The International Multi-centre ADHD Genetics (IMAGE) project with 11 participating centres from 7 European countries and Israel has collected a large behavioural and genetic database for present and future research. Behavioural data were collected from 1068 probands with the combined type of attention deficit/hyperactivity disorder (ADHD-CT) and 1446 'unselected' siblings. The aim was to analyse the IMAGE sample with respect to demographic features  and psychopathological characteristics . A particular focus was on the effects of the study design and the diagnostic procedure on the homogeneity of the sample in terms of symptom-based behavioural data, and potential consequences for further analyses based on these data.Diagnosis was based on the Parental Account of Childhood Symptoms (PACS) interview and the DSM-IV items of the Conners' teacher questionnaire. Demographics of the full sample and the homogeneity of a subsample  were analysed by using robust statistical procedures which were adjusted for unequal sample sizes and skewed distributions. These procedures included multi-way analyses based on trimmed means and winsorised variances as well as bootstrapping.Age and proband/sibling ratios differed between participating centres. There was no significant difference in the distribution of gender between centres. There was a significant interaction between age and centre for number of inattentive, but not number of hyperactive symptoms. Higher ADHD symptom frequencies were reported by parents than teachers. The diagnostic symptoms differed from each other in their frequencies. The face-to-face interview was more sensitive than the questionnaire. The differentiation between ADHD-CT probands and unaffected siblings was mainly due to differences in hyperactive/impulsive symptoms.Despite a symptom-based standardized inclusion procedure according to DSM-IV criteria with defined symptom thresholds, centres may differ markedly in probands' ADHD symptom frequencies. Both the diagnostic procedure and the multi-centre design influence the behavioural characteristics of a sample and, thus, may bias statistical analyses, particularly in genetic or neurobehavioral studies. Attention Deficit Hyperactivity Disorder ADHD is characterized by problems in allocating attention, regulating motor activity, and controlling behavioural impulses. Depending on diagnostic procedures, around 3 to 8 percent of the children worldwide are affected by ADHD ,2. AccorAt least half of the children with ADHD suffer from one or more comorbid disorders, of which oppositional defiant disorder, conduct disorder, anxiety disorders, and mood disorders are the most common -7. Althohttp://www.nimhgenetics.org and allow infinite DNA replication for future genetic analyses [Twin and adoption studies have shown that the mean heritability of ADHD accounts for about 75% of the variance in symptoms suggesting that genetic factors play an important role in the aetiology of ADHD . Howeveranalyses .http://image.iop.kcl.ac.uk/. The present contribution presents a comprehensive description and analysis of the diagnostic profile of those children who completed the full diagnostic process, including the interview, i.e., all 1068 probands of the IMAGE sample and the 339 siblings who were suspected to have ADHD.Until now, a variety of different analyses based on the IMAGE dataset or parts of it including molecular genetic studies have been published. These studies investigated the genetic association or linkage to ADHD -32, comoData were collected from different centres to enlarge the sample size and. hence, gaining power in statistical analyses. However, the subsamples of the different centres may differ from each other in numerous aspects in spite of standardized recruiting procedures, leading to a greater heterogeneity and a loss of statistical power. Thus, in multi-centre studies like the IMAGE project one might arrive at a conflict between a gain in statistical power by enlarging the sample size and a loss of power due to greater variance of data stemming from differences between centres.The diagnostic procedure may be another source of heterogeneity which is, more difficult to measure and control in comparison to the variance due to centre differences. The IMAGE project used DSM-IV diagnostic criteria which required probands to a pre-defined symptom threshold along with meeting criteria for age at onset and impairment . ParticuThe present analyses investigated the individual contribution of each DSM-IV ADHD symptom to the discrimination between probands and unaffected siblings. It also identified factors influencing the operational decision on the presence of a single symptom. Furthermore, there was a specific interest in the analyses of informant effects (parent vs. teacher ratings) and diagnostic instrument effects (interview vs. questionnaire) on frequencies of each of the 18 DSM-IVADHD symptoms. To summarize, findings based on the following analyses will be presented:- differences in age and sample size across gender, family status, and centres- differences in the number of symptoms and differences in the age the first symptom was detected across gender and diagnostic subtypes- comparison of frequencies of diagnostic subtypes across centres in the sibling sample- differences in medication across diagnostic subtypes and centres- comparison of centre effects on mean symptom frequencies across all 18 DSM-IV ADHD symptoms- informant effects on each of the 18 diagnostic ADHD symptoms- differences between interview and questionnaire ratings on each of the 18 DSM-IV ADHD symptoms- discriminant diagnostic strength of all ADHD symptoms- centre and gender effects on comorbid symptoms in probands.A comprehensive analysis of the dimensional behavioural measures of the IMAGE sample, i.e. the questionnaire scores and the IQ findings in the whole IMAGE sample of 1068 probands and 1446 unselected siblings, is provided in a companion paper .The participating families were recruited between April 2003 and April 2007 in 11 European specialist ADHD centres: Amsterdam (NLD_A), Dublin (IRL_D), Essen (GER_E), Gent (BEL_G), Göttingen (GER_G), Jerusalem (ISR_J), London and Southamptom (ENG_L/S), Nijmegen (NLD_N), Petah Tiqva (ISR_P), Valencia (ESP_V), and Zürich (SWI_Z). Approval was obtained by the Institutional Review Board of SUNY Upstate Medical University and from ethical review boards within each country. Informed consent was obtained for the use of the samples for analyses related to the genetic investigation of ADHD. Recruited families had at least one child with diagnosed or suspected combined type Attention Deficit-Hyperactivity Disorder (ADHD-CT) as defined in the DSM-IV manual . FurtherFamilies were excluded from genetic analyses, if either the proband or the participating sibling had an IQ<70, a diagnosis of schizophrenia or autism, a neurological disorder of the central nervous system or a genetic disorder that might mimic ADHD based on both history and clinical assessment. Children with classical or atypical autism were excluded from the IMAGE project because some genetic regions are known to be associated both with autism and ADHD . There wIn the study design of the IMAGE project, the genetic analyses were based on the comparison between ADHD probands and their 'unselected' siblings. In fact, the sibling group in the genetic analyses should contain children with ADHD symptoms of the whole continuum, except those with an ADHD-Diagnosis . The fulIn the present publication and in its companion paper  all 1446To assess children's symptoms more objectively than by questionnaires, Taylor and associates developed a standardized, semi-structured interview, the Parental Account of Childhood Symptom (PACS), which was used in a slightly adapted version in this study -50.At least one interviewer per participating centre underwent comprehensive training by a team under the supervision of Eric Taylor at the London Institute of Psychiatry (IoP), including cross validation of videotapes and interviews with parents of ADHD children referred to the IoP. If additional interviewers were used, each centre was responsible for their training and supervision. The interviewers were child psychiatrists or clinical child psychologists. The average inter-rater agreement across all centres was 96.6%, and the mean kappa coefficient was 0.88 (range 0.71-1.00) .In the PACS interview parents are asked to rate the behaviour of their child not in terms of deviance from normality, but rather by describing the behaviour according to its frequency  or severity ('What does the child do when in a temper?'). The interviewer then matches the parent's statement to a scale with specific categories for each question. The frequency categories of e.g., 'restlessness at mealtimes' are: (0) no restlessness, (1) leaving seat once only, (3) leaving seat 2 to 5 times (4) leaving seat > 5 times. The severity categories of e.g., 'severity of loss of temper', are the following: (0) no loss of temper, (1) mild: shouts, waves arms, stamps feet, (2) marked: throws things, kicks objects, (3) severe: breaks things, kicks or hits people. The PACS consists of four sections: (1) emotional patterns, (2) activity level and inattentive behaviour, (3) disruptive behaviour, and (4) comorbid and other problems.The ADHD-section of the PACS, which was used to confirm the ADHD combined type diagnosis, covers ADHD related behaviour in different situations . Depending on the situation, the parents have to rate the frequency or severity of their child's hyperactivity-related behaviour , inattention-related behaviour , and impulsive behaviour . A specific algorithm combines and weighs the rated behaviour across situations finally leading to a dichotomous statement about the presence or absence of the corresponding DSM-IV symptom. To check for other diagnostic criteria, such as, questions about age of symptom detection, parental perception of syndrome severity, clinically significant impairment, and problems at school are asked afterwards with respect to both the inattentive section and the hyperactivity/impulsivity section. Each major section ends with questions about the parental coping with the children's problems.Whenever possible, the ADHD section of the PACS focused on behaviour when the child was not medicated. To control the influence of medication on the ADHD section of the PACS, the medication status associated with the rated behaviour was recorded in a variable with five levels: (1) current behaviour, not under medication, (2) behaviour during a one-week-period off medication, (3) behaviour during intermittent days off medication, (4) retrospective assessment of behaviour due to constant use of medication, and (5) behaviour while medicated. For further analyses a secondary dichotomous variable (MED2), with the levels 'medicated behaviour' and 'unmedicated behaviour', was generated by collapsing the variable levels (1) to (4) of the primary medication status variable into one category.The sections dealing with emotional problems  and disruptive behaviour  in the PACS are structured similarly to the ADHD-section except that symptoms are not evaluated across multiple situations. The fourth section assesses co-morbid disorders  at a syndrome level except autism spectrum disorders, which are assessed at a symptom level. Finally, the positive and negative expressed emotions of the interviewed parents are rated by the interviewer.The Conners' ratings scales for parents and teachers  , the StrThe dimensional measures of all Conners' scales, the scales of the SDQ and the SCQ, and the IQ measures are described and analysed in the companion paper .Intelligence (IQ) measures were either assessed separately, or in combination with further neuropsychological testing, depending on the participation of each study centre in the neuropsychological part of the study . Former All parent and teacher questionnaires were used in the complete sample. The probands' behaviour at home was additionally assessed by the full PACS interview with their parents, except for the autism section of the interview that was administered to probands and siblings only if their SCQ score was 14 or higher. In contrast to the probands, only the ADHD section of the PACS was applied in those siblings who were suspected to have ADHD according to the criteria described above.The DSM-IV diagnosis of ADHD was based on the CTRS-R:L and the PACS interview. A DSM-IV symptom list was generated by combining the DSM-IV symptoms from the PACS with the 18 DSM-IV items of the CTRS-R:L. A symptom was rated as present if either the diagnostic criterion of the specific PACS algorithm combining and weighing the responses to the symptom-related questions was met, or if the corresponding DSM-IV item of the CTRS-R:L was coded 2 or 3. To diagnose ADHD-CT among probands, DSM-IV criteria for both the inattention subtype and the hyperactivity/impulsivity subtype had to be met, i.e., 6 out of 9 inattention symptoms (abbreviated IA1 to IA9), 6 out of 6 hyperactivity symptoms (abbreviated HYP1 to HYP6) and 3 impulsivity symptoms (abbreviated IMP7 to IMP9) (see the abbreviations section for a detailed description of the symptoms and the abbreviations used hereafter). Additional diagnostic DSM-IV criteria including age of symptom onset below the age of 7 years, or absence of other psychiatric or neurologic disorders which may cause ADHD symptoms, were derived from the PACS interview. Pervasiveness was fulfilled if at least 2 symptoms of both the PACS and the CTRS-R:L were present, or if symptoms were rated as present in 2 or more different situations of the PACS interview. Clinical impairment was inferred by the fact that at least 12 symptoms exceeded the diagnostic threshold, and additionally was verified in the PACS interview.The diagnoses of classical or atypical autism leading to the exclusion of a child from the study were defined by a specific algorithm based on the interview data of the PACS autism section.Most of the continuous variables examined were skewed and the various subsamples had unequal variances and unequal sample sizes. In particular, the questionnaire data were not only heavily skewed, but also skewed in opposite directions in probands and siblings. The assumptions of normality and homoscedasticity, which should be met for parametric statistical analysis, were violated for almost all continuous variables. Simulations have shown that even small deviations from normality can cause strong differences between the actual and the nominal Type I error and can result in low power, even with large sample sizes -58. Thertrimpb [- The percentile bootstrap procedure trimpb ,59, withtrimpb .- Chi-square-tests  were use- Hierarchical log-linear analyses with backward elimination  were uset2way and t3way [- Robust two-way and three-way analyses were calculated in R by applying the procedures nd t3way ,59 metholinconb6 [lincon [- Robust post-hoc pairwise comparisons were computed in R by using the bootstrap procedure linconb6 , an expa [lincon , which a- Binary logistic regression analyses  were com- Residuals of a linear regression of target variables on age were calculated  for use 2=57.1, df = 1, p < .001 . A three way analysis of variance including gender, family status, and centre revealed no main effects of gender and status on age, but a significant main effect by centre, Q = 44.9, crit.=20.8, p < .001. Post hoc pairwise comparisons between centres with a 5% family-wise error rate revealed that the children of SWI_Z were significantly younger than those of three other centres, namely NLD_G (CI = 0.01-2.22 years), ISR_P (CI = 0.16-2.48 years), and ENG_L/S (CI = 0.50-2.67 years). There was a significant centre by status interaction effect on age, Q = 34.8, crit.=20.7, p < .001. On the one hand, none of the 55 post hoc pairwise comparisons in the sibling sample were significant (probability level adjusted for multiple tests). On the other hand, ten pairwise comparisons between centres within the proband sample differed significantly as indicated by non-overlapping 95% family-wise CI's between centres , based on the PACS interview and the Conners' teacher questionnaire, was 8.5 in boys and 8.3 in girls, and the mean number of hyperactive/impulsive symptoms was 8.5 in boys and 8.4 in girls .Because age correlated negatively with the number of hyperactive symptoms , a similar analysis was calculated based on age-adjusted number of hyperactive/impulsive symptoms . Similar to the analysis of unadjusted number of symptoms, this analysis revealed significant centre effects only on number of hyperactive symptoms  and hyperactivity-/impulsivity (7.5), and highest in the GER_G subsample both for inattention (8.9) and hyperactivity (8.9). Pairwise comparisons of number of symptoms between centre sub-samples revealed six centre pairs differing significantly from each other in the inattention domain and five in the hyperactive/impulsive domain (probability level adjusted for multiple tests). The graphs in Figure S2 in the Additional file The mean age at inattention symptom detection was 4.2 years in boys and 4.1 years in girls. Similarly, girls were younger (2.0 years) at first detection of hyperactive/impulsive symptoms than boys (2.4 years).No significant gender effects were found in a two-way analysis of centre and gender on the age at symptom detection. The first inattentive symptom occurrence differed between centres  as well as the first hyperactive/impulsive symptom occurrence . A centre by gender interaction significantly influenced the age at first detection of inattentive symptoms , but not of hyperactive/impulsive symptoms.RES = 82.66, p < .001) and the centre by gender interaction effect  was significant, indicating that the parents' estimates of the first inattention symptoms differed between centres, independent of the actual age of the probands, and that gender effects varied across centres.Because the age of the probands significantly correlated with the age of first inattentive symptom occurrence , a similar analysis was performed on age-adjusted detection of inattentive symptoms . The results of this age adjusted analysis were similar to the non-adjusted analysis: the centre effect  changed their rank position, and the centre IRL_D no longer differed significantly from centres ISR_J and NLD_G  of these 339 siblings having combined type (ADHD-CT), 76 (22%) having inattentive type (ADHD-IT), 26 (8%) having hyperactive/impulsive type (ADHD-HT), and 79 (23%) having no ADHD diagnosis (ADHD-ND). The latter subtype resulted from number of symptoms below the diagnostic threshold  consisting of siblings with ADHD-CT only, two sub-samples (BEL_G and ISR_J) containing no siblings with ADHD-HT, and one sample (GER_G) having no siblings with ADHD-IT , based on the PACS interview and the Conners' teacher questionnaire, was highest in the CT subsample (8.4), followed by IT (7.5), ND (5.3), and HT (4.2) subsamples. Symptoms of hyperactivity/impulsivity were most frequent in CT (8.4), followed by HT (7.4), IT (3.7), and ND (3.6). Table RES = 11.20, p = .002) and subtype effects  on the number of symptoms present, with an additional gender by subtype interaction effect .A two-way ANOVA revealed significant gender effects and subtype effects on symptom numbers for both inattentive and hyperactive/impulsive symptoms, but no gender by subtype interaction effects. Inattentive symptoms were more frequent in male siblings compared to female siblings  and differed between subtypes . Similarly, male siblings had more hyperactive/impulsive symptoms than female siblings , and the symptom numbers differed between subtypes  when symptoms were present for the first time was lowest in siblings with ADHD-CT  and highest in children without an ADHD diagnosis .In two-way analyses, the first occurrence of ADHD-DSM-IV symptoms in these 339 siblings did not differ between boys and girls, neither for inattentive nor for hyperactive/impulsive symptoms. A subtype effect on the age of symptom detection was present with regard to inattentive symptoms  but not with regard to hyperactive symptoms; gender by subtype interaction effects on age at detection were not significant in both symptom groups of the sibling sample. Because the reported age of inattention symptom detection correlated with the age of the siblings , the same analysis was calculated based on age adjusted first occurrence of inattentive symptoms. Similar to the original analysis, only the main effect of subtype was significant  were permanently off medication, 186  were off medication for one week, 446  were off medication on intermittent days, 202  were rated retrospectively due to constant use of medication, and 132  were rated during a period of permanent medication. In summary, the interview data of 1268  children was based on unmedicated periods, while it was based on medicated periods for 132  children.The percentage of children rated under medication differed between ADHD subtypes. It was highest (10%) for ADHD-CT, followed by ADHD-ND (8.2%), ADHD-IT (3.9%), and ADHD-HT (0%). A total of 10.2% of the 1151 boys, but only 6% of the 249 girls were rated under medication. The percentage of children rated under medication also differed between centres. There were four centres with low percentages, namely ESP_V (0%), ISR_J (1.5%), ISR-P (2.1%), NLD_A (1.7); three centres with medium percentages, namely BEL_G (4.1%), GER_G (5.0%), IRL_D (3.0%); two centres with high percentages, namely GER_E (7.3%) and SWI_Z (7.6%), and two centres with percentages clearly above average, namely ENG_L/S (12.7%) and NLD_G (35%).2=8.374, df = 15, p = .908) did not indicate a significant difference between the model and the data. The gender by status interaction effect on MED2,  was the only significant effect when including the variable MED2 after the backward elimination procedure stopped. To break down this effect, chi-square tests on status and MED2 variables were performed separately for boys and girls. For boys, there was no significant association between family status and medication status, χ2 = .027, df = 1, p = .87, whereas for girls this association was significant, χ2=7.6, df = 1, p = .006. In terms of odds ratios, male probands were 1.04 times more likely to be medicated than male siblings, whereas female probands were 6.5 times more likely to be medicated than female siblings.A statistical analysis using a hierarchical loglinear model including the dichotomized medications status , the diagnostic subtype, family status, and gender resulted in a final model that retained only main effects and two-way interactions, but no three- and four-way interactions. The likelihood ratio for this model , only main effects and two-way interactions remained significant. The only significant two-way effect on MED2 after backward elimination was again for gender by status  indicating that medication did not vary across centres. Thus, the significant centre by medication effect can be ignored because it was confounded with the significant higher order effect of gender by status by MED2 due to the hierarchical character of the model.When centre was entered into the model  and the teacher questionnaire ratings (CTRS) contributed to the ADHD diagnosis. In boys and girls, all symptom frequencies were higher in the PACS compared to the CTRS, except for symptom IA2  and parent (CPRS) questionnaires were compared. All symptoms were more frequent when rated by parents than by teachers, both in boys and girls. The mean difference across inattentive symptoms was 14% in boys and 20% in girls; across hyperactive/impulsive symptoms the differences were 14% in boys and 22% in girls.A comparison of the two parental sources, i.e. PACS and CPRS, reflecting the effect of the diagnostic instrument revealed smaller effects across all symptoms compared to the differences which included different informants. The symptoms were equal or more frequent when recorded in the interview in 12/18 symptoms in boys (differences from 0% to 32%) and in 13/18 symptoms in girls (0% to 41%). The remaining symptoms with higher frequencies in the CPRS compared to the PACS were IA2 , IA3 , IA4 , IA9 (4% only in boys), HYP5 , and IMP6 , Mean differences across all 18 symptoms were 3% in boys and 6% in girls, both indicating higher frequencies in the interview compared to the questionnaire. When the outlier symptom IA2 was excluded from the calculation, these differences were larger in boys (5%) and in girls (8%).2 between 37.5 and 688.4, df = 2, all p < .001), when calculated separately in girls , and in boys . Pair-wise statistical parent vs. teacher comparisons (Wilcoxon test), i.e. 18 comparisons PACS vs. CTRS and 18 comparisons CPRS vs CTRS, revealed highly significant results for all parents vs. teacher comparisons . The pair-wise comparisons of instruments reflecting the parents view (PACS vs. CPRS) were not significant for three symptoms , significant in two comparisons , and highly significant (p < .001) in the remaining 13 comparisons.When all three sources were entered in a non-parametric analysis of variance, there was a significant effect of the source on symptom frequency in each of the symptoms in the whole sample , as assessed by the PACS interview. Slightly different effects resulted in symptoms that were obtained from the parent questionnaire (CPRS). All centre effects were highly significant (p < .001), except for IMP7 (p = .023), but no gender effects were significant except for HYP3  and for HYP6 .To evaluate gender and centre effects on symptom frequencies simultaneously, hierarchical log-linear analyses were performed for each symptom and separately for all three sources, i.e., PACS, CPRS, and CTRS. These analyses revealed no significant gender effects for all symptoms, but there were significant centre effects for all symptoms except in three inattention symptoms . All these significant differences reflected higher frequencies in boys. The centre effects, however, were all significant and were similar to the effects found for the parent ratings. .In contrast to these two parent ratings, teacher assessed symptom frequencies (CTRS) were higher in boys than in girls for 11 of the 18 symptoms, i.e. all but The following analyses are based on the combined symptom presence . Because the diagnosis was based on the combination of the parental interview (PACS) and the teacher Conners' questionnaire (CTRS), i.e., a symptom was counted as present when it was present either in the PACS or the CTRS.The frequencies of combined symptoms in the proband sample stratified by centres are presented in Table In the comparable control group , the overall mean symptom frequency was 50.6% across all symptoms, 57.1% across inattentive symptoms, and 44.2% across hyperactive/impulsive symptoms. The frequencies in the control sample did not differ between centres due to small sample size  to the discrimination between probands and unaffected siblings than inattentive symptoms (mean wT=1.97). Among the symptoms discriminating significantly, 'running about'  was the symptom that discriminated most strongly, followed by 'being on the go' , 'fidgeting' , 'listening' , 'organizing tasks' , 'difficulties waiting turn' , and 'attention to details' . See Table A binary logistic regression analysis in which the proband sample (N = 1068) was compared to the control sample  showed that hyperactive/impulsive symptoms contributed more , conduct disorder , anxiety disorders , and mood disorders   and that a higher proportion of girls (21.5%) compared to boys (14.5%) were affected.The final model for ODD retained all main effects and interactions. Partial associations were significant for ODD by centre, χThe frequencies of remaining conditions in the proband sample were assessed only at syndrome level and were clearly less prevalent. Obsessive compulsive disorder was possibly present in 35 boys (3.7%) and 4 girls (3.1%), Tourette's syndrome was possibly present in 22 boys (2.3%) and 3 girls (2.3%), substance abuse was possibly present in 19 boys (2%) and 1 girl (0.8%), psychosis was possibly present in 8 boys (0.9%) and 2 girls (1.5%), bipolar affective disorder was possibly present in 4 boys (0.4%) and 3 girls (2.3%), and reactive attachment disorder was possibly present in 4 boys (0.4%) and 1 girl (0.8%).The present paper deals with the analysis of behavioural data of the International Multi-centre ADHD Genetics (IMAGE) project. The main focus is on the impact of the multi-centre design and the diagnostic procedure on the homogeneity of the data. Aggregating data from several recruiting centres is an important research strategy in order to enlarge sample sizes and, thus, to increase statistical power which is needed for generalising results, i.e., for achieving a needed level of significance.The sample size is essential particularly in genetic linkage analyses of complex traits like ADHD when searching for markers contributing only to a small extent to the risk of ADHD . While sDespite the identical inclusion criteria (in terms of the numbers of ADHD symptoms) for children of all ages, we found a negative correlation between age and the mean number of hyperactive symptoms in the probands sample: older probands had lower numbers of symptoms than younger probands. At first sight, this could be interpreted as decreasing disease severity with age in our sample.The interpretation of this age effect, however, must take into account the interplay between population characteristics and the diagnostic procedure. Previous studies have shown that age is an important factor moderating the symptoms of ADHD, resulting in a general symptom decline . This isThese age effects have two important consequences in terms of disease severity: First, adolescents may deviate to a stronger extent from the normative mean in comparison to young children with the same number of ADHD symptoms present. Secondly, some evidence for genotype differences in groups differing in age but not in the number of ADHD symptoms can be derived. Therefore, if ADHD is seen as a quantitative trait, a probabilistic positive association may be assumed between the degree a phenotype  deviates from the population mean and the number of alleles present, which are associated with the trait ,64. If aThis implicit age effect inferred from epidemiological studies and a normative sample was moderated by the  negative correlation between age and the number of hyperactivity symptoms in our sample. As a consequence of these two features, one has to assume that, on the one hand, adolescents in our proband sample differed on average to a smaller extent from young children than inferred from the normative sample. On the other hand, individual differences between adolescents and young children with an identical number of symptoms remained. Therefore, we must conclude that the disease severity in terms of the deviation from normality increased with age, and that this effect was not represented in the number of ADHD symptoms present.We found no age differences between boys and girls in the proband sample. But among the 11 centres there were ten significant pairwise differences in mean age ranging from 1.4 to 2.6 years, with effect sizes between 0.9 and 0.5. As a consequence, one would expect that centres with rather young probands, e.g. ESP_V, would have a relatively lower mean number of hyperactive symptoms, indicated by a lower rank after age correction, and vice versa . Exceptions were higher frequencies of inattentive symptoms (PACS and CTRS combined) in boys compared to girls and higher frequencies in boys for two thirds of the ADHD symptoms in the CTRS.These differences were consistent with a meta-analysis reporting higher ADHD symptoms in boys compared to girls . ConcordThe multi-centre design is another possible source of sample heterogeneity. Analyses of the proband sample showed that centre effects played a more important role than age or gender effects. The centres differed significantly in age, in both inattentive and hyperactive/impulsive symptom numbers, in age of detection of both inattentive and hyperactive/impulsive symptoms, in fifteen out of eighteen ADHD symptoms in the PACS interview, in seventeen out of eighteen ADHD symptoms in the CPRS, in all ADHD symptoms in the CTRS, in five out of nine combined (PACS and CTRS) inattentive, and six out of nine combined hyperactive/impulsive symptoms, and in all comprehensively assessed comorbid conditions .Even if we would assume that centres did not differ with respect to genetic, socio-cultural, and methodological aspects, differences in gender and age ratios between centres, combined with differing sample sizes, could enhance the sample variance and introduce additional heterogeneity due to variables that were associated with gender or age. Such indirect effects were, however, either absent in the proband sample (gender), or only played a minor role with respect to ADHD symptoms (age), as discussed above. Consequently, we must assume that other factors caused the differences in psychopathology measures between centres  is recorded much more frequently by the CPRS  than by the PACS . A comparison between symptoms and between the three diagnostic sources suggests that the sensitivity of the PACS is too weak for this symptom. The higher general sensitivity of the interview compared to the questionnaire, however, does not imply a lack in the utility of questionnaires as screening instruments. In general, the cut-off criteria of screening instruments were set far below the diagnostic threshold (we used a T-score of 63), so that all subjects, who reach the diagnostic threshold of the interview, but not of the questionnaire, were positively screened in all cases.Informant and contrast effects were analysed and discussed on the basis of continuous data in the second part of this contribution, which concentrates on questionnaire scores .either in the CTRS or in the PACS. To prevent diagnoses based on a single informant only, at least two of the symptoms had to be present in both settings. This algorithm allows children to be positively diagnosed, even if their symptoms level is below the diagnostic threshold at home, at school, and even in both settings. This effect becomes evident when the frequencies of combined (PACS or CTRS) diagnostic symptoms (Table Some further comments on the diagnostic procedure with respect to heterogeneity in the proband sample should be made. The diagnostic procedure of the IMAGE study used a teachers' questionnaire (CTRS) and a parental interview (PACS) in combination, by counting a symptom as present if it was present ms Table  is compams Table . WhereasFinally, some comments should be made concerning the sibling sample of the present study. The sample of 339 diagnosed siblings was heterogeneous in various ways. The subtypes differed across centres and between genders. There were, in particular, higher rates of ADHD-CT in boys than in girls. The mean number of both inattentive and hyperactive/impulsive symptoms differed between gender (higher frequencies in boys) and between centres. Differences in implementing the criteria for conducting the sibling interview  may have introduced a bias leading to the large differences in subtype frequencies across centres. Additionally, differences in personnel resources, in combination with the declared purpose of the sibling interview (excluding ADHD cases in the sibling sample), may have introduced a centre bias. For these reasons, we do not further discuss the findings on the selected siblings but refer to the second part of this contribution dealing with analyses of the complete sample of 1446 siblings based on questionnaire data .The present IMAGE project used a multi-centre design in order to reach an acceptable power for detecting genetic variants involved in ADHD. The multi-centre design may have led to additional heterogeneity in the sample, as demonstrated by the present contribution. Additionally, a diagnostic procedure invariant to age, gender, and informant, as used in the IMAGE study, may have enhanced the heterogeneity in the proband sample. Our data do not allow us to define an optimal trade-off between sample size and sample homogeneity. In conclusion, we recommend that genetic analyses be either statistically adjusted for the known sources of variance  or that they be stratified by sources of heterogeneity. Removal of outliers or using robust statistics might also enhance statistical power.IA1 Often fails to give close attention to details or makes careless mistakes in schoolwork, work, or other activities; IA2 Often has difficulty sustaining attention in tasks or play activities; IA3 Often does not seem to listen when spoken to directly; IA4 Often does not follow through on instructions and fails to finish schoolwork, chores, or duties in the workplace ; IA5 Often has difficulty organizing tasks and activities; IA6 Often avoids, dislikes, or is reluctant to engage in tasks that require sustained mental effort (such as schoolwork or homework); IA7 Often loses things necessary for tasks or activities ; IA8 Is often easily distracted by extraneous stimuli; IA9 Is often forgetful in daily activities; HYP1 Often fidgets with hands or feet or squirms in seat; HYP2 Often leaves seat in classroom or in other situations in which remaining seated is expected; HYP3 Often runs about or climbs excessively in situations in which it is inappropriate ; HYP4 Often has difficulty playing or engaging in leisure activities quietly; HYP5 Is often 'on the go' or often acts as if 'driven by a motor'; HYP6 Often talks excessively; IMP7 Often blurts out answers before questions have been completed; IMP8 Often has difficulty awaiting turn; IMP9 Often interrupts or intrudes on others DSM-IV criteria for ADHD: PA has consulted with, received education grants from or spoken at sponsored meetings for Shire, Janssen-Cilag, Eli-Lilly and Flynn Pharma. JB has been in the past 3 years a consultant to/member of advisory board of/and/or speaker for Janssen Cilag BV, Eli Lilly, Bristol-Myer Squibb, Organon/Shering Plough, UCB, Shire, Medice, Servier, and Servier. TB served in an advisory or consultancy role for Bristol-Myers Squibb, Desitin, Lilly, Medice, Novartis, Pfizer, Shire, UCB and Viforpharma. He received conference attendance support or received speaker's fee by Lilly, Janssen McNeil, Medice, Novartis, Shire, UCB. He received unrestricted grants for organizing a CME conference by Lilly, Janssen McNeil, Medice, Novartis, Shire, UCB. He is/has been involved in clinical trials conducted by Lilly, Shire and Novartis. The present work is unrelated to the above grants and relationships. SVF has, in the past year received consulting fees and has been on Advisory Boards for Eli Lilly, Ortho-McNeil and Shire Development and has received research support from Eli Lilly, Pfizer, Shire and the National Institutes of Health. In previous years, SVF has received consulting fees or has been on Advisory Boards or has been a speaker for the following sources: Shire, McNeil, Janssen, Novartis, Pfizer and Eli Lilly. In previous years he has received research support from Eli Lilly, Shire, Pfizer and the National Institutes of Health. RDO received support from Janssen and UCB during this period. HR has served as an advisor to Shire and received research support from Shire and Lilly and conference attendance support from Lilly.The present study is unrelated to these relationships. AR declares the following competing interests: Advisory Board and Speakers Bureau: Lilly, Shire, Medice, Novartis; Research Support: Shire, German Research Society, Schwaabe; Travel Support: Shire; Educational Grant: Shire. JS declares the following competing interests: Advisory Board: Lilly, Shire, Research Grant(s) Lilly, Speaker's Fee: Shire, Lilly, Janssen-Cillag. ESB declares the following competing interests: Recent speaker board: Shire, UCB Pharma. Current & recent consultancy: UCB Pharma, Shire. Current & recent research support: Janssen Cilag, Shire, Qbtech, Flynn Pharma. Advisory Board: Shire, Flynn Pharma, UCB Pharma, Astra Zeneca. Conference support: Shire. HCS has served as an advisor and/or speaker to the following companies: Janssen-Cilag, Eli Lilly, Medice, Novartis, Shire, and UCB. MT has served as an advisor, speaker and had research grants from the following companies: Janssen-Cilag, Eli Lilly, Shire, and UCB. All other authors declare no competing interests to disclose.UCM and HCS jointly planned the analyses and drafted the manuscript with UCM performing all the statistical analyses. All other authors were principle investigators at the various centres and SVF was overall principle investigator of the IMAGE study. All authors commented on the manuscript and approved the final draft.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-244X/11/54/prepubFigure S1. Mean age of centre subsamples in ascending order, and significant post hoc pairwise comparisons.Click here for fileFigure S2. Trimmed means of symptom numbers and age at symptom onset in probands (N = 1068).Click here for fileTable S1. Diagnostic subtypes in the siblings sample.Click here for fileFigure S3. Subtype frequencies in the siblings sample across centres and gender.Click here for file


To the Editor,The role of infection in the pathogenesis of vaso-occlusive crisis in patients with sickle cell diseases, written by Dr. Ahmed SG. He pointed that these patients have impaired immunity and are thus predispose to infections which can precipitate the painful crisis.4We read with great interest the recent article Bartonella spp. are emergent bacteria with worldwide distribution. An increasing number of Bartonella spp. are regarded as zoonotic pathogens, creating a public health concern for human and veterinary medicine. The extent of Bartonella spp. infection is underestimated.Bartonella spp. bacteremia is potentially fatal, especially in immunodeficient patients. Immunocompetent individuals are also at risk for chronic infection by this intra-erythrocyte and intra-endothelial agent though the infection can be asymptomatic.Bartonella spp. infection, many of which were considered idiopathic prior to the diagnosis of chronic Bartonella spp. infection. A recent study from the United States of America found that almost 50% of patients with non-specific symptoms  had positive Bartonella spp. serology and/or blood PCR positive to Bartonella spp. One in four patients had Bartonella spp. bacteremia.8These patients frequently need blood transfusion and transmission of pathogens via transfusion in SCD patient infection has been documented.Bartonella spp. infection and false-negative results are frequent even with serology and multi-step molecular and microbiological techniques.Bartonella spp. remains challenging, warranting development of more sensitive and reproducible diagnostic methods.Previous studies show that blood donors can have asymptomatic bacteremia.Bartonella spp. infection rate as they present with inflammation, endothelial activation, asplenia, and the need for frequent blood transfusions; pathological features that can promote the invasion and progression of Bartonella spp..Bartonella spp. infection are manifest in SCD. Therefore, coordinated international efforts should be initiated to evaluate the relevance of this infection in SCD and other chronic immunodeficient patients.It is likely that SCD patients could have a higher prevalence of


Progress testing is gaining ground rapidly after having been used almost exclusively in Maastricht and Kansas City. This increased popularity is understandable considering the intuitive appeal longitudinal testing has as a way to predict future competence and performance. Yet there are also important practicalities. Progress testing is longitudinal assessment in that it is based on subsequent equivalent, yet different, tests. The results of these are combined to determine the growth of functional medical knowledge for each student, enabling more reliable and valid decision making about promotion to a next study phase. The longitudinal integrated assessment approach has a demonstrable positive effect on student learning behaviour by discouraging binge learning. Furthermore, it leads to more reliable decisions as well as good predictive validity for future competence or retention of knowledge. Also, because of its integration and independence of local curricula, it can be used in a multi-centre collaborative production and administration framework, reducing costs, increasing efficiency and allowing for constant benchmarking. Practicalities include the relative unfamiliarity of faculty with the concept, the fact that remediation for students with a series of poor results is time consuming, the need to embed the instrument carefully into the existing assessment programme and the importance of equating subsequent tests to minimize test-to-test variability in difficulty. Where it has been implemented—collaboratively—progress testing has led to satisfaction, provided the practicalities are heeded well. Progress testing is becoming increasingly popular both in the Netherlands and internationally –9 after But it is not as straightforward as it looks; introducing progress testing involves not only a change in thinking about assessment but also an academic cultural change. Even more so, when collaboration on progress testing is sought; in such situations openness, non-competitiveness, exchange and mutual trust are essential. The purpose of this paper is to summarize the most important expectations and to accompany them with experiences from actual practice.The many different descriptions of progress testing largely converge on the principle of longitudinal, repeated assessment of students’ functional knowledge. Often, a number of tests are set per academic year, each consisting of a large number of questions pitched at graduate level functional (relevant) knowledge. Each of these tests is sat by students of multiple or all year classes, and the results of each individual test are combined in a compensatory way to form the basis for a promotion decision at the end of the year. The test is comprehensive in that it consists of questions covering a broad domain of relevant medical knowledge, and it is organizationally founded on centralized test production, review, administration and analysis. Our description here is intentionally general because there are various different implementations possible, and more detailed descriptions are provided in the literature , 11, 12.Because progress tests are longitudinal measurements it is assumed that students will experience less examination stress, because a one-off bad result cannot undo a series of good results –13. The—Another reported advantage of progress testing is that it renders resit examinations unnecessary. Resits are a burden for the organization; they have to be good quality examinations for only a small number of students. Also, they can lead students to adopt a minimalistic study approach; why study hard when there are always the resits ? But agaUndisputed is the positive influence on student learning. This is actually why progress testing was originally developed , 11, andHowever, no assessment method can exert its influence on student learning in a vacuum; it always works in the context of the rest of the assessment programme , 20. WheAnother assumed advantage is that longitudinal data collection is more predictive of future competence/performance than one-off measurements. For this, choices have to be made with respect to how to combine the information of subsequent tests. Some schools opt for a more continuous approach  and use Finally, longitudinal combination of results adds to the reliability of the decision. Research in the 1980s and onwards , 27 has Another important discussion point in reliability is that most progress tests employ a correct-minus-incorrect (formula) scoring system. This is necessary because the tests are also administered to junior students. It is not considered desirable that our junior students—not being able to answer most of the questions—would be forced to guess on many items. Therefore, a question-mark option has to be offered with formula scoring. Whether or not this decreases the reliability of progress test scores is open to debate. When the test is taken under formula scoring conditions the number of correct reliabilities is higher—the difference being roughly 0.20 (unpublished results of the interuniversity progress test in the Netherlands)—but experimental studies where scores under formula scoring and number-right conditions were compared showed better reliabilities for the formula scoring , 31.The comprehensiveness of the test content is often seen as an advantage too, because specific strategic revision does not work  , 32, 33.A final advantage is the progress test’s curriculum independence. The fact that it is designed to test knowledge at graduate level makes it perfect for joint production, joint administration and joint research. The many emerging collaborations , 5–9, 35Progress testing is definitely an important addition to the available assessment methods. It has become clear that in a programme of assessment it should not be used to replace current methods but to add to them , 36, 37.Progress testing is a longitudinal test approach based on equivalent tests given at fixed intervals with the intention to assess the development on functional knowledge or competenceThe biggest advantage of progress testing is that it minimizes test-driven learning strategiesCombining the results on the repeated tests increases both the reliability of pass–fail decisions and its predictive validityA major concern with progress testing is ensuring the equivalence of the individual testsWhen progress testing is used in a collaborative fashion—sharing test production and administration—it is not only more cost-effective but also a rich source for continuous benchmarking and quality improvement


Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders among school-aged children. It is highly symptomatic and associated with significant impairment. This review examines the role of stimulant medications in the treatment of children and adolescents with ADHD. Published clinical studies that compared methylphenidate- and amfetamine-based stimulants in children and adolescents with ADHD support the therapeutic utility of stimulant treatments, and suggest robust efficacy and acceptable safety outcomes in groups treated with either stimulant. Evidence-based guidelines agree that each patient with ADHD is unique and individual treatment strategies that incorporate both drug and non-drug treatment options should be sought. In seeking to optimize individual response and outcomes to stimulant therapy, important considerations include the selection of stimulant class, the choice of long- or short-acting stimulant formulations, addressing effectively any emergent adverse effects and strategies aimed at enhancing adherence to dosing regimen and persistence on therapy. Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders among school-aged children, with a worldwide prevalence estimated to be 5.29 % , based on a meta-analysis of 102 studies incorporating more than 170,000 participants from all continents . ADHD isThis review examines the role of stimulant medications as part of a multimodal treatment strategy in children and adolescents with ADHD. The review first explores the place of stimulant medications in clinical treatment guidelines around the world and then briefly reviews the overlapping but distinct mechanisms of actions of the methylphenidate (MPH) and amfetamine (AMF) classes of stimulant in the pathophysiology of ADHD. Next, we provide an update of direct and indirect clinical comparisons of efficacy of these stimulants in the treatment of ADHD. Finally, we discuss the role of stimulants within a comprehensive strategy aimed at optimizing treatment for the benefit of an individual with ADHD and their family members or caregivers.Guidelines from around the world differ in their treatment recommendations . There i2 adrenergic receptor agonists clonidine and guanfacine (including short- and long-acting formulations) are all approved by the US Food and Drug Administration (FDA). However, the range of ADHD medications available to patients and physicians is not as extensive in many countries outside North America. In the USA, the American Academy of Child and Adolescent Psychiatry Practice Parameters recommend that treatment plans consist of psychopharmacotherapy and/or behavioural therapy. The initial medication should be one of the following FDA-approved drugs: MPH, AMF, mixed amfetamine salts, or atomoxetine , 160–341 and 40–238 nM, respectively) , 6143, 6Despite the carefully managed nature of the Multimodal Treatment Study of Children with ADHD (MTA), saliva assays for MPH revealed that approximately 25 % of 254 patients in the medication arms of the study were non-adherent on 50 % or more of repeated assays, and that barely half (54 %) were adherent at every assay point . FurtherThe importance of utilizing a multimodal treatment strategy that incorporates both medication and non-drug interventions is recognized by all ADHD clinical guidelines , 75, 91.Randomized and controlled clinical trials indicate that MPH and AMF offer robust medication options for the treatment of ADHD. In the drive to improve the treatment of ADHD for an individual, the nature of the stimulant, its formulation and optimization of the dosing regimen, with careful on-going monitoring of both positive and negative medication effects and adherence are all important considerations. Furthermore, concurrent non-drug treatments, including behavioural therapy, should all be considered as part of a multimodal treatment strategy. For those patients or caregivers who prefer not to take stimulants or for whom stimulants are contraindicated, non-stimulant drug options are available, though generally less effective.


Although Attention-Deficit/Hyperactivity Disorder (ADHD) was initially regarded as a disorder exclusive to childhood, nowadays its prevalence in adulthood is well established. The development of novel techniques for quantifying the thickness of the cerebral mantle allows the further exploration of the neuroanatomical profiles underlying the child and adult form of the disorder. To examine the cortical mantle in children and adults with ADHD, we applied a vertex-wise analysis of cortical thickness to anatomical brain MRI scans acquired from children with (n = 43) and without ADHD (n = 41), as well as a group of adult neurotypical individuals (n = 31), adult patients with a history of stimulant treatment (n = 31) and medication-naïve adults with ADHD (n = 24). We observed several clusters of reduced laminar cortical thickness in ADHD patients in comparison to neurotypical individuals. These differences were primarily located in the dorsal attention network, including the bilateral inferior and superior parietal cortex and a section of the frontal cortex . Further laminar thickness deficits were observed in the bilateral orbitofrontal cortex and medial occipital cortex. The deficits in the cortical surface were especially pronounced in the child sample, while adult patients showed a more typical laminar thickness across the cerebral mantle. These findings show that the neuroanatomical profile of ADHD, especially the childhood form of the disorder, involves robust alterations in the cortical mantle, which are most prominent in brain regions subserving attentional processing. Attention-Deficit/Hyperactivity Disorder (ADHD) is one of the most common psychiatric disorders of childhood, affecting approximately 8–12% of school-age children worldwide Initial studies investigating the neural bases of the disorder depended on the manual  delineation of the whole encephalon or of a priori defined regions of interest (ROIs) by trained neuroanatomists. The first study relying on this methodology in the early twentieth century detected a reduction of total brain volume in children with ADHD The manual segmentation technique, which is considered a gold standard in terms of its anatomical validity, is a very labor-intensive procedure that has to contend with problems of inter - and intra-rater reliability. Furthermore, findings derived from this methodology are unavoidably biased by the a priori definition of brain regions expected to show volumetric alterations. Traditional methods were soon complemented by automatic and highly replicable procedures, such as voxel-based morphometry (VBM), which are less time-consuming and allow the simultaneous assessment of whole-brain cortical and subcortical structures. Studies applying VBM not only confirmed cerebellar and basal ganglia alterations but also detected deviations in other sections of the brain, especially in the cortical mantle. VBM studies in children with ADHD revealed smaller grey matter volumes across several cortical regions. Reduced volume in the frontal and parietal cortex – especially in the superior/middle frontal gyrus, orbitofrontal cortex, premotor cortex and inferior parietal cortex— are among the most replicated The evidence of substantial cortical alterations in ADHD underscored the necessity to complement VBM techniques with other sophisticated methods, such as analyses of cortical thickness, which are devoted to specifically map differences in laminar thickness between diagnostic groups. Although VBM is a powerful tool to examine volumetric tissue properties, the amount of grey matter density or volume as estimated by VBM can be confounded by how convoluted the brain is in a given region. Cortical thickness analyses are commonly based on the estimation of the distance between the grey-white matter border and the pial surface, thus they use the local topography of the grey matter to generate a specific and quantifiable metric of a cortical anatomical property. Consequently, measuring the thickness of the cortex provides a close approximation of the underlying anatomical reality. Compared to volumetric measures, cortical thickness procedures are less susceptible to positional variance The few previous studies that have assessed cortical thickness in children and adolescents with ADHD obtained results that largely echoed those observed using automatic volumetric approaches Although several studies have applied cortical thickness analyses to children with ADHD To expand upon earlier findings and further explore cortical alterations associated with the adult and child forms of ADHD, we carried out a cross-sectional study of cortical thickness comparing both adults and children with ADHD to a group of neurotypically developed controls. We used a vertex-wise analysis of cortical thickness that allows for an exploratory data analysis of the laminar thickness across the cortical mantle without placing a priori constraints on the search space for anatomical alterations.The study was approved by the Hospital Universitari Vall d'Hebron ethics committee, and written informed consent was obtained from the subjects and from the parents or guardians of the child participants prior to their participation in the study.For this study, 188 scans were collected from previous studies performed in our research group After initial processing, eighteen subjects had to be removed from further analyses due to insufficient quality of the white and pial surfaces resulting from the tessellation. Our final sample consisted of 86 adults (55 patients and 31 control subjects) and 84 children (43 patients and 41 control subjects). In the adult group, 24 patients had never received any pharmacological treatment for their condition, while only 5 of the child patients were medication-naïve.http://surfer.nmr.mgh.harvard.edu/) implemented in the PICNIC platform (http://neuroweb.pic.es/), using a standard cortical thickness approach. Cortical thickness analyses have previously been validated using histological measures in human brains The analyses were performed in Freesurfer . To evaluate whether the child and adult form of the disorder are associated with a distinct neuroanatomical profile, we also performed an ANOVA and applied the interaction contrast ‘Age Group×Diagnosis’. To explore the effects of stimulant medication on cortical thickness, we performed some additional analyses separately for the medicated and never-medicated patients. The two sample t-tests comparing the patients with the control participants were repeated for both the adult and the child sample after excluding the medication-naïve patients. Furthermore, for the adult subjects, we also compared cortical thickness in the medication-naïve group of adult patients with ADHD with the medicated patient group. The interaction contrast (‘Age Group×Diagnosis’) was also repeated without the medication-naïve patients in both groups.To evaluate whether there are any effects of gender in the ADHD and control group besides the normal differences between male and female brains, we performed an ANOVA assessing the interaction between diagnosis and gender on the child sample . Moreover, to ensure that subtle differences in gender distribution between the adult and child groups did not underlie the observed differences in cortical thickness between the samples, we also repeated the interaction contrast excluding the 21 female participants from the child control and ADHD groups.To correct for multiple comparisons, we applied the monte carlo test simulation bootstrap (MCTSB) at a threshold of p<0.05. For completeness, when no differences were observed at this threshold, we reported the results at a threshold of p<0.001 uncorrected for multiple comparisons. In these cases, it is clearly indicated that the threshold was lowered for these comparisons and that no results were obtained at a corrected threshold.To evaluate the neuroanatomical profile associated with the child form of the disorder, we examined the thickness of the cortical mantle in the group of ADHD children in comparison to the child control sample. When comparing these groups, we observed substantial deficits in laminar thickness across the cerebral mantle, primarily localized in sections of the fronto-parietal cortex see . More spThen, we compared the adult ADHD patients – combining the medication-naïve sample and the patients with a history of pharmacological treatment- to the group of neurotypically developed adults. At the threshold of p<0.05 MCTSB corrected for multiple comparisons, however, we found no differences in cortical laminar thickness between the groups. Only when lowering the applied threshold to p<0.001, uncorrected for multiple comparisons, a few clusters surfaced. These comprised relative deficits in the thickness of the cortical mantle in the superior parietal, posterior cingulate, superior frontal and postcentral cortex, as well as some localized clusters of enlarged thickness in the frontal and temporal lobes see .2, p = 3.35E-07. R inferior parietal/lateral occipital/inferior temporal cortex: Talairach 39.3 −75.9 29.2, 2877.71 mm2, p = 9.20E-10. R superior parietal/postcentral cortex: Talairach 10.5 −63.4 54.2, 3103.33 mm2, p = 2.81E-05. R lingual/fusiform cortex: Talairach 10-5 −81.5 −1,7, 1386.22 mm2, p = 3.43E-04. L orbitofrontal/rostral middle frontal/inferior frontal cortex: Talairach −32.7 25.0 −16.3, 5540.25 mm2, p = 2.40E-05. R orbitofrontal/rostral middle frontal/inferior frontal cortex: Talairach 38.7 50.3 −7.2, 1369.08 mm2, p = 1.69E-04. L precentral cortex: Talairach −38.9 −5.1 53.0, 1394.64 mm2, p = 2.61E-05), which are depicted in To investigate whether child and adult patients with ADHD show a distinct neuroanatomical profile, we included all subjects into one model and applied an interaction contrast (Diagnosis×Age group). This comparison rendered widespread clusters across the cortical mantle . Statistical maps depicting these results are displayed in To assess whether these findings do not primarily reflect the differences between the child and adult sample in the distribution of medication-naïve patients, we repeated our comparisons using only the medicated patients, which represent the sample most commonly used for neuroimaging studies on ADHD. When performing the interaction contrast excluding the medication-naïve patients in each age group (24 of the adult patients and 5 of the child patients), we observed similar results to those obtained with the whole sample  as well as some clusters showing the opposite pattern .As the child patient and control groups included several girls, we wanted to examine the relation between ADHD and gender. Therefore, to search for effects of gender in the ADHD and control group besides the normal differences between male and female brains, we applied an interaction contrast on the child sample (‘Diagnosis×Gender’). At a threshold of p<0.05 MCTSB corrected for multiple comparisons, no results were observed. For completeness, we also checked the results of this interaction effect using a more liberal threshold of p<0.001 uncorrected. At an uncorrected threshold, we found several regions where neurotypically developed boys show larger cortical thickness values than neurotypically developed girls, while this pattern was not observed in boys and girls with ADHD . The results of these comparisons are depicted in To ensure that the observed differences in cortical thickness between the child and adult groups were not driven primarily by the divergent gender distribution in these samples, we repeated the interaction contrast including only the male participants in all groups (excluding 21 subjects: 13 girls from the child control group and 8 girls from the child ADHD group)  and the bilateral medial occipital cortex.Some previous studies have investigated cortical thickness in patients with ADHD, observing widespread reductions in cortical thickness. These deficits were mainly located in sections of the parietal and frontal cortex associated with attentional processing Only a few previous studies have applied an analysis of cortical thickness to evaluate cortical morphometry in adults with ADHD, and these, although primarily using mixed samples of medicated and medication-naïve patients, also point to deficits in regions that subserve attention and executive functions When inspecting our results, a remarkable similarity to the fronto-parietal attention networks, especially the dorsal attention network, is immediately evident. Corbetta et al. proposed that attention is subserved by two partially functionally and anatomically segregated neural circuits that reflect a distinction between goal-directed top-down and stimulus-driven orienting The ventral attention network is more ventrally positioned within the brain and more strongly lateralized to the right hemisphere. This network is centered on the temporo-parietal junction  and the ventral frontal cortex . In contrast to the dorsal system, this network supports stimulus-driven attention, and is specialized for the detection of behaviorally relevant stimuli, especially unattended or low-frequency events The regions that harbor the cortical differences between ADHD patients and control subjects observed in our study correspond to structures implicated in these attentional networks, especially the dorsal fronto-parietal attention network. In fact, the pattern of regions showing the most severe deficits in cortical thickness compared to control subjects bears a remarkable resemblance to the attention networks as described by previous studies , the bilateral frontal cortex  and the bilateral medial occipital cortex , showing a remarkable resemblance to the neural networks for attentional processing as described in the literature. The deficits in the cortical surface were very pronounced in the child patients. In the adult patients, however, a more typical laminar thickness was observed across the cortical mantle. These findings indicate that childhood ADHD is associated with robust deficits in the cortical mantle, which are especially prominent in brain structures subserving attentional processing.


Prescription stimulants are often used to treat attention deficit hyperactivity disorder (ADHD). Drugs like methylphenidate , dextroamphetamine (Dexedrine), and dextroamphetamine-amphetamine  help people with ADHD feel more focused. However, misuse of stimulants by ADHD and nonaffected individuals has dramatically increased over recent years based on students' misconceptions or simple lack of knowledge of associated risks. In this review, we discuss recent advances in the use and increasing misuse of prescription stimulants among high school and college students and athletes. Given the widespread belief that stimulants enhance performance, there are in fact only a few studies reporting the cognitive enhancing effects of stimulants in ADHD and nonaffected individuals. Student athletes should be apprised of the very serious consequences that can emerge when stimulants are used to improve sports performance. Moreover, misuse of stimulants is associated with dangers including psychosis, myocardial infarction, cardiomyopathy, and even sudden death. As ADHD medications are prescribed for long-term treatment, there is a need for long-term safety studies and education on the health risks associated with misuse is imperative. Attention deficit hyperactivity disorder (ADHD) is a treatable neurobehavioral disorder that is defined by persistent and maladaptive symptoms of hyperactivity/impulsivity and inattention . ADHD isIndividuals with ADHD often have substantial functional impairment in academic, family, and social settings. Youth with ADHD are at an increased risk for academic failure because of learning or language problems. Other consequences associated with ADHD include dangerous driving, impaired peer relationships, delinquent behavior, and impulsive sexuality . MoreoveThere are both pharmacological and nonpharmacological  treatments of ADHD. Stimulants, such as methylphenidate  and dextroamphetamine-AMP  are the most common pharmacologic treatments  and abunThe New York Times have reported a trend toward growing use of prescription stimulants, commonly called “smart pills,” by high school and college students for enhancing school or work performance . The nonmedical use of prescription stimulants represents the second common most form of illicit drug use in college, second only to marijuana use . Indeed,formance . Unfortuformance . StimulaThis review discusses recent studies regarding the use and misuse of stimulants among high school and college students, including athletes, with and without ADHD. Given the widespread belief that prescription stimulants are “smart pills,” we address if these drugs actually enhance cognition in a healthy individual. Athletes may see stimulants as a way to help maintain physical fitness for their competitive sport or to improve their concentration. Finally, we elaborate on the long-term effects of chronic stimulant use. Addiction and tolerance are major concerns, as are psychosis and cardiovascular effects. Surprisingly, these associated risks of stimulant misuse are not frequently addressed in the media and literature. Clearly, the widespread misuse of prescription stimulants represents an important public health issue faced by students, school officials, health centers, and parents.This review was initiated with a PubMed search of the US National Library of Medicine with combinations of the following key words: “Adderall,” “amphetamine,” “methylphenidate,” “dexamphetamine,” “ADHD,” “misuse,” “illicit use,” “non-prescription use,” “non-medical use,” “diversion,” “students,” and “athletes.” A review of all titles was conducted to include only pertinent publications. A hand search of psychiatry journals was performed and reference lists from relevant studies were searched.It is estimated that about two-thirds of the children diagnosed with ADHD receive pharmacological treatment  and the MPH and d-AMP are the most widely used prescription stimulants approved by the US Food and Drug Administration (FDA) for the treatment of ADHD. MPH is a short-acting stimulant drug. Generic MPH is available in many forms, and several versions of the long-acting MPH have been introduced, with Concerta getting the largest share of the market. According to the U.S. Drug Enforcement Administration (DEA), MPH has been the fourth most prescribed controlled substance in the United States since 2003, with over 58,000 Americans purchasing MPH in 2006 . Both thAlthough ADHD is a multifactorial disorder, disrupted dopamine (DA) neurotransmission plays an important role in its pathophysiology. In addition, polymorphisms in the dopamine D1 receptor (DRD1) are associated with the disorder . MPH andNew York Times  compared four distinct treatment strategies during childhood for children diagnosed with DSM-IV ADHD, Combined Type . ChildreThe misuse of a stimulant medication – taking a stimulant not prescribed by a physician or in a manner not in accordance with physician guidance – has been growing over the past two decades. In fact, in the past 10 years there has been a surge in prevalence rates of nonprescription stimulant use among both adolescents and young adults. In general, nonprescription use of MPH in 2000 was reported as 1.2% and in 2006 this number had risen to 2%. Breaking the sample down by age, nonprescription use among adolescents (ages 12–17) went from 2.2% to 1.8% between 2000 and 2006, a slight decrease. Among college-aged individuals (ages 18–25), however, usage increased significantly from 3.6% in 2000 to 5.4% by 2006. Finally, among those 26 and older, usage is the lowest of any group, but rates are rising. In 2000, only 0.7% reported any lifetime usage of MPH, but this number had doubled to 1.5% by 2006 .The majority of research on the misuse of prescription stimulants has focused on undergraduate college students. The nonprescription use of stimulants has increased in this population, to the extent that the misuse of prescription stimulants is second only to marijuana as the most common form of illicit drug use among college students . A 2001 The majority of nonprescription stimulant users reported obtaining the drugs from a peer with a prescription – a process termed diversion. The diversion of stimulants is very common and can begin in childhood, adolescence, or young adulthood. A study conducted by A descriptive, nonexperimental, cross-sectional study examined the nonprescription use of stimulants among student pharmacists . LifetimThe prevalence of prescription stimulant misuse in medical students is also high. In fact, discussion based websites such as Facebook, Medical School Forum, and The Student Doctor Network are rife with Adderall “experts” and informal question-and-answer sessions on the drug. An anonymous survey was administered to 388 medical students (84.0% return rate) across all 4 years of education at a public medical college. More than 10% of medical students reported using stimulants to improve academic performance. ADHD was diagnosed in 5.5% of students and 72.2% of those students were diagnosed after the age of 18 years . This stThe reasons why prescription stimulants are misused are numerous and include achieving euphoria, and helping cope with stressful factors related to their educational environment. According to a survey of 334 ADHD-diagnosed college students taking prescription stimulants, 25% misused their own prescription medications to get “high” . Like coStimulants are especially popular at the end of a school term when students will often use the drugs to stay awake through the night to study for exams or complete academic projects. In fact, prescription stimulants are most commonly misused to enhance school performance. According to a Web survey of 115 ADHD-diagnosed college students, enhancing the ability to study outside of class was the primary motive for misuse . PressurNeuropsychological studies of ADHD children and adults indicate impairments in many cognitive areas including selective attention, memory, reaction time, information processing speed, and executive control function such as set-shifting, and working memory. The benefits of prescription stimulants for enhancing classroom manageability and increasing attention and academic productivity in children are well established. Prescription stimulants may increase the quality of note taking, scores on quizzes and worksheets, writing output, and homework completion. Nevertheless, they do not normalize the ability to learn and apply knowledge . In factThe first review to describe the general academic functioning of adults with ADHD summarized the results from 23 studies . ADHD-diA recent controlled, cross-sectional study evaluated the effects of stimulants on cognition in adults with ADHD and found that treated ADHD subjects had significantly better scores on measures of IQ than did untreated patients . It has also resulted in a corresponding escalation of nonprescription stimulant use in many college students confirmed by numerous surveys. Studies consistently show that students report using stimulant medications, legally or illicitly, to improve academic performance, specifically to increase concentration and the ability to stay up longer and study. Intuitively, it would seem logical that drugs that improve attention and concentration should also promote learning and academic achievement. Inherent in terms like “cognitive enhancers,” “smart drugs,” and “neuroenhancers” is the assumption that MPH and d-AMP enhance cognition. Major magazines such as Adderall . UnfortuAdderall . Duke UnIn contrast to the types of memory, which are long lasting and formed as a result of learning, working memory is a temporary store of information that plays a role in executive function. Several studies have assessed the effect of MPH or d-AMP on tasks examining various aspects of working memory  see Tab. One claThe third type of cognition is cognitive control. Cognitive control is a broad concept that refers to guidance of cognitive processes in situations where the most natural, automatic, or available action is not necessarily the correct one . AttentiThe neural basis of error processing has become a key research interest in cognitive neuroscience. Recently, a single dose of MPH was shown to improve the ability of healthy volunteers to consciously detect performance errors . FurtherAs it remains unclear whether stimulant medication has the same effect on healthy individuals as for those with ADHD, it is possible that many reported effects of prescription stimulants in healthy individuals may stem from placebo effects. ADHD is a controversial problem in sport as participants with this disorder often require banned stimulants while competing. Many of the governing bodies of competitive sports have developed regulations that limit the use of stimulant medications to treat ADHD. In other cases, stimulant use is allowed in the setting of a documented diagnosis of ADHD. Most sports organizations around the world now follow the guidelines set forth by the World Anti-Doping Agency (WADA). According to this document, the diagnosis of ADHD is to be made by “experienced clinicians” and in accordance to the DSM-IV. Stimulant medications are considered to be a “medical best practice treatment” that do require the athlete to file a therapeutic use exemption (TUE). A TUE gives athletes with medical diagnoses an exemption to use a drug normally prohibited by MLB, to treat a legitimately diagnosed medical condition. WADA recommends reassessments of continued treatment every 3–4 months. Other organizations, such as the National College Athletic Association (NCAA) and individual professional leagues, such as the National Football League (NFL) and Major League Baseball (MLB), have developed their own regulations.The NCAA does not require that physicians prescribe a trial of nonstimulant medications before prescribing stimulants, only that the prescribing physician considers nonstimulants first. The NCAA acknowledges that nonstimulant medication may not be as effective as stimulant medications in treating ADHD. In contrast to the NCAA regulations, athletes who are also participating in events governed by the International Olympic Committee (IOC) and/or WADA are not allowed to use stimulant medications, even with a TUE. These organizations require that the athlete with ADHD on stimulant medications stop taking these medication or risk disqualification .It has been reported that MLB players are using an ADHD diagnosis to evade the AMP ban . AccordiSome athletes will only take medications episodically for school testing or for studying purposes. Others may feel that their sport performance is improved on stimulants, whereas others may temporarily stop taking them so that their sports play is more random and unfocused, which they feel improves their performance .ADHD is now recognized as a chronic disorder that continues into adulthood; therefore, some individuals take stimulants such as MPH and d-AMP for years. The medical literature provides abundant data to support the potentially positive effect of stimulants for the majority of children, adolescents, and adults with ADHD, and stimulants have been considered to be relatively safe . HoweverLarge doses of stimulants can lead to psychosis, seizures, and cardiovascular events. The induction of schizophrenic-like states in AMP abusers is well documented, although the onset of such states in children on prescribed doses of stimulant medication is observed far less often . Surles The most commonly observed cardiovascular effects linked with ADHD stimulant medications include hypertension and tachycardia. In addition, cardiomyopathy, cardiac dysrhythmias, and necrotizing vasculitis have been described. In February 2005, the brand medication Adderall XR  was withdrawn from the Canadian market by Health Canada. Case reports on serious cardiovascular adverse drug reactions (ADRs), sudden death, and psychiatric disorders led regulatory agencies to warn against the use of MPH in the pediatric population in 2006 and 2007 . In 2006Adderall use is associated with myocardial infarction and even sudden death . Gandhi In addition, a recent report by Unfortunately, there are few long-term studies  on the use of stimulants for the management of ADHD; therefore, the precise long-term effects – either adverse or positive – remain unknown. A recent study  suggestsA cohort study sought to determine whether use of MPH in adults is associated with elevated rates of serious cardiovascular events compared with rates in nonusers . All newAdditional potential ADRs associated with stimulant use are important to note including abdominal pain, anorexia, constipation, dizziness, dry mouth, headache, insomnia, jitteriness, irritability, nausea, and palpitations . CollegeAlthough prescription stimulants have been shown to be relatively safe and effective in managing the symptoms of ADHD, there exists a significant potential for misuse. The data are clear that individuals with and without ADHD, including athletes misuse stimulants to enhance performance. Although stimulants may improve an individual's performance when given a rote-learning task, they do not offer as much help to people with greater intellectual abilities. Stimulants do not increase IQ . In fact


Attention deficit/hyperactivity disorder (ADHD) is the most frequently diagnosed childhood neurobehavioral disorder. Much research has been done to identify genetic, environmental, and social risk factors for ADHD; however, we are still far from fully understanding its etiology. In this review we provide an overview of diagnostic criteria for ADHD and what is known about its biological basis. We also review the neuropsychological functions that are affected in ADHD. The goal is to familiarize the reader with the behavioral deficits that are hallmarks of ADHD and to facilitate comparisons with neurobehavioral deficits associated with environmental chemical exposures.Relevant literature on ADHD is reviewed, focusing in particular on meta-analyses conducted between 2004 and the present that evaluated associations between measures of neuropsychological function and ADHD in children. Meta-analyses were obtained through searches of the PubMed electronic database using the terms “ADHD,” “meta-analysis,” “attention,” “executive,” and “neuropsychological functions.” Although meta-analyses are emphasized, nonquantitative reviews are included for particular neuropsychological functions where no meta-analyses were available.The meta-analyses indicate that vigilance (sustained attention), response inhibition, and working memory are impaired in children diagnosed with ADHD. Similar but somewhat less consistent meta-analytic findings have been reported for impairments in alertness, cognitive flexibility, and planning. Additionally, the literature suggests deficits in temporal information processing and altered responses to reinforcement in children diagnosed with ADHD. Findings from brain imagining and neurochemistry studies support the behavioral findings.Behavioral, neuroanatomical, and neurochemical data indicate substantial differences in attention and executive functions between children diagnosed with ADHD and non-ADHD controls. Comparisons of the neurobehavioral deficits associated with ADHD and those associated with exposures to environmental chemicals may help to identify possible environmental risk factors for ADHD and/or reveal common underlying biological mechanisms. In recent years, there has been increasing awareness of the role of environmental factors in neurodevelopmental disorders, including attention deficit/hyperactivity disorder (ADHD) e.g., . In thishttp://www.ncbi.nlm.nih.gov/pubmed/) using the terms “ADHD,” “meta-analysis,” “attention,” “executive,” and “neuropsychological functions,” among others. Meta-analytic studies were included if they originated in 2004 or later, included children or adolescents, and measured the effect size of the association between neuropsychological deficits and ADHD in terms of Cohen’s d, which is a metric that is discussed ahead. If no meta-analysis was available for a particular neuropsychological function, nonquantitative reviews were included.Meta-analyses were obtained through searches of PubMed , Text Revision , which measure the ability to respond to a rare target  over an extended period of time .d, which is defined as the difference in means divided by the pooled standard deviation across study populations. Cohen’s d is a standardized measure often used to compare the effects of variables measured on different scales and to estimate effect size across different studies. d are not included.d = 0.39)  . Slower  = 0.39)  comparedVigilance is commonly assessed by errors of omission (misses) on CPTs. Two meta-analyses, one of 30 and the other of 33 studies that were published in 2004 or later, found that on CPTs, ADHD children made more errors of omission than non-ADHD controls did . Both med. The inclusion criteria for d and that analyzed studies whose samples included children. As in Executive function refers to a set of abilities including working memory, response inhibition, and error correction that are involved in goal-directed problem solving . ExecutiWorking memory is the ability to hold something in mind momentarily while doing something else or while using the information to perform an action . ResearcResponse inhibition refers to the ability to inhibit or interrupt a response during dynamic moment-to-moment behavior . Key pard effect size for SST studies that included or were limited to children. The analyses indicated that, compared with non-ADHD individuals, those diagnosed with ADHD were consistently slower in stopping an ongoing response, suggesting difficulty in response inhibition. Effect sizes for stop signal reaction times in ADHD samples were in the moderate range (d = 0.54–0.63).As d effect sizes (d = 0.51–0.56).Commission errors  in CPTs are also often used as a marker of response inhibition deficits in ADHD children. Since 2004, three meta-analyses  have exact sizes . As in tThe ability to switch attention from one aspect of an object to another, or to adapt and shift one’s response based on situational demands, such as changes in the rules, schedule, or type of reinforcement in a task, is defined as cognitive flexibility or set shifting . Tests uOn the WCST, subjects are asked to sort into two different piles a series of cards with figures that can differ in color, shape, and/or number. Each time a card is sorted, the subject receives feedback as to whether the choice was correct or incorrect, and based on this feedback the subject must infer the correct category  for sorting . After tIn the Stroop task, problems in cognitive flexibility are measured by the degree of difficulty subjects have in naming the color of the ink used to print color words when the two are mismatched . Interference scores quantify subjects’ difficulty in the task, with higher scores indicating greater difficulty. Effect sizes for Stroop interference scores reported in five recent meta-analyses  vary widd = 0.55 and 0.59 respectively, as shown in Another widely used tool for assessing cognitive flexibility is Trails-B, in which subjects are presented with numbers and letters inside circles that are randomly arranged on a sheet of paper. Subjects are asked to connect in ascending order the numbers and letters while alternating between them ; they are asked to do this as quickly as possible . Time toSome researchers have found that deficits in planning and strategy development discriminate well between children with ADHD and those without . ADHD chTower tasks such as TOH and TOL are a popular neuropsychological measure of planning . The mand = 0.24–0.69)  while following a number of rules  . Plannin24–0.69)  for the In summary, meta-analyses indicate that performance is impaired in ADHD individuals on a large number of attention and executive function tasks. Within the attention and executive function domains, larger deficits are found on tasks measuring vigilance, working memory , and response inhibition abilities, whereas smaller but significant deficits are also seen on tasks measuring alertness, cognitive flexibility, and planning abilities. There is overlap in the studies included in some of the meta-analyses discussed herein. Thus, the individual analyses cannot be taken as totally independent indicators of the effect. Also, deficits on any single test of attention or executive function are not sufficient for a diagnosis of ADHD e.g.,  or for dTwo other types of deficits related to the processing of temporal information and to responses to the reinforcing properties of rewards have been reported in ADHD children but have not been subjected to meta-analysis. These deficits could contribute to the difficulties ADHD children have in executive function tasks. Recent studies have focused increasingly on temporal information processing, which is believed to be key to the control and modulation of behavior . Toplak In terms of responses to reinforcement, The heterogeneity in symptoms and functional deficits observed in ADHD is paralleled by heterogeneity in the results of brain imaging studies. Although many individuals with ADHD do not have abnormal structural magnetic resonance imaging (MRI) results, when the results are considered across individuals in an ADHD sample, a pattern of structural changes becomes evident . OverallThere is strong evidence for altered corticostriatal circuitry in ADHD. This circuit includes the dorsolateral prefrontal and dorsoanterior cingulate cortices, the dorsal striatum , and the thalamus, which links to the cerebellum . The dorBilateral prefrontal cortices, the right caudate, and regions of the cerebellum were all found to be reduced in size in a meta-analysis of structural MRI findings , whereasA limited number of functional MRI studies suggest alterations in functional connections between components of the corticolimbic circuit . This ciConverging lines of evidence argue that dysfunctional catecholaminergic signaling underlies the cognitive alterations seen with ADHD . The preAlthough the exact nature of the neurochemical deficits underlying ADHD is still unknown, there is evidence that hypoactivity of frontostriatal dopamine circuits  and the dopamine 4 (D4) receptor gene (DRD4) have been most often associated with ADHD; other candidate genes with significant associations in meta-analyses include the dopamine D5 receptor (DRD5), serotonin transporter , serotonin receptor 1B , and synaptosomal-associated protein 25 (SNAP25)  also have been associated with ADHD  . PolymorHD e.g., , althoughenotype .a priori hypotheses , which are population based, differ from candidate gene studies in that the entire genome is analyzed without potheses . These apotheses , the finpotheses . This mapotheses . The abspotheses . In linepotheses , suggestGWAS is a more powerful, unbiased method used to search for risk genes of smaller effect . So far,ADHD is a complex disorder with great heterogeneity in the behavioral symptoms presented and brain functions and structures affected. It is clear, however, that several aspects of attention and executive function—particularly vigilance, working memory, and response inhibition—are compromised in ADHD children. Deficits in the processing of temporal information and the processing of rewards are also associated with ADHD and could be either related to or exacerbated by the deficits in executive function.Although much research has been done on the neuropsychological, neuroanatomical, neurochemical, and genetic bases of ADHD, we are still far from fully understanding its etiology. Given the inability to explain ADHD on a solely genetic basis, interest in the contribution of environmental factors—including exposure to chemical contaminants—has intensified. To date, most of what has been written on this topic focuses on just two contaminants, lead and PCBs, although potential contributions of other chemicals are beginning to be explored. In our companion review , we disc


There are new chemical substances that increase the strength of washing products such as surfactants. However, these products are not biodegradable and can all be found in surface water, groundwater. Cationic surfactants are one of the pollutants of greatest danger to man is his environment. Therefore, we have determined some parameters of three cationic surfactants by molecular modeling, using the CHEM 3D bio. We, therefore, optimized geometries and minimized the energy of cetyltrimethylammonium chloride (CTAC), the cetyltrimethylammonium bromide (CTAB) and cetyltrimethylammonium iodide (CTAI) by molecular mechanics. we calculated the size of these molecules and their molecular partition coefficients and their ovalities using molecular dynamics. The results showed that the three pollutants are adsorbed on Mt , Mt (Mg) and Mt (Ca) and are not adsorbed on Mt (Na). Mt (K) can adsorb only CTAC. The values of the partition coefficient of the three surfactants are equal to unity. The cationic surfactants studied are highly hydrophilic and spend very little through a membrane. Al so, these values showed that these surfactants are much more soluble in water than in octanol. Both surfactants, CTAB and CTAI have the highest ovality values. They can therefore more easily approach a spheric or cylindric form. CTAC has the lowest ovality, it presents more difficulty to approach a spherical or cylindrical shape.