Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous disorder with a high degree of psychiatric and physical comorbidity, which complicates its diagnosis in childhood and adolescence. We analyzed registry data from 238,696 persons born and living in Sweden between 1995 and 1999. Several machine learning techniques were used to assess the ability of registry data to inform the diagnosis of ADHD in childhood and adolescence: logistic regression, random Forest, gradient boosting, XGBoost, penalized logistic regression, deep neural network (DNN), and ensemble models. The best fitting model was the DNN, achieving an area under the receiver operating characteristic curve of 0.75, 95% CI (0.74–0.76) and balanced accuracy of 0.69. At the 0.45 probability threshold, sensitivity was 71.66% and specificity was 65.0%. There was an overall agreement in the feature importance among all models (τ > .5). The top 5 features contributing to classification were having a parent with criminal convictions, male sex, having a relative with ADHD, number of academic subjects failed, and speech/learning disabilities. A DNN model predicting childhood and adolescent ADHD trained exclusively on Swedish register data achieved good discrimination. If replicated and validated in an external sample, and proven to be cost-effective, this model could be used to alert clinicians to individuals who ought to be screened for ADHD and to aid clinicians’ decision-making with the goal of decreasing misdiagnoses. Further research is needed to validate results in different populations and to incorporate new predictors. Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental disorder characterized by impairing levels of inattention, hyperactivity/impulsivity, or both, with an estimated worldwide prevalence of 5–10% in children and 2–5% in adults , among oThe substantial heterogeneity and comorbidity of ADHD pose diagnostic challenges for clinicians and can lead to either missed or false positive diagnoses , 13. MisAlthough traditional statistical methods can assess predictive accuracy, they cannot deal with complex non-linear relationships, especially when many predictive features interact with one another to predict outcomes. In contrast, machine learning can handle such complex problems if a sufficiently large sample is available . AlthougIn this paper, we aimed to train different machine learning and deep learning algorithms for classifying childhood and adolescent ADHD to 1) aid clinicians’ decision-making in terms of diagnosis, and 2) offer a model for risk stratification and clinical referral of high-risk individuals. All models used Swedish population registry data including variables such as perinatal risk factors, medical and psychiatric comorbidities for the individual and the relatives, criminal convictions for the individual or the biological parents.This population-based study used several Swedish registers: the total population register, the medical birth register, the prescribed drug register (PDR), the national patient register (NPR), the multi-generation register, and the national crime register. The total population register includes demographic information for all individuals with permanent residence in Sweden . The medIndividuals with ADHD were identified based on either the presence of a diagnosis in the NPR (including inpatient and outpatient care services) from age 3 onwards using the International Classification of Diseases (ICD) version 9 code 314, ICD10-code F90 or a recorded prescription of any ADHD medications  from the PDR. The outcome variable was dichotomized indicating presence or absence of an ADHD diagnosis (1/0) at any point between 1995 and 2013.In order to predict childhood and adolescent ADHD, we considered a set of well-stablished predictors , 30–32 bAmongst the predictors related to the biological parents, we included: Maternal tobacco use during pregnancy, BMI from mother at the first prenatal visit, pregnancy length, type of delivery , presence of any criminal convictions of any of the parents. In terms of parental psychiatric disorders, we included all the following if they occurred before or during follow up: ADHD, alcohol use disorder (AUD), SUD, anxiety, eating disorder, depression, bipolar disorder, schizophrenia, personality disorder. In total, 40 features were selected.k-fold CV in the training of the DNN, we used a hold-out validation/development set for hyperparameter tuning. A flowchart describing the data split strategy is shown in Fig. For all features, zero-variance and near-zero-variance were checked and removed. Highly correlated features (≥0.95) were handled by randomly keeping one of them. Near-zero-variance features were removed to avoid the possibility for those features to become zero-variance during the data splits or cross-validation (CV). Next, an initial 80% stratified data split was performed to be used as the training data. The remaining 20% was used as testing data. For the deep neural network (DNN), the aforementioned 80% split was further split to create a hold-out validation/development set comprising 18% of the training set, and the remaining 82% was used as the training set. As such, all models were evaluated using the same independent testing set, however, to alleviate computational burden when using We used several machine learning algorithms: logistic regression, random forest (RF), gradient boosting (GB), XGBoost, naïve Bayes (NB), and regularized logistic regression (L1L2) and a DNN. Moreover, a soft-voting ensemble model combining the best performing models in the CV/validation set were trained. A soft-voting ensemble model predicts class membership based on the argmax of the sum of predicted probabilities from each model. Learning curves were plotted to assess the adequacy of our sample sizes. For the machine learning algorithms , hyperparameter optimization was performed using a stratified 10-fold CV in the training set by a manual grid search. To find the optimal hyperparameters in the DNN, we used distributed hyperparameter optimization (hyperopt)  with 100https://github.com/kmlstyle/ADHD-DNN. See Supplementary for code usage.Owing to the class imbalance in the test set, we used the Area Under the Receiver Operating Characteristic Curve (AUROC) as the evaluation metric with 95% confidence intervals using a fast implementation of the DeLong algorithm . The AUCOur cohort comprised 238,696 individuals, of whom 12,893 (5.4%) had ADHD. For the machine learning algorithms, the training dataset had 190,956 observations  and the testing dataset had 47,740 observations, of which 2579 (5.4%) had ADHD. For the DNN, the training set contained 156,583 individuals, 34,373 in the validation set, and the testing dataset 47,740 observations, of whom 5.4% had ADHD. As expected, those with ADHD were more likely to be diagnosed with the majority of the selected mental disorders and medical conditions (Supplementary Table SThe number of features was reduced from 40 to 22 based on low variance or high intercorrelations (see Methods). The logistic regression model achieved an AUC in the test set of 0.74 (0.73–0.75). After hyperparameter optimization, the RF model achieved an AUC of 0.68, 95% CI (0.67–0.69) in the test set, whereas the XGBoost model achieved an AUC of 0.69, 95% CI (0.68–0.70). Both models displayed signs of overfitting (training set AUC > 0.92). With a slightly better fit, the GB model and elastic net logistic regression achieved an AUC of 0.73, 95% CI 0.71–0.74) and 0.74, 95% CI (0.73–0.75), respectively. The best fitting model to the data was the DNN that achieved an AUC of 0.75, 95% CI (0.74–0.76) and balanced accuracy of 0.68 in the test set (Table –0.74 andλ = 1e-3. The DNN used the Adadelta optimizer (learning rate 7e-3) to train the model for 200 epochs with a batch size of 40 with the Xavier normal weight initializer (Glorot). Supplementary Fig. SThe DNN was built with two hidden layers of 10 and 15 units respectively with a rectified linear activation function and a dropout layer in between (dropout rate of 0.217). The first hidden layer included a kernel L1 regularizer with a cost function The top six most important features were having a relative with criminal convictions, sex of patient, having a relative with ADHD, number of academic subjects failed, speech/learning disabilities, and ASD diagnosis. All models showed high agreement as depicted by the correlations . The complete list of feature importance for the RF, GB, XGBoost, and DNN algorithms together with pairwise Kendall’s τ correlations are shown in Table SHAP values increase the interpretability of DNNs by explaining the predicted probability for ADHD of each individual. Supplementary Fig. SWe trained machine-learning algorithms to classify childhood and adolescent ADHD using registry data. This is the first study combining Swedish national registry data and machine learning/deep learning techniques to assess the combined accuracy of 22 predictors, including psychiatric and somatic comorbidities, criminal convictions, perinatal variables, and parental psychiatric comorbidities, to predict the onset of ADHD. The best-fitting model was a DNN. It achieved good discrimination in an independent test set . The DNN outperformed all other algorithms in all metrics.Although the DNN AUC of 0.75 is modest, several considerations suggest that the DNN would be clinically useful. As Ross et al. . have shIn practice, the model could be applied by selecting a meaningful cut point on the model’s predicted probability that an individual has ADHD. For example, Fig. There was a good agreement in the importance of the top predictors between different models with an average Kendall’s τb correlation > 0.5. The most important predictors for ADHD were having a parent with criminal convictions, sex of patient, having a parent with ADHD, number of academic subjects failed, and speech/learning disabilities. Previous literature had already established these relationships –32, but Regarding clinical utility, our top features could potentially alert clinicians for an early assessment using our model. Feature importance was similar for men and women, with the exception of head circumference and criminal convictions, which showed a larger importance in women. Similarly, having depression and a parent with ADHD displayed a higher importance among men  , and comk and increase the maximum number of evaluations in the hyperparameter optimization process by the same k factor. However, since we used a different validation method for hyperparameter optimization in the DNN model, comparing its performance to the other methods should be made with caution. Given that this was a registry-based study, ADHD diagnoses only capture clinically referred cases of ADHD. Thus, our model may not be relevant for cases of ADHD in the population that do not seek treatment. There are several important predictors of ADHD that we were not able to include given the unavailability within the registers, including IQ, reading and arithmetic scores, working memory, reaction time, risky decision-making [Amongst the strengths from this paper, we can highlight the use of a large, nationwide sample and the longitudinal nature of the study for 18 years. Additionally, in Sweden, ADHD is assessed at outpatient clinics exclusively by specialist psychiatrists after clinical somatic and psychiatric evaluation. An external validation of the diagnoses in the National Inpatient Register showed high validity with PPPs ranging from 85–95% . Despiten-making  that futIn conclusion, in this paper we presented a DNN model for discriminating childhood and adolescent ADHD using register-based data. The DNN model presented good discrimination and could potentially improve decision-making.Supplementary material


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.We searched the MEDLINE, EMBASE, Cochrane Library (Cochrane Database of Systematic Reviews), and Web of Science  databases for relevant studies and used Stata 15.0 software to carry out the meta-analysis.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  and decreased the continuous performance task (CPT) reaction time  in ADHD patients. The score for impulsive hyperactivity was slightly decreased . Moreover, executive function was improved . The capability of working memory appeared to be increased  between the two groups. Visual appraisal of the sensitivity analysis suggested the absence of heterogeneity, and no obvious publication bias was detected.Based on the existing literature evidence, we conclude that digital therapy can be a promising therapeutic strategy for ADHD patients. Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder that commonly occurs in childhood and is characterized by inattention, hyperactivity, and impulsivity. The prevalence of ADHD in children and adolescents ranges from 4.2–6.5%, and in 30–50% of cases, the symptoms persist into adulthood . To dateAt present, the main treatments for ADHD are drug therapies. Methylphenidate, dexamphetamine and atomoxetine are the drugs most often prescribed to treat ADHD in children and adolescents. However, the most common side effects were decreased appetite with possible weight loss, irritability, palpitations, and headache. More importantly, the medications are typically used in an attempt to ameliorate the behavioral symptoms but are not designed to address skill deficits and cognitive functions , 3. In aFortunately, non-pharmacological strategies have been introduced and widely applied in the field of ADHD interventions, ranging from behavior intervention, physical therapy, neurofeedback to counseling, and more recently digital therapy. The current evidence on non-pharmacological treatments for ADHD indicates that these interventions can lead to improvements in self-reported ADHD symptoms as well as in the symptoms reported by the parents and teachers of children , 7. The Non-pharmacological therapy is designed to be administered in a long-term setting to help ADHD patients acquire psychosocial skills or improve cognitive functioning by boosting their motivation, organization/planning skill, and adaptive thinking. A new and emerging form of non-pharmacological therapy known as prescription digital therapy is in the preliminary phase of development. According to the definition provided by the Digital Therapeutics Alliance, digital therapeutics (DTx) “deliver medical interventions directly to patients using evidence-based software therapeutic interventions to treat, manage, and prevent a broad spectrum of diseases and disorders” , 9. The Recent growing evidence suggests that digital interventions offer effective strategies for resolving the psychological problems and for improving the attentional and working memory performance of children and adolescents with ADHD, while posing minimal risk for adverse events . Based oHowever, due to the variety of digital interventions and limited sample sizes, the published studies regarding the efficacy of digital therapeutics have provided inconsistent findings . Therefohttps://www.crd.york.ac.uk/PROSPERO) with registration number CRD42022350349.In this meta-analysis, the Preferred Reporting Items of the Systematic Reviews and Meta-analysis (PRISMA) guidelines and the Cochrane Handbook of Systematic Reviews of Interventions were followed , 14. We For the meta-analysis, we searched all quantitative and qualitative studies, reports, letters, reviews, editorial articles, or conference abstracts examining the efficacy of digital therapeutics in pediatric ADHD. The following inclusion criteria were applied: (1) clinical trials or prospective studies; (2) pediatric participants aged 4–17 years with a clear primary diagnosis of ADHD; (3) digital intervention that is directly provided to ADHD patients online or through mobile application via computer, phone, or tablet, to treat or manage ADHD. The intervention can be a standalone software program or a program used in combination with self-help therapies or with hardware-assisted therapies; and (4) outcomes reported as measurable continuous variables. Studies and patient populations were excluded for the following reasons: (1) comorbidity of neurodevelopmental disorder with ADHD; (2) studies that have overlapping or duplicate samples; and (3) studies with poor designs or data unavailable for extraction.For the meta-analysis, two reviewers independently evaluated the final included papers using a standardized form. Data extraction from each study was conducted separately by two reviewers, who then double-checked the results. The authors of the original studies were contacted with questions to identify the study's unique execution procedure, if necessary. If disagreement occurred, it was resolved through conversation or with the help of a third investigator. The following data were collected: first author's name, year of publication, country/region, age, gender ratio, years of follow-up, and research sample size. The primary outcomes of this study were the effectiveness of digital therapeutic interventions for the core symptoms  of ADHD as determined by assessment tools including the ADHD-Rating Scale (ADHD-RS). The secondary outcomes were attention control evaluated by Continuous Performance Task (CPT) tests and executive functions and working memory assessed by the Behavior Rating Inventory of Executive Function questionnaire (BRIEF). The Newcastle-Ottawa Quality Assessment Scale (NOS) was selected to assess the methodological quality of included studies. Three major components of each study were examined: patient selection, the comparability of the intervention and the observation groups and outcome assessment. NOS score ranges from 0 to 9, with high quality defined as a NOS score ≥7.The ADHD-RS is based on the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for ADHD and consists of inattentive items, hyperactivity/impulsive behavioral items for parents and teachers graded on a scale. For this study, we used the subscales inattention and hyperactivity as dependent variables, and other subscales or scales not rated by parents/teacher were not considered.The CPT is a series of computerized tests of attention and hyperactivity/impulsive behavior and several versions including the Conners CPT , Integrated Visual and Auditory Continuous Perform Test (IVA-CPT), and Test of Variables of Attention (TOVA) have been developed since the 1950s. Even when different CPT versions were used, the tests typically measure reaction time, number correct, and errors of omission and commission, which correlate with inattention and impulsivity, and thus, pooled analysis could be performed. For this study, due to the limitation of the included sample size, we used the reaction times as dependent variables.The Behavior Rating Inventory of Executive Function (BRIEF) is a rating scale for parents and teachers to assess eight sub-domains: Inhibit, Shift, Emotional Control, Initiate, Working Memory, Plan/Organize, Organization of Materials, and Monitor with 75 items. For this study, we used the BRIEF2 subscale Working Memory and the Total Scale, which are associated with ADHD severity as dependent variables, and other forms of scales were not considered.2 test and Cochran's Q-statistic were used to assess heterogeneity among the included studies based on the odds ratio (OR) and 95% CI. Funnel plots were created, and publication bias was assessed using Begg and Egger regression. Statistical significance was defined by a P value < 0.05.The meta-analysis was performed using Stata 15.0. ADHD patients who completed digital interventions were compared with controls who received no intervention or another type of intervention. Differences in ADHD-RS and BRIEF scores were analyzed for significant. CPT reaction times from different platforms were normalized according to the mean values from different studies and were applied for pooled analysis. Different meta-analyses were performed with stratification by the type of intervention . Effects between digital intervention and control groups, and their 95% confidence intervals (CIs) were calculated using a continuous random effects model. The IWe identified 31 English language publications focusing on the efficacy of digital therapeutics in pediatric ADHD. The results of the selection process from our literature search are presented in P = 0.002. This result suggests that digital interventions significantly improved attention in pediatric ADHD patients. To further explore the heterogeneity among included studies, chi-square and I2 analyses were performed, and small differences in heterogeneity were observed between treatment groups   with = 0.005) .P = 0.018. This result suggests that digital interventions improved hyperactivity symptoms in pediatric ADHD patients. Chi-square and I-square analyses revealed differences in heterogeneity between treatment groups   with = 0.004) .P = 0.013. This result suggests that digital interventions led to significant improvement in the total ADHD-RS score for pediatric ADHD patients. Chi-square and I-square analyses identified significant differences in heterogeneity between treatment groups   with = 0.000) .P = 0.707). We next investigated the influence of each individual study on the summary assessment of the overall meta-analysis. The recalculated ORs with the exclusion of each study were not significantly altered   with = 0.004) .P = 0.83). We next investigated the influence of each individual study on the summary assessment from the overall meta-analysis   with = 0.000) .P = 0.001. This result suggests that digital interventions significantly improved working memory in pediatric ADHD patients. Chi-square and I-square analyses detected no differences in heterogeneity between treatment groups , but heterogeneity was not observed within the three included studies  with  studies .P > 0.05). We next investigated the influence of each individual study on the summary assessment of the overall meta-analysis  than digital therapeutics without a difficulty-adjusting system . However, digital therapy without personalized difficulty adjustment had a more pronounced positive effect on ADHD-related hyperactivity . Similarly, on executive functions, Asian ADHD patients receiving digital therapeutics showed a better performs compared with that in Europe , and a decrease in CPT reaction time also was observed , revealing a positive effect of digital therapeutics on inattention symptoms and functioning. Measures of executive function  also were improved based on data from two studies. The score for impulsive hyperactivity was slightly decreased after treatment . Additionally, working memory appeared to be increased, but the different between the treated and control groups was not significant. Visual appraisal of the sensitivity analysis results suggested the absence of publication bias. Together these results indicate that digital interventions could be a possible therapeutic strategy for pediatric ADHD, especially with regard to attention control.Previous studies of the use of digital therapeutics for ADHD treatment have provided preliminary evidence of their effectiveness. Multiple studies showed that video games can improve cognition by promoting the formation and restructuring of neurobiological pathways , 52, andDigital therapeutics was defined by the Digital Therapeutics (DTx) Alliance as “delivering evidence-based therapeutic interventions to patients that are driven by software to prevent, manage, or treat a medical disorder or disease.” To date, a broad spectrum of digital therapeutics has been recommended and adopted to treat developmental, behavioral, and emotional disorders in children. However, these digital treatments are based on different treatment mechanisms, which is referred to as the “active component”, and supported by various forms of technology, including big data, artificial intelligence, sensor technology, video-game and virtual reality. Because of the heterogeneous nature of these digital treatments, several issues remain to be addressed, including: (1) the lack of consensus about the outcome measures for efficacy; (2) the limited validation of the digital devices in non-English languages; (3) the lack of digital treatment categorization based on the “active component” and technology platform; and (4) the lack of standardized protocols for intervention based on categorization. Thus, there is an urgent need for methodologically robust, adequately powered research evaluating the safety, efficacy, and effectiveness of digital interventions for children and young people with ADHD, especially digital therapeutics in languages other than English. This research may require the inclusion of children and adolescents as well as therapists in the product design and development processes to ensure the interventions are fit for purpose and user-centered. Continuous evaluation of evolving interventions is also necessary.Another important issue in digital therapy studies is the choice of the control group. Although recent clinical trials have applied different type of digital interventions as control groups, waitlist studies were more common. There is a need to further clarify the potential adverse effects of digital therapy. Video game therapy was reported to lead to symptoms of headache, dizziness, agitation, and other adverse effects . MoreoveOne method for categorizing digital therapeutics is by their core active component, which is considered reflective of the “therapeutic mechanisms” of digital interventions. Mechanisms of digital therapies include neuroplasticity and neural reorganization boosting through cognitive training. Cognitive training includes a series of tasks designed to improve one or more aspects of executive function, such as attention, working memory, reaction time, cognitive flexibility, and motor performance . In addiA major limitation of the implementation of digital therapy in clinical practice is the ongoing need to identify the best intervention protocols, efficacy, safety, feasibility, and benefit-to-cost ratio of these therapies. Currently, clinicians should be cautious about recommending different digital therapies, because even those that appear similar may have different core mechanisms and technology platforms and thus offer differing efficacies.A strength of the present study was the use of reliable quantitative evaluation methods to systematically compare the clinical efficacy of digital therapy in pediatric ADHD. Based on the current evidence in the literature, we explored important elements of interventions that can be specifically linked to their effects on outcomes including inattention, hyperactivity, executive function, and working memory. In previous studies, essential elements of behavior or digital interventions were frequently omitted in the data synthesis and interpretation. This led to the duplication of effort, uncertainty, and confusion and undermined the potential to accumulate evidence across studies for determining the efficacy of specific therapeutic approaches. This also points to the urgent need for the identification and analysis of essential elements in digital treatment , 59.The present study also has several limitations. Firstly, the scales adopted for ADHD symptom assessment were inconsistent, which limited the interpretation of treatment outcomes. More studies employing the same assessment scales are needed in the future to obtain more reliable results . SecondlIn summary, the results of our study suggest that digital therapy, mostly in the form of video game-based technology, offers potential clinical efficacy for improving attention, sensory perception, and a variety of cognitive functions in pediatric ADHD patients. However, additional research is needed to identify the optimal conditions for digital therapy as well as any potential adverse effects . Overall, based on the existing literature evidence, we conclude that digital interventions demonstrate possible efficacy on improving clinical symptoms of pediatric ADHD.The original contributions presented in the study are included in the article/All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.


Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are two types of developmental disorders that have gained significant attention in the field of developmental and behavioral pediatrics. However, in clinical practice, the etiology of these disorders is under investigation and their management is still challenging. The current topic, therefore, aims to focus on the horizons of the two developmental disorders in clinical practice , 2. So fWang T. et al., children with ASD are introduced to complementary foods later in their early developmental stage, which is associated with later feeding problems. Compared to typically developing controls, children with ASD also experience more feeding problems that can be linked to core symptoms of the disorder. Pediatricians should therefore advise parents to watch for difficulties in adjusting to the introduction of complementary foods, as this may indicate a higher risk of feeding problems later in life and atypical social interaction and communication development. Chen et al. have also found that the communication warning behavior sub-scale of the children neuropsychological and behavioral scale-revision 2016, a commonly used developmental assessment tool for children aged 0–6 years in China, can be used to screen for ASD. A communication warning behavior score that is 12 points or more above the norm requires further attention and comprehensive diagnostic evaluation to achieve early detection and diagnosis of ASD in children.Early identification and screening for ASD are crucial for improving the prognosis of autistic children through evidence-based early intervention . The earZhang et al. have observed a significant increase in sialidase NEU1 mRNA levels in children with autism, and have also found a correlation between increased NEU1 expression and social dysfunction. These findings suggest the need for further investigation into the relationship between NEU1 and ASD. Maternal low vitamin D status is regarded as a possible risk factor for ASD in offspring. Serum hypo vitamin D is common and has been recommended as a possible biomarker for ASD diagnosis , and the effectiveness of the Early Start Denver Model (ESDM) treatment. The authors discovered that ESDM was effective in treating all three types of children with ASD, with the group experiencing liver qi stagnation exhibiting the most notable improvements. A multi-center prospective investigation of outcome of behavioral intervention on the different traditional Chinese medicine types of ASD may be useful to give strong evidence to predict the effect of the behavioral intervention.Early intervention of ASD has a significant effect on the rehabilitation of ASD. Although the effectiveness of the Early Start Denver Model (ESDM) for treating ASD has been established, there remains significant variability in treatment response among individuals. As per a prior study, a collection of social cognitive skills such as receptive and expressive language, intention to communicate, and attention to faces, have consistently been associated with response to ESDM . It is rWu et al., there could be a link between early exposure to screens and hyperactive behaviors in children. The study revealed that more than 90 minutes of screen time per day in children under the age of 3 was associated with hyperactive behaviors. These findings suggest that restricting screen time in toddlers may prove advantageous in preventing ADHD.The etiology of ADHD is still uncertain now, however, genetic conditions and many environmental factors are involved in the pathogenic process. Excessive screen exposure time is adverse to children's health . AccordiMainstreams of ADHD management include medication and non-medication therapy. Medications including stimulants  and non-stimulants  are usually used in ADHD children over 6 years . HoweverChu et al. investigated the impact of combining group executive functioning and online parent training on school-aged children (between 6 to 8 years old) diagnosed with ADHD. Their findings suggest that this combination approach holds potential as a non-pharmaceutical therapeutic option for younger students with ADHD. Wang Y-c et al. have designed the scheme that effects of high-definition transcranial direct current stimulation (HD-tDCS) on the right orbital frontal cortex in the treatment of ADHD. This study draws cautious conclusions that HD-tDCS leads to significant improvements in cognitive measures of attention maintaining.In their study, The current work explores the basic practice in clinics for ASD and ADHD. These results support that early behavioral study for recognition, diagnosis and early intervention for ASD are crucial to improve the clinical symptoms, limiting screening time in toddlers may be beneficial for ADHD prevention in toddlers and nutritional vitamin D status in children with ASD, and non-medication therapy is still important in clinical practice. More studies based on clinical practice would be valuable in guiding treatment decisions and improving the prognosis of ASD and ADHD.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.


Attention deficit hyperactivity disorder (ADHD) is associated with risk‐taking behavior, leading to accidents and unintentional injuries (summarized here as incidents). Main aim of this study is to determine if men and women with and without ADHD differ in the risk of mild (treated outpatient) and severe (treated inpatient) incidents across the adult lifespan . Secondary aim: investigate the role of comorbid mental disorders and drugs for the treatment of these comorbidities, and ADHD‐medication.N = 4,575,027), adults with ADHD diagnosis during 2016–2019  were compared with a 1:4 age and sex‐matched group without ADHD diagnosis. Regression analyses statistically tested group differences.Using anonymized German claims data (Incidents occur in a U‐shaped form across the adult lifespan. Individuals with ADHD show the same pattern but at a substantially increased risk of both mild and severe incidents throughout the lifespan. Women without ADHD are at lower risk in young adulthood than men but at higher risk in older adulthood. Women with ADHD show the same pattern for severe incidents, but for mild incidents they have the highest risk throughout the lifespan. Co‐occurring anxiety disorder and the use of psycholeptics and ADHD‐medication decreased the incident risk.We extend available knowledge which has hitherto focused on young adult males and traffic accidents. ADHD is associated with increased incidents across the adult lifespan, with distinct patterns regarding age, sex, and incident severity. An accurate diagnosis of ADHD in adulthood provides the first step towards prevention of accidents and unintentional injuries. Throughout their entire adult lifespan, adults with attention deficit hyperactivity disorder (ADHD) are at a significantly higher risk for accidents and unintentional injuries (summarized as incidents) as compared with adults without ADHD.Especially women with ADHD are at an increased risk for incidents, already as young adults.ADHD‐medication, comorbid anxiety disorder and psycholeptics decrease the risk for incidents in adults with ADHD. Hence, early diagnosis and treatment may reduce incident risk.Individuals with ADHD were identified within the claims dataset based on an ICD‐10 diagnosis from the inpatient and outpatient setting, including primary care. Therefore, the study sample built upon the administrative prevalence of diagnosed individuals may represent more severe cases compared with individuals with ADHD in in the general population, which may have led to an overestimation of the incident risk associated with ADHD.The study includes adults with ADHD across the entire adult lifespan and stratifies within age groups. Nevertheless, the observed time was restricted to a one‐year observation which may have led to an underestimation of the incident risk associated with ADHD across the adult lifespan.Individuals with ADHD in this study may have received ADHD‐medication before or after an incident (sequence of events was not tracked). Hence, the observed protective overall effect of ADHD‐medication against incidents may be underestimated.1Attention deficit hyperactivity disorder (ADHD) in adults has been increasingly recognized as an impairing mental health condition.22.1Approximately 90% of the overall German population is insured in statutory health insurances (SHI). For this study, claims data from the Institute for Applied Health Research Berlin (InGef) database was used. This database contains approximately 5 million member‐records and is representative of the German population in terms of age and sex and shows good overall accordance in morbidity, mortality, and drug usage.For each individual identified with ADHD, four adults identical in age and sex but without ADHD diagnosis were randomly drawn. Index was set as at the quarter of first ADHD diagnosis at which individuals must have been at least 18 years old. For individuals without ADHD, a pseudo‐index at the same day as their matched ADHD comparator was set. After index, each individual was observed for 1 year for the occurrence of accidents and unintentional injuries, as well as medication, including drugs for the treatment of (ADHD‐medication), psycholeptics, antidepressants, drugs for the treatment of addictive disorders and the occurrence of pre‐defined comorbidities ; coding, see Table 2.2All data are anonymized in the research database to comply with German data protection regulations. Institutional review board/ethical approval and informed consent was not required.2.3Demographic information, occurrence of accidents and unintentional injuries and mortality rates are described stratified by sex and age  groups. To formally test if there are age and sex specific patterns in mild and severe incidents that differ among individuals with and without ADHD, we conducted multinomial logistic regression analyses. In all regression models, age was analyzed in categories to accommodate for the presence of potential non‐linear effects across the lifespan. Specifically, we studied if ADHD, sex and age and the interactions of ADHD with sex and age  were associated with the likelihood of incidents according to incident severity.In addition, we tested in a second model (by adding to the first regression model), effects of the presence of (comorbid) mental disorders and medication use and the respective two‐way interactions with ADHD . This informed us on whether findings of our main analysis were altered by taking account of comorbidities and co‐medication in adults with ADHD. In a third model, testing if ADHD‐medication altered the occurrence of incidents, we included only individuals diagnosed with ADHD . Main effects were ADHD‐medication, sex and age as well as two‐way interaction effects  and the three‐way interaction effect sex by age by ADHD‐medication.p < 0.05 using z tests. For all analyses, the statistical software Microsoft R Open 3.5.0 was used.Estimates from the multinomial regression analyses were shown as risk ratios (RR) with 95% confidence intervals (CI) and significance tested at a level of 33.1Out of 4,575,027 individuals insured in the database from January 2016 to December 2019, 70,758 individuals with diagnosed ADHD were identified. Among those, 17,041 were above 18 years old, continuously insured, and therefore included in the analyses.Figure Table Figure Table 3.23.2.1Table Throughout the lifespan and regardless of sex, individuals with ADHD are at a significantly higher risk for both mild and severe incidents than individuals without ADHD  and medication  to the initial regression model. For the percentage of individuals with and without ADHD with these mental disorders and medication intake see Table p = 0.062).In a third regression model, within the ADHD group  and intake of psycholeptics (severe incidents). In addition, use of ADHD‐medication is associated with a decreased risk of mild incidents especially in young and older age when incident risk is highest.An important finding in this study is the U‐shaped occurrence of both mild and severe incidents. In literature, mostly driving behavior in relation to traffic accidents has been studied. A high risk of traffic accidents in young adulthood is generally explained by inexperience and higher risk‐taking behavior that characterizes young adults.So far, most studies have focused on predominantly male samples, in particular young adult males with ADHD in relation to traffic accidents. Here, we identified important sex differences across the lifespan. We showed that, in general men and women show opposite trends in incident occurrence, with females at lower risk in young adulthood than males but surpassing them in middle adulthood such that they have a substantially higher risk in older adulthood. However, in individuals with ADHD, this general pattern holds for severe, but not mild incidents, which form the majority of all incidents. The lifetime plot of mild incidents risk revealed that women with ADHD are at highest risk for mild incidents not only in middle and older adulthood, but across the entire adult lifespan. Related to this is that men and women with ADHD are more similar in experiencing mild incidents than men and women without ADHD, which was particularly salient in young adult women with ADHD compared with young adult women without ADHD. Both hyperactivity and impulsivity, which is more prominent in young adult males with ADHD, and attention problems, more prominent in adult females with ADHD, may contribute to incident risk.Further, we confirmed previous findings that ADHD‐medication significantly reduces the incident risk,A major strength of this study is that findings were based on a large, representative sample of referred patients form the general German populationAn important limitation, however, is that claims data are first and foremost collected for billing purposes, which is not so much a limitation with regard to accidents and unintentional injuries, but it is with regard to ADHD. We could only study individuals with a documented ADHD diagnosis who were referred to a health care facility, as opposed to assessing ADHD in the general population using measurement instruments (e.g. diagnostic interviews) regardless of whether individuals with ADHD sought professional help or not.To conclude, this study showed that individuals with ADHD have more mild and severe incidents than individuals without ADHD throughout the adult lifespan. For severe incidents, individuals with and without ADHD display a similar lifespan pattern, which only differs by the higher risk associated with ADHD: higher in young adulthood than in middle adulthood but highest in old age. For mild incidents, individuals with and without ADHD have different patterns of risk. That is, women with ADHD have a higher incident occurrence than men with ADHD throughout the adult lifespan, whereas women without ADHD only surpass men without ADHD in risk of incidents in middle adulthood and older age. Co‐occurring AD, intake of psycholeptics and ADHD‐medication buffer against the ADHD‐related increased risk. Our findings support recommendations to adequately diagnose and treat adult ADHD in order to reduce accidents and unintentional injuries.All authors meet the ICMJE criteria for authorship. Berit Libutzki, Benno Neukirch, Andreas Reif, and Catharina A. Hartman formulated the research question. Berit Libutzki (lead), Benno Neukirch, and Catharina A. Hartman designed the study, carried out data collection in collaboration with the database and analyzed the data. All authors contributed to writing the article and reviewed the article.Berit Libutzki is employed at Janssen‐Cilag AG, which, however, has no connection to this work. Benno Neukirch has nothing to declare. Sarah Kittel‐Schneider has received author's and speaker's honoraria from Medice Arzneimittel Pütter GmbH and Takeda. Andreas Reif has received honoraria and/or served on advisory boards from Medice, Shire/Takeda, Janssen, SAGE/Biogen, Boehringer Ingelheim and Cyclerion. Catharina A. Hartman declares honoraria as a speaker for Medice which has no connection to this work.https://publons.com/publon/10.1111/acps.13524.The peer review history for this article is available at This work was supported by Hochschule Niederrhein ‐ University of Applied Sciences. The study was conducted by Hochschule Niederrhein ‐ University of Applied Sciences and the Institute for Applied Health Research Berlin (InGef).Table S1. Inclusion criteria and coding of comorbid condisions and medication intake, including ADHD‐medicationTable S2. Occurrence (%) of accidents and unintentional injuries across adulthood for males and females with and without ADHDTable S3. Type of accident and unintentional injuries coded at index and within one year of observation stratified by age and sex in all individuals with and without ADHDTable S4. Percentage of individuals with mental disorders and medication intake with and without accidents or unintentional injuriesTable S5. Multinomial Logistic Regression 2: extended model assessing ADHD, age, sex, mental comorbid disorders, medication intake and interaction effectsTable S6. Multinomial Logistic Regression: assessing the role of ADHD‐medication within the ADHD population on the likelihood of accidents and unintentional injuriesClick here for additional data file.


Attention deficit/hyperactivity disorder (ADHD) is a prevalent and impairing neurodevelopmental disorder affecting 2-5% of children. These children are at risk of negative health, social and educational outcomes; ADHD incurs an estimated £670 million annual cost to health, education and social care in the UK. Children with ADHD often experience severe difficulties at school despite drug treatment: effective psychosocial interventions are needed. There is mixed evidence for the effectiveness of existing school-based interventions for ADHD, which are complex and resource-intensive, contradicting the preferences of teachers for short, flexible strategies that suit a range of ADHD-related classroom-based problems.To develop a prototype of a school-based intervention for ADHD.Intervention Mapping, a framework for developing theory- and evidence-informed interventions with explicit consideration of implementation context, was used. Logic models were developed of the behaviour change steps required by each agent in the school system to improve outcomes for students with ADHD.A comprehensive evidence synthesis was conducted for interventions that targeted the key outcomes of relevance ; findings were integrated alongside behaviour change theory and theories of the underlying aetiology of ADHD, in order to develop a logic model for the intervention. Components of the intervention were then developed in line with the logic model using evidence-based behaviour change methods, with input from people with ADHD, school staff and other key stakeholders at every stage of the development process.The development process resulted in a prototype digital platform that can be utilised to deliver a personalised behavioural intervention for children with ADHD within primary schools. It contains some core components that all teachers and children will complete, and then is individualised based on the key problems each child is currently facing. There are six optional modules, each containing a range of behavioural strategies for teachers to implement with the student or the whole class. The toolkit includes a symptom tracking graph that teachers can use to visualise the progress a child is making, and is developed to align with the current resources and capacity of primary schools in the UK.The prototype intervention is designed explicitly to fit with existing school structures and demands, and to be low cost in terms of delivery and training. It focusses on adapting the school environment to better suit children with high levels of ADHD symptoms. It is now being feasibility tested, and in this talk I will describe the development process using Intervention Mapping, and the initial feedback from the first testing of implementation of the prototype.None Declared


Background: Every year, 14 million babies are born with low birth weight (LBW) and/or intrauterine growth restriction (IUGR) in developing countries. In Sudan, 15-25% of all newborns are born with LBW, with half being Term-LBW. The importance of nutrition in the first 1000 days of life has been well demonstrated. Evidence links IUGR to various health and developmental disorders, and intrauterine programming of the hypothalamic-pituitary-adrenal (HPA) axis has been strongly suggested as a possible mechanism. Sudan has been listed among the lowest four countries regarding food security which has a massive impact on maternal and infant health.Hypothesis: We hypothesize that infants who suffer from intrauterine growth retardation will have exaggerated physiological and behavioural responses to physical stressors.Objectives: To compare T-LBW with T-NBW on (a) Salivary cortisol level at rest and after a physical stressor and (b) Behavioural response to physical stressors.Methods: Hospital-based matched case-control study. Cases were 65 T-LBW neonates, and controls were 67 T-NBW neonates matched for age 4-6 hours, gestational age, and mode of deliverymeasurements: Anthropometry, salivary samples for cortisol before and after heel prick, and behavioural ratings.Results: Compared with controls, the IUGR neonates were lighter, shorter, and thinner (p <0.0001) and had lower basal cortisol levels (p <0.03). Following stressors, IUGR neonates had lower (p >0.0001) and inhibited cortisol response (p <0.02), and cried less vigorously (p <0.0001). All anthropometric measures were significantly and positively correlated with behavioural responses and pre- and post-stress cortisol levels. Stunting was more strongly associated with behavioural inhibition than wasting.Conclusion: The severity of intrauterine growth retardation correlated with behavioral and physiological inhibition, which can lead to the development of mismatch diseases such as allergies, autoimmune diseases, and conjunctive disorders.


Studies have reported significant associations between asthma and attention‐deficit/hyperactivity disorder (ADHD), but whether the association is due to shared etiology such as shared genetic risk factors remains unclear. We aimed to investigate patterns of familial co‐aggregation of asthma and ADHD and also to quantify the relative contribution of genetic and environmental influences.Through Swedish register linkages, we obtained a cohort of 927,956 individuals born 1992–2001 and identified monozygotic twins (MZ), dizygotic twins (DZ), full‐ and half‐siblings, and full‐ and half‐cousins. Clinical diagnosis of asthma and ADHD were identified from the Swedish national registers. We used logistic regressions to investigate the within‐individual association and familial co‐aggregation between asthma and ADHD. We then used bivariate twin modeling to quantify the genetic and environmental correlations and their contributions to the familial liability.Individuals with asthma had significantly higher risk of ADHD . Relatives of individuals with asthma had an increased risk of ADHD compared to relatives of individuals without asthma; in familial co‐aggregation analysis, the association was strongest in MZ twins  and attenuated with degree of genetic relatedness. In the twin modeling, the phenotypic and genetic correlations between asthma and ADHD estimated from the ACE model were 0.09  and 0.12 , respectively. The bivariate heritability was 0.88 . Estimates for contributions from shared and non‐shared environment factors were not statistically significant.Asthma and ADHD co‐aggregate in families primarily due to shared genetic risk factors. Within‐individual and family history of either disorder should prompt clinical assessment of the other condition. Future studies should further investigate genetic variants underlying the co‐occurrence of ADHD and asthma. Asthma and attention deficit/hyperactivity disorder (ADHD) co‐aggregate in families. The comorbidity between asthma and ADHD may be mostly explained by shared genetic risk factors. Previous studies reported a robust association between asthma and attention‐deficit/hyperactivity disorder (ADHD), but the underlying mechanisms remained largely unknown.Our analysis revealed that asthma and ADHD co‐aggregate in the family, and the phenotypic correlation between the two disorders may mostly be explained by shared genetics.The familial co‐aggregation of asthma and ADHD supports joint services for clinicians with expertise on developmental psychopathology and allergic/atopic conditions to aim for early identification and proper management of either disorders.The bivariate heritability and genetic correlation may facilitate future research to identify biological pathways from genetic variants to the specific phenotypes.Asthma is the most common chronic respiratory disease with onset in childhood  to investigate the shared familial liability to asthma and ADHD by analyzing multiple types of relatives, and (2) to conduct the first twin study using clinically diagnosed asthma and ADHD to estimate the relative contribution of genetic and environmental influences to the association.The study was approved by the Regional Ethics Committee in Stockholm Sweden. Since this is a register‐based study using anonymized data, informed consent for study individuals was not required, except for information on zygosity of the twins where consent was obtained from the participants.Data was identified by linkage through multiple Swedish national registers using unique personal identification numbers. The main cohort included individuals born in Sweden between January 01, 1992 and December 31, 2001, identified from the Medical Birth Register  with two‐sided 95% confidence intervals (CIs) for the association between asthma and ADHD on individual level and within the family. For all models, we accounted for dependence of rows of data from within family clusters using cluster‐robust variance estimation to adjust the standard errors.We started by comparing the risks of ADHD among individuals with and without asthma, adjusting for sex and year of birth, to validate the phenotypic association .We estimated the ORs of having ADHD in individuals (outcome person) whose relatives (exposure person) had asthma compared to individuals whose relatives did not have asthma. We adjusted for sex and year of birth for both the exposure person and outcome person. An increased risk of having ADHD among individuals whose twins, siblings or cousins had asthma indicates the existence of shared familial liability underlying the phenotypic association between asthma and ADHD. Existence of familial liability can be inferred by the different magnitude of associations in different degrees of siblings .Unique twin pairs were used in this part. We calculated the intra‐class  and cross‐twin‐cross‐trait  correlations. We used bivariate twin modeling to estimate the relative genetic, shared‐, and non‐shared environmental contributions to the familial liability and to estimate the genetic correlation between asthma and ADHD. Asthma and ADHD were treated as binary conditions representing underlying normal distribution of liability of getting the diagnosis based on a liability threshold framework , the familial co‐aggregation analysis was done using version 15.1 (StataCorp), and the quantitative genetic modeling part was conducted using OpenMx  and a genetic correlation of 0.12 (0.02–0.21). Shared genetic factors explained almost all of the covariance between asthma and ADHD, with bivariate heritability of 0.88 (0.30–1.46) estimated from the ACE model. Correlation coefficients for E was not statistically significant . None of the models supported significant contributions from shared or non‐shared environmental factors for the phenotypic correlation.To our knowledge, this is the largest study using family data from about 1 million individuals to investigate the familial liability underlying the association between clinically diagnosed asthma and ADHD. It is also the first to quantify the relative contribution of genetic and environmental influences to the familial liability using twin modeling analysis. We found that individuals with asthma were at a higher risk of having ADHD compared to those without asthma. The association was strongest in MZ twins, then attenuated with degree of genetic closeness and the pattern was mostly explained by a shared familial liability. Using twin analyses, we also found that a substantial part of the association between asthma and ADHD were explained by genetic factors.We found, for the first time, that relatives of probands diagnosed with either asthma or ADHD have elevated risk of being diagnosed with the other. Two early sibling studies did not find evidence of familial co‐aggregation between asthma and ADHD . However, results from the sensitivity analysis when defining asthma only by clinical diagnosis from NPR were similar with the main analysis, indicating robustness of our asthma definition. The overall phenotypic correlation between asthma and ADHD was weak, which may make it hard for us to conclude on the environmental contributions. We did observe attenuated ORs when adjusting for asthma or ADHD in the outcome person in the familial co‐aggregation analysis and a weak and non‐significant correlation for non‐shared environmental factors in the ACE model, indicating possibly weak causality between asthma and ADHD. Future twin modeling studies with larger sample size may be able to further clarify this issue.Asthma and ADHD co‐aggregate in families, and the familial liability may mostly be explained by genetic factors. Our results have important implication for the clinical practice and the understating of the pathophysiology for both disorders. Asthmatic patients with personal or family history of ADHD symptoms should be considered to be referred for assessment of ADHD, and children with ADHD assessed for asthma. Future studies should further investigate genetic variants explaining the genetic correlation between asthma and ADHD, and clarify the biological pathways from genes to the phenotypic correlation.Advances. The remaining authors report no financial relationships with commercial interests. Samuele Cortese declares reimbursement for travel and accommodation expenses from the Association for Child and Adolescent Central Health (ACAMH) in relation to lectures delivered for ACAMH, Canadian ADHD Alliance Resource (CADDRA), British Association of Psychopharmacology (BAP), and from Healthcare Convention for educational activity on ADHD. He is a member of the Editorial Advisory Board for JCPP Advances. Zheng Chang is also a member of the Editorial Advisory Board for JCPP Advances. The remaining authors have declared that they have no competing or potential conflicts of interest. Henrik Larsson has served as speaker for Evalon and Shire and has received research grants from Shire. He is also Editor‐in‐Chief of JCPP The study was approved by the Regional Ethics Committee in Stockholm Sweden. Since this is a register‐based study using anonymized data, informed consent for study individuals was not required, except for information on zygosity of the twins where consent was obtained from the participants.S. Sun and H. Larsson were responsible for the study design. S. Sun and R. Kuja‐Halkola conducted the analysis. S. Sun drafted the manuscript and all co‐authors contributed in the study by providing ideas and comments on the manuscript.


The advantages of the modified PB transposon system or high transposable efficiency and broad host ranges have led to their widespread application in transgenesis, mutagenesis, and gene therapy. At present, there is no systematic report on PB transposon in bees. Therefore, this study focused on annotating the transposons of the PB superfamily in bees to reveal the distribution, diversity, structural characteristics, evolutionary pattern and activity of PB transposons in the available genomes of bees.Bees are one of the mega-diverse class of insects in Hymenoptera. As predators and the main crops pollinator, bees play an essential role in improving crop yield and the quality whiles providing substantial economic importance. Transposable elements (TEs) exist widely in nature and they make up a significant portion of prokaryotic and eukaryotic genomes. piggyBac (PB) transposons in 44 bee genomes from the Apoidea order, which is a superfamily within the Hymenoptera, which includes a large number of bee species crucial for pollination. We annotated the PB transposons in these 44 bee genomes and examined their evolution profiles, including structural characteristics, distribution, diversity, activity, and abundance. The mined PB transposons were divided into three clades, with uneven distribution in each genus of PB transposons in Apoidea. The complete PB transposons we discovered are around 2.23–3.52 kb in length and encode transposases of approximately 580 aa, with terminal inverted repeats (TIRs) of about 14 bp and 4 bp (TTAA) target-site duplications. Long TIRs  were also detected in some species of bees. The DDD domains of the three transposon types were more conserved, while the other protein domains were less conserved. Generally, most PB transposons showed low abundance in the genomes of Apoidea. Divergent evolution dynamics of PB were observed in the genomes of Apoidea. PB transposons in some identified species were relatively young, whiles others were older and with some either active or inactive. In addition, multiple invasions of PB were also detected in some genomes of Apoidea. Our findings highlight the contribution of PB transposons to genomic variation in these species and suggest their potential as candidates for future gene transfer tools.In this study, we investigated the presence of  The Apoidea superfamily, which originated from the early-to-middle Cretaceous period, is one of the main categories of Hymenoptera Apocrita . ApoideaTransposable elements (TEs) are DNA sequences that can be independently copied or broken from their original site and inserted into another site, playing a regulatory role in the evolution and gene regulation of all organisms. They ‘jump’ from one position in the genome to another through a series of processes, such as cutting and reintegrating, also called the jumping gene. The TE generally moves the TE sequence itself and is not dependent on the sequence relationship between the donor and recipient. TEs have been detected in various organisms, including bacteria, fungi, and insects , and thepiggyBac, Tc1/mariner, pogo, hAT, Helitron, and PIF-Harbinger, have been reported, and their evolutionary profiles have been well-defined for some groups, such as Tc1/mariner and pogo DNA transposons -transposases [PB superfamily and other transposon superfamilies [piggyBac transposons [piggyBac-like elements were found in Myotis lucifugus, and display recent activity, forming a strong cluster with the sea squirt, Ciona intestinalis [PB elements in Microcebus murinus, divided them into three categories, and found that those three types of PB transposons were relatively young [piggyBac-like elements in the red flour beetle Tribolium castaneumre are divided into 14 diverse groups [piggyBac (PGBD) have been found in the human genome [PB transposons, although their internal classification at the family level remains largely unknown.The active ribution ,34. PB emammals) ,36. The r vector  with potr vector ,38,39,40ectively ,36,41,42ectively . PB transposases  and are sposases . In addifamilies ,44. The nsposons ,47,48. Hstinalis . Anotherly young . In addie groups . Moreovepogo and mariner, belonging to the ITm group (IS630-Tc1-Mariner), being well-defined in bees [PB transposons in each species to determine their structural characteristics, overall distribution, and phylogenetic location and classification, and conducted evolutionary dynamics analysis. Our data shed light on the evolutionary pattern of PB transposons in Apoidea and enhanced our understanding of their contribution to the evolution of the Apoidea genome.Currently, there is limited information on DNA transposons in bees, with only  in bees ,52. In tPB transposase sequences [https://www.ncbi.nlm.nih.gov, accessed on 22 November 2022) using TBLASTN (v. 2.12.0) [https://primerdigital.com/fastpcr.html, accessed on 25 November 2022) [PB > 10 copies in genome) of transposons in each genome were used to determine the genomic copies (coverage > 40% and similarity > 80% of queries) by BLAST.All reference equences  were use 2.12.0)  with the 2.12.0)  were exter 2022)  and the er 2022) . The rephttps://www.bing.com/search?q=genescan, accessed on 29 November 2022), and the sequence identities were calculated using the BioEdit tool [https://github.com/CJ-Chen/TBtools/releases, accessed on 30 January 2023) [PB transposases were aligned using MAFFT [http://weblogo.threeplusone.com/create.cgi, accessed on 16 December 2022) was used to create logo images of TIRs.The transposases of the mined transposons were predicted by Genescan (dit tool . The seqry 2023) . The PB ng MAFFT  and manung MAFFT . The strng MAFFT . The onlPB transposase reference sequences collected from the previous report [https://www-is.biotoul.fr/scripts/search-db.php, accessed on 23 January 2023) [PB transposases in Apoidea, together submitted for phylogenetic analysis. A multiple sequence alignment was carried out by using the G-INS-I method of MAFFT (v7.310) [Overall, 13 s report  and 10 Iry 2023) , which ary 2023) , combine(v7.310) ; then, t(v7.310) ,62.PB transposon in each genome was annotated using the RepeatMasker program . Then, the Kimura (K) divergence was calculated using the calcDivergenceFromAlign.pl package from RepeatMasker [The atMasker . The KimatMasker . It is gatMasker .PB transposons showed an uneven distribution across the genus of Apoidea, as summarized in PB elements in 44 species (34.65%) belonging to 27 genera within eight families of Apoidea. The majority of PB transposons were found in Apidae, with 26 species (38.81%) of Apidae containing PB transposons, while other families had fewer detections, such as three species (13.04%) in Halictidae, four species (66.67%) in Crabronidae, four species (57.14%) in Andrenidae, and four species (50%) in Megachilidae. PB transposons were only detected in one species in each of the following three families of bees, Colletidae, Melittidae, and Ampulicidae (ulicidae .PB transposons were found in 12 species (36.36%) of Bombus, four species (57.14%) of Andrena, two species (66.67%) of Ceratina, two species (66.67%) of Megachile, and two species (40%) of Tetragonula. In some lineages, PB transposons were detected in only one species  to 335 (Eufriesea mexicana) in the 44 species harboring PB elements . Among these, very high copy numbers were identified in the genomes of A. haemorrhoa (236) and E. mexicana (335). Additionally, most PB transposons existed as truncated copies, with only 20 species harboring intact PB transposons (encoding transposase longer than 500 amino acids and detectable two-end TIRs), which accounted for 45.45% of the species containing PB copies. Although some species had high full copy numbers of PB, the intact copies were very low or not detectable. For example, B. terrestris contained 86 copies of PB, but only two of them were intact copies, while A. haemorrhoa, B. soroeensis, and E. mexicana had totals of 236, 58 and 335 in copy numbers, respectively, but intact copies were not detected in these genomes. In general, PB transposons were not significantly amplified in bees, and most species displayed a low abundance of PB  (A. dorsata has the longest transposon length (3518 bp) and encodes the longest transposase (681 aa). Most PB transposons carry short TIRs (<25 bp); however, few PB transposons harbor long TIRs, such as PB in B. bifarius (TIR: 201 bp), B. terrestris (TIR: 200 bp) and Exoneura robusta (TIR: 489 bp). The conserved and consistent TSD (TTAA) was observed in most PB transposons  . Among tnsposons . The seqelements . High sielements .PB transposases (≥100 aa) was constructed using the IQ-tree program [PB transposases in Apoidea with robust bootstrap supports (≥78%), as summarized in The evolutionary tree of the excavated  program , with 24 program , and thePB transposases are known to contain five well-defined domains: the N-terminal domain (NTD), the Dimerization and DNA-binding domain 1 (DDBD1), the catalytic domain , DDBD2, and the C-terminal cysteine-rich domain (CRD) [PB activity and thought to be the driver of TIR binding [in (CRD) . Sequencin (CRD) ,60,66, ain (CRD) ,67, is c binding , exhibit binding   represent K divergences of less than 2%, and seem to have invaded very recently. Furthermore, intact copies were detected in some species   . These dB. bifarius, Bombus hypnorum, Bombus haemorrhoidalis, C. calcarata, Ctenoplectra terminalis, E. robusta, Habropoda laboriosa, and Mimumesa dahlbomi) show high K divergences (K > 15), suggesting that they may be old invaders in these lineages  and invertebrates  [PB transposons were detected in approximately one-third of bee species , and they were unevenly distributed across families and genera of bees. Notably, due to the high species diversity of Bombus, the number of PB transposons detected in Bombus was significantly higher than in other genera. Moreover, the transposons in Bombus were relatively conservative, with almost all PB transposons found in Bombus belonging to Clade B, suggesting a possible vertical propagation of PB transposons in Bombus. According to the available data, PB transposons have great diversity in arthropod species, and besides the PB family, Tc1/mariner, Busters and other transposons are found mostly in arthropods [PB transposons also showed high diversity in Apoidea. Three distinct clades of PB transposases (A–C) were identified in Apoidea, with low sequence similarity among them. Megachile, Bombus, Ceratina, and Andrena all harbored two types of PB transposons. When determining the distribution, we considered PB transposons to be present in the genome when sequence similarity reached 80% and query coverage reached 40%. However, this approach may have led to the exclusion of short, truncated elements derived from PB, potentially underestimating the taxonomic distribution of PB transposons in Apoidea. In addition, due to the continuous update of genome sequencing data, new families are constantly appearing in the PB superfamily, meaning the number of PB transposon categories in Apoidea will be more than the currently identified, and their diversity may be higher than we predicted.minthes) ,36,69,70thropods ,72,73. HPB transposons have invaded a large number of bee genomes, the total copy number is very low in most species, indicating that most PB transposons do not show significant amplification in bees. Bombus, which transitioned from solitary bees to social bees [PB, due to lack of functional domains of transposases or TIRs, lost transposition activity. Other transposon families such as ZB and SB, which have been identified from animal genomes and belong to the Tc1/mariner superfamilies, exhibit high intact copy numbers (ranging from 10 to over 80 copies) in some genomes, with over 70% of species containing intact copies [PB transposons are rare in Apoidea, with only 20 out of 44 species showing intact copies, and the copy numbers of intact copies are low in each detected species, with only H. calliopsidis having more than 5 intact copies in its genome, suggesting potential activity.After invading the host genome, transposons undergo amplification, diversification, inactivation, and elimination. The presence of intact copies may indicate that transposons are in the amplification stage or have recently undergone amplification and may be active ,75. Howeial bees , has mort copies . In contPB transposons in bees was found to be similar to the original sequence found in T. ni, consisting of five domains that have been previously defined [PB transposons had CAC instead of CCC/GGG for their first three TIR bases. In seven bees , the TSDs of the PB transposons were not TTAA, which suggests possible mutations. Our data, along with previous studies, revealed that PB transposases may contain a highly divergent DDD domain, analogous to the widely distributed DDE domain found in many DNA transposases and retroviral integrases, which consists of two highly conserved aspartic acids and one glutamic acid [PB transposons [PB transposon in M. dahlbomi can encode protein of 596 aa with consistent 16 bp TIR at both ends, the second conserved residue in the catalytic domain of DDD mutated from “D” to “N”. Similarly, PB transposons in A. compressa encode a protein of 552 aa and have 14 bp TIR at both ends; the third conserved remnant in the catalytic domain of DDD mutated from “D” to “H”. These results suggest that PB transposons in these two species may have lost their transposable activity, which is supported by the late insertion age of transposons in M. dahlbomi, as determined by evolutionary dynamics analysis. In contrast, the DDBD1 and DDBD2 domains among the three types of PB transposons are not as conserved as DDD. DDBD1 and DDBD2 are special all-α-helix domains, knitting the protein together and interacting with TIR [PB transposases are not conserved, they contain several highly conserved cysteines, with conserved distances between them. The CRD in the PB transposases do not match many other known C-rich domains [The structure of most complete  defined . TIRs pl defined ,77,78. P defined ,79. Howemic acid . The DDDmic acid ,60,66, wnsposons ,44. Althwith TIR . While t domains . NTD is  domains . NTD resPB elements in Apoidea, with most of the excavated PB transposons representing old copies indicated by high K divergence. However, PB transposons in several species  showed very low K divergences, indicating that these transposons are recent invaders and might still be active, contributing to ongoing genome renewal. In addition, multiple waves of PB amplifications were detected for some species, suggesting repeat invasions of PB transposons. The copy number of each transposon appears to be related to its insertion age and evolutionary mode. For instance, PB transposons in B. hypnorum and B. bifarius had relatively old insertion times, and the copies of PB transposons in these genomes tend to be degenerated due to the accumulation of mutations. In contrast, PB transposons in H. calliopsidis display very low K divergences, indicating young insertion ages, and more intact copies were detected.Generally, differential evolutionary dynamics were observed for PB transposons in 44 species of Apoidea and has analyzed their activity, phylogeny, and structural characteristics. In general, PB transposons are widely distributed in Apoidea and can be divided into three classes. Despite low overall sequence similarity among the three clades, each class of transposons exhibits highly conserved DDD domains. Furthermore, we detected low copy numbers of PB transposons in most Apoidea genomes. Interestingly, we observed divergent evolution dynamics of PB transposons in the genomes of Apoidea, with intact copies being rare in these 44 species.Our study provides the first comprehensive information on the distribution of


Attention-deficit/hyperactivity disorder (ADHD) has a considerable impact on an individual’s daily life. Some difficulties with timing deficits may be associated with deficiencies in attention, reading, language skills, or executive function. Music therapy, either active (playing an instrument) or passive (listening to music) has demonstrated its efficacy in reducing symptomatology in many disorders. Video games may prove to be a useful assessment and treatment tool in compensating for the difficulties with multimodal treatment in ADHD.The aim of the study is to (1) analyze the evidence that music is beneficial in reducing the symptomatology of ADHD using systematic review and (2) propose the application of music in video games following music therapy strategies.Searches were conducted in PubMed, Embase, PsycINFO, Cochrane, and gray literature (Google Scholar and WorldCat). We used the following search syntax: ((music[Title/Abstract]) or (music therapy[Title/Abstract])) and (attention deficit disorder[MeSH or thesaurus term]).Of the 70 records identified, 17 provided findings that music can be beneficial in various domains of ADHD. Active music therapy improves hemispheric synchrony, social skills, aggressivity, and impulsivity. Passive music therapy improves academic skills like arithmetic, drawing, and reading comprehension, as well as attention and disruptive behaviors. The effects depend on the music genre, tempo, or task difficulty. Music in video games was generally found to be beneficial for people with ADHD. Music improves immersion and flow while playing video games. Using rhythm may also improve timing skills and immersion in patients with ADHD. Regarding the proposed application of aspects of music to therapeutic video games for ADHD, some paradigms in timing and music therapy were considered in the proposed design of video games.Improving ADHD treatment through the application of music in video games is proposed.PROSPERO CRD42021288226; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=288226 Attention-deficit/hyperactivity disorder (ADHD) is the most frequent neurodevelopmental disorder with a worldwide prevalence of 5% . DespiteRecent neuropsychological models suggest ADHD deficits are implicated in 3 independent pathways: the dorsal frontostriatal pathway involved in cognitive control, the ventral frontostriatal pathway involved in reward processing, and the frontocerebellar pathway related to temporal processing . TemporaCurrently, alternative treatments have tried to compensate for the problems associated with multimodal treatment in ADHD. These alternative treatments include neurobiofeedback , mindfulAn initial search was performed using the terms (music[MeSH Terms] and video games[MeSH Terms] and ADHD[Title/Abstract]), with no results. To amplify our search, we then searched for so-called “gray literature.” Gray literature refers to any scientific material not controlled by commercial publishers, such as doctoral and master’s dissertations or technical reports . To do tA PI(E)COS   approachThe inclusion criteria were (1) studies that apply music or music therapy in people with ADHD; (2) randomized clinical trials, prospective comparative studies, and case-control studies; (3) papers published in peer-review journals; and (4) written in English, French, or Spanish. Searches were conducted in English, French, and Spanish in PubMed, Embase, PsycINFO, and Cochrane. We used the following search syntax, adapted for each database: ((music[Title/Abstract]) or (music therapy[Title/Abstract])) and (attention deficit disorder[MeSH or thesaurus term]). The exact syntaxes used for every search and database are described in No results were found for the 3 search terms chosen  in the databases, so we searched for gray literature in Google Scholar and WorldCat. The systematic review search was refocused on symptom improvements in ADHD due to music or music therapy.A total of 70 papers were identified from databases of which 15 duplicates were eliminated. Fifty-five papers were evaluated based on titles and abstracts. Of these, 32 reports were excluded due to not being related to the area of our review. Twenty-three full-text papers and 10 gray literature papers were evaluated. A final total of 17 papers were included: 8 from PubMed, 2 from PsycINFO, 3 from Embase, 1 from WorldCat, and 3 from Google Scholar, not counting duplicates see . The selEffects of active and passive music therapy on people with ADHD are summarized in Active music therapyHemispheric synchronySelf-esteemSocial skillsAggressive behaviorImpulsivityPassive music therapyArithmetic skillsReading comprehensionDrawing task (slow tempo)Balance performanceAttention Disruptive behaviorMotor activity (rock music)Heart rate variability (relaxing music)Arousal and mood (negative when using silence)No scientific literature on video games and music applied in ADHD was found in PubMed, Embase, PsycINFO, and Cochrane. Most of the video game studies found do not focus on timing skills or musical abilities , and musVideo games are generally effective and well-accepted tools for cognitive skills training in ADHD. The immediate feedback from video games provides direct performance support for individuals with ADHD; they tend to have engagement rates with low numbers of dropouts and increased participation, motivation, and sense of agency . RepetitTherefore, we focused on applied music therapy methods  to design specific video games to study timing deficits in ADHD. Audio may improve interactivity in video games in two ways, active and passive: a player causes sounds with his actions (active) and music can modulate the focus and emotional state of the player (passive) . Due to Regarding the passive way of using music in serious video games, the effect of listening to music in video games is unclear. A study suggests that music reduces the experienced duration of playing with or manipulating time perception . HoweverMusic is a complex cognitive challenge that apparently has not provided us an evolutionary advantage. However, music provides us great pleasure , and braIt is a commonly accepted statement that children with ADHD need reduced environmental distraction and silence to perform better. On the contrary, some studies indicate that listening to music before or during a task could improve attentional performance better than silence ,37,38. IRegarding active music performance, regularly playing a musical instrument can promote interhemispheric synchronization in people with ADHD, although this higher neural efficiency does not reach the musically trained controls. The choice of musical instrument can help increase practice frequency. Drums or guitars were preferred by people with ADHD, while piano was the preferred choice in children with dyslexia . MoreoveAs mentioned earlier, people with ADHD have timing deficits, which can range from milliseconds and seconds  to days or years  . MoreoveThis study has limitations. Few studies were found while searching the databases, so we opted for broadening the search using gray literature from Google Scholar and WorldCat. In addition, the studies were quite heterogeneous, so a meta-analysis could not be carried out. Instead, we qualitatively integrated outcomes. We structured the outcomes considering 2 main variables, music therapy modality  and reduction in symptomatology, but qualitative reviews are nonetheless more prone to biases in their conclusions . These rThe benefits of music as a part of serious video games for people with ADHD have not been directly assessed. In general terms, this systematic review shows that active (playing music), passive (listening to music), and interactive (music-making with feedback) music therapy are beneficial in reducing ADHD symptomatology and increasing task performance in people with ADHD. Rather than being a distraction, music can help to modulate emotional and cognitive states. Rhythm seems to be a music component particularly benefitted by improved timing perception and regulation. We propose integrating music into the mechanical design of ADHD serious video games, especially related to rhythm-based mechanics.