P = 0.001}, at 81 months {6 years 9 months; 15 min (95% CI: 8–22), P < 0.001} and at 115 months {9 years 7 months; 11 min (95% CI: 4–18), P = 0.001}. The attention deficit hyperactivity disorder group had more night-waking at every age, significant from about 5 years. When tracking children’s sleep along a normative centiles chart, a shift in sleep duration from one centile to a lower centile was a useful predictor of attention deficit hyperactivity disorder. Age-specific decreases of >1SD in sleep duration across adjacent time points was a significant predictor of attention deficit hyperactivity disorder at 3–5 years (P = 0.047). In children with attention deficit hyperactivity disorder, shorter sleep duration and sleep disturbances appear early and predate the usual age of clinical diagnosis. The rate of change of sleep duration relative to an individual, rather than absolute sleep duration at any stage, may prove beneficial in identifying increased risk of attention deficit hyperactivity disorder.Associations between sleep duration and disturbance in infancy and early childhood and attention deficit hyperactivity disorder diagnoses were investigated. Data from the Avon Longitudinal Study of Parents and Children, a population-based prospective longitudinal birth-cohort study of children born in 1991–1992 in South-West England, were employed. Eight thousand, one hundred and ninety-five children were assessed using the Development and Well-Being Assessment. One hundred and seventy-three cases (2.1%) met criteria for attention deficit hyperactivity disorder. Parental report at eight time points showed children with attention deficit hyperactivity disorder slept less than peers. Absolute differences were small and mainly restricted to night-time sleep, with no strong evidence of differences from controls, except at 69 months {5 years 9 months; 12 min (95% CI: 5–19),  The study was approved by the Local Research Ethics Committee and by the ALSPAC Ethics and Law Committee. Data were collected and collated at the University of Bristol, School of Social and Community Medicine. Further information on ethical approval and procedures around informed consent are available on the ALSPAC website.The ALSPAC is a longitudinal cohort study following the health and development of children who had an expected date of delivery between April 1991 and December 1992, and were resident in the Avon area of South-West England at the time of their birth. Fourteen thousand, five hundred and forty-one mothers enrolled in pregnancy, resulting in 14 062 live births, of whom 13 988 survived the first year. Full details of the questionnaires used, the biological samples retained, the examinations and observations of the children are available on the ALSPAC website . Night-time waking events were categorised into none, 1, 2 or 3 or more. Age windows were used for each questionnaire to ensure data were from the child at the appropriate age. A more detailed account of the sleep data collection methodology and analysis has recently been published  expected at age 16 years or no qualifications and those partners whose occupation was classified as IV/V (semi-skilled or unskilled) according to the Registrar General’s occupational classification  statistical program. For the univariable analysis the chi-squared test was utilised to test differences in proportions and Fisher’s exact test when an expected cell was less than 5. Multivariable linear regression modelling was conducted using the sleep duration as the dependent variable and controlling for factors significantly associated with ADHD or sleep duration. Statistical significance was measured at the 5% level and the Backward Step variable selection was used. Standardised residuals were plotted against predicted values and Cook’s distances plotted to measure influential observations.Data manipulation and analysis was performed using the z-scores for sleep duration and then considering the proportion of children at each time point who decreased sleep duration by more than 1SD. Multivariable logistic regression modelling was conducted controlling for factors significantly associated with ADHD.Rates of falls in sleep duration across normative centiles were analysed by constructing In total there were 173 ADHD cases (2.1%), of which 70 were classified as ‘inattentive’ ADHD (40.5%), 24 classified as ‘hyperactive-impulsive’ ADHD (13.9%), and a further 79 children had a combination of the two types of disorder (45.7%). It was not possible to obtain parent and teacher reports on everyone, with 96 (55%) including both and 77 (45%) being based on DAWBA interview of parent alone. In this paper we present results for all 173 children with ADHD, compared with the remaining 8022 children in the cohort who underwent DAWBA assessment at aged 7 years.Children with ADHD differed from subjects without ADHD in a number of variables .P = 0.051). Male sex was consistently associated with inattentive , hyperactive-impulsive  and combined  ADHD types.Although ADHD diagnosis was not more common amongst children of deprived families, from larger families, those of non-white ethnicity or amongst older mothers, there were significant univariable associations with young maternal age, pre-term birth and male sex. Birth weight was not a significant factor, but was noted to be very close to significant , and slightly less for the two subsequent time points.Children with ADHD slept on average 13 min less than the rest of the cohort at night during infancy , and conChildren with diagnosed ADHD consistently went to bed later than the rest of the cohort across most ages, although the average difference rarely exceeded 10 min. They also tended to wake earlier by a few minutes .The proportion of children who woke three or more times during the night was higher amongst the children with ADHD at every time point, but was not significant in infancy or amongst pre-school children. From 5 years old, frequent waking was negligible (<1%) amongst the rest of the cohort, but began to increase amongst children diagnosed with ADHD from 3% at 5 years to 6% at 11 years .P = 0.23).Children with ADHD had marginally shorter reported daytime sleep in early childhood and slightly longer in later childhood . RestricAt every evaluation, children with ADHD and related sub-types had decreased sleep duration compared with the rest of the cohort, but this was more marked and only statistically significant during the younger primary school years .Using a multivariable linear regression model and adjusting for variables associated with both sleep duration and ADHD, the total sleep duration was significantly less for ADHD children at 69 months (by 12 min), 81 months (by 15 min) and 115 months  between 42 and 69 months, when 34/136 children with ADHD (25.0%) had a substantial fall in sleep duration compared with 1100/6528 (16.9%) making up the rest of the cohort. Between 42 and 69 months the mean fall in sleep duration in the overall cohort was only 13 min between these ages, but the fall of 1SD constitutes a further 71 min decrease. In a logistic regression model this fall of more than 1SD remained a significant predictor of ADHD {P = 0.047, OR = 1.49 (1.01–2.22)} after controlling for gender, maternal age and gestational age. There was also a significant difference (Chi-square test: P = 0.03) found between 115 and 140 months, when 22/113 children with ADHD (19.5%) had a substantial fall in sleep duration compared with 732/5767 (12.7%) of the rest of the cohort. In a logistic regression model this fall of more than 1SD remained a significant predictor {P = 0.008, OR = 1.93 (1.19–3.12)} after again controlling for gender, maternal age and gestational age.Comparing children who decreased sleep duration between two time points by more than 1SD, there was a greater proportion of children with ADHD at each time point except between 6 and 18 months . This waet al., In all measures of sleep duration and continuity children with ADHD slept for a shorter time, and woke more than their peers. The main reason for their shorter sleep durations was later bedtimes. The effect sizes were very small, little strong evidence of cross-sectional differences from controls at most time points. The age when children diagnosed with ADHD slept significantly less than their peers seems to be about 5–9 years old. Although children with ADHD slept less than their peers, and stopped requiring a daytime sleep at an earlier age than their peers, we did not find strong evidence of differences in daytime sleep duration. This finding does not contradict the objective evidence reported of increased sleepiness on formal multiple sleep latency testing, which measures sleep pressure during carefully confined conditions, rather than actual daytime sleep duration  measures of sleep patterns and sleep behaviours. There are often differences between sleep difficulties reported by parents and those shown on objective sleep measures (Cortese A limitation of most longitudinal studies conducted over several years is that missing data and loss to follow-up are more likely in the most socioeconomically deprived groups. The ALSPAC study is no different, but of sufficient size that although some of the vulnerable groups were lost through this attrition, enough families remained in the study to differentiate between even relatively small social groupings.et al. (et al., et al. (We have not addressed whether psychosocial problems in the family might be associated with poor sleep and ADHD in children (Thunstrom, et al.  suggest  et al., . In a re, et al.  concludeet al. (We do not have accurate information on which children were prescribed stimulant or other medication for their ADHD. At the time of the study it is very unlikely in the UK that medication treatment with stimulants would have commenced before 6 years old. The UK has historically treated far fewer children with ADHD than other countries. In 1995, for example, only 0.03% of children in the UK were on medication for ADHD in contrast to 3% in the USA and 1.7% in Australia (Parliamentary Office of Science and Technology., et al.  and otheet al., et al., et al., et al., Comorbidities commonly associated with ADHD include anxiety, depression oppositional defiant disorder and autistic spectrum disorders (ASD; Faraone et al., Recent research has shown links between ADHD and restless legs syndrome (Cortese et al. (et al., In a recent review paper, Corkum et al.  highligh et al., . Our pre


Medicating ADHD is a controversial subject that was acutely inflamed in 1995 when high rates of ADHD diagnosis and treatment were documented in southeastern Virginia. Psychologists in southeastern Virginia formed a regional school health coalition to implement and evaluate interventions to address the problem. Other professionals with strong ties to the pharmaceutical industry launched ad hominem attacks on the coalition’s research and work. These attacks contributed to the work being terminated in 2005. In the ensuing years, ADHD drug treatment continued to escalate. Today, the national rate of ADHD diagnosis exceeds all reasonable estimates of the disorder’s true prevalence, with 14 % of American children being diagnosed before reaching young adulthood. Notable key opinion leaders continue to claim that there is no cause for concern, but with a message shift from “the prevalence is not too high” to “high prevalence is not too concerning.” This paper provides an object lesson about how innovative research can be derailed to the detriment of sound medical and mental health care of children when industry interests are threatened. Tenure may be the only option for protecting innovative research from specious attacks. The authors offer a summary of the data on ADHD drug treatments, suggest judicious use of such treatments, and add their voices to others who are once again sounding a cautionary alarm. In the mid-1990s, a practicing psychologist in southeastern Virginia, Gretchen LeFever , began a program of ADHD research that included epidemiologic surveys. This research documented exceptionally high rates of ADHD diagnosis and drug treatment in her community. With support from Children’s Hospital of The King’s Daughters and Eastern Virginia Medical School (EVMS), LeFever formed a regional school health coalition to improve ADHD treatment. Based on community input, she and her colleagues developed a systematic public health approach to improving the identification and care of children with behavioral problems in the region.In the course of this work, LeFever was repeatedly attacked for reporting high rates of ADHD diagnosis and treatment. One of the attacks came in the form of an anonymous allegation of scientific misconduct and resulted in the premature termination of LeFever’s work, including her part of a multi-site, multi-million dollar study funded by the Centers for Disease Control and Prevention (CDC) Lenzer , b. The First, the attacks contributed to the suppression of a large and unique dataset of risk and protective factors associated with ADHD diagnosis and treatment. Second, the attacks led to the total dismantling of a school health coalition and associated behavioral and public health interventions that showed promise for improving ADHD care.American Journal of Public Health (AJPH)  was a regional coalition that LeFever formed in partnership with diverse providers, policy makers, parents, and other community members .Interestingly, parents in the region reported greater satisfaction with behavioral interventions than drug treatment, although their children were far more likely to receive drug treatment than other interventions LeFever . To expaThese community-oriented interventions appeared to be making a difference. Between 1998 and 2004, southeastern Virginia witnessed a significant (32 %) decrease in the rate of ADHD diagnosis. Among children in first through fifth grade, it declined from a high of 19 % in 1998 to 13 % in 2004  the significance of the fact that a sizeable proportion of Barkley’s taxable income came from the pharmaceutical industry. Barkley’s own website once showed, for example, that approximately 8 % of his taxable income came from Eli Lilly alone. Eli Lilly manufactures Strattera, a commonly prescribed medication for ADHD. Other income categories that were explicitly tied to the pharmaceutical industry accounted for approximately 19 % of his income LeFever . Like otAJPH) with leading healthcare providers in southeastern Virginia. In response to growing concerns about ADHD treatment trends, EVMS pediatric faculty invited Barkley to address the topic as the keynote speaker for the region’s annual pediatric meeting. The annual professional meeting included a talk that was open to the public. As a recognized authority on a topic of great concern to the general public, Barkley drew a huge crowd for his public address. Barkley contended that ADHD was a genetic disorder that was not being overdiagnosed or overtreated, but that most children with ADHD were not receiving medication when they should have been , Charles Cunningham (Professor at McMaster University and ADHD researcher), and, of course, Barkley (perhaps the most widely recognized name in the ADHD field). What ensued was not so much of a planned discussion of treatment solutions but, rather, a debate about ADHD drug treatment trends.Barkley returned to Hampton Roads in 2000 to debate LeFever on the topic of medicating ADHD. She was allotted 15 min to present; Barkley was given 45 min. Barkley began his talk by asserting that LeFever was not a scientist, summarily dismissing her research out of hand. Just a few months later, Barkley again attempted to discredit LeFever when LeFever was invited to join an APA panel discussion on ADHD treatment solutions. The panel was comprised of experts who had been working in the field of ADHD much longer than LeFever, including Drs. Peter Jensen who had recently stepped down from a lead position at the National Institutes of Health, William Pelham , Larry Diller  another international group of mental health professionals responded by publishing a critique of Barkley’s statement . In response, EVMS conducted an internal investigation of LeFever’s past and current research. Against EVMS policy and common protocol for investigation of allegations of scientific misconduct, the medical school confirmed to the media that LeFever was under investigation.Before LeFever was aware of the allegation of misconduct, the medical school had conducted a review of more than a decade of her research. The process identified that there might be a typo between the wording of a survey item and the manner in which the survey item was described in the appendix of a published article. Until the reported typo was brought to LeFever’s attention, neither she nor any of her three co-authors had ever noticed the discrepancy.Scientific or research misconduct is defined as fabrication or falsification of research, plagiarism, or other practices that deviate significantly from what is commonly accepted within the scientific community research. It does not pertain to honest error or differences in interpretations or judgments of data  had repeatedly asked her to publish the error statement. Phelps lamented to LeFever that she and her co-Editor, who also felt that the error was too minor to warrant any action, finally decided to turn the matter over to the publishing house. The journal’s publishing house decided for the sake of public relations/business reasons—not for reasons pertaining to scientific integrity—that they would publish a brief error statement in the next issue of the journal , which appeared in a subsequent issue  permanently terminated LeFever’s research, placed her on administrative leave Lenzer  and wrotA long-anticipated newspaper “expose” of LeFever’s “wrongdoing” was finally published on January 25, 2005 —the rate that once sparked national and international debate. Calculations based on 2010 CDC data also suggest that nearly 20 % of American boys are now diagnosed with ADHD by 15–17 years of age  layer to the story of ADHD treatment trends. Many children are being treated with more than one psychotropic drug at a time (Mojtabai and Olfson The more a drug is prescribed, the more it is available for diversion and abuse. Research has shown that as early as 15 years ago in some communities, up to 16 % of elementary through high school students had been approached by classmates to share or sell their ADHD medications (Musser et al. Analysis of national poison control data for 1998–2005 showed a sharp increase in the number of children between 13 and 19 years of age who were reported to poison control due to ADHD medication abuse—an increase that was disproportionately higher than drug abuse generally or for teen substance abuse in particular (Setlik et al. Even when used as prescribed, ADHD drug treatment often brings with it adverse side effects. The side effects may include undermining of an individual’s motivation to take other steps to address behavioral issues, deflating of one’s sense of self-efficacy, and/or flattening of one’s affect or natural exuberance. ADHD drugs also carry the potential for side effects such as sleep disturbance and growth suppression, as well as more serious side effects like elevated risk for drug dependence, psychosis, cardiac arrest, and violence against oneself or others (Moore et al. prior to the initiation of drug treatment, 75 % of children fully resolved their ADHD symptoms (Pelham Despite the fact the FDA requires that mainstream ADHD stimulant drugs carry a “black box” warning label noting the drugs’ risks for addiction, psychosis, and cardiac arrest, many professionals, parents, and patients underestimate the power of prescription pills due to “successful” marketing campaigns (e.g., Lacasse and Leo s Pelham . Yet, ths Pelham . In facts Pelham , 2002—ths Pelham .In addition to overselling drug benefits, the pharmaceutical industry minimizes drug risks (Lacasse and Leo ADHD experts with ties to the pharmaceutical industry and/or CHADD repeatedly launched ad hominem attacks on work by a psychologist whose research findings conflicted with drug industry interests. These attacks ultimately led to a decade of significant ADHD research and community-based interventions being mischaracterized in professional venues and media outlets. The net effect was that research on psychosocial interventions that also raised questions about the effectiveness of ADHD drug treatment was terminated and study findings were suppressed. This helped pave the way for continued escalation and expansion of ADHD diagnosis and drug treatment among American children, youth, and adults. The rate of ADHD diagnosis now exceeds all reasonable estimates of the true prevalence of the disorder. As a consequence, ADHD drugs are readily available on American high school and college campuses where they are increasingly abused with serious and sometimes lethal consequences.With mounting evidence of serious risks associated with widespread use of psychotropic drugs, the case of the attack on LeFever and suppression of the data she generated can serve as a wake-up call for mental health professionals. This case provides an object lesson about why tenure is so important in protecting academic freedom. Without tenure, the risks to the independent academician can be great if billions of industry dollars may be threatened (Antonuccio et al.


We aimed to investigate the influences of attention deficit/hyperactivity disorder (ADHD) on response evaluation, as reflected by the postimperative negative variation (PINV), a slow event-related potential.We investigated PINV as an indicator of performance uncertainty in an audio-visual contingent negative variation (CNV) paradigm with an interstimulus interval of 3 seconds. A constant, unilateral, quick motor reaction with either the right or the left thumb was required after an auditory forewarned (S1) visual imperative stimulus (S2). We examined 18 ADHD patients (combined or hyperactive-impulsive subtype) aged between 8 and 14 years and an age-, sex and IQ-matched control group of 19 healthy subjects using 64-channel high-density EEG. A first run was recorded drug-free, a second one under methylphenidate (MPH) medication in the ADHD group.We found a significantly increased negativity of the PINV-component over the ventrolateral prefrontal cortex in ADHD children compared to the healthy control group. PINV amplitude was influenced by movement side, most likely due to the slightly more difficult task when left hand responses were required. After the intake of MPH, PINV amplitudes of ADHD children normalized.We conclude that children with ADHD are likely to be more uncertain about the correctness of their performance and interpret the increased PINV as a hint towards compensatory mechanisms for a deficit in the evaluation of contingencies. Further studies are needed to assess the exact extent to which remainders of eye-movement related potentials contribute to PINV amplitude despite the correction for eye-artifacts. Attention deficit/hyperactivity disorder (ADHD) is one of the most common  and at tClear deficits in executive functions like planning, inhibition and evaluation of movement have been found. On the other hand, it is still controversially discussed to which extent motivational aspects and deficits in delay aversion are responsible for the development of ADHD-typical symptoms .Certain event-related potentials have been discussed as markers for the disorder but previous studies have pointed out heterogeneous neurophysiological profiles in ADHD patients ,4.Recently, a decreased error related negativity (ERN) over the anterior cingulate cortex (ACC) has been interpreted as ADHD children's diminished capacity to monitor their error responses and their failure to predict the likelihood that an error occurs in a given context -7.These findings suggest deficits in the children's cognitive processing of movement caused by diminished internal monitoring processes .In the current study we chose the PINV (postimperative negative variation) component as another important marker of movement/action monitoring processes, representing the individual's uncertainty about the correctness of a given answer , aimed tEnhanced PINV amplitudes have been found in a number of studies, reflecting a lack of control over aversive events, an unexpected change in controllability ,12 and rEspecially schizophrenic ,15 and dPINV amplitude is sensitive to ambiguous contingencies and is thought to reflect an unexpected outcome, which causes performance uncertainty . PINV usWe hypothesized that• ADHD children's contingency evaluation and their cognitive performance monitoring is disturbed, resulting in an increased PINV amplitude of ADHD children compared to age-matched healthy controls.• Methylphenidate (MPH) has a positive influence on the cognitive evaluation represented by a normalized PINV-amplitude after MPH-intake in the ADHD group.We analyzed eighteen right-handed , led toAs Quinn et al.  found noTwelve out of 18 ADHD children were treated with extended release MPH with a mean dosage of 0.85 mg/kg body weight (0.25 to 1.29 mg/kg), the other six with immediate release MPH with a mean dosage of 0.4 mg/kg (0.15 to 0.74 mg/kg).Nineteen right-handed  healthy, age-, gender- and IQ-matched children and adolescents , who took no psychoactive medication and did not suffer from any neurological or psychiatric symptoms, were recruited as control group at Heidelberg's elementary and secondary schools.In both groups we screened for visual impairments (corrected visus ≥ 0.8).All subjects and their parents provided written informed consent according to the Declaration of Helsinki and the study was approved by the local ethics committee.We recorded a CNV paradigm, using an auditory warning stimulus S1  and a visual imperative stimulus S2 . The interstimulus interval was 3 seconds, intertrial intervals varied randomly from 7 to 11 seconds.Subjects were instructed to correctly respond as fast as possible when S2 occurred on the screen by pressing a button on the STIM response pad  with the thumb of either the right or the left hand .40 trials per hand were recorded in a counterbalanced order across subjects. Two runs were recorded: In the control group both runs, T1 and T2, were drug-free. In the ADHD group, the first one (T1) was drug-free (after at least 24 hours after the last intake of MPH), the second one (T2) after 70 minutes after the intake of the individual used dose of MPH. In other studies the same experimental period of 70 minutes after the intake of MPH was chosen, so comparability is ensured.Participants fixated a cross on a computer screen in order to minimize eye artifacts. Neuroscan Synamp Amplifiers  were used to record continuous DC 64-channel EEG with a sampling rate of 250 Hz. An anti-aliasing filter was set at 70 Hz (low-pass). Surface Ag-AgCl sintered electrodes were fixed using an equidistant electrode cap  and are named according to an extended international 10-20 system. The vertical and horizontal electrooculogram (EOG) was recorded by electrodes 1 cm next to the outer canthi and above/below the left eye.Impedances were kept below 5 kΩ. Data were recorded against a reference near Cz and transformed offline to average reference. Recordings 1 s before S1 served as baseline. For the analysis of PINV, the EEG-signal was digitally filtered (30 Hz high cut-off), segmented into epochs of 7.5 s (1 s pre S1 to 3.5 s post S2), corrected automatically for DC-drifts by linear regression , and for eye movements and blinks .Artifacts were rejected automatically if the signal amplitude exceeded 150 mV. This procedure was confirmed by visual inspection; only artifact free trials entered further analysis. Bad channels were interpolated using nearest neighbours. Trials were rejected from further analysis if subjects responded with the wrong hand or after more than 3.5 s after S2.Two ADHD patients and one control child  had to be excluded from further evaluation due to recording errors or excessive artifact-prone data. N = 18 ADHD children and n = 19 controls were included for further statistical analysis.As a first step, planned comparisons for group differences between the PINV-amplitudes of unmedicated ADHD versus control children over the left and right ventrolateral prefrontal areas  were exNext, in order to assess the influence of medication on PINV topography in more detail, results were examined by multivariate analysis of variance (MANOVA), using the between subject factor GROUP  and the within subject factors SIDE of the response movement (left vs. right hand), HEMISPHERE (left vs. right VLPFC), RUN (T1 vs. T2) and ELECTRODES  followed by simpler separate MANOVAs for left and right hand response CNV tasks.Significant main effects or interactions in the MANOVA were subsequently further examined by post-hoc tests (Newman Keuls).Mean reaction times (± standard deviation) were 317 ± 65 ms (right hand button presses) and 333 ± 84 ms (left hand button presses) for children with ADHD as well as 305 ± 63 ms (right hand button presses) and 320 ± 81 ms (left hand button presses) for healthy control children.A repeated measurements ANOVA with the factors SIDE of the response movement and GROUP  revealed shorter reaction times for responses with the dominant right than with the left hand  = 5.9; p = 0.02). In contrast, GROUP had no significant main effect on reaction times  = 0.3; p > 0.59) and did not interact with response movement side either  = 0.0; p > 0.90).Group differences of the PINV amplitudes over the ventrolateral prefrontal areas between unmedicated ADHD patients and the control group T1) are presented for left  in the ADHD group in comparison to the healthy control group, when the unilateral motor response was given by the left hand p = 0.01; t = 2.7). For the ipsilateral, left prefrontal area there was no significant difference . Figure ; t = 2.7For the unilateral response movement with the right hand, there were no significant group differences , the visual examination of the single trials also confirmed that the time-course of the potentials in the leads over the ventrolateral prefrontal areas could not be explained by remainders of insufficiently corrected eye artifacts, as the time-courses differed in single trials as well.During T2, about 70 minutes after the intake of MPH, the PINV amplitude in children with ADHD decreased to a normal level Figure .The overall MANOVA model  yielded an interaction between GROUP, SIDE of the response movement and ELECTRODE  = 6.0; p = 0.006. This interaction effect was further examined in separate MANOVAs for left and right hand response CNV tasks.A main effect for the factor HEMISPHERE  = 12.8, p = 0.001) pointed towards higher PINV amplitudes over the right VLPFC  = 3.8, p = 0.059). Newman Keuls post-hoc tests showed that this effect was due to a decrease in PINV amplitude after MPH intake in the ADHD group (p = 0.03), which could not be found in the healthy control group (p = 0.85).An interaction of the factors HEMISPHERE x ELECTRODE  = 7.3, p = 0.002) indicated a different PINV topography for the left and right hemisphere. The strongest negativity was found at AF8 for the right hemisphere and at FP1 for the left hemisphere  = 10.1; p = 0.0004). Newman Keuls post-hoc tests showed that this effect has been identified as a consequence of a higher PINV amplitude especially in FP1/2 in T1 in the ADHD group. At FP1/2 during T1 there was a difference between the diagnostic groups (p = 0.005). For other combinations, e.g. at FP1/2 during T2 (p = 0.34) or at AF7/8 during T1 (p = 0.16) the level of significance was not reached for any group differences.Table A significant interaction of the factors GROUP x ELECTRODE  = 3.9, p = 0.03) irrespective of the run (T1/T2) indicated that the PINV amplitudes of children with ADHD were larger than those of healthy control children at FP1/FP2 but not other surrounding electrodes: Newman Keuls post-hoc tests showed a significant difference between the two diagnostic groups at the electrodes FP1/FP2 (p = 0.015), which did not exist for the other electrode positions, e.g. at F9/10 (p = 0.99).A main effect for the factor RUN  = 6.54, p = 0.02) pointed towards lower amplitudes at T2.Another main effect for the factor HEMISPHERE  = 7.11, p = 0.01) pointed towards higher amplitudes over the right hemisphere.Our most important findings werea) a significantly elevated negativity during the PINV over the VLPFC in unmedicated children with ADHD in comparison to healthy, age- and gender-matched subjects, especially when the unilateral response movement was given with the left hand. Longer reaction times indicated, that left hand responses represented the slightly more difficult task for our right-handed subjects. For right hand responses, there was also an elevated PINV amplitude in children with ADHD, but the PINV increase was more limited to leads Fp1/Fp2. Very easy tasks may decrease group differences. The differences in the healthy controls' PINV amplitudes between left and right hand responses (higher for the right handes) were not statistically significant and thus not further interpreted.b) a normalization of the elevated negativity under MPH for elevated PINV amplitudes in the left hand response task, i.e. where the most pronounced group differences between unmedicated patients and healthy controls had been found.Recent electrophysiological studies have suggested deficits in response monitoring and a diminished capacity to monitor error responses in children with ADHD, represented by decreased amplitudes of the ERN over the ACC, a region which is important for the discrimination between stimuli and the monitoring of actions and errors .Our finding of a significantly elevated PINV amplitude over the VLPFC could be interpreted as a compensatory mechanism in the response monitoring process. Thus the deficits in error detection could by compensated by increased evaluation processing in other brain areas.As the ACC and the VLPFC represent important parts of a monitoring network, responsible for the evaluation of the correctness of a given answer and the impairment of cognitive control in case of failure, the two cortex areas interact dynamically with each other and thus ensure the permanent self monitoring and adjustment of all target-oriented actions ,27.The VLPFC's role in particular is thought to be the processing of negative feedback in order to correct action with the objective of optimisation of performance; it is implicated in contingency detection and in the evaluation of stimuli ,29.An overall right-sided preponderance of PINV has been found also in previous studies  and poinSince the PINV appears in simple reaction time tasks, it seems to be a fundamental mechanism that plays a role in many goal-directed actions and is not limited to the two-stimulus situation of the CNV-paradigm.The increased compensatory efforts for self-monitoring and contingency detection, represented by the enhanced PINV amplitude, may contribute to ADHD children's inability to concentrate on relevant stimuli in their environment.increased PINV over the right VLPFC while fMRI-studies highlight prefrontal processing deficits in more challenging tasks, despite clear differences between the deficits in subjects suffering from schizophrenia and subjects suffering from ADHD.Using functional magnetic resonance imaging (fMRI), a lower response in the right mesial prefrontal cortex was found during a stop task in hyperactive adolescents in comparison to healthy peers and it was concluded that ADHD is associated with subnormal activation of the prefrontal systems responsible for higher-order motor control . From scIt has to be mentioned critically that in the inspection of the single trials we found some examples in which the potentials over the ventrolateral prefrontal area followed the time-course of the EOG before and after eye artifact correction. In general, PINV occurred independently from the EOG with a different time-course, as illustrated by our findings in the group grand average findings in Figure MPH, as an indirect dopaminergic agonist, could conceivably lead to an effect on error awareness, contingency evaluation and thus to modified PINV-amplitudes:An increased ERN caused by stimulants could be found in adult patients , howeverIn other studies it was concluded that the inaccurate behaviour of ADHD children in conflict tasks might be related to reduced error-awareness and higher sensitivity to response conflict. The amelioration after the intake of MPH was interpreted as its positive influence on brain networks, enabling children with ADHD to allocate more attention to significant events .MPH's influence on early error detection, however, seems to play a lesser role than the positive effect on subsequent processing steps. It has been concluded that the effect of MPH on self-monitoring processes is mediated rather by the noradrenergic than by the dopaminergic system .However, no final statement can be made to which extent MPH has an influence on the amplitude of PINV:Another important point, interpreting the approximation of the PINV-amplitudes in T2, could be learning effects due to the test repetition. In the second test run T2 the paradigm was already familiar to the children. They knew the stimulation and what reaction was expected and already practiced it in T1. Moreover, practice effects could differ between ADHD and healthy control children.Accordingly, the increased performance uncertainty which we found in T1 could be decreased to a normal level (the uncertainty level of controls) in T2. The control group could not have shown any change between T1 and T2 due to a floor effect.This interpretation would be consistent with the above-discussed theory of the PINV representing a deficient contingency evaluation.In any case, the fact that differences in PINV amplitude were reduced and not produced by MPH shows that PINV differences were not due to acute medication effects of MPH . FurtheIn the present study, we examined children with ADHD with regard to their slow movement related potentials in an audio-visual two-stimulus paradigm in comparison to age-matched, healthy controls.We found a significant increase of the negative variation after the target stimulus S2 (PINV) over the right ventrolateral prefrontal cortex area in the ADHD group for left hand responses (the slightly more difficult task).As elaborated above, the detected increase of the prefrontal PINV-amplitude can be interpreted as a deficit in contingency-evaluation representing ADHD children's higher uncertainty about the correctness of their own actions caused faulty monitoring processes.The presented results can be used to better understand ADHD children's specific needs and incertitude. It may help to take another step into creating optimized learning conditions by reinsurance from the outside by immediate extremely clear feedback and drawing the child's attention to relevant stimuli to minimize the distraction by disturbed self-monitoring-processes.ACC: anterior cingulate cortex; ADHD: attention deficit/hyperactivity disorder; CNV: contingent negative variation; EOG: electrooculogram; ERN: error-related negativity; fMRI: functional magnetic resonance imaging; MPH: methylphenidate; PINV: postimperative negative variation; VLPFC: ventrolateral prefrontal cortexJW reports no competing interests.MW has recently finished an investigator-initiated trial sponsored by Esparma and signed a contract concerning the development of neuropsychological diagnostic and training tools with Schuhfried.FR reports no competing interests.VR has received honoraries for lectures from Lilly, Medice, Novartis, Shire. He has been member of an advisory board of Lilly, Novartis. He has received research support from Novartis.SB has received honoraries for lectures from Novartis and support for symposia by Shire.JW performed the EEG measurements, conducted large parts of data analysis and has drafted the manuscript.MW and VR were involved in data interpretation and manuscript preparation.FR was involved in fund raising, data interpretation and manuscript preparation.SB planned the study design, supervised the data acquisition and analysis, and critically revised the manuscript.All authors have read and approved the final manuscript.


Several clinical trials have demonstrated that long-acting stimulants are effective in reducing ADHD symptoms compared with placebo. Analog classroom and simulated adult workplace environment studies have shown that long-acting stimulants produce symptom reduction for at least 12 h. Long-acting stimulants exhibit similar tolerability and safety profiles to short-acting equivalents. While variations in gastric pH and motility can alter the availability and absorption of stimulants released from long-acting formulations, the systemic exposure to d-AMP following LDX administration is unlikely to be affected by gastrointestinal conditions. Long-acting formulations may also improve adherence and lower abuse potential compared with their short-acting counterparts. The development of long-acting stimulants provides physicians with an increased range of medication options to help tailor treatment for individuals with ADHD.Individuals with attention-deficit/hyperactivity disorder (ADHD) show pervasive impairments across family, peer, and school or work functioning that may extend throughout the day. Psychostimulants are highly effective medications for the treatment of ADHD, and the development of long-acting stimulant formulations has greatly expanded the treatment options for individuals with ADHD. Strategies for the formulation of long-acting stimulants include the combination of immediate-release and delayed-release beads, and an osmotic-release oral system. A recent development is the availability of the first prodrug stimulant, lisdexamfetamine dimesylate (LDX). LDX itself is inactive but is cleaved enzymatically, primarily in the bloodstream, to release  Attention-deficit/hyperactivity disorder (ADHD) is a common neurobehavioral disorder that is estimated to affect 5–12 % of children and persists into adulthood in more than half of cases  with distinct immediate- and delayed-release profiles  stimulant formulations were developed that combined a rapid onset of action with extended coverage throughout the day. One strategy for the biphasic delivery of stimulants is to mix beads with different drug release profiles. CR capsules contain beads that incorporate MPH (MPH-CR) or les Fig. . CR-mixeAn alternative technology designed to deliver the controlled and biphasic delivery of stimulant medication is the osmotic-release oral system methylphenidate (OROS-MPH). OROS-MPH utilizes osmotic pressure to control the rate of delivery of the active ingredient, racemic MPH. Each capsule consists of a three-compartment core that is enclosed by a semipermeable membrane that, in turn, is surrounded by a drug overcoat Fig. . After id-AMP is covalently bound to the amino acid lysine. LDX itself is therapeutically inactive but, after oral administration, enzymatic hydrolysis of LDX releases the therapeutically active moiety d-AMP   is the first prodrug stimulant. Rather than utilizing a mechanical or physical mechanism to achieve a prolonged duration of action, LDX is a prodrug in which  Pennick . The ratClinical trial evidence supports the efficacy of long-acting stimulants. Tables d-AMP, and pemoline in boys with ADHD, sustained-release MPH demonstrated efficacy versus placebo in some behavioral measures, some performance-based tasks, and structured assessments by counselors on the Abbreviated Conners’ Teachers Rating Scale (ACTRS), but not on the teacher-rated ACTRS  is effective versus placebo for reducing ADHD symptoms in children, adolescents, and adults Table  Biederm. An analStudies of the efficacy of controlled-release AMP (AMP-CR) in participants with ADHD are limited. Pelham et al. compared treatment arms with AMP-CR, IR-MPH, MPH-SR, and pemoline in boys. Although all treatments were superior to placebo in some behavioral measures, only pemoline and AMP-XR were superior to placebo by the teacher-rated ACTRS. The duration of efficacy was characterized as within 2 h of ingestion and up to 9 h post-dose  greater than the pooled effect size of the other medications  was negatively related to the average cumulative exposure to psychostimulants. Growth slowing for newly medicated versus untreated participants was found for the first 14 months, was attenuated at 24 months, and was non-significant at 36 months  was favored over placebo  did not produce subjective abuse-related liking scores  than that for short- (0.43 [0.35]) and intermediate-acting (0.47 [0.35]) stimulants. Similarly, the mean (SD) persistence (defined as the number of days out of 365 days plus the index day that the patient remained on their index therapy) on long-acting stimulants (239.5 [145.8]) was significantly greater (p < 0.0001) than for short- (186.7 [154.8]) or intermediate-acting (185.6 [153.4]) stimulants (Christensen et al. Non-adherence to medication for chronic illnesses is estimated to be approximately 50 % (World Health Organization Evidence-based ADHD guidelines recognize that medication strategies should be tailored for the individual. Among the factors to consider when selecting an appropriate medication for a patient with ADHD are drug class and the formulation required to give the desired pharmacokinetic and pharmacodynamic profiles. The choice of medications for ADHD includes both stimulants and non-stimulants. With regard to stimulants, although mean responses to MPH and AMP are similar, individuals may respond differently to the two drugs. As reviewed by Arnold , approxiThe development of controlled-release formulations of stimulants and the stimulant prodrug LDX has greatly increased the number of pharmacological treatment options for patients with ADHD. At equivalent systemic exposures, the efficacy and safety of long-acting stimulants appear to be equivalent to short-acting formulations. However, long-acting medications offer several potential benefits to patients. Long-acting stimulants offer efficacy for at least 13–14 h without augmentation. The convenience of once-daily dosing may contribute to improved adherence of long-acting stimulants compared with short-acting stimulants. Prodrug technology may also provide lower inter- and intra-patient variability in exposure than mechanical controlled-release systems. Furthermore, long-acting stimulants may be less prone to abuse than their short-acting counterparts. Thus, the development of long-acting formulations of stimulants provides important additional treatment options for the management of ADHD.


Reduced total brain volume is a consistent finding in children with Attention Deficit/Hyperactivity Disorder (ADHD). In order to get a better understanding of the neurobiology of ADHD, we take the first step in studying the dimensionality of current self-reported adult ADHD symptoms, by looking at its relation with total brain volume.In a sample of 652 highly educated adults, the association between total brain volume, assessed with magnetic resonance imaging, and current number of self-reported ADHD symptoms was studied. The results showed an association between these self-reported ADHD symptoms and total brain volume. Post-hoc analysis revealed that the symptom domain of inattention had the strongest association with total brain volume. In addition, the threshold for impairment coincides with the threshold for brain volume reduction.This finding improves our understanding of the biological substrates of self-reported ADHD symptoms, and suggests total brain volume as a target intermediate phenotype for future gene-finding in ADHD. Attention Deficit/Hyperactivity Disorder (ADHD) affects 1–4% of adults and has an even higher prevalence in children et al, in which attention problems in children vary along a severity continuum from mild to severe; children with ADHD were at the extreme of the continuum et al showed the reduced cortical thinning with increasing ADHD severity Currently, ADHD is thought to be the extreme of a continuum of behavior in the population In order to get a better understanding of the neurobiology of ADHD, we take the first step in studying the dimensionality of current adult ADHD symptoms, by investigating the association between a biological construct of ADHD, brain volume, and current self-reported ADHD symptoms in an adult population. In addition, ADHD is a highly heritable disorder In this study, 652 subjects aged 18–35 years from the Brain Imaging Genetics (BIG) study at the Donders Institute for Brain, Cognition and Behavior of the Radboud University Nijmegen Medical Centre were included. The BIG study is a study of self-reported healthy individuals included into earlier imaging studies at the Donders Centre for Cognitive Neuroimaging. Structural imaging data of these studies were pooled for which subjects had to give their consent. About 80% of the subjects have their consent to include their structural imaging data. Subjects were of European Caucasian descent and generally highly educated . Normalizing, bias-correcting, and segmenting into gray matter, white matter, and cerebrospinal fluid was performed using the VBM toolbox (VBM5.1 Toolbox version 1.19) in SPM using priors (default settings). This method uses an optimized VBM protocol Subjects were scanned at 1.5 Tesla (n = 302) and 3 Tesla (n = 350) MRI scanners and T1-weighted structural magnetic resonance imaging data (3D MPRAGE) were acquired . In order to explore effects of the distinct ADHD symptom domains on total brain volume, a similar analysis was performed including either Hyperactivity/Impulsivity (HI) symptom count or Inattentive (IA) symptom count as an independent variable. Permutation tests were performed to overcome multiple testing problems see . As a doIn addition, we tested whether total brain volume of subjects with 6 or more self-reported ADHD symptoms in either one symptom domain or 6 or more symptoms in both domains , differed from that of subjects with 4–5 self-reported ADHD (IA and/or HI) symptoms . The regression coefficients of the total number of self-reported ADHD symptoms were similar in the two independent samples scanned at different MRI field strengths . Brain volume decreased with an increasing number of self-reported ADHD symptoms , rather than by HI- symptoms  (p = .26). Neither total gray or white matter volume were associated with the number of self-reported ADHD symptoms .The total number of self-reported ADHD symptoms was significantly associated with total brain volume  . The assp = .008 and p = .04, respectively), indicating that the threshold for brain volume reduction coincides with the threshold for functional impairment in patients >0.05, data not shown) in our large sample. Indicating that brain volume was globally affected.There were no significant differences in the local gray or white matter volumes assessed by the VBM analysis (both This study shows (a) that current ADHD symptoms in healthy adults, assessed by self-report as a continuum in the population and therefore largely independent of disease or treatment, has a neurobiological substrate; reduced total brain volume, (b) that this substrate is global rather than localized in the brain, and (c) that the threshold for impairment coincides with the threshold for brain volume reduction in patients.The results of this study match the results of a previous study in healthy children and adolescents showing cortical thinning, not corrected for total brain volume, to be associated with symptoms of ADHD Total brain volume reductions were global rather than localized in the brain. This suggests general mechanisms affecting brain development in neuron number, number of neurites and/or neuronal connections. This is also consistent with hypotheses based on findings from genome-wide association studies in ADHD implicating neuronal migration and neurite outgrowth in disease etiology This study shows that self-reported inattention symptoms are the main predictor of total brain volume reductions. This could be explained by the known association between inattention and processing speed While this is the largest study of its kind and also the first to show neurobiological dimensionality of self-reported ADHD symptoms in an adult population, it also has a number of limitations. Firstly, we used a self-report measure of adult ADHD symptoms. Self-report measures are likely to be less accurate than interviews, but for the ADHD rating scale we know from research in patients that it has a substantial correlation with diagnostic assessment by a clinician Finding genes for ADHD has been proven difficult, our findings, in combination with those of previous studies showing brain volume to be heritable Figure S1a) Displayed are the number of subjects in this study (frequency) with their numbers of total self-reported ADHD symptoms (upper panel) and numbers of self-reported Inattentive symptoms and Hyperactive/Impulsive symptoms (lower panel). b) Displayed are subjects with 6 or more self-reported symptoms in both domains (upper bar), the number of subjects with 6 or more self-reported HI symptoms but less than 6 symptoms in the IA domain (middle bar) and the number of subjects with 6 or more self-reported IA symptoms but less than 6 symptoms in the HI domain (bottom bar).(DOC)Click here for additional data file.Text S1Supplementary Methods.(DOC)Click here for additional data file.


To explore the influence of age on treatment responses to atomoxetine and to assess the relationship between core symptoms of attention deficit/hyperactivity disorder (ADHD) and health-related quality of life (HR-QoL) outcomes.Data from five similar clinical trials of atomoxetine in the treatment of children and adolescents with ADHD were included in this meta-analysis.Atomoxetine studies that used the ADHD Rating Scale (ADHD-RS) and the Child Health and Illness Profile Child Edition (CHIP-CE) as outcome measures were selected.Treatment with atomoxetine.Treatment group differences (atomoxetine vs placebo) in terms of total score, domains, and subdomains of the CHIP-CE were compared across age groups, and correlations between ADHD-RS scores and CHIP-CE scores were calculated by age.Data of 794 subjects  were pooled. At baseline, adolescents showed significantly (p < 0.05) greater impairment compared with children in the Family Involvement, Satisfaction with Self, and Academic Performance subdomains of the CHIP-CE. Treatment effect of atomoxetine was significant in both age groups for the Risk Avoidance domain and its subdomains. There was a significant age-treatment interaction with greater efficacy seen in adolescents in both the Risk Avoidance domain and the Threats to Achievement subdomain. Correlations between ADHD-RS and CHIP-CE scores were generally low at baseline and moderate in change from baseline and were overall similar in adolescents and children.Atomoxetine was effective in improving some aspects of HR-QoL in both age groups. Correlations between core symptoms of ADHD and HR-QoL were low to moderate. Attention deficit/hyperactivity disorder (ADHD) is one of the most frequently diagnosed psychiatric disorders in childhood, characterized by 3 core symptoms: inattentiveness, hyperactivity, and impulsivity. According to a recent meta-analysis, ADHD afThe impact of ADHD goes beyond the direct effects of core symptoms on the individual's everyday functions and represents a serious burden on the patient's and the family's life, seriously impairing the emotional, social, and physical well-being of patients and hence their health-related quality of life (HR-QoL).HR-QoL has received increasing attention in children and adolescents with ADHD, both from clinicians and investigators -10. HR-QBased on consistent findings in the literature, effective treatments exist for the management of ADHD with both pharmacotherapy and psychosocial interventions. The treatment options for ADHD include psychostimulants  or atomoxetine, which is a non-stimulant treatment option for ADHD , both inAlthough it has previously been thought that ADHD is essentially a disorder of childhood, a growing body of literature suggests that the disorder persists through adolescence and into adulthood with some core features and associated impairments still evident ,7,27-29.The clinical symptoms of ADHD change over time ,28-32. SThus, it is important to understand the implications for the individual as they get older and to evaluate medication effects with respect to age.We therefore conducted a meta-analysis all atomoxetine clinical trials measuring HR-QoL using the Child Health and Illness Profile, Child Edition (CHIP-CE) Parent Edition that were in the Lilly data base to investigate the possible age effect on baseline impairments with regard to HR-QoL ,33-35, aData from 5 atomoxetine clinical trials  with similar inclusion and exclusion criteria and similar duration of treatment (8-12 weeks follow-up) were included in the meta-analysis ,36-39. TAll included patients met the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV)  diagnostStudies 1 and 2 recruited only stimulant-naïve patients. Study 3, which was carried out in Italy, did not explicitly require medication-naïve patients, but at the time of recruitment, there were no ADHD drugs approved by authorities in that country.The primary scale on which this meta-analysis was based is the CHIP-CE Parent Report Form ,34, a 76The structure of the CHIP-CE was developed in non-ADHD samples. The CHIP-CE scores are standardized to t scores with a mean (± SD) of 50 (± 10), with higher scores indicating better health. Normative data were derived from a sample of 1049 school-aged children from the United States ,34.The evaluation of the treatment effect of atomoxetine on core ADHD symptoms was based on the ADHD-RS , which eThe demographic and baseline data were summarized by descriptive statistics unadjusted for study. Group comparisons at baseline were based on two-way analysis of variance (ANOVA) using the terms age and study for continuous variables and based on the Cochran-Mantel-Haenszel test controlling for study in the case of categorical variables.Treatment efficacy over time was analyzed on an intent-to-treat basis. The intent-to-treat population included patients who had been randomized, had a baseline observation, and at least one postbaseline observation. The last observation was the one reported for change from baseline. Treatment-group differences were compared using a fixed effect analysis of covariance (ANCOVA) model including the terms treatment, study, age group, baseline ADHD-RS score, and the respective baseline CHIP-CE score. The model was run for a second time with the treatment-by-age subgroup interaction term added. Effect size (Cohen's d) was calculated for treatment overall and within age subgroups. Effect size was calculated as the ratio of the difference between atomoxetine and placebo at endpoint divided by the standard deviation of the residuals.A consistent treatment effect in the groups is stated, if the overall treatment effect is significant and the effect sizes are clinically similar in both age groups.Correlations between ADHD-RS scores  and CHIP-CE scores  at baseline, at endpoint, and for the change from baseline to endpoint, are shown by age subgroup using Pearson's correlation coefficient and the corresponding 95% confidence interval.All tests of hypotheses were considered statistically significant if the two-sided p-value was < 0.05. An alpha level of 0.10 was used to judge the statistical significance of an interaction. No correction was done for multiple testing as this is a post hoc analysis on existing data. The Statistical Analysis System  was used for all analyses.Data from a total of 794 patients were included in the analysis. The age range was 6 to 15 years. The mean age was 9.7 years SD 2.30 years). Most of the patients of the pooled sample were children (< 12 years): 611 (77.0%), and male 658 (82.9%). For the evaluation of the effect of atomoxetine on HR-QoL, as measured by the CHIP-CE, samples from only the placebo-controlled trials were included. In total, data of n = 183 and n = 92 children (6-11 years) and n = 72 and n = 40 adolescents (12-17 years) were analyzed in the atomoxetine and placebo groups, respectively. For the comparison of the correlations between core ADHD symptoms and HR-QoL, across age groups, we included the data of all studies in the analyses. Demographic data of the pooled sample are summarized in Table 0 years. In the population of the five studies, gender distribution was similar across age groups. The proportion of ADHD combined subtype according to DSM-IV was significantly higher and, accordingly, the proportion of the inattentive subtype was significantly lower in children compared with adolescents. This difference was also reflected in the ADHD-RS scores, where the hyperactive/impulsive subscore was significantly higher in children, leading to a significantly higher total score Table .Impaired HR-QoL was observed at baseline as the CHIP-CE total score and four of the five domain scores Table  had meanThe treatment effect of atomoxetine as reflected by the CHIP-CE was significant overall and consistent within both age groups for the total score, the Emotional Comfort sub-domain, and for the Achievement domain with its two sub-domains Academic Performance and Peer Relations. In the Risk Avoidance domain, there was a significant age interaction with the therapeutic effect of atomoxetine p < 0.10). This interaction was due to the significant interaction found in the Threats to Achievement sub-domain (p < 0.10). Specifically, in the Risk Avoidance domain and in its two sub-domains , effect sizes indicated a more pronounced therapeutic effect of atomoxetine for adolescents compared with children  in children and adolescents with ADHD . SeveralIn comparing children and adolescents with ADHD, this meta-analysis investigated three different aspects: the evaluation of HR-QoL at baseline, the association between HR-QoL and ADHD core symptoms, and the treatment effect of atomoxetine on HR-QoL. The first two aspects were based on all 5 studies, whilst the treatment effect could only be evaluated in the 3 placebo-controlled trials.In the population of the five studies, gender distribution was similar across age groups. As the studies were not designed to include the same proportion of boys across different age-groups, this finding is surprising. Usually one would assume that there would be a larger proportion of boys in a sample of children compared to a sample of adolescents. This could be due to the composition of samples in clinical trials as opposed to epidemiological samples.Analyzing the ADHD-RS in the present post-hoc analysis, children had significantly higher hyperactive/impulsive sub-scores and total scores compared with adolescents at baseline. This finding is in line with previous literature regarding the differences in symptom patterns across age groups. Specifically, hyperactive/impulsive symptoms show a definite decline over time, while inattentive symptoms may become even more pronounced during adolescence ,29-32. IBaseline impairments in HR-QoL as measured by the CHIP-CE were seen on several dimensions  in both age groups. Previous studies consistently reported on remarkable impairments in HR-QoL among children and adolescents with ADHD, especially in the emotional, behavioral, and achievement aspects . SimilarThe baseline correlations between the CHIP-CE and ADHD-RS scores indicated a consistent, small-to-moderate negative correlation between the core symptoms of ADHD and HR-QoL in both age groups without substantial age differences. This finding provides additional insight into the broad effect of ADHD symptoms. However, it should be noted that these correlations do not fully explain the background of the impaired HR-QoL in children and adolescents with ADHD. Besides the core symptoms (as measured by the ADHD-RS), other factors might play a role in the observed HR-QoL impairments. For example, comorbidities such as oppositional defiant disorder (ODD), conduct disorder (CD), anxiety, and depression were found to increase impairment and decrease HR-QoL in children and adolescents with ADHD as measured by the CHIP-CE in a cross-sectional analysis of observational data . This maBased on our analysis, atomoxetine was effective in improving certain HR-QoL dimensions in both age groups. This finding is in line with several previous studies ,18-25,48In both age groups, correlations between the ADHD core symptoms and the HR-QoL were small to moderate at endpoint and with regard to the change from baseline. There was no substantial age effect on the correlations, except for a clear trend in the Risk Avoidance domain and sub-domains. Specifically, the correlations between the ADHD-RS scores  and the Risk Avoidance domain and sub-domains were smaller in adolescents with regard to change from baseline. This reduction in the strength of the correlation between changes in core symptoms and HR-QoL may indicate a slight detachment from the primary therapeutic effect of atomoxetine on core symptoms, especially when taking into account that atomoxetine showed the highest effect sizes in improving HR-QoL in the Risk Avoidance domain and sub-domains. Our findings regarding the low and moderate correlations between core symptoms and HR-QoL , warrant further investigation to determine more precisely which additional factors contribute to the overall impairment in ADHD beyond core symptoms, and which particular factors have an adverse impact on the HR-QoL of the individuals and their family.The results of this meta-analysis need to be interpreted in light of a number of limitations. First, the samples of the five clinical trials showed heterogeneity in terms of cultural diversity, history of stimulant medication, and comorbidity. For example, the patients were from five different countries, where both public opinion on ADHD and approaches to treatment by physicians vary considerably. Such differences in terms of cultural diversity could have had an impact on the evaluation both of core symptoms as measured with the ADHD-RS, and health-related quality of life as measured with the CHIP-CE. Moreover, the pooled sample size of the adolescent treatment group from the three placebo-controlled trials was rather small, and thus, effect size estimations have to be interpreted with caution.Second, drug history of the patients was mostly unknown : this could have introduced some variability in the evaluation of treatment efficacy. It has been already suggested in the literature that medication-naïve patients show better improvement . HoweverThird, 8-12 weeks of follow-up might have been too brief for the evaluation of the improvement of HR-QoL. Though the findings of Perwien et al.  indicateFourth, in all studies, parents were the source of information on both core symptoms of ADHD and HR-QoL. This might have influenced the results in the sense that the parents and patients might have provided different responses, especially when evaluating adolescents. The views of the young people themselves, however, need to be sought in addition to parent reports, as the patient perspective reflects the subjective well-being of these children and adolescents and takes into account their autonomy as individuals .An additional limitation that introduces a difficulty in interpreting our results is that HR-QoL is a construct that, to date has not yet been well-defined. Hence, measuring this construct is still a challenge, as are all measurements of subjectively perceived psychological constructs . AlthougThis meta-analysis also had several strengths. Most importantly, the sample size was large. Secondly, three of the five studies were placebo-controlled. Thirdly, the analysis was based on individual patient data rather than publication-based meta-analysis. Fourthly, the inclusion and exclusion criteria of the five studies included in the meta-analysis  were verOverall, this meta-analysis found that, compared with children, adolescents with ADHD were somewhat more impaired at baseline, in regard to some domains of HR-QoL as measured by the CHIP-CE. Impairments were seen in the Risk Avoidance and Achievement domains and their sub-domains as well as in the sub-domains Emotional Comfort, Satisfaction with Self, Family Involvement, and Social Problem Solving, both in children and adolescents. Atomoxetine was generally shown to be effective in improving certain aspects of HR-QoL as reflected by the CHIP-CE. In the Risk Avoidance domain and Threats to Achievement sub-domain, there was a significant age effect with better efficacy seen in adolescents. Correlations between ADHD core symptoms and HR-QoL at baseline and for change from baseline to endpoint were small to moderate, suggesting that next to the effect of core symptoms, other factors might play a role in the background of the observed impairments in HR-QoL. Further studies are needed to investigate the long-term effects of atomoxetine on HR-QoL, as well as to develop more specific tools in the assessment of the effect of ADHD treatments on HR-QoL in children and adolescents.The research was funded by Eli Lilly and Company. PMW, AS, RE, and NS are full-time employees and stakeholders of Eli Lilly. VH has received research grants and speaker honoraria from Eli Lilly and has served on several advisory boards for Eli Lilly.PMW, AS, and RE developed the meta-analysis on which this manuscript is based. All Authors participated in interpreting the data. PMW and AS drafted the manuscript. RE, NS and VH revised the manuscript for important intellectual content. All authors have read and approved the final version of the manuscript.


Effective and accurate diagnosis of attention-deficit/hyperactivity disorder (ADHD) is currently of significant interest. ADHD has been associated with multiple cortical features from structural MRI data. However, most existing learning algorithms for ADHD identification contain obvious defects, such as time-consuming training, parameters selection, etc. The aims of this study were as follows: (1) Propose an ADHD classification model using the extreme learning machine (ELM) algorithm for automatic, efficient and objective clinical ADHD diagnosis. (2) Assess the computational efficiency and the effect of sample size on both ELM and support vector machine (SVM) methods and analyze which brain segments are involved in ADHD.High-resolution three-dimensional MR images were acquired from 55 ADHD subjects and 55 healthy controls. Multiple brain measures  were calculated using a fully automated procedure in the FreeSurfer software package. In total, 340 cortical features were automatically extracted from 68 brain segments with 5 basic cortical features. F-score and SFS methods were adopted to select the optimal features for ADHD classification. Both ELM and SVM were evaluated for classification accuracy using leave-one-out cross-validation.We achieved ADHD prediction accuracies of 90.18% for ELM using eleven combined features, 84.73% for SVM-Linear and 86.55% for SVM-RBF. Our results show that ELM has better computational efficiency and is more robust as sample size changes than is SVM for ADHD classification. The most pronounced differences between ADHD and healthy subjects were observed in the frontal lobe, temporal lobe, occipital lobe and insular.Our ELM-based algorithm for ADHD diagnosis performs considerably better than the traditional SVM algorithm. This result suggests that ELM may be used for the clinical diagnosis of ADHD and the investigation of different brain diseases. Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent behavioral disorders in childhood and adolescence. Approximately 5% of school-age children and 2–4% of adults are diagnosed with ADHD or have ADHD-associated symptoms To aid the development of a new ADHD diagnostic method, objective experimental differences between ADHD and control subjects (CS) should be defined. To date, most studies have explored differences in the connectivity of complex human brain networks between ADHD and normal children In the past several years, numerous anatomic imaging studies have accrued evidence for structural brain abnormalities in ADHD. Results for children with ADHD from recent findings showed a decrease in total cortical volume of over 7 and 8% and a decrease in surface area of over 7% bilaterally Moreover, structural MRI has a high resolution and uses relatively stable imaging technology. Several studies using structural MRI have demonstrated anatomical differences between ADHD and normal children To date, traditional machine learning techniques have been utilized to distinguish the MRI data of two groups of subjects who have multiple obvious defects. This involves time-consuming training sessions for the experimental dataset, classification inefficiency with changes in sample size and selection of one or more parameters for the classifier In this study, we focused on developing an automatic, effective, rapid and accurate ADHD diagnosis method to overcome the deficiencies of traditional methods. We first proposed an ADHD classification model using the extreme learning machine (ELM) with F-score and SFS feature selection methods to provide objective clinical diagnosis. The simple and efficient ELM method was introduced to build a robust model for ADHD classification. It is based on 5 basic cortical properties: thickness, surface area, folding index, curvature and volume. Our findings demonstrate that the ELM learning model performs better and has an extraordinarily higher accuracy than the commonly used SVM learning algorithm in terms of computing efficiency and the dependence of experimental dataset size. We also found that the surface area (SA) and volume (V) data of the human brain provide the most salient information for discriminating between ADHD and CS.http://fcon_1000.projects.nitrc.org/indi/adhd200/). The dataset contains a total of 152 subjects including 59 ADHD and 93 healthy controls. Fifty-five of 59 ADHD subjects with were selected for the current study according to the age range from 9 to 14 (mean age 11.8) and 4 overage subjects were excluded. Other fifty-five of 93 age matched healthy adolescents were selected to form the control group (mean age 11.5). Patients with a history of medication use were also included. The inclusion criteria were as follows: 1) right-handedness; 2) no lifetime history of head trauma with loss of consciousness; 3) no history of neurological disease, and no diagnosis of schizophrenia, affective disorder, pervasive development disorder, or substance abuse and 4) full-scale Wechsler Intelligence Scale for Chinese Children-Revised (WISCC-R) score of greater than 80.The data used in the present study were part of the dataset from the Peking University (Peking_1 and Peking_2) ADHD-200 Global Competition Test Dataset (http://fcon_1000.projects.nitrc.org/indi/adhd200/). A description of the Peking University ADHD-200 Global Competition data acquisition can be found in the scan parameters item of the website. Briefly, the MRI data were collected using a SIEMENS TRIO 3-Tesla scanner. The MRI protocol included acquiring a high-resolution T1-weighted MPRAGE volume . For processing, the original MRI data were first subjected to a series of preprocessing steps, including motion correction, T1-weighted image averaging, registration of the volume to Talairach space and stripping the skull with a deformable template model  is a simple and efficient feature selection criterion obtained by measuring the discrimination between two sets of real numbers Sequential forward selection (SFS) is a simple efficient feature selection approach As shown in Support vector machines (SVM) are popular machine learning methods for classification and regression that are based on the learning theory originally developed by Vapnik and his colleagues in 1995 http://www.csie.ntu.edu.tw/~cjlin/libsvm/).In the present study, the LIBSVM software package was applied to implement the SVM algorithm, and simple efficient linear function and radial basis function (RBF) were respectively selected as the kernel functions. LIBSVM, an integrated software package that is extensively used for regression and classification in machine learning, was developed by Dr. Chih-Jen Lin and his colleagues (LIBSVM v3.12 available at Extreme learning machine (ELM) is an extremely fast learning algorithm with good generalization performance that was developed by Huang and his research group However, for most cases the number of hidden nodes is far less than the number of distinct training samples Our extreme learning machine (ELM) training and classification computing program was compiled using MATLAB based on the relative research theories of Dr. Huang. In this study, we selected a simple sigmoidal kernel function Additionally, as the threshold for each decision function of the binary method may affect the performance of classification a lot, it should be determined according to the receiver operating characteristics (ROC) curves. In the current study, thresholds of all three algorithms were set to the default 0 since the discrimination showed balance performance between true positive rate and false positive rate then.The permutation tests have been adapted to assess statistical significance of the classifier and its performance in many research fields The F-score feature ranking method was used to arrange the 340 features of ADHD and CS in descending order according to the F-score value. We combined each feature with all preceding feature rows as an experimental dataset. For example, the seventh feature . Both ratio of SVM grid-search time to ELM training time for the first 50 experimental datasets increased rapidly with increasing experimental dataset size . This meThe results of ADHD classification show that all three classification algorithms achieve the maximum before the forty-sixth experimental dataset. To further enhance the classification accuracy, the sequential forward selection (SFS) method was executed on the first 46 features of the F-score method and the results are shown in The testing accuracy of all three methods in ADHD classification were improved as is detailed in To further compare the three methods, the receiver operating characteristics (ROC) curves were generated by varying a threshold applied to the continuous prediction score that each of the algorithms generated . The areThe permutation distribution of the estimate using the ELM classifier is shown in In this study, we established an automatic and efficient ADHD classification method using the ELM learning algorithm on structural MRI data to provide accurate, objective clinical diagnosis. In this study, we achieved two main findings. First, our results indicate that it is possible to classify ADHD and control subjects with a high degree of accuracy using an automatic procedure that combines structure with ELM. Our results from ADHD and control classification achieved an excellent prediction accuracy of 90.18%. This high testing accuracy will improve the actual auxiliary diagnostic accuracy. Second, we demonstrated that the ELM method is much faster (more than 1000 times faster) than other prediction models, such as SVM, making the ELM algorithm a high efficiency method for ADHD diagnosis.The cortex can be divided into five major segments according to the anatomical structure and function of the human brain, including the frontal lobe, the occipital lobe, the parietal lobe, the temporal lobe and the cingulate. To further understand the relationship between different brain segments and the etiology of ADHD, we pick off the most discriminative 11 brain structure features from the classification results and categorize them in major lobes shown in The cuneus and lingual are portions of the human brain in the occipital lobe. Both of them are linked to receiving and processing the visual information, especially related to letters. The disorder of these portions of brain can lead to a confusion of visual information which may further cause inattention. Additionally, insular cortex is a portion of the cerebral cortex folded deep within the lateral sulcus separating the temporal lobe from frontal lobes. Numerous studies have established that frontal lobe, temporal lobe and insular are mainly associated with attention, motivation, sensory, emotions and memory, which are likely to be involved in ADHD behavioral symptoms, such as inattention, hyperactivity, impulsivity and impaired executive function. In addition, since the ELM classification relied heavily on the anatomical MRI data of these regions, these findings could indicate that these cortical regions mentioned above have the most ADHD-related structural changes in the human brain.The computational efficiency of a pattern recognition method directly influences the performance of ADHD diagnosis in practice. An ideal ADHD machine classification method should achieve both high discrimination accuracy and fast classification speed. In the data presented in For traditional pattern recognition methods, a large training sample is usually necessary to ensure classification accuracy because most common pattern recognition algorithms are probabilistic and use statistical inference to determine the best label for a given instance The average training and testing rates of three methods are all influenced to a certain extent by the experimental dataset size, while the overall ADHD classification accuracy of ELM is significantly higher than that of both SVM algorithms during the whole experiment process. In contrast to SVM, the ELM algorithm performs more smoothly in ADHD discrimination with the changing of experimental dataset size . This suIn our study, thirty of 55 adolescents with ADHD received medical treatment. For ADHD medication, stimulant medications are the most frequently choice of pharmaceutical treatment. There are a number of non-stimulant medications, such as atomoxetine, that may be used as alternatives The current study only considers structural MRI data from the subjects in the ADHD-200 Global Competition. Several resting state functional connectivity studies suggest that ADHD is associated with large-scale brain sub-networks dysfunction To our knowledge, this is the first study to propose an ADHD classification model using the extreme learning machine (ELM) with F-score and SFS feature selection methods to perform objective diagnosis. Our results show that the ELM algorithm has considerably good performance and an extremely high efficiency in discriminating ADHD subjects from healthy controls. Compared with traditional ADHD diagnosis methods, ELM has the following advantages: 1. extremely fast discrimination speed and satisfactory high classification accuracy; 2. ADHD discrimination using objective MRI data; 3. excellent ADHD classification performance with small training sample sizes and robustness with changes in sample size and 4. does not need to select the training parameters because the hidden nodes are randomly chosen. Moreover, we observed that the frontal lobe, temporal lobe, occipital lobe and insular are potentially involved in ADHD-related structural changes in the human brain. These findings suggest that our ADHD classification method using the ELM learning algorithm is not only a promising method for ADHD aided diagnosis and the study of disease etiology but can also identify which features of the brain are involved in different diseases.Appendix S1(DOC)Click here for additional data file.


In this podcast we talk to Prof Eric Taylor about the changes to the diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) in DSM-5 and how these changes will affect clinical practice.http://www.biomedcentral.com/sites/2999/download/Taylor.mp3.The podcast for this interview is available at: Prof Eric Taylor is Emeritus Professor of Child and Adolescent Psychiatry at King’s College London, Institute of Psychiatry and is an honorary consultant at the Maudsley hospital. He has developed specialist clinics for child neuropsychiatry and higher training for child and adolescent psychiatry. His research has included longitudinal epidemiology, nosological distinctions within the ADHD spectrum, neuropsychology and neuroimaging, molecular genetics and treatment trials. Prof Taylor has chaired the NICE guidelines development group for ADHD, was senior author for the various European Guidelines from EUNETHYDIS and also a Trustee of the National Academy of Parenting Practitioners and a Non-Executive Director of the South London and Maudsley NHS Foundation Trust. He is a Fellow of the Academy of Medical Sciences, an Honorary Fellow of the Royal College of Psychiatrists, and a Board Member of the Association for Child and Adolescent Mental Health and Place2Be . Prof Taylor’s publications include more than 200 empirical scientific papers and several reviews, chapters, editorials and several books Figure .http://www.biomedcentral.com/sites/2999/download/Taylor.mp3.The podcast for this interview is available at:(i) ADHD is now classified as one of the neurodevelopmental disorders rather than being included as a disruptive disorder.(ii) The diagnostic criteria that apply to adults have been relaxed and this reflects growing evidence that some people are still impaired by ADHD symptoms even if the symptoms have reduced in number. The criteria for children remain at six out of nine from a list of inattentiveness symptoms and/or six out of nine from a list of symptoms of hyperactivity and impulsiveness. Adults over 18, however, need only to display five out of the same lists. Furthermore, for adults being diagnosed for the first time, the criteria for onset in childhood have also been relaxed. Previously there had to have been “some impairment” before the age of seven. Now it is only necessary to show that symptoms were present (not impairment) before the age of twelve.(iii) The traditional subtypes of predominantly inattentive, predominantly impulsive hyperactive and combined have been downgraded from subtypes to presentations. This reflects new knowledge that one subtype frequently changes into another.(iv) Autism is no longer an exclusion and both autism and ADHD can be diagnosed together.(v) Rapid and labile mood changes, which often accompany ADHD, now have a new diagnosis of their own. This is termed “Disruptive mood dysregulation disorder” (DMDD), which describes a group of children with frequent and severe outbursts of temper whose mood between tempers is angry or miserable.th version of the International Classification of Diseases (ICD-10) and in professional guidelines. The fundamental conceptualisation of the disorder has not been changed. There may be a modest increase in the recognition of ADHD in adult life, but this is happening anyway without the additional spur of DSM changes.The impact is not likely to be great. Practitioners in the UK do not usually add up the symptoms in the way that DSM envisages. Instead, they match the case to their prototype idea of the disorder, as described by the 10They are mostly tweaks to the diagnostic description and most of the changes are welcome. Some opportunities have been missed and these include the possibilities of moving to recognise the distinctive problems of attention deficit in the total absence of hyperactivity, the opportunity to move to a more dimensional system of describing psychopathology, and the notion of providing a clear system to describe severity, staging and impairment. The specific changes include:(i) While ADHD has many features in common with disruptive disorders, I believe that the shift to “neurodevelopmental” is correct and timely. Like other neurodevelopmental problems, ADHD has an early onset, steady course, high male/female ratio, strong genetic influences and multiple associations in altered brain function.(ii) I think it is correct to have made the adult diagnosis a little easier to achieve. User groups complain strongly that the NHS fails to recognise their difficulties even when they are presented to general psychiatry.(iii) I agree that research has not been kind to the idea that there are valid subtypes. However, some of this failure of validity has to do with poor operational definitions. The “predominantly inattentive” subtype can apply to children who have as many as five of the hyperactivity symptoms, which is quite a lot, but fall just under the cut-off point. Nevertheless, inattentive children with no hyperactivity at all can still be seriously impaired but in a different way. Their school work and occupational success suffer from a wide range of neuropsychological problems. These problems deserve scientific study, but have not received this partly because they are not included in the existing diagnostic schemes.(iv) Autism used to be excluded, but autism and ADHD frequently coexist. It is therefore important to recognise both disorders as patients with ADHD are treated successfully even when they have autism spectrum disorders.(v) The new diagnosis of DMDD does not really have a full scientific basis. It has been included largely to tame an epidemic in the USA in which irritable children are diagnosed as having bipolar disorder, with a consequent massive increase in the use of powerful neuroleptic drugs even in the under-fives. I am inclined to doubt whether the existence of a new diagnosis will in fact reduce the epidemic of diagnosis, but luckily it has not reached the UK anyway.As indicated above, I do not think that there will be a big impact because of the different bases of practice in the USA and in the UK. There is, in any case, a continuing increase in the recognition and treatment of ADHD, and concomitantly in the prescription of stimulant medication. This change represents more accurate recognition, especially in adult life and even after the increase the UK is close to the bottom of the European tables in diagnosis and treatment. I hope that we will not catch up with the USA where ADHD is the commonest childhood diagnosis (around 5%) and stimulant medication is even more common (around 7%). I do not see anything in the changes that are likely to take us in that direction. The new condition of DMDD may, in practice, be hard to distinguish from the states of agitation and angry depression that often coincide with severe conduct problems in young people. Nevertheless, irritability is a very common reason for referral to Child and Adolescent Mental Health Services (CAMHS), and it is likely to be helpful if there is now a language within which to think about such presentations.It seems likely that advances in understanding the neurophysiological and neuropsychological alterations that are seen in ADHD will lead us towards a more discriminating recognition of conditions. If we can shift to formulations of the brain mechanisms involved, this could lead us to diagnoses that predict more closely to treatment response more closely and suggest new treatments for components of the disorder.See references-6.ET has no competing financial interests to declare but was a member of work groups for the revision of DSM.