To estimate whether the “Diagnostic and Statistical Manual of Mental Disorders” (DSM) is biologically accurate for the diagnosis of Attention Deficit/ Hyperactivity Disorder (ADHD) using a biological-based classifier built by a special method of multivariate analysis of a large dataset of a small sample (much more variables than subjects), holding neurophysiological, behavioral, and psychological variables.Twenty typically developing boys and 19 boys diagnosed with ADHD, aged 10–13 years, were examined using the Attentional Network Test (ANT) with recordings of event-related potentials (ERPs). From 774 variables, a reduced number of latent variables (LVs) were extracted with a clustering of variables method (CLV), for further reclassification of subjects using the k-means method. This approach allowed a multivariate analysis to be applied to a significantly larger number of variables than the number of cases.From datasets including ERPs from the mid-frontal, mid-parietal, right frontal, and central scalp areas, we found 82% of agreement between DSM and biological-based classifications. The kappa index between DSM and behavioral/psychological/neurophysiological data was 0.75, which is regarded as a “substantial level of agreement”.The CLV is a useful method for multivariate analysis of datasets with much less subjects than variables. In this study, a correlation is found between the biological-based classifier and the DSM outputs for the classification of subjects as either ADHD or not. This result suggests that DSM clinically describes a biological condition, supporting its validity for ADHD diagnostics. The validity of the Diagnostic and Statistical Manual of Mental Disorders—DSM American Psychiatric Association, 1994–2013) , since mental phenomenology stem from biological systems. However, it is still not possible to perform any reductionist analysis that could unambiguously uncover the cerebral mechanisms of mental disorders or reveal any biomarkers that determine any diagnosis.Mental disorders are multidimensional complex entities, with non-linear relationships among their biological processes  rather tThe objective of this study was to evaluate the accuracy of DSM based on the correspondence between clinical classification and classification using multidimensional biological measures from neurophysiological and behavioral data. Thus, we have assumed that these biological data contain patterns that can explain the nosological entity called ADHD. It does not matter whether we know which these patterns are or not as long as they are really embedded in these objective measures. Multivariate analysis can empirically find these patterns that synthetize this complexity. These informative patterns are treated as latent variables (LVs).From this standpoint, multivariate analysis techniques have been applied to electroencephalographic or biochemical data since the 1970’ in order to develop high-sensitivity and accuracy models for the diagnosis of mental disorders . HoweverIn the present study, our aim was to deal with a small sample of subjects with well-controlled confounding variables and bias. A large number of characteristics have been collected from typically developing boys (TD) and boys diagnosed with ADHD using the DSM-IV-TR criteria. There were three groups of data: (1) behavioral (related to reaction time –RT), (2) neurophysiological , including late cognitive component P3 or P300 , both obThis study does not address controversial issues, e.g., if the ADHD phenomenology actually constitutes a mental disorder or not. The present study seeks to infer about the accuracy of the DSM as a tool to identify this phenomenology, which could be important for further discussions about the validity of this manual for ADHD diagnostics.This transversal and exploratory study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the National Institute of Women, Children, and Adolescents Health Fernandes Figueira. Before the first recruitment, the project was registered at plataformabrasil.saude.gov.br, under the number CAAE 08340212.5.0000.5269. All the participants provided their oral consent in the presence of their caregivers, who provided written informed consent after receiving a complete description of the study.Sixty boys, aged 10–13 years, were included according to DSM-IV-TR: 35 with ADHD (coded from T001 to T035) and 25 typically developing . The exclusion criteria were: (1) history of chronic diseases, and any suspicion of psychiatric disorders other than ADHD  as screened by K-SADS-PL ; (2) useThe following were considered as confounding variables: years in school, monthly family income , sleep hours the night before, and mean weekly time which the boy dedicated to computer activities and videogames , as well as age.After applying the exclusion criteria and performing the behavioral analysis of accuracy (AC) and speed-accuracy tradeoff (see below), 19 ADHD and 20 TD boys remained in the sample for analysis.Each subject was evaluated using a structured interview where his or her caregivers were shown the DSM-IV-TR criteria and were instructed to point out carefully whether or not each specific criterion was an exact characteristic of their child’s behavior. If there was any doubt about or hesitation concerning any item, it was disregarded. Thus, subjects were classified as typically developing (TD) (comprising the control group) or ADHD in accordance with the DSM-IV-TR.I.Q. was estimated by Block Design and Vocabulary subtests from the Wechsler Intelligence Scale for Children, WISC-III . The Ari2), at 50 cm distance between nasion and screen), fitting his/her glance on the central black cross (1.4° ×1.4°). He was instructed to observe the horizontal orientation of a yellow fish as target stimulus (1.7° ×1.1°), appearing for 350 ms, which was (or not) preceded by a cue signal  with onset of 1,650 ms before the target and 150 ms duration. The target appeared above or below the fixation cross , always flanked by two distractors at each side, which were identical yellow fishes oriented towards the same (congruent) or opposite (incongruent) direction of the target. The flank distractors appeared 100 ms before the target (according to The ANT version adapted for children was used . It was Subjects with AC lower than 70% and speed-accuracy tradeoff (estimated as AC × RT) lower than the mean sample value minus two standard deviations were excluded.During the ANT, the subject’s EEG was recorded using a Nihon Kohden NK1200 EEG System at 20 scalp points according to the International 10/20 System , with reRegarding the comparison tests between ADHD group and TD group of subjects , we perfSeveral behavioral variables were gathered from the ANT for each subject: mean AC of task performance, i.e., the percentage of correct responses; mean RT and its standard deviation, called intra-individual variation of RT (IVRT), for each cue and target condition. Additionally, data included the ANT scores of the subjects: alerting, orienting, and conflict resolution, mean RT for correct and incorrect responses, and learning rates .The peak amplitude, peak latency, and mean amplitude of the ERPs were estimated inside three time intervals of interest  was 774: four scores obtained from the above-mentioned WISC-III subtests, 29 behavioral variables obtained from ANT, and 741 neurophysiological variables (39 for each of the 18 channels and C3-C4).10.6084/m9.figshare.7914422.The neurophysiological variables obtained represent topographical parameters of cerebral activity, while the variables from ANT and WISC provide the integral characteristics of the subject. For the analysis, the activity in certain brain regions of the subjects performing ANT  was assumed to best correlate with ADHD phenomenology . For this reason, 40 different channel sets  were useThe data from each investigated set of EEG channels were analyzed either with or without behavioral (ANT) and psychological (WISC) variables. They were submitted to CLV, an unsupervised method for multivariate analysis . The aimOur ultimate purpose was to reclassify the subjects into two groups according to the objective behavioral, psychological, and neurophysiological data, all of which were summarized around the extracted LVs. A k-means clustering method  was perfIn order to determine whether reclassification outputs are robust against a variation of the subject’s sample, a cross-validation approach has been undertaken. The objective was to better assess the performance of our numerical processing workflow by repeatedly simulating a training sample set, on which the statistical model is built, and an independent test set, on which the reclassification performance is finally evaluated. In practice, the whole sample of the 39 subjects is split into a training set of 31 subjects (about 80%) and a test set of 8 subjects (about 20%). The selection of the test set observations is performed so as to have the same proportion of ADHD and TD subjects (by DSM classification) in the test set as in the whole set. The CLV method is applied on the training set, and one to six LVs are considered for k-means clustering into two clusters. The number of LVs to be retained is based on the percentage of agreement with the data driven partition and the DSM diagnostic. The last step is to predict group membership of the test set subjects, who play the role of independent observations, using statistical modelling.This cross-validation procedure is repeated a large number of times. Herein we performed 100 repetitions. The mean level of agreement in reclassification across all the test sets is the performance indicator we considered for identifying the combination of EEG channels providing the best outputs. See Considering the best choice of VOI variables, a sensitivity and specificity analysis for the ADHD DSM criteria is suggested.p < 0.001, ADHD > TD scores). The hyperactivy+impulsivity scores are not different between groups (p = 0.09). Among variables considered as confounders, the I.Q. scores in ADHD group were lower than in TD boys (p = 0.010) although they were always higher than 80. No other variables were significantly different between the two groups. See these results in For descriptive purposes, we compared DSM scores of two samples, with subjects individually classified as ADHD or TD according to the DSM: as expected, Control and ADHD groups showed significant differences regarding DSM-IV-TR criteria for attention and total scores  were observed in all channels. Peak amplitude varied from the maximum value of 18 µV for the frontopolar target ERP to the minimum value of 1 µV for the difference between C3 and C4 . In Fig.According to a preliminary data analysis, it turns out that the mean amplitude was highly correlated with the peak amplitude measurement. The mean amplitude was thus discarded and only peak amplitude and peak latency measures were subsequently considered.For all the 40 channel sets, values of agreement with DSM  varied fBased on the results of the test sets, the worst mean agreement level between DSM and k-means reclassification was 55.3% when all the ERP channels were involved. The best mean agreement level with DSM was 76.4% for  channel set (set 33). Two other channel sets showed a good performance . Those oχ2 = 7.20, p = 0.004). The estimated specificity and sensitivity of the DSM-IVTR regarding these ERP variables were 75.00% and 89.47%, respectively. This accuracy corresponds to the kappa index of 0.75, i.e., a substantial strength of agreement  to the ADHD group, and two ADHD subjects  to the control group. There was an accuracy of 82.05% , while in the latter, it was not significant: 10.13 vs. 8.13, respectively for control and ADHD groups   P300 wave showed higher difference between the two new groups than between those based on the DSM classification. In the former case, this difference was very highly significant: 10.64 in controls (MOM estimator) vs. 7.43 in ADHD  .Our study tackled the accuracy and biological adequacy of examining attention deficit/hyperactivity disorder using the DSM manual, with reference to classifier variables based on objective variables of biological nature. This classifier has comprised a new synthetic dimensional reduction method, the CLV , and a tIn order to classify subjects as TD or ADHD according to DSM criteria, caregivers were asked which criteria were well-defined characteristics of their children. Other assessment methodologies should also be used along with DSM for ADHD diagnosis both in scientific research and in clinical practice. Moreover, the manual should not be applied as a questionnaire in clinical practice. However, in this case, the object of evaluation is the DSM itself; it was thus the only clinical diagnostic tool used for the classification of subjects as either ADHD or not-ADHD. It was the most objective and controlled way to obtain the scores without interference from any other clinical impression. Supporting the present methodology, the ASRS (the WHO questionnaire for adult ADHD screening) was self-administered .Although this study was not focused on neural mechanisms of ADHD, it seems to be important to tackle this aspect briefly to show that there is real neurophysiological basis under our models. The selected neurophysiological variables with which DSM best agrees were topographically asymmetrical and represented the binded information from ERPs mainly in cue- and target-related late components from mid-frontal (Fz), mid-parietal (Pz), right frontal (F4), and right anterior temporal (F8) sites. The P3 wave, a late potential related to cognitive tasks  is partiDue to the correlation with the pattern of variables compatible with the current biological models for ADHD, the present result suggests that DSM-IV-TR is actually a biologically justified tool for ADHD diagnosis, as it was applied here. Although a Kappa index of 0.75 should be considered with reservations for some clinical settings, for mental disorders, a clinical method such as DSM showing this level of agreement with biological characteristics should be considered as particularly relevant. First, we must consider the inherent complexity of mental disorders that have no validated biomarkers. This complexity reaches its maximum when we deal with dimensional clinical phenomenology, whose symptoms are simply, sometimes extreme, variations in the expression of normal behavior, as is the case of ADHD. How many different measures are necessary to cluster these conditions? Furthermore, the ADHD has been regarded as a heterogeneous condition with inattentive, hyperactive, and combined subtypes, which could be the answer for this level of agreement since these subtypes were not intended for reclassification. The overlay of three discrete subtypes could lead to a flawed reclassification.The only psychiatric tool for diagnosis and intervention is still phenomenological examination, which must be systematically  performed based on judgement about whether the subject meets the criteria from manuals such as the DSM. Thus, it is reasonable to regard that the information embedded in the objective measures from the EEG and behavior in ANT, even distorted by all those nonlinearities, is more reliable a priori for classifying subjects than the DSM, which is a subjective assessment.The small sample size can naturally raise doubts. However, this sample was designed to be very consistent and homogeneous. Any subject with the slightest suspicion of comorbidity was excluded. Potentially confounding factors commonly ignored were monitored . Therefore, the sample should be regarded as well representative of ADHD. On the other hand, in order to classify the subjects according to their mental condition  it is necessary to gather a considerable number of objective variables (as many as possible). Since it did not seem feasible to collect a sample with thousands of subjects evaluating hundreds of variables in an experiment with optimal control of confounders and bias, the dataset had to have a much smaller number of observations than variables. A small but strictly controlled and well-exploited sample was considered preferable, even in conditions of high prevalence such as the ADHD. Multivariate statistical modeling, such as Linear Regression, Discriminant Analysis, or Factor Analysis, are well known as unsuitable for this situation. Thus, in order to tackle a frequently encountered methodological problem, often referred to as the curse of the dimensionality, an explorative data analysis suitable for small samples was adopted to identify a small number of synthetic latent variables. Instead of the Principal Component Analysis, which does not always provide easily interpretable LVs , an approach with clustering of variables was chosen to reduce data dimensionality to a small number of new LVs. The CLV method  has alreA major limitation of this study is the impossibility of testing all possible combinations among variables. Since the consistency of our paradigm lies on the fact that no biological / behavioral assumptions were considered in the grouping of variables, it is necessary to test them randomly grouped. However, there are more than one million possible combinations of EEG channels. The number of combinations grows exponentially if the other variables are included individually. For computational feasibility, sets of variables were arbitrarily chosen for analysis. Considering the eighty sets studied, it can be assumed that DSM has at least a ”substantial level of agreement” with biological determinants. Perhaps some untested set of variables may manifest higher agreement with the DSM, but the results found already satisfy our objective of testing the accuracy of the DSM criteria for ADHD, discussing about its adequacy for it.In the ANT paradigm used here , the flaThe estimated I.Q. scores were different between the groups diagnosed using DSM-IV-TR, but this was not regarded as bias. Literature has shown that intelligence tests are sensitive to ADHD, and scores of TD subjects are generally higher .Even taking into account the above restrictions, there is no doubt that the data obtained seem to be quite consistent.Using the CLV method, suitable for samples with a much smaller number of cases than the number of variables analyzed, we conclude that the DSM criteria “A” for ADHD diagnosis have a substantial (nearly 80%) correlation with the biological dimension, especially with the neurofunctional responses related to attentional networks of Posner . Thus, D10.7717/peerj.7074/supp-1Supplemental Information 1Detailed mathematical description of CLV method.Click here for additional data file.10.7717/peerj.7074/supp-2Supplemental Information 2Inference of the magnitude of agreement between two categorical data .Click here for additional data file.10.7717/peerj.7074/supp-3Supplemental Information 3For emulate independent samples –see main text for details.Click here for additional data file.10.7717/peerj.7074/supp-4Table S1Windows holding Cue-related potentials (CUE), contingent voltage variation (CVV), and Target-related potentials (TGT) for each channel (ms) to calculate peak amplitude, peak latency, and mean amplitude. Zero ms refers to Target onset see .Click here for additional data file.10.7717/peerj.7074/supp-5Dataset S1In the first sheet: inattention, hyperactive+impulsive, and total scores for ADHD according to DSM-IV-TR; second sheet: all data concerning (1) scores of the WISC-III subtests, (2) ANT performance  for each experimental condition  and attentional network  plus learning indexes (IVRT or RT at the last ANT block/first ANT block), and (3) the neurophysiological measures  for the EEG channel set.Click here for additional data file.10.7717/peerj.7074/supp-6Figure S1Individual waves from the sample for each channel , by page. The waves (gray) are superimposed to their mean values (black thick line) and their standard error of mean (black thin dotted line). Amplitude in microvolts. Waves related to all ANT conditions indistinctly.Click here for additional data file.10.7717/peerj.7074/supp-7Figure S2n = 39) of No Cue (blue), Neutral Cue (black) and Spatial Cue (red) -related potentials are superimposed in (A), and Congruent (blue) and incongruent (black) -related target conditions are superimposed in (B). See caption of figure 1 for more details.Sample means (Click here for additional data file.


Children with neurodevelopmental disorders (NDDs) exhibit a shared phenotype that involves executive dysfunctions including impairments in mental flexibility (MF). It is of interest to understand if this phenotype stems from some shared neurobiology.n = 88; 8–15 years) with autism spectrum disorders (ASD), attention deficit hyperactivity disorder (ADHD) and obsessive-compulsive disorder (OCD), as they completed a set-shifting/mental flexibility task.To investigate this possibility, we used magnetoencephalography (MEG) neuroimaging to compare brain activity in children  contains supplementary material, which is available to authorized users. Neurodevelopmental disorders (NDDs) are a heterogeneous group of disorders, characterized by compromised central nervous system development and aberrant brain function –3. The mOne cognitive characteristic observed in all three groups is that of impaired executive functions, including mental flexibility (MF). Mental flexibility comprises the ability to alter behavioural and thought patterns in response to environmental changes , 11 and Mental flexibility relies on a network of brain regions spanning prefrontal, posterior parietal and insular regions, the basal ganglia and anterior cingulate cortex ACC; –13), as , as 13])Most studies of MF have used fMRI as their method of choice. While this tool is excellent for spatial investigations, it is more limited in its temporal resolution . MagnetoTo investigate the neural bases of mental (in) flexibility in children with NDDs, we recruited children with ASD, ADHD and OCD to complete a set-shifting task in the MEG scanner. As there is increasing research suggesting that NDDs may exist along a continuum, we hypothesized that the common behavioural manifestation of cognitive inflexibility across ASD, ADHD and OCD groups may be due to some shared underlying neural substrates, existing along a spectrum. Specifically, based on Ameis et al.’s DTI research, we expected to find greater similarities in activity in ASD and ADHD groups, with both groups more affected than the OCD group.We recruited 116 children with an NDD between the ages of 8–15 years. After data cleaning for artefacts, a total of 88 children  were included in our final analyses  and AutFull-scale intelligence quotients  and four parent-questionnaires were administered to measure repetitive ), o), o29]))To assess MF in our clinical groups, we employed an MEG-compatible Intra-Extra Dimensional Set Shift task (IED-task) previously used in our group to test adults  and chilAccuracy and reaction time for correct Shift and Non-Shift trials were compared across groups using a linear fixed-effects model in SPSS® (v24), with repeated measures for shift type, age as a covariate and an unstructured repeated covariance type.MEG data were acquired supine in a 151-channel CTF Omega system . Analyses were conducted using SPM12  and Fielt test [SPM(T)], corrected for multiple comparisons with a modified Bonferroni applied to the p value of 0.05 )  of 0.05 . All res MRIcron .We first conducted a within-group analysis where, for each group, we used a multifactorial design  to contrTo explore differences between groups, a multifactorial design  was usedTo further probe the cross-diagnosis shared neurobiological correlates of mental inflexibility, we investigated brain-behaviour relations collapsed across the group. We used a linear regression model (controlled for age) to test whether the magnitude and/or latency of brain activity predicted behavioural measures , regardless of clinical group  = 4.187, p = 0.044] but not for ‘Group’ nor ‘Shift Type’. There were no significant interactions. The average age-adjusted accuracy scores per trial type, for each group, are contained in Table For accuracy, a significant main effect was observed for ‘Age’  only. Post hoc analyses, adjusted for multiple comparisons using the Bonferroni method, revealed that Non-Shift trials were faster than Shift trials [p < 0.001]. There were no significant main effects for ‘Group’ and no significant interactions. The mean age-adjusted reaction times by group and trial type can be found in Table For reaction time, the fixed effects model revealed a main effect for ‘Shift Type’  and left IFG pars triangularis , was negatively related with TOCS score. That is, faster peak latencies in these two frontal regions were associated with higher scores, or greater morbidity, regardless of clinical group, on the TOCS scale.For the measure of obsessive-compulsive behaviours captured by the TOCS, we found that the peak latency in two frontal regions, the right superior frontal gyrus (SFG) . Peak power values in the left angular gyrus were significantly positively related to RBS-R total scores, , indicating increased power/activation was associated with greater RBS-R total scores or greater morbidity.For the measure of repetitive behaviours, we found that a significant linear regression equation predicted RBS-R total scores based on peak power values, extracted during peak two (150–300 ms), [In this study, we used MEG to investigate neural processing involved in a MF task in children with ASD, ADHD and OCD. The ease with which participants completed the task  indicated that the children were able to set-shift successfully.In both adults  and typiThe literature in both adults  and chilAccording to the posterior-to-anterior theorem of brain development , 45, we While the NDD groups all showed a similar pattern of sustained parietal activity, the pattern of frontal activations was significantly different between groups, suggesting that this may be a distinguishing feature. Based on the pattern of findings by Ameis et al. in the same NDDs, and in line with our within-group results Fig. , we expeOur between-group analyses (OCD > ASD and OCD > ADHD) revealed that children with ASD and ADHD display significantly decreased activity in prefrontal regions compared to children with OCD. The OCD > ADHD contrast revealed the greatest differences, with ADHD showing bilaterally reduced frontal activity across the inferior and middle frontal gyri. These findings are consistent with other functional neuroimaging studies in ADHD which have shown hypofrontality in MF, as well as executive functions more broadly , 50–54.The sustained prefrontal activity in OCD may be reflective of hyperfrontality, a functional characteristic that has previously been reported in the OCD literature , is consistent with many studies showing that individuals with ADHD have extensive hypoactivity that includes the frontal lobes and the parietal regions, as well as the striatum, insula and ACC , 51–53.In ASD, previous studies have shown dysregulations in the connectivity and synchrony of brain regions/networks involved in MF , as wellFor our first set of MEG analyses (featuring the within- and between-group neuroimaging contrasts), we grouped participants according to their primary diagnosis. While our MEG contrasts did reveal unique MF group-specific brain activity profiles, we also found striking similarities across the NDDs. Increasingly, there is evidence that NDDs are not separate entities that sometimes co-occur, but in fact, may be part of a spectrum with shared aetiologies and overlapping phenotypes . To thisWe used the RBS-R, TOCS and SWAN as measures of severity of symptomatic behaviours reflective of, and/or contributing to, mental inflexibility. For both the RBS-R and the TOCS, we found that brain activity predicted symptom severity, albeit in opposite directions. Bilaterally in the dorsolateral prefrontal cortices (right SFG and left IFG), we found a negative relation between peak latency and TOCS scores, such that faster peak latencies were significantly related to poorer (increased) TOCS scores. As expected, the OCD group had the greatest morbidity on the TOCS scale. There are a few different ways that we could interpret this finding. It is likely that this brain-behaviour relation is tied to the earlier and generally greater frontal activity observed in the OCD cohort during the MF task. Consistent with the literature, these findings may suggest that the prefrontal regions are hyperactive in children with OCD-like symptoms  stereotypical motor behaviour, and the limbic circuit with motivation-associated facets of behaviour and obsessions and compulsions . DiffereResearch into the structural and functional health of frontostriatal regions in NDDs shows ubiquitous atypicalities. Children with ASD and ADHD show decreased white matter integrity along the corticostriatal tracts compared to controls . Other sTo further explore the health and function of corticostriatal fibres in children with NDDs, future studies may consider taking a multi-model imaging approach, exploring white matter integrity of the loops and whether any correlations can be found with MF function. As well, it would be of interest to take a blind approach to the analysis and see whether primary diagnoses hold.There are some important limitations to consider. We are not able to draw direct comparisons between the NDD groups and typically developing children as there was not a control group in this study. Our previous work  in typicIn conclusion, while children with ASD, ADHD and OCD behaviourally share the same impairment in MF, using MEG, we found a pattern of similarities and differences in the neurobiological bases supporting this executive function. We observed that the three groups share neurofunctional characteristics in the parietal regions, but differ primarily in the frontal lobes. We observed that the NDD groups showed an absence of sequential brain activations, but instead, they showed sustained parietal activation which overlapped with frontal activation. This finding suggests that the three clinical groups share a delay or irregularity in brain development; a longitudinal study with a control group is recommended to draw firmer conclusions within this domain. ASD and ADHD groups seemed more affected than the OCD with limited and late frontal lobe activations; however, it remains to be seen whether the sustained prefrontal engagement in OCD is typical. Analyses linking brain activity with behavioural symptom measures revealed significant relations between the activity in prefrontal and parietal regions, and morbidity as measured on behavioural scales of repetitive and stereotypical behaviours, as well as obsessive-compulsive behaviours. These, in turn, may be reflective of a dysfunction in the associative loop of the corticostriatal system, which has been associated with inflexible behaviours, and has been found to be affected in children with NDDs. These findings raise the possibility that this neural system may be a target for intervention. Finally, we believe our findings are in line with new thinking that the NDDs exist along a complex continuum, where, despite the differing core phenotypic characteristics of the existing diagnostic groupings, NDDs appear to share some ‘deeper’ facets that become evident when probing genetic or neurobiological underpinnings of the disorders.Additional file 1: Supplement 1. (PDF 212 kb)


How commonly are youths with attention-deficit/hyperactivity disorder treated with antipsychotic medications and what factors are associated with their use of antipsychotic treatment?In this cohort study of 187 563 commercially insured youths with new episodes of attention-deficit/hyperactivity disorder, 2.3% were treated with an antipsychotic medication, among whom 52.7% had a potential clinical diagnostic rationale for antipsychotic treatment. Factors for antipsychotic medication use included older patient age, male sex, recent inpatient and other pharmacologic mental health treatments, self-harm/suicidal ideation; and oppositional defiant, substance use, depressive, and anxiety disorders.Approximately 1 in 40 commercially insured youths were treated with an antipsychotic medication without an approved indication in the year following a new attention-deficit/hyperactivity disorder diagnosis; mental health comorbidities may be associated with antipsychotic treatment in this group. Significant concern exists over treating youths with attention-deficit/hyperactivity disorder (ADHD) with antipsychotic medications, yet little is known about the factors associated with antipsychotic treatment.To describe the percentage of youths who fill antipsychotic prescriptions in the year following a new diagnosis of ADHD and characterize the clinical and demographic factors associated with antipsychotic initiation.A retrospective longitudinal cohort analysis of antipsychotic treatment was performed in 187 563 youths, aged 3 to 24 years, with a new diagnosis of ADHD (without recent diagnosis of any US Food and Drug Administration [FDA]–indicated conditions for antipsychotic treatment). The sample was derived from the 2010 to 2015 MarketScan Commercial Database, with the analysis completed between November 1, 2018, and May 30, 2019.The percentage of youths prescribed an antipsychotic in the first year following a new diagnosis of ADHD. Among those prescribed antipsychotic medications, the percentage who received a diagnosis of conduct disorder, oppositional defiant disorder, or a disorder for which 1 or more antipsychotic medication has received an indication for use in youths from the FDA  and the percentage that filled an antipsychotic prescription before filling a stimulant prescription (methylphenidate or amphetamine derivative).Of the 187 563 youths included in the study, 114 305 (60.9%) were male with a mean (SD) age of 13.74 (5.61) years. In the year following a new ADHD diagnosis, 4869 youths  with ADHD were prescribed an antipsychotic. Youths treated with antipsychotics with ADHD were more likely than their peers who were not receiving an antipsychotic to have recently received diagnoses of self-harm and/or suicidal ideation , oppositional defiant disorder , and substance use disorder . The youths who received antipsychotics were also more likely to have received inpatient treatment . During the year following the new ADHD diagnosis, 52.7%  of youths treated with antipsychotics received a diagnosis for which antipsychotics have either an FDA or evidence-supported indication for their use. Among youths who initiated antipsychotic medications, 47.9%  did not receive a stimulant prescription between their ADHD diagnosis and antipsychotic initiation. Antipsychotic prescribing was proportionally highest for preschool-aged children (4.3%) and associated with neurodevelopmental disorders  and recent inpatient mental health treatment .Approximately half of youths with a new ADHD diagnosis may have an evidence-supported indication for an antipsychotic medication. Less than half of these youths received a stimulant; the evidence-supported first line treatment for ADHD, before the antipsychotic was initiated. Use of antipsychotic prescribing appears to be associated with high levels of psychiatric comorbidity. This cohort study examines the use of antipsychotic medication in youths, aged 3 to 24 years, following a new diagnosis of attention-deficit/hyperactivity disorder. With prolonged exposure, these medications frequently cause adverse metabolic effects, including weight gain, hyperlipidemia, and increased risk of type 2 diabetes.16 with varying age limitations. These policies have lowered overall antipsychotic use in young children,17 although little is known about the clinical characteristics of young patients who are treated with antipsychotics in community practice.Public and professional concern over the safety of antipsychotic use in young people has led to policies aimed at reducing use of these medications. Policy interventions have targeted absolute reductions in antipsychotic prescribing with less consideration of the clinical characteristics of patients treated with antipsychotics. As of 2014, most states had implemented prior authorization policies for use of antipsychotics in children in their Medicaid programs,18 Yet, ADHD alone is not an evidence-supported indication for antipsychotic medications. Furthermore, little is known about which youths with ADHD are most likely to be treated with antipsychotic medications. Mental health comorbidity is one potential factor associated with antipsychotic treatment in youths with ADHD. Among Medicaid beneficiaries, youths treated with antipsychotics are often diagnosed with depression, oppositional defiant disorder (ODD), or conduct disorder (CD).19 Although depression is not an evidence-supported indication for antipsychotic treatment in youths, some evidence supports the effectiveness of risperidone for treatment of ODD or CD in stimulant-resistant youths with ADHD.27Nearly half of all non–FDA-indicated antipsychotic medication use in young people is for individuals with ADHD diagnoses, with or without other mental health diagnoses.The prevalence of antipsychotic use in youths following a new ADHD diagnosis is not known. Questions also exist regarding the extent to which comorbid mental disorders are associated with antipsychotic treatment in youths with ADHD. In addition, the frequency with which young people with ADHD receive antipsychotic medications before a trial of stimulants is not known. Closing these knowledge gaps will help to focus quality-of-care efforts aimed at safe and judicious antipsychotic prescribing.We analyzed claims records of commercially insured youths, aged 3 to 24 years, with a new diagnosis of ADHD. Patients recently diagnosed with conditions for which antipsychotics have an FDA-approved indication  were excluded from the cohort. To better understand antipsychotic prescribing in this population, this study (1) determined the prevalence of antipsychotic use over the following year, (2) evaluated the associations between clinical and demographic factors and antipsychotic prescribing, and (3) examined the frequency with which stimulant treatment preceded antipsychotic treatment in the first year following a new ADHD diagnosis. Before conducting the analyses, we hypothesized that males and older youths would have higher rates of antipsychotic treatment. We further anticipated that most youths with ADHD who initiated antipsychotic medications would be diagnosed with comorbid, evidence-supported clinical diagnoses , and would fill stimulant prescriptions before initiating antipsychotic medications.28 The data were deidentified and the study was determined to be exempt from human subjects review by the Rutgers University Institutional Review Board. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies.Data were obtained from the Truven Health MarketScan database of commercially insured individuals from January 1, 2010, to December 31, 2015. This database comprises medical and prescription drug data for more than 115 million enrollees, including demographic characteristics, outpatient and inpatient service codes, diagnostic codes, and detailed pharmacy files.International Classification of Diseases, Ninth Revision (code 314.xx), and International Statistical Classification of Diseases, 10th Revision (code F90.xx), aged 3 to 24 years, after at least 120 days without an ADHD diagnosis. This 4-month period was chosen because youths with ADHD often are not seen by clinicians during summer months.29 Youths were excluded if they had been prescribed an antipsychotic or stimulant or had received a diagnosis with an indication for an antipsychotic medication  in the previous 6 months. This process excluded 4555 youths . In addition, we required 12 months of continuous health care enrollment following the initial ADHD diagnosis.We examined records for youths with a new ADHD diagnosis , other mental health clinical diagnoses  and recent mental health treatment, including inpatient care, being seen by a psychiatrist, and other psychopharmacologic treatments during the 180 days before the initial ADHD diagnosis , clinical, and demographic characteristics of youths who did and did not receive an antipsychotic medication during the 12 months following the initial ADHD diagnosis. We examined the incidence of antipsychotic treatment in the year following a new ADHD diagnosis. Unadjusted and age- and sex-adjusted logistic regressions evaluated the associations of each clinical and demographic characteristic with antipsychotic treatment during the 12-month follow-up period.Second, to characterize stimulant treatment before antipsychotic initiation, we calculated the percentages of youths who received stimulant prescriptions before antipsychotic initiation among youths initiating antipsychotic medications overall and stratified by sex and age group. Stimulant treatment was defined as no stimulant, only 1 stimulant class (methylphenidate or amphetamine derivative), or both classes (methylphenidate and amphetamine derivative) during the period between new a ADHD diagnosis and antipsychotic initiation.Third, we examined the first antipsychotic initiated for the cohort who received treatment with antipsychotics. We calculated percentages for each agent and mean (SD) number of antipsychotic prescriptions during the 180-day follow-up period.Fourth, restricted to the antipsychotic-treated cohort, we examined percentages of youths who received an FDA-indicated diagnosis in the year following new ADHD diagnosis (post-ADHD diagnosis) and percentages of youths who received evidence-supported diagnoses in the 6 months before and 12 months after the new ADHD diagnosis. These results were then stratified by age group.P < .05. All analyses were completed with SAS, version 7.15 HF7 (SAS Institute Inc).Fifth, we performed a subgroup analysis of preschool or very young children (aged 3-5 years) from the initial cohort, using the same variables and adding neurodevelopmental disorders  were male, with a mean (SD) age of 13.74 (5.61) years. Within 1 year of a new ADHD diagnosis, antipsychotic medications were initiated by 4869 of 187 563 youths . The prevalence of antipsychotic treatment was 4.3%  for very young children (3-5 years), 2.0%  for older children (6-12 years), 3.2%  for adolescents (13-18 years), and 2.4%  for young adults (19-24 years). Overall, antipsychotic initiators were more likely to be male (114 305 [60.9%]); adolescent (13-18 years); recently diagnosed with comorbid mental health conditions, with the most frequent being anxiety ; and recent admission for inpatient mental health treatment . Antipsychotic initiation was associated with self-harm and/or suicidal ideation , ODD diagnosis , substance use disorder , and inpatient mental health care  in the preceding 6 months .Among youths who initiated antipsychotic medications, 47.9%  did not receive a stimulant prescription between their ADHD diagnosis and antipsychotic initiation. Approximately half of the youths  who were treated with antipsychotics were prescribed 1 stimulant and 8.4%  were prescribed methylphenidate or a methylphenidate derivative and an amphetamine derivative before antipsychotic initiation .By the end of the follow-up year, 2565 of 19 990 youths  treated with antipsychotics had received either a diagnosis for which antipsychotics are FDA indicated in youths  or had received a clinical diagnosis for which there is evidence of antipsychotic efficacy in youths  .A total of 432 of 10 125 (4.3%) very young children (aged 3-5 years) with ADHD were treated with an antipsychotic medication. Compared with those who were not treated with an antipsychotic, those who received an antipsychotic were more likely to have been diagnosed with a neurodevelopment disorder , received inpatient mental health care , and received care from a psychiatrist  . The likThe eFigure in the Antipsychotic medications were prescribed for 2.6% of commercially insured youths in the year following a new clinical diagnosis of ADHD without a recent diagnosis that has an FDA indication for antipsychotic treatment. Factors for antipsychotic treatment included a wide range of comorbid psychiatric diagnoses. Conduct disorder and ODD were factors associated with antipsychotic treatment. However, only approximately half of the antipsychotic treated patients received diagnoses  with evidence of clinical benefits from antipsychotics during the pre- or post-ADHD diagnosis period. These data reveal the extent to which antipsychotics are prescribed to young people with ADHD and raise concerns regarding potential non–evidence-based antipsychotic use and underuse of stimulant medications.31 Despite public policies and interventions aimed at reducing off-label antipsychotic medication prescriptions for youths,33 young people diagnosed with ADHD appear to have an increased likelihood of filling antipsychotic prescriptions. Professional statements and practice guidelines released by the American Psychiatric Association and the American Academy of Child and Adolescent Psychiatry have encouraged clinicians to reduce use of antipsychotic medications in youths without an approved or evidence-supported indication.34 Although these efforts may have reduced off-label prescription of antipsychotic medications to young people overall, their use among young people with ADHD remains significant.The percentage of youths with a new ADHD diagnosis who were treated with an antipsychotic without an FDA indication (2.6%) was greater than the overall annual prevalence of antipsychotic treatment among youths in the general population (0.6%).2 This pattern may be associated with the use of antipsychotics in the management of impulsive and aggressive behaviors in youths with ADHD.20 After adolescence, decreases in the fraction of antipsychotic prescribing for young adults with ADHD have previously been described and are consistent with treatment of conduct problems that peak in adolescence.35 This decline is potentially associated with suppression of aggressive behaviors and improved impulse control in late adolescence from maturation of prefrontal gray matter and proliferation of white matter tracts.37The demographic profile of antipsychotic prescribing among youths with ADHD diagnoses is consistent with patterns observed in the general population of young people. Within the general population, the likelihood of antipsychotic use is also higher among male than female individuals and adolescents than children.18 A possible explanation of a flat curve is that symptoms are being addressed through the availability of nonpharmacologic, school-based interventions available to elementary school children.38 However, because these interventions are not recorded through insurance databases, we are unable to measure this.The flattest antipsychotic initiation curve occurs in school-aged youths (6-12 years). Based on new incidence, this is the age group at highest risk for initial ADHD presentations and when most medications are first used.41 Although antipsychotics could be prescribed because of incomplete response to other treatments, many of these conditions do not have empirical evidence supporting antipsychotic treatment. Outside of FDA indications, only ODD, CD, and aggression in ADHD have clinical experimental evidence to support the use of antipsychotics and only approximately half of the cohort of youths with ADHD who received antipsychotics had 1 or more of these clinical diagnoses.27Among youths with ADHD, several clinically diagnosed mental disorder comorbidities have been associated with an elevated likelihood for antipsychotic treatment. In youths with ADHD, many of these comorbidities are related to poorer response to stimulant treatment and adverse outcomes.44 Young people whose symptoms have led to hospitalization likely have more complex clinical presentations than their peers who are not receiving antipsychotics. However, the effectiveness of antipsychotics for the treatment of severe uncomplicated ADHD has not been established. The youths with ADHD who were prescribed an antipsychotic but lacked an ODD or CD diagnosis could also have aggression or represent poor community pharmacologic management of ADHD.Recent inpatient mental health care was associated with antipsychotic treatment. Symptom severity thresholds for receiving acute inpatient mental health care are often high, particularly for severe ADHD.46 Furthermore, although nonpharmacologic treatment is generally regarded as first line in this age group, evidence-based psychosocial interventions, such as parenting training and parent-child interaction therapy, are not widely available.47Antipsychotic treatment was proportionately highest among very young children (4.3%). This group accounts for approximately a quarter of a percent of the total ADHD cohort, with very young children accounting for a small percentage of ADHD-treated youths. These children were more likely to have neurodevelopmental disorders than their age-matched peers who were not treated with antipsychotic medications and received high rates of inpatient mental health care. Antipsychotic treatment may be reserved for children with greater symptom severity. While ADHD uncommonly presents in very young children, those with ADHD tend to have severe symptoms and relatively poor response rates to stimulants.48 This treatment pattern raises concerns that some youths with ADHD may be treated with antipsychotics prematurely, before receiving trials of adequate dose and duration of both classes of stimulants, potentially unnecessarily exposing them to antipsychotic treatment.Fewer than half of the youths received a stimulant before their antipsychotic and fewer than 1 in 10 received a methylphenidate and amphetamine derivative. Antipsychotics are only potentially indicated in youths with ADHD after treatment trials of both methylphenidate and mixed amphetamine salts.27 However, nearly two-thirds of the antipsychotic-treated sample initially were treated with other antipsychotics that either have negative trials or lack trials to support their use in ADHD.27Risperidone was the most commonly first prescribed antipsychotic for youths with ADHD. This practice is consistent with recommendations. Risperidone has the strongest evidence base for off-label use in youths, particularly in ODD, CD, and aggression.50 Consistent with this hypothesis, antipsychotic-treated youths with ADHD had clinical characteristics commonly associated with aggression in ADHD, such as inpatient hospitalization and a higher prevalence of comorbid disorders.53 However, few youths treated with antipsychotics with ADHD received the evidence-indicated trials of 2 stimulants before an antipsychotic.A wide range of clinical characteristics, including mental disorder comorbidities, and inpatient mental health care are associated with antipsychotic treatment in youths with ADHD. Aggression, which is common in ADHD and not always responsive to stimulant medications, has been hypothesized to account for much of the off-label use of antipsychotics in youths with ADHD.15 including telephone consultations with psychiatrists, letters to prescribers, and age-related prior authorization policies.15 A greater understanding of the clinical rationale and timing of antipsychotic treatment of youths with ADHD might help to guide more clinically sensitive policies to regulate antipsychotic use.Current therapy management efforts in both private and publicly insured populations have been focused on curbing antipsychotic use in youths with less attention devoted to the clinical rationale for use. These policies have been particularly widely applied to Medicaid populations,55 Yet some aspects of our sample resemble those in antipsychotic-treated Medicaid youths. For example, similar to analyses of Medicaid samples, our sample was predominantly male and had similar rates of CD, anxiety, and depression diagnoses.57This analysis was limited to commercially insured children. Much of the prior work on antipsychotic use in children has focused on Medicaid populations. Important socioeconomic and health differences exist between commercially insured and Medicaid-insured populations.57 Although Medicaid programs have implemented management programs to limit antipsychotic use, few commercial insurance programs have followed suit. Nevertheless, these programs, along with medical society guidelines,48 may be associated with diagnostic and prescribing practices for commercially insured patients. Fourth, several potentially important factors to understanding antipsychotic treatment patterns, such as race/ethnicity, family circumstances, and home environment, were unavailable in the data set. Furthermore, we were unable to measure symptoms that might have provided a clinical rationale, such as severe aggression, for antipsychotic treatment. In addition, data on medication use were based on filled prescriptions rather than observed medication consumption.This analysis has several limitations. First, diagnoses were based on clinical judgment—not structured interviews. Second, we were unable to examine antipsychotic treatment following the first lifetime diagnosis of ADHD. Patterns of antipsychotic treatment may be different following initial and new episodes of clinical ADHD diagnosis. Third, we examined commercially insured individuals; different results might be obtained from Medicaid beneficiaries in whom antipsychotic treatment is more common.11 Our results suggest associations between comorbid psychiatric diagnoses and the use of antipsychotic treatment in youths with ADHD. While some of these young people were diagnosed with conditions for which antipsychotics have some evidence of clinical effectiveness, many others were not. In view of the serious safety risks posed by antipsychotic treatment of young people, these patterns highlight the importance of remaining vigilant concerning antipsychotic medication prescribing patterns in the community treatment of ADHD.Among diagnostic groups in young people, ADHD may account for the largest share of antipsychotic treatment.


Unilateral neglect is a poststroke disorder that impacts negatively on functional outcome and lacks established, effective treatment. This multicomponent syndrome is characterised by a directional bias of attention away from contralesional space, together with impairments in several cognitive domains, including sustained attention and spatial working memory. This study aimed to test the effects of guanfacine, a noradrenergic alpha-2A agonist, on ameliorating aspects of neglect.Thirteen right hemisphere stroke patients with leftward neglect were included in a randomised, double-blind, placebo-controlled proof-of-concept crossover study that examined the effects of a single dose of guanfacine. Patients were tested on a computerised, time-limited cancellation paradigm, as well as tasks that independently assessed sustained attention and spatial working memory.On guanfacine, there was a statistically significant improvement in the total number of targets found on the cancellation task when compared with placebo . However, there was no evidence of a change in neglect patients’ directional attention bias. Furthermore, Bayesian statistical analysis revealed reliable evidence against any effects of guanfacine on search organisation and performance on our sustained attention and spatial working memory tasks.Guanfacine improves search in neglect by boosting the number of targets found but had no effects on directional bias or search organisation, nor did it improve sustained attention or working memory on independent tasks. Further work is necessary to determine whether longer term treatment with guanfacine may be effective for some neglect patients and whether it affects functional outcome measures.NCT00955253. Up to 80% of patients suffering from right hemisphere stroke exhibit features of unilateral neglect,There is substantial evidence linking vigilance to noradrenergic pathways.The previous study of guanfacine in neglectTo further explore the possible beneficial effects of noradrenergic stimulation in neglect, we conducted a larger proof-of-concept, randomised, double-blind, placebo-controlled crossover investigation of the effects of a single dose of guanfacine. In this within-participant design, participants were assessed over five consecutive days. To investigate spatial exploration, we employed an invisible cancellation task. In contrast to the previous study of guanfacine in neglect, we set a fixed time limit to rule out the possibility that patients find more targets due to extended search durations. In addition, independent tests of sustained attention and working memory were administered. A secondary objective was to observe whether guanfacine might improve neglect only in patients without significant damage to prefrontal cortex.Stroke patients with evidence of neglect on bedside testing were recruited from Imperial College Healthcare NHS Trust, the National Hospital for Neurology and Neurosurgery and Northwick Park Hospital. Patients were recruited during their inpatient rehabilitation or via the outpatient clinic. As in the study by Gorgoraptis and colleaguesExclusion criteria were concomitant illnesses that might affect interpretation of findings, labile blood pressure following stroke, systolic blood pressure <100 mm Hg or diastolic blood pressure <70 mm Hg, initiation of new antihypertensive medication within 3 weeks before testing, hepatic or renal dysfunction, treatment with neuroleptic medication, diagnosis of brain tumour, weight <55 kg, pregnancy or breast feeding, severe coronary insufficiency or myocardial infarction in the 6 months prior to testing, dysphasia, dementia or any other cognitive or physical impairment that would prevent a patient from providing consent or performing standard clinical tests for neglect.Recruitment was terminated after expiry of the drug and placebo supply, at which point a total of 13 patients had been recruited, 10 of whom had frontal cortical damage of varying severity  and 3 ofA stratified crossover protocol was employed, allowing for within-patient comparison between treatment and placebo, while removing between-patient variability. Oral guanfacine  and bias (criterion (c)) in terms of signal-detection theory.A shortened version of a vertical  spatial working memory task that has previously been used to assess neglect patientsBaseline performance was determined for each patient by averaging scores on days 1, 3 and 5, as well as the preadministration sessions on days 2 and 4. Group averages and differences were computed between treatment type  across individuals.To test whether there was a systematic effect of treatment type, we employed repeated-measures analyses of variance (ANOVAs). Drug was a factor in all analyses, with three levels: baseline, guanfacine and placebo. For the sustained attention task, time bins were included as an additional factor, with five levels: one for each time bin. This allowed us to assess performance over the course of the experiment. For the spatial working memory task, sequence length was included as an additional factor, with five levels: one for each sequence length.10). This is the probability of the alternative hypothesis (‘guanfacine changes patients’ performance’) divided by the probability of the null hypothesis (‘guanfacine does not change patients’ performance’). In essence, the Bayes factor is a quantification of how much confidence one can have in either hypothesis. We interpret our results following the guidelines of Jeffreys,Traditional (frequentist) repeated-measures ANOVAs produce P values, which inform us whether the null hypothesis should be rejected or not but not how well it is supported by the data.Data were handled in custom Python2=0.26, BF10=4.926. Post hoc paired-sampled t-tests revealed a significant improvement in the total number of targets found between baseline  and guanfacine , t(12)=−2.21, P=0.047, Cohen’s d=−0.613, BF10=1.687, as well as between the placebo  and guanfacine conditions, t(12)=−2.93, P=0.013, Cohen’s d=−0.813, BF10=4.806. Importantly, by contrast, there was no significant difference between baseline and placebo conditions, t(12)=1.52, P=0.154, BF10=0.704. These results provide moderate evidence of a significant effect of drug on search performance with the total number of targets found increasing by, on average, five on guanfacine compared with placebo  cancelled on guanfacine versus placebo, F=5.66, P=0.010, ω placebo .Qualitatively, there did not seem to be a difference between the patients with (grey lines in figures) and without (orange lines) frontal involvement on any of the metrics reported here and in the supplementary materials.10=0.231, and no main effect of drug on the centre of cancellation  and guanfacine  conditions revealed no difference between the two, t(12) = 0.03, P=0.976, BF10=0.278.Independent repeated-measures ANOVAs revealed no main effect of drug on the difference between the cancellations on the right and left sides of the cancellation task , F=0.96, P=0.371, BF10=0.100, nor a main effect of time, F=0.20, P=0.939, BF10=0.022. There was also no interaction between drug and time, F=0.72, P=0.673. These results provide moderate to strong evidence that there was no effect of drug or time on reaction time variability in the sustained attention task.A repeated-measures ANOVA revealed no main effect of drug on reaction time variability online . FGreenhSignal-detection variables were also computed and analysed and are reported in the supplementary materials.10=0.082, a main effect of sequence length, FGreenhouse-Geisser=6.39, P=0.003, ω2=0.30, BF10=28 919.401 and no interaction effect, F=1.42, P=0.200. These results provide strong evidence that there was no effect of drug on response accuracy and decisive evidence that there was an effect of sequence length on response accuracy .A repeated-measures ANOVA revealed no main effect of drug on response accuracy, F=0.84, P=0.446, BF10 for sequence lengths 1, 3, 4 and 5 ranged between 0.358 and 0.554, and BF10 for sequence length 2 was 1.533) nor any difference between placebo and guanfacine for each sequence length . For sequence lengths 1–4, there was no difference between baseline and placebo . In sum, there was a reliable absence of an effect of treatment type on accuracy in the spatial working memory task.Post hoc paired-sampled t-tests indicated that there was no difference between baseline and guanfacine for each sequence length  interventions might prove more efficacious than a single therapy.Neglect is considered to be a heterogeneous syndrome, consisting of a core directional bias and additional cognitive deficits that increase clinical severity.We conducted a randomised, double-blind, placebo-controlled, crossover study examining the effects of a single 2 mg dose of guanfacine, a noradrenergic alpha-2A agonist. Thirteen stroke patients with unilateral neglect were tested on an ‘invisible’ cancellation paradigm, as well as sustained attention and spatial working memory tasks. A significant improvement in the total number of targets patients found on the cancellation task was observed on guanfacine versus placebo, but there was no evidence for or against beneficial effects of guanfacine on directional bias. Guanfacine did not improve search organisation and did not affect performance on sustained attention or spatial working memory tasks. Further work is now necessary to determine whether regular treatment with guanfacine has beneficial effects on neglect and activities of daily living.


The study of Attention Deficit Hyperactivity Disorder (ADHD) addresses variables related to three core symptoms: inattention, hyperactivity, and impulsivity. However, it has been suggested that in recent years emotional difficulties and subsequent social challenges have not received sufficient attention. This study had two objectives: (1) to compare the performance of participants (age range: 8–14 years) on facial emotion recognition tasks using the Affect Recognition subtest of the Children Neuropsychological Battery II; and (2) to assess the perceptions of family members in relation to variables associated with emotional problems, difficulty in regulating emotions, and anger management using the Spanish Assessment System for Children and Adolescents. Assessments were conducted before and after applying an emotion regulation intervention designed for this study. Following the intervention, there was a significant decrease in scores associated with emotional regulation, and an improvement in the identification of affect on facial recognition tasks. The results suggest that despite ADHD children and adolescents having social and emotional deficits secondary to the core symptom triad, emotional regulation in this group can be improved by the application of socio-emotional intervention programs. Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders in childhood and adolescence. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5)  defines The syndrome tends to persist into adulthood in more than half of the cases , hence tThese children and adolescents have an interaction pattern characterized by low levels of self-control and high levels of disruptive, aggressive, or oppositional behavior . In geneAs early as pre-school, some parents report that their children experience difficulties with emotions, behavior, and relating to peers . TherefoThe concept of emotion refers to innate and involuntary psychophysiological mechanisms that arise as a consequence of environmental stimuli and that generate avoidance or approach reactions. Environmental stimuli are detected by the sensory cortex and processed in the limbic system by the amygdala, which is responsible for activating a physical response and for altering cognitive processing according to the emotion that is appropriate to the given stimuli. Physical reactions can be associated with the specific object that caused them, forming a propositional representation of the relationship between the emotional state and the stimulus that triggered it. Given the repeated experience of such situations and the capacity of the brain for learning, this representation would be of assistance in predicting the presence of this stimulus in a given setting and in anticipating future responses .Several authors have emphasized the adaptive value of emotions e.g., . EmotionThus, adequate emotion self-regulation increases the opportunities for ADHD patients to obtain and integrate the socio-cognitive skills needed to successfully meet the demands of their environment during childhood, adolescence, and adulthood.This aspect is particularly true in relation to adults with ADHD because the labor market has recently undergone a variety of changes with little regard for the personal needs of workers and their wellbeing .There is no well-established body of models and theories that explains the origin of emotional deficits in ADHD and their associations with EF. In fact, there is little research on emotional processing and regulation in children and adults with ADHD. In general, the limited research available has taken two approaches. One line of research has investigated whether emotional impairment in ADHD is a primary or secondary deficit. Such studies have addressed the relationship between emotions, feelings, and the ability of individuals to interact appropriately in social situations. The second line has suggested that issues in emotional identification and expression are secondary to executive deficits in ADHD individuals.Several studies have suggested that ADHD individuals have emotional reactivity traits as well as difficulties in emotional control or regulation . EmotionOn the other hand, traditional theories of ADHD  have sugAlthough “emotional arousal” is mainly regulated by the ascending reticular activating system, which connects the reticular formation and cortex, “emotional arousal” can also affect the activity of higher cognitive processes . TherefoSimilarly, the DSM-IV describes emotional impairments in ADHD as secondary to or associated with executive deficits, because they manifest as a consequence of the core symptom triad. A behavioral study  suggesteThese impairments not only negatively impact emotions, but also reduce the patient’s capacity to adapt to the social setting. Generally, children and teenagers with ADHD experience difficulties other than the core symptom triad. Classmates of ADHD children complain of their interpersonal difficulties with them, and typically state that they are annoying and noisy, talk too much, interrupt conversations, do not respect game rules, or very easily become angry . In addiDeficits in social and emotional skills are probably due to dysfunctions in the neurotransmitter pathways involved in emotional and motivation processes. These types of dysfunction appear to be one of the main causes of the disorder itself . ChangesCurrently, ADHD is included in the diagnostic classifications of the International Classification of Diseases, tenth edition ICD-10,  and the The subsequent intervention phase involves treatment procedures. These have proliferated in recent years, and some of them are based on excessive claims that lack scientific rigor. At present, such procedures can be classified into pharmacological, behavioral, cognitive-behavioral, and psychoeducational treatments. These treatments are sometimes administered alone, but typically two or more treatments are used in combination. The effectiveness of each type of treatment varies depending on the aspects of the disorder being addressed. However, there is a consensus among researchers and professional therapists that the most effective approach is the use of combined pharmacological and psychoeducational treatment. Some researchers have suggested that this combination includes more variables, while professional therapists have suggested that it can be applied to a variety of settings  .Combined pharmacological and psychoeducational treatment significantly reduces the core symptoms of the disorder and improves self-control, thus reducing problems associated with learning and with adapting to the environment . This liThe present study included a sample of 64 children and adolescents diagnosed with ADHD (age range: 8–14 years). The study had two objectives: (1) to compare their performance on facial emotion recognition tasks before and after an intervention specifically designed to improve affect recognition (AR) and emotional regulation; and (2) to compare the perceptions of 110 participating parents in relation to variables associated with emotional problems, difficulty in regulating emotions, and anger management before and after training with their children.The study was conducted during the 2015–2016 school year by the HUM-347 research group from the Department of Developmental and Educational Psychology at the University of Malaga (Spain) and the team from the Centro de Diagnóstico y Tratamiento de TDAH [ADHD Diagnosis and Treatment Center (ADHD-DTC)] in Malaga. The ADHD-DTC is a private therapeutic center managed by a multidisciplinary team that includes a neuropediatrician, two psychologists, and three educational psychologists. The center mainly treats individuals diagnosed with ADHD, but it also treats individuals with learning difficulties and behavior disorders. All clients are drawn from Andalusia, Ceuta, and Melilla (Spain).The study design was quasi-experimental. Partially repeated measures (A-B-A) were obtained before and after conducting an intervention that was specifically designed for this study. In the pretest phase, clients made their first contact with the TDAH-CDT and the research project was described to them. Recruitment was conducted by e-mail or telephone.The final sample was selected according to the following inclusion criteria:○Having a diagnosis of combined-type ADHD, predominantly inattentive ADHD, or predominantly hyperactive/impulsive ADHD. Symptoms must have been present for more than 6 months and in at least two different settings.○Clear evidence of a clinically significant deterioration in social and/or emotional activity.○No signs of schizophrenia, psychotic disorder, or any other mental disorder. No signs of intellectual disability and no sensory or motor deficits.○An IQ score equal to or more than 80 on the Wechsler Intelligence Scale for Children-Revised (WISC-R) or on the Wechsler Intelligence Scale for Children-IV (WISC-IV).○Being between 7 and 14 years old.○No previous or current treatment specific to the social and emotional domains.The initial sample comprised 130 children and adolescents, of which 64  met the inclusion criteria. The study included 110 parents, who signed the informed consent form and were briefed on the different phases and characteristics of the study. The ADHD participants and their families were tested in the pretest and posttest phases using two instruments (see below for details).We designed an emotion regulation intervention (ERI) that included AR and regulation tasks. Particular attention was given to negative primary emotions, such as rage, sadness, and fear. This intervention mainly addressed the acquisition and development of emotional identification, expression, and regulation techniques. Some activities were based on the recognition of primary emotions through faces, the analysis of social situations with emotional content, and the acquisition of cognitive strategies to express emotions in an appropriate manner while taking the setting into account. The intervention also included strategies to control and regulate negative emotions . After each session, parents received advice on how to achieve the goals pursued in each session, and were given guidelines on how to help their children apply what they had learned to other settings.The ERI was based on our review of In order to develop the overall design of the intervention, we also reviewed classic pyschoeducational intervention programs for normotypical individuals and ADHD patients .Different activities were designed for two age ranges (8–9 years and 10–14 years). Each activity had the same goal, but the presentation format and the level of difficulty varied according to age range. The intervention consisted of 10 sessions. The first and last sessions were used to administer the pretest and posttest assessments, and thus evaluate the efficacy of treatment. The intervention comprised cognitive, behavioral, and emotional dimensions. Each session comprised 60 min of working with the children, and at least 15 to 20 min of working with their parents. The children were taught specific strategies and skills, and how and when to use them. Information was provided to parents on what the children had learned in each session, guidelines were established, and questions and concerns were solved. Finally, the parents were given advice on how to reinforce at home the skills the children had learnt.The intervention was administered by dividing the ADHD group into 15 groups of three to five participants. The groups were formed according to age range and availability . There were 6 groups for ages 8 to 9 years , 4 groups for ages 10 to 11 years , and 5 groups for ages 12 to 14 years .Pretest and posttest data were collected using the following instruments:•The AR subtest of the NEPSY-II Neuropsychological Battery  . This in1. Direct scores and T-scores were used to obtain a profile for each subject and family.The Emotional Problems, Emotional Regulation Problems, and Anger Control Problems subtests of the Spanish Assessment System for Children and Adolescents (SENA) . This scWe chose the general sample  from the different normative samples available to evaluate the results of the participants. High scores on these variables indicate that the participants have emotional, emotion regulation, and anger management issues.t-test.All data were analyzed using the SPSS Statistical software package, version 23. The efficacy of the ERI was analyzed by comparing the pretest and posttest mean scores of the psychometric tests and the self-report questionnaires using a paired sample t(63) = -3.83; P = 0.00; see t(63) = 2.63; P = 0.01] in emotional problems. The parents reported that their children had fewer emotional problems after the intervention  and posttest phase (25.85) [tion see .t(63) = 4.11 and P = 0.00]. The parents reported that their children had less difficulty in emotional regulation after the intervention (see t(63) = 2.36 and P = 0.02; see Significant differences were found between the pretest mean (66.15) and posttest mean (61.07) in emotional regulation .In relation to AR, significant differences were found between the means of the pretest phase (23.15) and posttest phase (25.85)  in emotional problems. The parents reported that their children had fewer emotional problems after the intervention.Significant differences were found between the results of the pretest and posttest phases [Several authors  have rept(63) = 4.11 and P = 0.00]. The parents reported that their children had less difficulty in emotional regulation after the intervention. Similarly, significant differences were also found between the pretest mean (66.56) and posttest mean (63.01) in anger management [t(63) = 2.36 and P = 0.02].Significant differences were found between the pretest mean (66.15) and posttest mean (61.07) in emotional regulation [Other studies  have higOur results are consistent with those of other studies  that hadBanaschewski and other authors have suggested that the severity of ADHD symptoms may statistically mediate the relationship between neuropsychological dysfunctions and symptoms of emotional lability . HoweverResearch has suggested that specific interventions on cognitive variables, significantly reduces symptoms and improves the interactions between children and adolescents and their environment, particularly when the intervention includes combined treatment and family participation . The resIn recent decades, ADHD has become one of the neurodevelopmental disorders receiving more attention from researchers and professionals working in psychology, education, and medicine. Advances in this area have led to the development of new explanatory neuropsychological models of the disorder, consensus guidelines for its detection and diagnosis, and pharmacological and psychoeducational treatment strategies increasingly adapted to the needs of ADHD individuals.Within this setting, genetic factors that modulate biochemical neurotransmission processes that interfere with the correct development and functioning of the ES have been found to be relevant. However, research suggests that most ADHD individuals have emotional control and regulation problems, leading to difficulties in social adaptation. These problems increase with age and persist despite the application of interventions to reduce the core symptom triad.The scientific literature is replete with descriptions of these difficulties, drawing a portrait of individuals who do not understand their own emotions or who are unable to control and regulate them, do not understand the emotions of other people, and even have problems recognizing them correctly. As a consequence, such individuals exhibit maladaptive social behavior .One of the motivations for this study was precisely the lack of attention given to the study and creation of treatment programs and strategies to modify inappropriate social interaction patterns, which derive from impaired emotional, cognitive, and socio-communicative processing. These impairments lead to peer rejection and increase the risk of experiencing emotional imbalances in childhood, adolescence, and adult life.The results show that the identification of emotional states in others and the application of negative emotional control strategies, as well as emotional regulation problems, can be improved in ADHD individuals. These improvements can be achieved if it is assumed that one of the primordial functions of the ES is the control and regulation of emotions, and that this system plays a leading role in the development of feelings and the management of social skills. Treatment should be applied using combined programs in which participants are given strategies and skills to decrease the impact of ADHD deficits. If possible, interventions should be implemented in young ADHD individuals to prevent disruptive behavior becoming habitual and the development of negative thoughts about themselves, which may lead to feelings of low self-esteem.In summary, the difficulties that ADHD individuals experience when they attempt to identify, express, and regulate emotions are due to the delayed development of emotional processing skills caused by the executive deficits that characterize the disorder. These difficulties could be improved by the application of an early multidimensional intervention that includes emotional variables and is combined with pharmacological and psychoeducational treatment.Future lines of research could extend the focus of the present study and address some of the limitations of our study. Firstly, it would be of interest to compare the performance of ADHD participants and a control group of normotypical participants. Our study addressed the improvement of deficits related to ES functioning in ADHD individuals. However, it would be of interest to compare our results with those of a non-ADHD population of the same age and sex. Furthermore, we would compare variables as subjective perception of time, well-being and happiness . Such reThe inclusion and exclusion criteria used in this study were established before the sample was selected in order to control for as many confounding variables as possible . In subsequent studies, it would be of interest to begin the selection process at the assessment stage, leading to better control of the confounding variables. It could also be of interest to include groups with comorbid disorders , such that their performance could be compared and phenotypes established based on diagnostic labels .In summary, the main findings of this study show that emotional difficulties in individuals diagnosed with ADHD, and their resulting social challenges, are relevant issues that should receive the same level of attention as the three primary symptoms of this disorder. The present study had two aims: (1) to compare the performance of ADHD patients on facial AR tasks; and (2) to assess the perceptions of family members in relation to variables associated with emotional problems, difficulty in regulating emotions, and anger management. Assessments were conducted before and after applying an ERI specifically designed to identify and regulate emotions. Our results suggest that although children and adolescents with ADHD show social and emotional deficits secondary to the core symptom triad, emotional regulation in this group can be improved by socio-emotional intervention programs that complement classic treatment packages.This study was carried out in accordance with the recommendations of the Faculty of Educational Sciences and the Regulations of the Ethical Committee of Experimentation of the University of Malaga. In addition, it complies with the requirements of the Organic Law on Data Protection 3/2018, in force in Spain. Ethics approval was not required as per the University of Malaga’s guidelines and national regulations. Written informed consent was obtained from the parents of all participants.MS collected and processed the experimental data, performed the analysis, drafted the manuscript, designed the figures, and wrote the manuscript with support from RL and JR. RL and JR conceived the presented idea, involved in the planning, and supervised the work. EE worked out almost all of the technical details, and performed the numerical calculations for the suggested experiment.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


ADGRL3 (LPHN3), SNAP25, FGF1, DRD4, and SLC6A2 genes are associated with ADHD. We genotyped 26 SNPs harboured in genes previously reported to be associated with ADHD and evaluated their potential association in 386 individuals belonging to 113 nuclear families from a Caribbean community in Barranquilla, Colombia, using family-based association tests. SNPs rs362990-SNAP25 , rs2282794-FGF1 , rs2122642-ADGRL3 , and ADGRL3 haplotype CCC  were significantly associated with ADHD. Our results confirm the susceptibility to ADHD conferred by SNAP25, FGF1, and ADGRL3 variants in a community with a significant African American component, and provide evidence supporting the existence of specific patterns of genetic stratification underpinning the susceptibility to ADHD. Knowledge of population genetics is crucial to define risk and predict susceptibility to disease.Attention Deficit Hyperactivity Disorder (ADHD) is a highly heritable and prevalent neurodevelopmental disorder that frequently persists into adulthood. Strong evidence from genetic studies indicates that single nucleotide polymorphisms (SNPs) harboured in the  Attention deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental behavioural disorder that affects ~5% (with figures reaching 17%) of children and adolescents of different cohorts worldwide ,3,4,5,6.ADGRL3, also known as Latrophilin 3 or LPHN3; markers rs2345039, rs6551665, and rs1947274), the Synaptosomal-associated protein of molecular weight 25 kDa (SNAP25), the Fibroblast growth factor 1 (FGF1), the Solute carrier family 6  member 2 (SLC6A2), and the Dopamine receptor D4 (DRD4) genes predispose one to ADHD [Genetic factors are strongly implicated in the aetiology of ADHD, CD, ODD, and SUD ,10,11,12 to ADHD , as conf to ADHD ,19,20,21In this study, we explored the association of ADHD with SNPs within these genes in a family-based sample of 386 individuals ascertained from a community inhabiting the city of Barranquilla located in the Caribbean coast of Colombia. Barranquilla, with a population of ~2.4 million, is a cosmopolitan city that represents the confluence of many populations , Syrian–Lebanese, Sephardic Jew, German, Italian, and English communities). These communities settled in the Atlantic coast of Colombia during the last five centuries  and estaOur overarching goal was to evaluate the effect of genomic variants, already associated with ADHD, in the susceptibility to develop this condition in families ascertained from this Caribbean community and compare those with genomic variants predictors of ADHD in other Colombian communities. This will allow us to define specific biological predictors and study the role of genetic flow as a pivotal factor shaping the susceptibility to this neuropsychiatric disease.We studied 386 individuals (218 (56.5%) males and 168 (43.5%) females) from 113 nuclear families whose members were born in the Barranquilla, Colombia, metropolitan area . A totalGrupo de Neurociencias del Caribe carried out an extensive clinical, neurological, and neuropsychological evaluation to define ADHD status and the presence of other comorbidities, using a multi-stage scheme. The full evaluation protocol is described elsewhere [Grupo Neurociencias del Caribe’s website.The lsewhere . Brieflylsewhere ,32 as thlsewhere ,32,33. Tlsewhere . Persistlsewhere  and the lsewhere ,37. Initlsewhere , advertihttp://adhd.psych.ac.cn/) [Twenty-six SNPs were selected from the ADHD gene data base (.ac.cn/)  as well .ac.cn/) ,6,18,40.®DNA Purification Kit  according to the manufacturer’s protocol and stored at −80 °C. DNA concentrations were measured using a NanoDrop spectrophotometer . The integrity of DNA samples was verified via 260/280 absorbance ratios. Genotyping was performed using multiplex Sequenom® Technology on the Agena Bioscience MassARRAY® MALDI-TOF instrument at the University of Arizona Genetics Core (UAGC). Primers designed for PCR amplification and extension were prepared by the UAGC. To avoid potential biases, samples were placed randomly, and laboratory personnel were blinded to the identity and source of DNA samples.Genomic DNA was isolated from blood samples using the MasterPurep-value < 0.05/m, where m is the number of SNPs being tested  8.4.0 .SNPs with a minor allele frequency (MAF) ≥ 0.05 were classified as common and as rare otherwise . Rare SNn = 33; 29.2%), five  and six , and not only by trios , we used the family-based association test (FBAT) to study the association of SNPs and ADHD. The FBAT provides a unified framework to generalize the transmission disequilibrium test (TDT) [Given that this cohort is comprised by nuclear families of size four (st (TDT) ,47, initst (TDT) . The FBAst (TDT) ,49,50,51st (TDT) ,53. AddiThe PBAT module also performs the FBAT and haplotype tests for selected combinations of phenotypes and markers on the actual patients’ genotypes, both as a group and individually, automatically controlling the Type I error rate to adjust for multiple comparisons , and thep-value of the FBAT indicates the direction of the effect; a positive p-value indicates susceptibility to ADHD, while a negative p-value indicates a protective effect.FBATs use affected subjects as cases, and family members, parents, or siblings as “controls” . Furthermore, low genotype call rates are compensated by the existence of parents’ genotypes, and paternity and Mendelian inconsistencies are also controlled ,53. All Haplotype-based association analyses were also performed using the Parent TDT algorithm available in HaploView  includinOut of the 26 SNPs genotyped, 14 had one or more than two alleles, six had a MAF < 0.05, and six passed filters and quality control . The totSNAP25-rs362990, FGF1-rs2282794, and ADGRL3-rs2122642 reached statistically significant FBAT statistics and confer susceptibility to ADHD  model, p = 5.21 × 10−4; FGF1-rs2282794 confer susceptibility to ADHD in our cohort under three different inheritance models  within the ADGRL3 gene confers susceptibility to ADHD in our set of nuclear families  family and is expressed in key areas of the brain related to attention and activity  and to major depression  [FGF1 is associated with ADHD in this Caribbean community reinforces the importance of further studying the FGF1 gene as a novel candidate gene for ADHD [It is notable that SNPs in  isolate ,40, were cortex)  that may cortex) . The enc cortex) ,85,86. TADGRL3 is a member the latrophilin subfamily of G protein-coupled receptors and has already been implicated in ADHD susceptibility, predicting ADHD severity, disruptive behaviours comorbidity, long-term outcome, response to treatment, and SUD [ADGRL3 in shaping the hyperactive/impulsive phenotype [ and SUD ,20,21,74henotype ,88,89,90SNAP25, FGF1, and ADGRL3 genes and ADHD in this Caribbean community, which exhibits a strong genetic admixture between Aboriginal Amerindian communities with Spaniards and Africans, and later with other communities [Altogether, our results suggest an association between SNP located in the munities . Althougmunities ,92,93,94munities  of ADHD munities ,95,96, amunities ,18,97, amunities . In the munities ,101,102.