Children with attention-deficit/hyperactivity disorder (ADHD) have deficits in performance monitoring often improved with the indirect catecholamine agonist methylphenidate (MPH). We used functional magnetic resonance imaging to investigate the effects of single-dose MPH on activation of error processing brain areas in medication-naive boys with ADHD during a stop task that elicits 50% error rates.Twelve medication-naive boys with ADHD were scanned twice, under either a single clinical dose of MPH or placebo, in a randomized, double-blind design while they performed an individually adjusted tracking stop task, designed to elicit 50% failures. Brain activation was compared within patients under either drug condition. To test for potential normalization effects of MPH, brain activation in ADHD patients under either drug condition was compared with that of 13 healthy age-matched boys.During failed inhibition, boys with ADHD under placebo relative to control subjects showed reduced brain activation in performance monitoring areas of dorsomedial and left ventrolateral prefrontal cortices, thalamus, cingulate, and parietal regions. MPH, relative to placebo, upregulated activation in these brain regions within patients and normalized all activation differences between patients and control subjects. During successful inhibition, MPH normalized reduced activation observed in patients under placebo compared with control subjects in parietotemporal and cerebellar regions.MPH normalized brain dysfunction in medication-naive ADHD boys relative to control subjects in typical brain areas of performance monitoring, comprising left ventrolateral and dorsomedial frontal and parietal cortices. This could underlie the amelioration of MPH of attention and academic performance in ADHD. Attention-deficit/hyperactivity disorder (ADHD) is defined by age-inappropriate inattention, impulsiveness, and hyperactivity (DSM-IV) . ChildreIn this study, we investigated the effect of MPH on neural processes of error monitoring in medication-naive children with ADHD by use of a challenging tracking stop task, optimally suited to test for error detection networks because it ensures 50% of inhibition failures in every subject.To overcome the limitations of previous ADHD fMRI studies of inhibition of regions of interest analyses and/or a medication history in patients , we condTwelve medication-naïve, right-handed boys aged 10 to 15 years  who met clinical diagnostic criteria for the combined (inattentive/hyperactive) subtype of ADHD (DSM-IV) were recruited through clinics. Clinical diagnosis of ADHD was established through interviews with an experienced child psychiatrist (A-MM) using the standardized Maudsley Diagnostic Interview to check for presence or absence of diagnostic criteria for any mental disorder as set out by DSM-IV . ExclusiThirteen male right-handed adolescent boys in the age range of 11 to 16 years  were recruited through advertisements in the same geographic areas of South London to ensure similar socioeconomic status and were scanned once. They scored below cutoff for behavioral problems in the SDQ and had no history of psychiatric disorder.All participants were above the fifth percentile on the Raven progressive matrices performance IQ   = 2, p = .2] but did for IQ . IQ is associated with ADHD in the general population . We did not covary for IQ because when groups are not randomly selected, covarying for a variable that differs between groups violates the standard assumptions for analysis of covariance. When the covariate is intrinsic to the condition, it becomes meaningless to “adjust” group effects for differences in the covariate because it would alter the group effect in potentially problematic ways, leading to spurious results  showed no group differences between boys with and without ADHD for age  due to a significant univariate group effect in the standard deviation to go trials , which were higher in patients under either medication condition compared with control subjects (p < .05). Post hoc tests furthermore revealed a trend for MPH compared with placebo to slow down reaction times within ADHD patients to both go (p < .06) and post-error go trials (both p < .07) (A multivariate ANOVA between control subjects and ADHD patients under either drug condition showed a trend for a significant group effect .Multivariate ANOVA showed no significant group differences between control subjects and ADHD patients under either drug condition in mean or maximum rotation or translation parameters in the x, y, or z dimensions [Control subjects activated relatively large clusters in left and right inferior frontal cortex (IFC)/anterior insula, medial frontal/anterior cingulate cortex (MFC/ACC), precentral, inferior parietal, middle and superior temporal areas, posterior thalamus and caudate, parahippocampal gyri, precuneus/posterior cingulate, occipital, and cerebellar areas.Activation in ADHD patients under placebo was in MFC and superior temporal cortex reaching into anterior and posterior insula, caudate, and inferior parietal and occipital cortex.Activation in ADHD patients under MPH was in a large cluster of ACC and MFC, in left and right IFC/anterior insula, left premotor cortex, right basal ganglia, bilateral middle and superior temporal, inferior parietal and occipital areas, hippocampal gyri, posterior cingulate, precuneus, and cerebellum .Activation in healthy control boys was in a large cluster comprising left and right orbital and IFC, dorsolateral and MFC, insula, basal ganglia, hippocampus, posterior thalamic regions, pre- and postcentral gyri, inferior and superior parietal, temporal and occipital cortices, precuneus, and posterior cingulate.Activation in ADHD patients under placebo was in small clusters in right MFC, supplementary motor area (SMA), right superior temporal, postcentral, left inferior and superior parietal, and occipital cortices.Activation in ADHD patients under the MPH condition was in superior and MFC/ACC, right globus pallidus and putamen, right superior temporal and superior and inferior parietal cortex, posterior insula, and left cerebellum .MPH contrasted with placebo elicited enhanced activation in left IFC, reaching into insula and putamen; in right IFC reaching into insula, putamen, and caudate; in left medial frontal lobe; and in left inferior parietal, precuneus, and occipital regions , Table 2r = .7, p < .02) and between go reaction times and right IFC activation  and a negative correlation between response variability and right inferior parietal activation .To investigate whether brain regions that differed with MPH were associated with task performance, statistical measures of the BOLD response were extracted for each subject in each ANOVA cluster and then correlated with performance variables. There was a significant positive correlation in patients between post-error reaction times and left and right IFC activation  (including pre-SMA), right premotor, superior and inferior parietal cortices, posterior cingulate/precuneus, posterior thalamus, and bilateral inferior temporo-occipital areas .Under the MPH condition, ADHD patients did not differ from controls in any of these regions.r > .6 for all clusters, p < .05) as well as with superior parietal, occipital, and cerebellar activation . Standard deviation of reaction times was correlated with dMFC activation in controls .Post-error slowing in ADHD patients under placebo, but not in control subjects, was significantly positively correlated with activation in left IFC, premotor, dMFC, and thalamic underactivation clusters .Activation in posterior cingulate and lingual gyrus correlated significantly positively with post-error go reaction times in ADHD boys under placebo  and the between-group ANOVA (control subjects > ADHD placebo) were both significant . Three cDuring error trials, ADHD boys under placebo compared with healthy control subjects showed significant underactivation in a typical error processing and performance monitoring network comprising dMFC, left IFC, thalamus, posterior cingulate/precuneus, and inferior temporoparietal regions. Among patients, MPH compared with placebo significantly upregulated activation in overlapping medial frontal, IFC, and parietal regions as well as the lenticular nucleus. Under MPH, brain activation differences between control subjects and ADHD patients were no longer observed. Reduced fronto-thalamo-parietal activation that was normalized with MPH was, furthermore, negatively associated with faster post-error reaction times in patients, which were trendwise slowed with MPH.During successful stop trials, ADHD boys showed underactivation in a right hemispheric network of medial temporal and inferior parietal brain regions and, at a more lenient threshold, in small clusters of bilateral IFC, thalamus, and pre-SMA. Although within-patient comparison between MPH and placebo did not show significant activation differences, all underactivations in patients relative to control subjects under placebo were normalized with a single dose of MPH.The dMFC, comprising Brodmann areas 8, 6, and 32, including pre-SMA and ACC, is a typical region of error processing and performance monitoring in adults  and chilActivation in dMFC during errors triggers additional activation in functionally interconnected left IFC, as well as striatal, premotor, and parietal components of the error monitoring system, leading to post-error performance adjustments . IFC undPosterior thalamic regions have been associated both with motor response inhibition  and perfThe fact that lower dMFC, IFC, and thalamic activation in ADHD patients was associated with faster post-error slowing, both of which were enhanced by MPH, reinforces the role of this network for abnormal error monitoring in ADHD. Posterior cingulate and precuneus are connected with MFC and parietal areas and form part of the performance monitoring network , mediatiNormalization with MPH of reduced activation in typical frontoparietal regions of saliency processing and performance monitoring is consistent with the dopamine-deficiency hypothesis of ADHD given that dopamine agonists enhance stimulus salience . It is aDuring successful stop trials, MPH also normalized underactivation in the cerebellum, which, together with subthalamic nucleus, caudate, and IFG, forms a neurofunctional network of motor response inhibition . These fWithin patients, MPH also enhanced activation of caudate and putamen. This is in line with previous fMRI findings of caudate upregulation in ADHD patients after acute and chronic doses of MPH during inhibition and attention tasks  and is lThe findings of more pronounced normalization effects of MPH on abnormal performance monitoring than inhibition networks could suggest that MPH enhances generic attention and performance monitoring functions more than inhibitory capacity. This would be in line with the behavioral effect of MPH of modulating go and post-error reaction times, but not inhibition speed, which, furthermore were correlated with the reduced frontothalamic error-processing activation that was normalized with MPH. Relative to control subjects, patients only significantly differed in intrasubject response variability. Small subject numbers, a relatively older child group, and fMRI task design restrictions may have been responsible for minor behavior differences. The findings of brain dysfunctions in boys with ADHD and their normalization under the clinical dose of MPH despite minor performance differences and only trend-level improvements with MPH show that brain activation is more sensitive than performance to detect both abnormalities and pharmacologic effects. This is in line with previous findings of marked brain dysfunctions in ADHD adolescents despite no stop task impairment  and highMPH prevents the reuptake of catecholamines from the synaptic cleft by blocking dopamine and norepinephrine transporters (DAT/NET) , with hiA limitation of the study is that patients were tested twice, whereas control subjects were only scanned once, for ethical and financial reasons. Practice effects, however, were overcome by the counterbalanced design. Another limitation is the relatively small sample size. Minimum numbers of 15 to 20 participants have been suggested for fMRI studies . RepeateTo our knowledge, this is the first study to show that a single dose of MPH in ADHD upregulates and normalizes the underfunctioning of dMFC, left IFC, posterior cingulate, and parietal regions that in concert play an important role in error processing. The normalization findings of these key regions of both performance monitoring and ADHD dysfunction reinforce the association between dopaminergic neurotransmission abnormalities, ADHD, and poor performance monitoring and may underlie the behavioral effects of improving attention and school performance in boys with ADHD.


To investigate the effects of social-skills training and parental training programme for children with attention deficit hyperactivity disorder (ADHD).We conducted a randomized two-armed, parallel group, assessor-blinded superiority trial consisting of social-skills training plus parental training and standard treatment versus standard treatment alone. A sample size calculation showed at least 52 children should be included for the trial with follow up three and six months after randomization. The primary outcome measure was ADHD symptoms and secondary outcomes were social skills and emotional competences.2) of ADHD symptoms (p = 0.40), social skills (p = 0.80), and emotional competences (p = 0.14) were not significantly influenced by the intervention.children  with ADHD were randomized, 28 to the experimental group and 27 to the control group. Mixed-model analyses with repeated measures showed that the time course (y  =  a + bt + ctSocial skills training plus parental training did not show any significant benefit for children with attention deficit hyperactivity disorder when compared with standard treatment. More and larger randomized trials are needed.NCT00937469ClinicalTrials.gov  Attention-deficit hyperactivity disorder (ADHD) affects 3% to 5% of all children Recently, we conducted a Cochrane systematic review of randomized clinical trials to investigate the effect of social skills training for children with ADHD. Our review showed no statistically significant treatment effects either on social skills competences  , on general behaviour  , or on ADHD symptoms  . Because of the high risk of bias (systematic errors) in all the included trials and insufficient power , these findings are inconclusive. All the included trials had no blinding of outcome assessment and more than half of the trials had high risk of bias regarding generation of allocation sequence and allocation concealment which makes the results questionable and inconclusive. Our review suggests that there is little evidence to support or refute social skills training for adolescents with ADHD. Therefore, there is a need for more trials, with low risk of bias and with a sufficient number of participants, investigating the efficacy of social skills training versus no training for both children and adolescents Some studies suggest a possible connection between insecure attachment patterns and ADHD, and the specific attachment style has a prognostic influence Previously we have described the design and plan for the analysis of the SOSTRA trial The inclusion period for the trial was from August 2009 to January 2011.The children were suspected to have an attention deficit hyperactivity disorder and were referred to the Child Psychiatric Clinics in Holbaek or Roskilde. They were screened according to the following inclusion criteria: ADHD diagnosis according to the Diagnostic and Statistical Manual of Mental Disorders , 8 years to 12 years at the time of the start of assessment, and parents willing to take part in the trial and giving consent for medical treatment of the child as well as to participation of the child in the trial. Exclusion criteria were: schizophrenia or all the autism diagnoses according to DSM IV, violent and criminal children, both verbal and nonverbal intelligence quotient (IQ) below 80, previously medicated for ADHD, and resistance against participating.The children were screened at entry by the The Schedule for Affective Disorders and Schizophrenia for School-aged Children (K-SADS). This semi-structured interview includes algorithms from the DSM-IV in children and adolescents All of the children were tested using the Children Attachment Interview (CAI) The outcomes measured at three months and six months after randomization included indexes from the Conners 3 and the Conners Comprehensive Behaviour Rating Scale (CBRS) rating scales. The primary outcome was: ‘hyperactivity/impulsitivity’. The secondary outcomes were: ‘social problems’; ‘peer relations’; ‘aggressive behaviour’; ‘emotional distress’; ‘executive functioning’; and ‘academic performances’ The Copenhagen Trial Unit (CTU) conducted central randomization with computer generated, permuted randomization sequences in blocks of four with an allocation ratio of 1:1 stratified for sex and comorbidity. The block size was unknown to the investigators. A research secretary randomized the patient by calling the CTU providing a personal pin code, patient number, and information on the stratification variables.The interventions given were not ‘blind’ to participants, parents, treating physicians, or personnel in the Child Psychiatric Clinic in Holbaek. However, the outcome assessors of the primary and secondary outcomes (the teachers) were kept blinded of the allocated intervention. The involved parties were also instructed not to inform the assessors of the intervention allocated. To secure integrity, the principal investigator hid all data that could be used to identify the patient’s allocation before data entry. Blinded data were then handed over to the CTU, which was in charge of data entry and statistical analyses. Standardized procedures including double data entry were assured.www.clincal trials.gov NCT00937469.Participants were informed of the trial in writing and orally; written informed consent was obtained from the participant’s principal caregiver. There were no apparent ethical problems since all participants were offered medical treatment, and there were no known disadvantages of social-skills training; nevertheless, any adverse events of the intervention were reported. The trial obtained approval from the Regional Ethics Committee of Zealand (SJ-85), was registered at the Danish Data Protection Agency DO50892, and registered at The standard treatment offered to both the experimental group and the control group encompassed the normal practice regarding ADHD patients at the Child Psychiatric Clinic in Holbaek. After assessment and confirmation of the ADHD diagnosis, the family was offered medical treatment for the child following a medication protocol. The children had never previously received medical treatment for ADHD. We followed defined treatment algorithms for the medication of ADHD. The treatment started with the first choice: methylphenidate; the second choice: dexamphetamine; and atomoxetine was considered in patients where there was a suspicion of abuse of dexamphetamine or a significant anxiety component change. During the eight months following randomization, the children were not offered any supplementary treatment, such as anti-psychotics or antidepressants. All children were examined one week and again one month after the start of medical treatment; positive effects and adverse effects were evaluated. The standard treatment involved an educational parent group, where the parents met three times during the eight week trial and received general information about ADHD.Social-skills training aimed to improve and maintain the individual’s social skills. The children were taught how to adjust their verbal and nonverbal behaviour in their social interaction. Social-skills training also included efforts to change the child’s cognitive assessment of the ‘social world’ During the process where the children received social skills training, the parents attended parental training. The themes from the children’s groups were discussed during the parental groups. The children’s homework was also discussed. The efficacy of the intervention was assessed by studying the amount of improvement in ADHD symptoms and social skills per se, or by assessing psychological functioning on a broader aspect, including the quality of peer relationships and emotional competency.rd Edition Rating Scale ‘hyperactivity-impulsivity’ subindex (the primary outcome) and an assumed standard deviation of 5 points on the same scale The sample size was calculated on the basis of a type I error (α) of 5% and a type II error (β) of 20%, thus a power of 80%, and an allocation ratio of 1:1. With a minimally clinical relevant difference of 4 points between the intervention group and the control group on the Conner’s 3The statistical analysis of the outcomes was based on the ‘intention-to-treat’ principle and primarily conducted with adjustment for the protocol specified stratification variables (sex and presence of co-morbidity) and secondarily conducted without this adjustment 2 + f⋅intervention-group⋅t + g⋅intervention-group⋅t2, where co-morbidity, sex and intervention-group are binary indicator variables and t is treated as a continuous variable; a through g are coefficients to be estimated during the analysis. The basic model is Outcome measure  =  a⋅sex + b⋅co-morbidity + d⋅t + e⋅t2, where the outcome measure is modelled as a linear function of time (t) and time squared (t2). The latter term is included to model a time course that may be almost linear initially and then blunted as time goes by. If sex or co-morbidity is having an impact on the outcome measure this effect is compensated for by including the terms sex and co-morbidity in the model to improve the precision.The mixed-model repeated measures method (SAS version 9.1) was used to compare the effect of the two interventions over time on the outcome measures. The model is the following: Outcome measure  =  a⋅sex + b⋅co-morbidity + c⋅intervention-group + d⋅t + e⋅t2 the terms intervention-group + intervention-group⋅t + intervention-group⋅t2, respectively, are added to the model.To model a possible impact of the intervention on the mean level, the slope of the linear function (t), and the slope of tA sequential hypothesis testing was used, which is appropriate for polynomial models. Since the measurements within a given patient are probably dependent, this dependency is modelled by a co-variance matrix, common to all patients. Initially, three types of covariance matrices were examined: compound symmetric, AR(1), and unstructured. Using the Akaike and the Schwartz Bayesian criteria, the best of these three covariance structures was chosen.Prior to each analysis the six distributions of the outcome measure defined by time and intervention-group were examined to see if the assumption of normality was fulfilled (tests of kurtosis and skewness as well as Shapiro Wilks test (p<0.01) plus inspection of histograms and probability distributions). Prognostic factors measured were: assessment of the attachment between the child and the parents and an assessment of the parent’s own ADHD symptoms For the purpose of this trial the baseline values of the variables CAI group, ASRS score (father), and ASRS score (mother) were re-coded into binary variables -binary, and ASRS (mother)-binary, respectively). .100 families were eligible and 26 refused to participate in the trial see . 21 of tTwo children were excluded a few days after the randomization, one of them because his mother did not want her child to receive central stimulating medication, and we were not allowed to obtain outcome assessment from this child. The other child and his parents did not want to participate in the treatment, but all his outcome assessments were obtained and this child is included in the analysis.2 that on no occasion did the time course of an outcome measure differ significantly between the two intervention groups. This was not altered if insignificant effects including the intervention indicator were removed from the model one at a time and the analysis each time repeated using the reduced model. An analysis not including the two protocols specified stratification variables (sex and co-morbidity) gave similar insignificant results.The outcome measure changed significantly over time for most outcome measures, but the time course did not differ significantly between the two intervention groups for any outcome measures  and 3. I2 showed that on no occasion did the CAI-binary significantly influence the time course of an outcome measure. The same was found when the analysis was repeated but this time with all fixed effects involving the intervention indicator   and mean value in the 6 month outcome 1.84 (95% CI: −3.98 to 7.66)), is in accordance with the findings in our Cochrane review as well as with the conclusions of the meta-analyses performed by Kavale et al. and Van der Oord et al. However, both of these latter meta-analyses had no evaluation of systematic errors (bias) in the trials included and the results are therefore questionable. We could not find support for our hypothesis that adding social skills training and parental training to the standard treatment would give a statistical significant difference on the children’s ADHD symptoms and social and emotional competences compared with the standard treatment alone.One of the baseline findings in SOSTRA is especially interesting, as only 7.3% of the children had a secure attachment competence, as opposed to 61% in a normal population In the SOSTRA trial we discovered a large effect over time for both the groups together, e.g., the children’s social problems scores, aggressiveness, and hyperactivity scores showed highly significant changes towards fewer symptoms . We cannThe strength of the SOSTRA trial is that we published the design protocol before we embarked on the trial In accordance with our Cochrane systematic review on social skills training for children with ADHD, we found no significant benefit or harm in any of the outcome measures of the SOSTRA trial. This suggests that on the basis of our sample size calculation and our consideration of a necessary relevant effect size, currently, there is no evidence to recommend or reject social-skills training with or without parental training for ADHD children. This result and the fact that 93% of the children who were assessed by the Child Attachment Interview at baseline had a insecure attachment disorder, leads us to believe that there may be a need for more profound, longer lasting types of interventions that might result in a change in children’s ADHD symptoms, to improve their social and relational competence, and thereby avoid serious further development of the disease.Checklist S1CONSORT Checklist.(DOC)Click here for additional data file.Protocol S1Trial Protocol.(DOC)Click here for additional data file.


To ascertain whether factors of the family environment and gestational period are associated with the appearance of ADHD in children, as reported by various different informants (mothers and teachers).This paper presents results from the dataset of a longitudinal study to evaluate behavioral problems among schoolchildren in São Gonçalo, Rio de Janeiro State, in 2005 and 2006. The cross-section considered for this paper comprises records of exposure factors and ADHD. In all, 370 schoolchildren of the public school system were assessed by 3-stage cluster sampling. The Child Behavior Checklist (CBCL) and the Teacher Report Form (TRF) were used to measure outcomes. The exposure factors examined were: profile of child and mother, variables relating to the family environment, and perinatal considerations. The questions were answered by mothers and teachers. A hierarchical logistic regression model was used.Precariously functioning families, lack of social support for mothers, adverse life events and discord during pregnancy were the factors associated with mother-reported ADHD. When ADHD was reported by teachers, the variables selected were: Intelligence quotient (IQ) and sex, with children with low IQ scores and boys more likely to display the disorder.Assessment of ADHD by teachers or mothers reveals specific characteristics that reflect how each of these informants understands the children. This highlights the importance of using informants from different environments in diagnosing the disorder. The first systematic explanation of Attention Deficit Hyperactivity Disorder (ADHD) appeared in 1902 in a description of the history of 20 children whose symptoms were similar to those that today we call hyperactivity [Although the origin of the disorder is explained substantially by genetics ,3, interAnother aspect important to understanding ADHD relates to behavior and problems experienced by the mother during pregnancy. On this line of etiology, some studies indicate that tobacco and alcohol use and psychological stress during pregnancy increase the risk of the child’s developing ADHD ,11.ADHD is one of the commonest childhood disorders, occurring in 3% to 7% of school-age children on clinical diagnosis. Although clinical assessment is considered the yardstick for diagnosis of psychiatric disorders, clinical psychiatrists are little used in epidemiological studies for practical and financial reasons . In popuHowever, it is usual for there to be some degree of discrepancy between parents’ and teachers’ assessments of the behavior of children with ADHD . In thisFew studies have linked environmental factors to ADHD through the perspective of different informants. An example is the article of Kollins et al. , which aThis paper aims to ascertain whether factors relating to family environment and gestational period are associated with the appearance of ADHD in children and if these factors vary according to different informants (mothers and teachers). Despite the importance of the subject, there has been little discussion in Brazil about how environmental and psychosocial factors relate to ADHD . Prior tThis paper presents baseline results from a 2005 longitudinal study measuring exposure factors and ADHD.The sampling plan was based on a record of public schools, classes and mean number of pupils per class provided by the São Gonçalo municipal education department for 2005 . The sampling design employed is the three-stage cluster selection type . Random selection of the 25 schools was by systematic probability proportional to size (PPS) sampling; two classes were drawn at random from each school, and 10 pupils from each class, totaling 500 pupils in the sample. Two chances were given for the mother or guardian to attend the interview at the school. In the case of non-attendance after two opportunities, or if the pupil had left the school, a new interviewee was summoned according to the prior draw. 1% of participants recruited refused to take part in the study, and approximately 35% of the pupils originally selected were replaced by the next candidate on the list for their class, mainly due to faulty class record keeping.In this paper, 370 children are assessed (4935 in the expanded sample). The 130 exclusions responded to the following criteria: children with intelligence quotient (IQ) ≤ 69, given the difficulty of assessing ADHD in children with such a low intellect score ; one chiThe group of losses and the group selected were compared by analysis by sex, age and social class, but no statistically significant differences were encountered (p < 0.05).ADHD’symptoms was assessed using the CBCL and the TRF. Both instruments were formulated by the same authors , and diaBrasil and Bordin  shows thThe CBCL evaluates behavioral problems occurring in the prior six months in children 6–18 years old, on the basis of information given by their parents. Specifically as regards the inattentive and hyperactive behavior considered in this paper, informants responded to 10 items, including questions such as whether the child is restless, never still; is impulsive, acts without thinking; can’t manage to finish what it starts; and is easily distracted, unable to pay attention for long. The answer options varied from false to very true (0 to 2 points). The items were added and standardized so that they had a mean of 50 and standard-deviation of 10, enabling to categorize results as: normal (< 65) and borderline/clinical (≥ 65). It was assembled cases borderline and clinical to analyze.The TRF is an instrument similar to the CBCL, but directed to teachers, educationalists and other professionals involved in the children’s development at school. It evaluates the child’s behavior over the prior two months. There are more questions relating to attention problems (26 items) than in the instrument intended for parents and guardians, particularly because teachers perceive attention deficit and hyperactivity problems better. The cutoff procedure is similar to that used with the CBCL.The survey data that gave rise to this paper yielded a significant Pearson correlation  between the CBCL and TRF evaluations of attention disorder.In the cases examined in this paper, the multidimensional questionnaire of the study was answered exclusively by the children’s mothers. Of the questionnaire answered by the teachers, only the TRF was used. CBCL e TRF’s items related to others behavior problems were answered by the mothers and teachers, but here only the problem attention’s items was analyzed.profiles of child and mother were sex, age, mothers’ schooling (≤ 7 years of education versus that used to correspond to an incomplete primary grade of education in Brazil and > 7 years of education), whether or not the mother was a restless child/teenager , and the child’s intelligence quotient (IQ). The latter was measured by the Wechsler Intelligence Scale for Children (WISC-III), which comprises 13 sub-tests that make up total IQ. When subdivided, it makes it possible to evaluate verbal IQ  and execution IQ . The test was applied complete to 26 children from the sample, and to the rest of the sample in reduced format (comprising two sub-tests – vocabulary and cubes). A Pearson correlation coefficient of 0.85 was obtained between the reduced test and total IQ, and 0.88 and 0.83 for verbal IQ and execution IQ, respectively.The variables used to gauge the present family environment were: a) social support – whether there are people with whom the mother feels comfortable and can talk about almost anything; b) whether or not the mother had got drunk in the prior year; c) the family’s overall functioning, as evaluated by the General Functioning Scale of the McMaster Family Assessment Device [The variables that evaluate the child’s and mother’s t Device , which it Device   and by mother (CBCL). Variables in the univariate models that were significant at the 10% level entered the selection process for the multiple model. Inclusion of variables in selection for the multiple model was hierarchical : distal Exemplifying the use of the hierarchical model, Leech et al.  investigWithin each block, the criterion for selecting variables was to withdraw the variable with the least significant effect from the model sequentially until all the effects present in the model were significant to the 5% level.The information regarding design of the sample was considered in all the analyses (model fit and tests of association). Accordingly, weights were introduced to correct the point measures, and adjustments were also made for the accuracy estimates. For model fit, the library survey function of R version 2.11.1 software was used.This project was approved by the research ethics committee of Brazil’s national school of public health (ENSP/FIOCRUZ). The school directors and parents signed a declaration of free and informed consent.The 370 children studied can be profiled as follows: 6 to 13 years old (mean 7.9 and SD = 1.1); 50.8% boys; 32.4% identified by guardians as white; 67.3% black/brown and 0.3% yellow/indigenous; 56.8% living with both parents, 25% with only one of them, 17.4% with father and stepmother or mother and stepfather, and 0.8% living with other relatives. Mean members per household was 4.7 (SD = 1.4); 67.7% of mothers reported not completing fundamental education; 5.2% of families had monthly per capita income of less than one minimum wage (R$ 300.00 in 2005), and 70.8%, up to half a minimum wage. IQ ranged from 70 to 140 .Prevalence of ADHD among the children studied was 13.3%  when the informant was the mother, and 9.2%  when teachers reported the disorder. The Kappa between the parents’ and teachers’ evaluations was 0.12, while prevalence-adjusted Kappa was 0.60.Table Table As regards maternal conditions during pregnancy and childbirth, mothers who had fights or who consumed alcohol in that period had odds ratios of 4.5 and 2, respectively.Table Comparing the crude odds ratios Table  and oddsTable The prevalences of ADHD measured by the TRF differed markedly by sex (14.4% of boys and 3.8% of girls). The prevalence among girls was quite different from the corresponding mother-reported prevalence (11%); there was closer agreement as regards the boys (15.4%) (Table From the data in Table In the two models (CBCL and TRF) the interaction terms were tested, but were not significant.The results show a difference between the percentage of ADHD  as reported by parents and by teachers. Mothers reported more in their children than the teachers did (13.3% against 9.2%), and that trend persists even when comparing only the prevalence of clinical cases in the two samples (7.0% against 5.4%). Recent review studies have shown major variations in prevalences (from 0.2% to 26.8%), which relate to the different methodological strategies used in the studies , which can affect these measurements of prevalence . A studyIn addition, the ADHD’s percent is expected to vary by information source (parents or teachers). The traditional Kappa found weak agreement between mothers and teachers, although part of that result can be explained by the low frequency of ADHD in the population studied, given that the adjusted Kappa was considered substantial on the criteria of Landis and Koch . SimilarReported percentage de ADHD among boys was similar , but quite the opposite was true among girls , corroborating the findings indicated in the literature that teachers have more difficulty evaluating lack of attention, hyperactivity and impulsiveness among girls, who culturally are expected to be quieter and more introverted . ParentsThe association between precarious family functioning and mother-reported ADHD, as observed in this study, is also reported by other authors. Scahill et al.  found moChild ADHD as seen by the mother is also explained by lack of social support, stressful life events, and a pregnancy marked by conflict. Lange et al. and Counts et al. ,6 also fIn the teachers’ view, besides male sex, only the child’s IQ showed an association with ADHD, corroborating the finding that teachers tend to evaluate more by reference to neurocognitive considerations .Some variables that showed an association only in the univariate analysis deserve brief mention. One is alcohol use during pregnancy and maternal drunkenness in the months prior to the study. Mick et al.  found thLimitations of the study that deserve special mention are the use of retrospective measures  and a screening instrument directed to behavioral problems in general (and not a diagnostic instrument exclusive to ADHD). The cross-sectional study design precludes evaluating causal relations between the effects analyzed and the outcome. The lack of evaluation by psychiatrists and of information provided by the children themselves (replaced in the study by mothers and teachers) contribute to continuing imprecision as to the presence of this very complex phenomenon in Brazil. The lack of information on co-morbidities parallel to ADHD is another limitation, because the high rate of co-morbidities in childhood is one of the factors that most hinders diagnosis. Biederman  in a revLastly, the sample studied in this paper comprised public school pupils only, making it difficult to study effects related to socioeconomic conditions.In spite the substantial number of children excluded from the analysis, these losses did not constitute a profile differentiated from the study sample, i.e., by sex, age and social class.In order to understand the phenomenon better, it is important that more studies should be conducted on the views of different informants in assessing ADHD. Correct diagnosis of the disorder depends on the existence of a clearly defined history of behavioral symptoms and of the harm resulting from those symptoms .The authors declare that they have no competing interests.TOP conducted the literature search and data analysis, and drafted the article. CMS and SGA made a substantial contribution to the methodology and interpretation of results and helped draft the manuscript. All of the authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-244X/13/215/prepub


Successful automated diagnoses of attention deficit hyperactive disorder (ADHD) using imaging and functional biomarkers would have fundamental consequences on the public health impact of the disease. In this work, we show results on the predictability of ADHD using imaging biomarkers and discuss the scientific and diagnostic impacts of the research. We created a prediction model using the landmark ADHD 200 data set focusing on resting state functional connectivity (rs-fc) and structural brain imaging. We predicted ADHD status and subtype, obtained by behavioral examination, using imaging data, intelligence quotients and other covariates. The novel contributions of this manuscript include a thorough exploration of prediction and image feature extraction methodology on this form of data, including the use of singular value decompositions (SVDs), CUR decompositions, random forest, gradient boosting, bagging, voxel-based morphometry, and support vector machines as well as important insights into the value, and potentially lack thereof, of imaging biomarkers of disease. The key results include the CUR-based decomposition of the rs-fc-fMRI along with gradient boosting and the prediction algorithm based on a motor network parcellation and random forest algorithm. We conjecture that the CUR decomposition is largely diagnosing common population directions of head motion. Of note, a byproduct of this research is a potential automated method for detecting subtle in-scanner motion. The final prediction algorithm, a weighted combination of several algorithms, had an external test set specificity of 94% with sensitivity of 21%. The most promising imaging biomarker was a correlation graph from a motor network parcellation. In summary, we have undertaken a large-scale statistical exploratory prediction exercise on the unique ADHD 200 data set. The exercise produced several potential leads for future scientific exploration of the neurological basis of ADHD. Attention deficit hyperactive disorder (ADHD) is a highly prevalent psychiatric disorder affecting millions of people. The core symptoms of excessive impulsive, hyperactive, and distractible behavior can have a pervasive impact on functioning across multiple settings with documented long-term consequences including high rates of academic underachievement, unemployment, substance abuse, and criminal activity. ADHD diagnosis currently depends on ratings of behavioral symptoms, which can be unreliable. Better understanding of the physiological, and especially neurological, underpinnings of the behavioral sequelae would be of great use from medical, basic science, and policy perspectives. Moreover, further understanding of the biological basis of the disease would greatly demystify the substantial public uncertainty surrounding the disorder.ADHD is increasingly recognized as an neurodevelopmental disorder due to converging evidence from structural and functional neuroimaging research. The vast majority of the ADHD neuroimaging literature has focused on pinpointing abnormalities in isolated brain regions [see meta-analyses: Dickstein et al. , Valera “Despite advances in understanding aspects of the etiology of some developmental neuropsychiatric disorders, translating these insights into clinical practice has remained daunting. Significant obstacles include the lack of reliable and valid biomarkers and an insufficient understanding of the underlying pathophysiology. We believe that a community-wide effort focused on advancing functional and structural imaging examinations of the developing brain will accelerate the rate at which neuroscience can inform clinical practice.” Hence, we engaged in the creation of prediction algorithms using ADHD 200 data. Herein we present the insights obtained from the creation of the final ensemble algorithm.The ADHD 200 data set is a landmark study compiling over 1000 functional and structural scans including subjects with and without ADHD. As stated on the ADHD 200 website Caution in interpreting the results presented is warranted, as the work was performed while competing in the ADHD 200 prediction competition with the aim of maximizing the competition points earned. The authors of the manuscript include the competitors of the Johns Hopkins team and our collaborators who could not participate in the competition by being members of a data contributing site .The final prediction algorithm presented in this paper had the best official score for predicting the ADHD status of children in the withheld test data. Though we report and discuss the competition results for the full algorithm, we focus on two specific submodels of the final prediction model and evaluate these submodels via diagnostic accuracy using training sample performance rather than external test set performance.The two primary models of investigation employ feature extraction then ensemble machine learning on the extracted features. The first feature is a voxel selection technique using the so-called CUR decomposition and rs-fMRI. The second evaluates rs-fc regionally in a data-derived motor network mask.The ADHD consortium collected, compiled, and released data from 776 subjects: 491 typically developing controls (TDs) and 285 children diagnosed with ADHD  with subdiagnosis classification of combined, hyperactive/impulsive, or inattentive  or the mode (for others) for the observed values. All models also included data contributing site, which is a proxy for many processes including technical  and site demographics.All models included demographic variables as predictors. These included age, IQ (described further below), gender, and handedness. In addition, data quality control metrics and missing data processes were also investigated. However, these were not used in final algorithms. Available IQ measurement depended on data contributing site and included the WISC IV . Anatomical images were de-obliqued, reoriented, and skull stripped. Functional scans were de-obliqued, reoriented, motion corrected, skull stripped, smoothed (6 mm FWHM Gaussian filter), grand mean scaled, temporal band pass filtered, de-trended (linear and quadratic), and masked to exclude the background voxels . Functional scans were registered to anatomical scans using FLIRT in FSL   as the outcome. In addition, we fit a logistic regression model relating ADHD status (regardless of subtype) to rs correlations. Both analyses investigated potential confounding relationships due to demographic factors such as age, data contributing site, etc.Table Figure With regard to the performance of the final submitted predictions, the internal data-splitting measure of accuracy for each of the subteams was 75, 75, 78, and 72%, respectively. The competition test results can be found at the ADHD 200 web site. The final algorithm test set performance is reported as 119 points (61%). The specificity (control versus ADHD of any type) was reported as 94% with an associated sensitivity of 21%. Youden's J statistic (sensitivity + specificity − 1) was then 15%. The conditional subtype classification accuracy given a correct classification of ADHD was 80%.We further elaborate on the performance of models from subteams 1 and 3. The internal test set accuracy for the random forest algorithm using only demographic information  was 71% with a specificity of 89% and a sensitivity of 44%. Including the rs correlations from the M1 parcellation resulted in an estimated 75% accuracy with a specificity of 97% and a sensitivity of 35%. For Subteam 3, the two-stage gradient boosting method (GBM) using only demographic variables as input achieved 73% accuracy with a specificity of 71% and a sensitivity of 69%. However, if the CUR imaging decomposition results were included in the model, accuracy improved to 78% with a specificity of 84% and a sensitivity of 53%. These results show that adding imaging information improved the specificity of the algorithms. These findings should be interpreted with caution since the development of the algorithms was focused on improving the prediction accuracy as described in section 2.2, which rewarded the correct classification of TD children.P-values of <0.01, 0.01 and 0.06 for the three models investigated, respectively), with the lowest correlation among the ADHD combined group.Table Given the salience of motor abnormalities in children with ADHD, further exploration of the relationship of intra-motor correlations with disease status is of interest. We used logistic regression where we ignored ADHD subtype, considering only 0  and 1 (ADHD). Each of our 10 models included the four demographic variables along with one pair of M1 clusters as predictors in the logistic regression. First, we found that for most cases, data collection site did not change the direction of the relationship. We found that increased correlation between some pairs of clusters implied significantly lower odds of ADHD, while increased correlation between a few other pairs of motor clusters implied higher  odds of ADHD.The ADHD 200 consortium and competition was a remarkable achievement, encouraging scientists from different backgrounds to work collaboratively and competitively on one of the largest collections of (f)MRI data with the goal of advancing our understanding of an important disorder. Our team used hundreds of statistical approaches to predict disease status, and our final ensemble prediction algorithm demonstrated low sensitivity and high specificity. Admittedly, these measures were tuned by the competition rules, which favored methods that correctly identified TD children. Nonetheless, analysis of the results suggests that the imaging data does not provide a great deal of diagnostic benefit, despite several interesting directions of scientific inquiry relating imaging data to disease status being apparent. We elaborate on these points below.The amount of data provided by the imaging components was very large in the context of statistical prediction. In such cases, if the data has strongly apparent features that are good predictors of outcomes, effective learning procedures can be developed for classification. However, in this case, the amount of data was large enough and the signal weak enough that models were prone to so-called overfitting. In other words, if the imaging predictors are used fully in the model, then predictions may be distorted by the sheer amount of non-informative data.Gold standard diagnoses were governed by behavioral measures, which themselves are measured with error and are subject to other idiosyncratic biases and variance. Thus, the ultimate goal of the imaging data is to uncover a more accurate phenotype. Perfect agreement with behavioral diagnosis in this data set or others was neither possible nor desirable.In addition, this data set contained several important sources of variation, some addressable and others not, that influenced our ability to develop meaningful generalizable scientific associations between biomarkers and disease status. A partial list would include: site-specific differences in behavioral measurement, imaging data acquisition, basic processing, scanner quality, technicians and protocols, subject populations from data contributing site including protocols for subject recruitment, policies for contributing data to the consortium, potentially informative missing data processes, as well as other unmeasured confounding and mediating variables. Because of these sources of variation and bias, even weak, non-prognostic associations from this data set may prove invaluable, and conversely, the possibility of identifying spurious associations is quite high. Including site in the regression models improved model performance, suggesting that biologically valueless predictors were, in fact, important.The demographic makeup of the dataset was also very unbalanced. Data were collected from eight international imaging centers, each with their own research agenda and without coordination prior to aggregation. Thus, many sites collected more data from TD children than from children with ADHD, and this imbalance would cause learning algorithms to err toward classifying subjects as TD as opposed to ADHD. The IQ measurements provided for each subject also varied across sites and resulted in a missing structure that would be predictive of the site where the observation was collected. In developing our algorithms we used imputation methods to account for as much of the data imbalance as possible. For instance, we used the median of all IQ measurements available for each child as a composite measure of IQ in all of our models. However, it is crucial to note that this is an observational study and hence has all of the issues inherent to analysis of imbalanced data.From our investigations, two approaches used for prediction were especially interesting. One approach appeared to automatically detect residual motion effects that was common across subjects and appeared to differ across diagnostic groups. This raises questions about the residual effect of motion on the statistical analysis and interpretation of fMRI images even after compensatory spatial realignment and regression of motion estimates from the data have been performed. We also observed that a motor network parcellation was a good predictor of disease status.We pursued the use of the motor parcellation to predict ADHD status based on extensive evidence suggesting that, in parallel to their age-inappropriate impulse control, children with ADHD also demonstrate age-inappropriate motor control. (Denckla and Rudel, Given the extensive discussion in literature on motor control impairments in children with ADHD, we used the M1 parcellation as a predictor of ADHD status. Figure Finally, Table In summary, our final prediction models do not provide immediately translatable clinical prediction tools. However, with the collective work of the teams from the competition, numerous interesting directions of scientific inquiry have been uncovered for obtaining a better understanding of the biological basis for this important disorder.The project was supported by grants P41EB015909 and R01EB012547 from the National Institute of Biomedical Imaging and Bioengineering, grant R01NS060 from the National Institute of Neurological Disorders and Stroke. The organizers of the ADHD 200 competition. The Neurobureau.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.


The UK Adult ADHD Network (UKAAN) was founded by a group of mental health specialists who have experience delivering clinical services for adults with Attention Deficit Hyperactivity Disorder (ADHD) within the National Health Service (NHS). UKAAN aims to support mental health professionals in the development of services for adults with ADHD by the promotion of assessment and treatment protocols. One method of achieving these aims has been to sponsor conferences and workshops on adult ADHD.This consensus statement is the result of a Forensic Meeting held in November 2009, attended by senior representatives of the Department of Health (DoH), Forensic Mental Health, Prison, Probation, Courts and Metropolitan Police services. The objectives of the meeting were to discuss ways of raising awareness about adult ADHD, and its recognition, assessment, treatment and management within these respective services. Whilst the document draws on the UK experience, with some adaptations it can be used as a template for similar local actions in other countries.It was concluded that bringing together experts in adult ADHD and the Criminal Justice System (CJS) will be vital to raising awareness of the needs of ADHD offenders at every stage of the offender pathway. Joint working and commissioning within the CJS is needed to improve awareness and understanding of ADHD offenders to ensure that individuals are directed to appropriate care and rehabilitation. General Practitioners (GPs), whilst ideally placed for early intervention, should not be relied upon to provide this service as vulnerable offenders often have difficulty accessing primary care services. Moreover once this hurdle has been overcome and ADHD in offenders has been identified, a second challenge will be to provide treatment and ensure continuity of care. Future research must focus on proof of principle studies to demonstrate that identification and treatment confers health gain, safeguards individual's rights, improves engagement in offender rehabilitation programmes, reduces institutional behavioural disturbance and, ultimately, leads to crime reduction. In time this will provide better justice for both offenders and society. UKAAN was established in 2009 in response to UK guidelines issued by the National Institute for Clinical Excellence (NICE) in 2009  and the ADHD is a clinical syndrome defined in the Diagnostic and Statistical Manual - Fourth Edition (DSM-IV) and International Statistical Classification of Diseases - Tenth Revision (ICD-10) by high levels of hyperactive, impulsive and inattentive behaviours beginning in early childhood. The disorder is common in the population with prevalence estimates in the UK of around 3-4% ; with arWhile ADHD-like symptoms are found in many people some of the time, in people with ADHD they are severe, persistent over time and lead to clinically significant impairments. Impairments can impact on an individual in several ways including: low self-esteem, educational and occupational problems, problems in social interactions and relationships, antisocial behaviour, the development of comorbid psychiatric symptoms, syndromes and disorders, and the capacity to cope with police interviews and court procedures . ComorbiResearch suggests there is a disproportionately high concentration of ADHD individuals involved with the CJS, and for these individuals criminal justice procedures often interface with a complex web of behaviour, substance use and mental health issues. International studies from the USA , Canada UK prison studies have indicated a rate of 43% in 14-year-old youths  and 24% Thus the rate of ADHD in the CJS far exceeds that in the general population, and offender behaviour, both within and outside of prison settings, is something that society cannot afford to ignore. The higher rate of ADHD individuals involved in the CJS however is not paralleled by the knowledge, skills and training of practitioners in the disorder and who are involved in their care. NICE Guidelines for ADHD  were comIn the past few years commissioning responsibilities for prison healthcare have transferred from the prison service to the NHS in order to:1) Increase investment in prisoner health.2) Raise services to NHS standard.3) Provide continuity for those in prison who later return to communities.A central tenet is that prisoners should be considered as part of the community and treated within mainstream services with access to the same standards of health and social care as the rest of the population. Nevertheless, it is recognised that there exists a sub-group of individuals who have particular difficulty navigating the system, perhaps due to poor educational ability, disturbed mental state, and/or substance misuse. By supporting these individuals in their care and through the provision of integrated services, the justice they receive will also be supported.Offender Health now exists as a partnership between the Ministry of Justice and the DoH and, to date, the focus has been to:1) Develop mental health transfer protocols to facilitate the transfer of those with severe mental illness to mental health settings.2) Introduce an Integrated Treatment System, which draws together clinical interventions for prisoners .In response to the recommendations of the Bradley Report , a natio1) Improve system effectiveness and efficiency.2) Work in partnership.3) Improve capacity and capability.4) Develop an equity of access to existing general services and/or specialised services for ADHD.5) Improve pathways and continuity of care.The Health and Criminal Justice Programme Board is supported by a National Advisory Group, which provides independent, evidence-based advice to the Board on the developing agenda, and highlights examples of good practice and the commissioning of in-depth studies in areas of interest. Thus this National Advisory Group will provide a mechanism for UKAAN to raise the profile of ADHD offenders at the highest level.However, the volume and scale of activity within the CJS will influence what can realistically be achieved in terms of ADHD screening, assessment and treatment, and new developments must be integrated with existing protocols and run in a system at high capacity. Health inequality is common in the prison population for many reasons , and the DoH has expressed commitment to raising standards for the benefit of prisoners and with a view to improving longer term outcomes such as a reduction in reoffending and positive integration into the community. However there is no 'quick fix' as most prison inmates are young men with complex healthcare needs, including alcohol and substance misuse problems and psychological problems. On the other hand health assessments and interventions often have to be rapidly implemented as approximately half of prison inmates stay in prison for an average of six months or less. Nevertheless there is room for innovation - screening at prison reception has improved and non-health staff are now involved in a preliminary screening process, which triggers a more comprehensive assessment, if required, conducted by health staff. The Integrated Treatment System is the appropriate pathway for introducing ADHD assessment and management as this will include after-care arrangements, e.g. for treatment post-discharge.The Bradley Report  was commCurrently the National Criminal Justice Board meets regionally and nationally, with representation by the courts, police, probation and prison services. Screening systems already exist in CJS services and we need to identify ways of building on these systems to incorporate screening for ADHD. Making representations to the National Criminal Justice Board might be one way to move forward. In developing an effective and efficient screening protocol for ADHD within various CJS settings and in developing appropriate care pathways, it will be important to determine the level of awareness that exists in services, what screens are currently used, and what a positive screen triggers in terms of individuals progressing through CJS procedures and services.Table The Criminal Intelligence System database includes mental health data and, once improved, screens will be standardised and introduced nationally providing an efficient and cost-effective way of sharing data and alerting staff to particular needs . Currently a Risk Assessment screen is given to every person received into custody and this includes questions about current mental state . This triggers a follow-up primary care screen within 48 hours (to which ADHD items could be added) and/or contact with a forensic medical examiner to ensure that the individual is fit to be detained and interviewed. It also identifies individuals who require regular observations (e.g. to prevent suicide). For those fit for interview, other provisions can be made. In the UK for example, if a detainee is suspected of having a mental health need they must be supported by an appropriate adult (AA) during interview. The AA can give advice to all parties, furthers communication and ensures that the interview is fair, however even when ADHD is recognised, detainees will not necessarily be entitled to an AA unless triggered by some additional problem (e.g. learning disability). It is important to note that for many young offenders the AA will be a parent and, given the hereditary nature of ADHD, this in itself may have implications for the custody process. Furthermore, some countries do not have the AA system in place, in which case the vulnerability of detainees with ADHD (recognised or unrecognised) is more serious as they get no additional support. It is recognised that the introduction of improved screening may result in more detainees requiring an AA, and a revised AA scheme is due to be introduced, providing opportunities to introduce ADHD training and/or psychoeducational materials on ADHD recognition, treatment and management.In completing any screen, detainees may be resistant to engage with officers who have arrested or detained them, thus it is important that screens are completed sensitively to avoid disclosure being limited if detainees perceive stigma associated with their endorsing mental health problems. Language barriers are routinely overcome by the use of interpreters who can attend the police station within two hours. Cultural barriers also need consideration, as does the perception that if a mental health need is disclosed or suspected, the criminal justice process will be lengthened.The need for close working relationships between health professionals and the courts has been documented in The Bradley report  see Tab and by tShould ADHD be recognised at any stage of the court process, it could be referred as necessary to health professionals and/or the Probation Service to assist the court in its sentencing decisions. The National Probation Service provides pre-sentence reports to assist the judiciary with sentencing decisions. Some reports are described as 'Standard Delivery' taking up to three weeks (i.e. involving more serious offending and/or complexity of offender needs) and others are 'Fast Delivery' taking up to five days. Considerations necessitating the request of psychiatric reports arise from Section 157 of the Criminal Justice Act 2003 which places an obligation upon the court to consider a medical report in "any case where the offender is or appears to be mentally disordered" (s157 (1)) "unless the court is of the opinion it is unnecessary" (s157 (2)). Section 207 of the same Act also requires evidence of a registered medical practitioner if a mental health treatment requirement as part of a community order is required. Currently some court areas are developing service level agreements for the provision of such reports as suggested within the Bradley Report .There is a Government expectation that the proportion of Fast Delivery Reports will increase to 70%, therefore ADHD screening needs to be built into initial screening processes (which vary across probation areas) in order to flag up whether the greater level of assessment provided by a Standard Delivery Report is required. With this in mind, probation staff would need training to screen for ADHD and learn how and from where to access diagnosis and treatment. The most likely procedure would be referral to a forensic psychiatric service for a comprehensive assessment. An area for development is for Local Criminal Justice Boards to establish effective protocols with health service providers to ensure that there are cost effective and practical arrangements for diversion and treatment for Court users with mental health problems and/or learning disabilities.As part of the National Offender Management Service, the probation service is made up of 42 Probation Trusts that operate independently from each other to manage offenders and monitor them through the orders imposed by the courts (Sentences). Offender Managers provide interventions,  and monitor their clients' progress and, while there are national standards, each Trust and is encouraged to tailor responses to local needs and priorities and the offender profiles within their areas. Joint Needs Assessments are thus conducted between the National Offender Management Service and Primary Care Trusts (PCTs) resulting in targeted Offender Care Pathways that also reflect national initiatives . One such initiative is the provision of mentoring/peer education services invested in by Probation Trusts and PCTs . These initiatives are in the early stages of development (relatively speaking) but have a significant role to play in an offenders' journey as they provide continual support for the offender from custody to the community. Thus Peer Health Educators could develop their knowledge and skills about ADHD and prompt referrals from Offender Managers.A useful tool for the identification of need is the Offender Assessment System (OASys), which has the potential to provide further determination of what barriers may exist for an offenders' ability to adhere to their rehabilitation requirements. OASys provides an opportunity for the identification of non-criminogenic needs with work ongoing to identify how Offender Managers can be made aware of issues such as ADHD, thus influencing the care pathway for an individual, and the use of OASys for this purpose could well be in addition to any local assessment tools that exist.Whichever stage an offender is at  a protocol would need to be established for the effective identification of which offenders have ADHD so that this can be taken into account in terms of assessing offending behaviour  and ensuring that the interventions meet offender needs (in order to maximise their chances of compliance and successful completion). Any protocol would need to be established with each Probation Trust, ideally working in partnership with other agencies, including health, thus providing the best means of ensuring that the needs of offenders with ADHD are identified, diagnosed and met.Table 1) Primary care health workers.2) Mental health in-reach teams.3) General forensic psychiatrists.4) GPs.5) Specialist learning disability nurses.More informally, wing staff are the 'eyes and ears' of the prison. They interact with inmates on an intensive, daily basis and, whilst they usually lack the ability to describe perceived difficulties in medical terms, they are well placed to identify when a prisoner is 'different' or unwell.Prison reception health screens are currently being reviewed. The current procedure (the 'Grubin' screen) is a two-part procedure comprising a brief screen for depression and suicidal ideation followed by a more comprehensive health screen to which ADHD items could be added. Currently around half of individuals entering the prison system complete both sections. While ADHD could be incorporated into this screen, it is important to maintain the brevity of the screen. Furthermore, several needs will compete with ADHD for inclusion , however given the high rate of ADHD among prisoners involved in institutional critical incidents, we need to lobby for ADHD to be prioritised. A substantial barrier to the identification of ADHD and the delivery of mental health care in prison is the high turnover of inmates. The prison population nears 90,000 with around 200,000 new names introduced each year, and over 50% of prisoners serve less than six months before moving on to community supervision. In addition, the frequency of inter-prison transfers means that data-sharing protocols across authorities will be essential.Rates of ADHD are disproportionately high in personality disorder wards in forensic mental health services , and addiction populations (20%) , and witWithin mental health services there is an existing infrastructure into which ADHD awareness will fit. In order to successfully build on this framework, two important factors were identified:1) The development and provision of accessible information and resources for staff and patients and their families.2) The development and provision of a monitoring checklist to record assessment and prescription information for the patient, which can be completed by multidisciplinary staff.However, whilst routine screening is conducted on admission to forensic inpatient services, this is not routinely conducted in community services where the majority of ADHD offenders with mental disorder are likely to be found. Existing screening procedures, where provided, are unlikely to include ADHD, and in some cases ADHD may be misdiagnosed , thus emphasising the importance of training for professionals in ADHD assessment and diagnosis, which does not currently feature in generic training curricula.The conclusion of NICE guidelines for the treatment and clinical management of adults with ADHD  was thatThe treatment of ADHD in the prison population is expected to have three main benefits. First, the reduction of symptoms of ADHD that impact adversely on behaviour within the prison setting, such as inattentiveness, physical restlessness, impulsive responding and mood instability. Second, the reduction of ADHD symptoms will enable individuals within the prison system to take better advantage of rehabilitation programs aimed at the reduction of recidivism and improved behavioural control. Third, the treatment of underlying ADHD may lead to improvements in comorbid disorders such as antisocial and borderline personality disorders, substance abuse disorders including addiction, and anxiety and depression including the risk for suicide.We can therefore see that treatment of ADHD within offender populations fits well with the Risk-Needs-Responsivity principle, which proposes that treatment is targeted at the riskiest cases and at needs relevant to the service (e.g. treatment targeting criminogenic needs in offending populations). Programmes that adhere to the Risk-Needs-Responsivity principle, with strong strategies for reducing criminality, have been shown to be particularly effective in rehabilitating offenders and reducing recidivism . Working1) Pharmacological treatments to alleviate ADHD symptoms.2) Psychological treatments aimed at improving strategies for self-control and reduction of antisocial attitudes and behaviours.3) Concurrent treatment of comorbid disorders.Offenders with untreated ADHD can be particularly difficult to manage in prison/institutional environments. Individuals with high levels of ADHD symptoms were recently found to have an 8-fold greater number of critical incidents in a Scottish prison and a 6-fold greater number of critical incidents than inmates with Antisocial Personality Disorder ; mainly The reasons for the particularly high rates of behavioural disturbance with prison inmates with ADHD are likely to stem from several sources related to the core syndrome of ADHD, including impulsive responding, mood instability, emotional dysregulation and low frustration tolerance -30. GudjClearly ADHD has a greater impact on people than just the core symptoms of the disorder. In most cases the disorder starts during early childhood and has a negative impact in many areas of life throughout the lifespan [reviewed in 1]. One view of ADHD, supported by available data, is that children with ADHD are particularly susceptible to risk factors for the development of behavioural disorders, such as background social environment and genetic factors, and the often adverse negative events resulting from ADHD such as poor social interactions, poor engagement with education and exclusion from mainstream activities. Thus treatment within criminal justice settings will usually require the integration of interventions for comorbid mental illness, personality disorder, substance misuse, psychological problems, educational and occupational needs, criminogenic and other offence related factors. Treatment of ADHD is expected to enhance the effectiveness of these important interventions by reducing key symptoms and behaviours that act as a barrier to recovery and rehabilitation; including greater control over emotional and impulsive responses, reduced levels of restlessness, increased ability to focus and plan ahead and improved ability to take part in psychological treatment programs.The use of pharmacological treatments for ADHD in children is well established in the UK and across Europe, with approximately 1% of the child population receiving stimulants or atomoxetine for ADHD . The phaThe recommended first line treatment for ADHD in adults is methylphenidate, followed by dexamphetamine or atomoxetine. Currently none of the drugs available to treat ADHD in the UK are licensed for use in adults, although treatment trials required by the regulatory bodies are underway that are expected to lead to extension of current licensing to the adult population. Atomoxetine is licensed for use in adults but only as a continuation of treatment first initiated during childhood or adolescence (before the age of 18 years). This situation is an anomaly because in many cases pharmacological treatments are licensed for use in adults but not paediatric populations and the risks associated with stimulants are not thought to be greater in adults. Particular concerns in adults include cardiovascular changes such as increased pulse and blood pressure that need to be carefully monitored, although this is similar to many other drugs used in adults. Despite these potential problems, having fully reviewed available evidence, UK national guidelines from NICE [The main treatment effects recorded in drug treatment trials are improvements in levels of inattention, hyperactive and impulsive behaviours and symptoms. Studies have also documented a wider range of improvements on social and academic function and an individual's overall sense of well-being. Some studies have specifically reported on reductions in aggressive behaviour, with stimulant effect sizes being similar to those reported for core ADHD symptoms . An impoThe nature of the symptoms that improve with stimulant medication can best be understood from the descriptions given by patients being treated for ADHD . The rapPrescribing stimulant medication in CJS settings may be perceived as unattractive due to the drug being (currently) off-licence, the controlled drug status for stimulants and abuse potential. The potential for abuse was recognised by NICE who suggest that atomoxetine may be a better option where this is a particular concern because it is not a controlled drug and is a non-stimulant. However the overall effectiveness of stimulants, which NICE consider to be greater than atomoxetine, means that stimulants should also be considered either as a first line or second line choice. The delivery of medication within the prison setting should not however be a problem, since many prisons already run medication-based programmes for controlled drugs (e.g. methadone maintenance) and successfully adhere to protocols and policies that aim to reduce the chances of mismanagement.The abuse potential for stimulants is however often overstated and usually by professionals who are not familiar with the effects of stimulants in the treatment of ADHD. First, we know from follow-up studies that the use of prescribed stimulants is not associated with an overall increase in drug abuse problems and may be associated with a reduction in illicit drug use -39. SecoDrugs with low abuse potential include atomoxetine which is a non-stimulant and long acting formulation, those where the stimulant cannot be easily extracted for injection, such as methylphenidate OROS in the UK or skin patches and long acting lisdexamphetamine in the USA.NICE recommends that drug treatment should always form part of a comprehensive treatment plan that includes psychological, behavioural and educational advice and interventions. Medication is likely to improve adherence to psychological treatments such as offender treatment programmes and other therapeutic, educational and occupational activities. Thus addressing ADHD may have a two-fold impact in crime reduction, first by directly treating the disorder (e.g. reducing symptoms) and secondly by improving engagement with rehabilitative programmes. Specific programmes have been developed that integrate the two, and there is some evidence from studies in children that psychological therapies, in combination with drug treatments lead to greater sustained effects and greater effects on comorbidity . HoweverProviding access to regular treatments of the right kind is generally a commissioning matter, however the evidence base needs to be expanded to evaluate newly developed, specialist programmes. A useful starting point might be to simply promote awareness of ADHD among those facilitating treatments.Treatment protocols in prison are supported by PCT commissioning through links to care standards in the wider community, and it may be beneficial to take a phased approach. It may be sensible to target those with longer sentences, maximising opportunity for initiation and optimisation of treatment. Identification and treatment of ADHD inmates is likely to reduce behavioural disturbance within the prison setting but additionally improve engagement with therapeutic, education and occupational activities. Education is provided on a smaller scale in prison than in the community (e.g. two or three to a class) and one-to-one attention will optimise motivation, co-operation and learning. Greater understanding about ADHD and associated problems will maximise treatment benefit and increase the chance of successful rehabilitation and constructive skills acquisition.The NHS is now responsible for the delivery of prison healthcare, however in the past practitioners in forensic mental health services have lacked confidence in prescribing stimulants, perhaps due to a lack of clinical guidelines. Thus, treatment plans need to be multidisciplinary and comprehensive, and need to recommend stimulant/drug therapy as a precursor to psychological work addressing criminogenic factors.In the short-term, outcome needs to be assessed using symptom screens and staff measures to assess behavioural improvement . Longer-term effects may include transfer to a lower (and therefore less costly) level of security with greater opportunity to access rehabilitation, and reduction in antisocial and criminal behaviour.In the community, after discharge from prison, some individuals will have contact with probation staff and/or be subject to a Multi Agency Public Protection Arrangements (MAPPA) review. This service provides psychosocial support for prisoners in the community, thus effective links with local mental health services and support agencies, and information sharing is necessary.A common theme that arose during the meeting was the need for integrated care pathways between CJS agencies. Excellent service provision in one setting is of little benefit without continued care through integrated pathways. For persistent offenders, the pathway is not linear but often cyclical as they may move through stages multiple times . The contribution of mental health staff at court will improve identification of mental health issues, including ADHD. It will be important to develop joint (or comparable) risk and health assessments across CJS partners, and provide training and common information sharing protocols and management systems. Referral pathways post-identification must be effective with RCT research a priority, as a strong health economic case must be established.The core NHS care within the CJS is provided by primary care services (GPs) and secondary psychiatric services, and the key to an integrated pathway for many offenders will be the transfer of care, especially for those leaving prison (e.g. via their GP). The GP is the gatekeeper for referrals to community services. For those offenders without a GP, PCTs aim to implement straightforward procedures to facilitate GP registration . This process will be assisted by the probation service who are involved with offenders from before they leave prison in order to assess risk, and continue to mentor them in the community. This includes a multi-agency Reducing Reoffending Delivery Plan, which aims to reduce reoffending and ensures that all offenders have a GP. However, probation staff do not work with everybody leaving prison and those with short-term custody tariffs are unlikely to receive a probation service at all.Awareness about ADHD and its implications (e.g. in different settings) throughout the whole care pathway will be essential in supporting ADHD offenders to rehabilitate into the community and make lasting change. This involves ensuring that services exist within the community to support offenders with ADHD in bringing about continuity of care. Gaining support from a keyworker or mentor will assist ADHD offenders to access continued care. The provision of psychoeducational materials about ADHD for voluntary sector community agencies and charities will assist them in their endeavours to support ADHD offenders in linking with healthcare, re-housing, and management of finances and employment.However, we are in a climate of strong competition for resources; some individuals may require a lot of home supervision in the community, frequent medication monitoring/delivery and occupational support may also be required. One factor that will impact on service provision will be a move towards 'payment by results', which involves the clustering of detainees to correlate improvement over time with outcome measures. These clusters are likely to represent major sources of concern, such as schizophrenia. Adult ADHD patients may require the same amount of resources as severely psychotic patients but respond to treatment more quickly and effectively. This emphasises the need to develop an evidence base for the treatment of ADHD offenders and, critically, to include health economic modelling when evaluating outcome.either experts in adult ADHD or experts within the CJS. This illustrates well the challenge that lies before us in raising awareness of adult ADHD within the CJS. Given the disproportionately high rates of ADHD offenders compared with the normal population and the association with violent, persistent offending, ADHD is a condition that the CJS cannot afford to ignore.The aim of putting health and social care at the heart of the CJS has governmental support. However, it is important that health and criminal justice agencies work together to find 'win-win' solutions for managing individuals and their care, in turn providing better justice, more efficient services and better health and social outcomes. At present, ADHD is not on the agenda, and bringing together key experts in the field proved difficult, with most being Training and work force development will be important to improve awareness and basic understanding of ADHD in order to signpost appropriate healthcare and rehabilitation. This needs to be introduced at every stage of the offender pathway to maximise the support that can be offered and the success of rehabilitation. Table Having identified ADHD in an offender, appropriate support needs to be made available and the development of shared communication across disciplines/services via IT services will provide opportunities to help individuals who otherwise go without. GPs appear to be ideally placed for early identification and intervention, but variability in services due to the broad and complex range of individuals seen in primary care, and the different pathways through which individuals enter the CJS means this cannot be the only provision relied upon. Continuity of care is critical both through and after the CJS, with patient education and system training essential. It is important to bear in mind that, while there is a need for shared responsibility in terms of understanding and evaluating adult ADHD, services within the CJS are not surrogate health and educational services. Provisions need to be made in the community, in police stations, and in the transition from other services, to maximise the opportunity for identification, intervention and prevention.A comprehensive research programme will be required to expand existing ADHD evidence into the realm of the CJS involving joint working and commissioning. In particular, proof of principle studies are needed to demonstrate effectiveness in health, behaviour and offence-related outcomes (including crime reduction). There are effective interventions for ADHD at any age, however a separate but related strategy for youth offenders will offer a preventative focus by providing crucial opportunities for treatment and support. It will be essential to include health economic modelling to demonstrate the service consumption costs of 'doing nothing' compared with the financial benefit of intervention and, potentially, prevention.AA: Appropriate Adult; ADHD: Attention Deficit Hyperactivity Disorder; CJS: Criminal Justice System; DoH: Department of Health; DSM-IV: Diagnostic and Statistical Manual Fourth Edition; GP: General Practitioner; ICD-10: International Statistical Classification of Diseases Tenth Revision; MAPPA: Multi Agency Public Protection Arrangements; NHS: National Health Service; NICE: National Institute for Clinical Excellence; OASys: Offender Assessment System; PCT: Primary Care Trust; R&R: Reasoning and Rehabilitation; RCT: Randomised Controlled Trial; UKAAN: United Kingdom Adult ADHD Network.Support for the publication costs of this article was provided from an educational grant by Janssen-Cilag Ltd., Saunderton, Bucks HP14 4HJ, United Kingdom.SY has been a consultant for Janssen-Cilag, Eli-Lilly and Shire; MA and UM for Janssen-Cilag; JT for Janssen-Cilag and Eli-Lilly; and PA for Janssen-Cilag, Eli-Lilly, Shire and Flynn Pharma.SY has given educational talks at meetings sponsored by Janssen-Cilag, Shire and Flynn-Pharma, Novatis, Eli-Lilly; MA at meetings sponsored by Shire; UM at meetings sponsored by Bristol-Meyers Squibb, Eli-Lilly, Janssen-Cilag, Pharmacia Upjohn and UCB Pharma; JT at meetings sponsored by Janssen-Cilag and Eli-Lilly; and PA at meetings sponsored by Janssen-Cilag, Shire and Flynn-Pharma.SY has received research grants from the National Institute of Health Research, Janssen-Cilag, Eli-Lilly and Shire; UM a research grant from Janssen-Cilag and grants from the Alexander von Humboldt Foundation, Medical Research Council (MRC) and Isaac Newton Trust; and PA has received a research grant from Shire, an educational grant from Janssen-Cilag and grants related to ADHD from Wellcome Trust, The Medical Research Council, US National Institute of Mental Health and the National Institute of Health Research.SY and PA were members of the NICE guideline development group for ADHD.MP and BB no disclosures at present.th and 20th November 2009. The first draft manuscript was prepared by the lead author SY with contributions from all authors via electronic discussions and face-to-face meetings. A draft was reviewed by all the experts who attended the November meeting and other relevant colleagues (see acknowledgements section). The final manuscript was read and approved by all authors.All authors contributed to the manuscript by discussing the issues at the expert UKAAN Forensic Special Interest Group Meeting held in London on 19The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-244X/11/32/prepub