Deficit Hyperactivity Disorder (ADHD) is a highly prevalent childhood disorder, and related research has been increasing in recent years. However, it remains a challenging issue to accurately identify individuals with ADHD. The research proposes a method for ADHD detection using Recursive Feature Elimination-Genetic Algorithm (RFE-GA) for the feature selection of EEG data. Firstly, this study employed Transfer Entropy (TE) to construct brain networks from the EEG data of the ADHD and Normal groups, conducting an analysis of effective connectivity to unveil causal relationships in the brain's information exchange activities. Subsequently, a dual-layer feature selection method combining Recursive Feature Elimination (RFE) and Genetic Algorithm (GA) was proposed. Using the global search capability of GA and the feature selection ability of RFE, the performance of each feature subset is evaluated to find the optimal feature subset. Finally, a Support Vector Machine (SVM) classifier was employed to classify the ultimate feature set. The results revealed the control group exhibited lower connectivity strength in the left temporal alpha and beta bands, but higher frontal connectivity strength compared to the ADHD group. Additionally, in the gamma frequency band, the control group had higher top lobe connectivity strength than the ADHD group. Through the RFE-GA feature selection method, the optimized feature set was more concise, achieving classification accuracies of 91.3%, 94.1%, and 90.7% for the alpha, beta, and gamma frequency bands, respectively. The proposed RFE-GA feature selection method significantly reduced the number of features, thereby improving classification accuracy. .
