Clinically impairing irritability affects 25% to 45% of children with attention-deficit/hyperactivity disorder (ADHD); yet, we know little about what interventions are effective in treating children with ADHD and co-occurring irritability. We used data from the Multimodal Treatment Study of Children With ADHD (MTA) to address 3 aims: to establish whether irritability in children with ADHD can be distinguished from other symptoms of oppositional defiant disorder (ODD); to examine whether ADHD treatment is effective in treating irritability; and to examine how irritability influences ADHD treatment outcomes.Secondary analyses of data from the MTA included multivariate analyses, and intent-to-treat random-effects regression models were used.Irritability was separable from other ODD symptoms. For treating irritability, systematic stimulant treatment was superior to behavioral management but not to routine community care; a combination of stimulants and behavioral treatment was superior to community care and to behavioral treatment alone, but not to medication alone. Irritability did not moderate the impact of treatment on parent- and teacher-reported ADHD symptoms in any of the 4 treatment groups.Treatments targeting ADHD symptoms are helpful for improving irritability in children with ADHD. Moreover, irritability does not appear to influence the response to treatment of ADHD.http://www.clinicaltrials.gov; NCT00000388.Multimodal Treatment Study of Children With Attention Deficit and Hyperactivity Disorder (MTA);  Clinically impairing irritability affects 25% to 45% of children with attention-deficit/hyperactivity disorder (ADHD)DSM.ADHD is among the most common child psychiatric disorders worldwide.DSM-5One approach to this question is to consider irritability as one of the manifestations of behavior problems that are typical of ADHD. Indeed, irritability is characteristic of children with oppositional defiant disorder (ODD), which is highly comorbid with ADHD.Here we use data from the MTA to address these questions by examining 3 aims. First, we wanted to establish the robustness and clinical relevance of irritability in the MTA. In particular, it is important to know whether irritability in children with ADHD can be distinguished from other typical symptoms of oppositionality, namely, headstrong symptoms. We hypothesized the following: that irritability would be separable from headstrong behaviors in multivariate analyses; that irritability would have different external correlates/consequences ; behavioral treatment ; combined treatment ; or treatment-as-usual community comparison . The first 3 groups were treated for 14 months in specified protocols. Briefly, MedMgt consisted of a 1-month double-blind titration with methylphenidate for best dose, progressing to an open titration with other drugs, such as d-amphetamine, pemoline, or imipramine if methylphenidate was unsatisfactory. Beh consisted of intense, multi-component individual and group parent training; teacher consultation; a child-directed, 8-week, full-time summer treatment program; and use of a 12-week, half-time classroom behavioral specialist. Comb integrated the MedMgt and Beh strategies, with more extensive assistance from the behavioral therapist to assist in medication adjustment and information from the pharmacotherapist to aid in decision making about escalation of behavioral interventions. The fourth group (CC) was referred for community treatment of the parents' choosing. The mean age of the children at baseline was 8.5 years , and 114 children were female (19.7%). Ethnic composition of the sample included 60.8% of white ethnicity, 19.9% African American, and 19.3% Hispanic, racially mixed, or from other ethnic origins. Treatment groups did not differ significantly at baseline on gender, ethnicity, IQ, comorbidity, Conners Parent and Teacher Rating Scales scores, impairment, and medication for ADHD before the study. The only significant difference was age, although all participants were actually in a tight age range . At least 1 parent and all participants in the original MTA study provided written permission and assent for participation before initiation of any study procedures as approved by each site’s institutional review board. For the present study, all of the participants from the original study were included. Additional details about the sampling and the procedures in the MTA have been widely described elsewhere.The measures relevant to our study are described below. A comprehensive description of the assessment measures used in the MTA has been described elsewhere.ADHD symptom severity was measured by using the mean score of items 1 to 18 of the parent- and the teacher-reported Swanson, Nolan, and Pelham (SNAP) rating scale,In accordance with previous studies,A headstrong dimension was generated by adding up 4 ODD items on the parent-reported SNAP: “Argues with adults,” “Actively defies or refuses adult requests or rules,” “Does things deliberately that annoy other people,” and “Blames others for his or her mistakes or misbehavior.” The scores ranged from 0 to 12. The only ODD item not used for either the irritability or the headstrong scales was “Is spiteful or vindictive.”The CBCL was used to assess general psychopathology. The CBCL is a parent-report checklist mapping onto multiple aspects of psychopathology over a 6-month period.Data analyses for each specific aim were as follows: 1) To establish whether irritability was independent from other ODD symptoms in the MTA sample, we proceeded in 4 ways. First, we explored differences in the multivariate structure using a confirmatory factor analysis (CFA) comparing 2 models . Second, we explored the longitudinal continuity of each measure (irritability and headstrong behaviors) using path analysis. Third, we explored whether irritability and headstrong behaviors had different correlates in linear regression models in which the 2 variables were introduced as predictors, Finally, we ran a linear regression in which irritability and headstrong behaviors were predictors of impairment to test whether the 2 dimensions contributed independently to it. This is important because impairment can be independent of symptom severity.The de-identified MTA dataset  was provided by the National Institute of Mental Health (NIMH) upon public-access request. The Psychiatry, Nursing, and Midwifery Research Ethics Subcommittee (PNM RESC) at King’s College London approved the secondary analysis of these data (reference PNM/13/14-34).p < .001) and with the CISP  were in the medium range.The mean score for the whole sample for the parent-reported irritability subscale derived from the ODD items of the SNAP was 4.30 (SD = 2.48) and the median value was 4. Internal consistency was high (Cronbach’s α = .83), and it showed good convergent validity by correlating highly with a scale comprising irritability items from the CBCL . This measure of irritability derived from the CBCL has also been used in previous research.p ≤ .001).The 2-factor model (irritability versus headstrong behaviors) showed a better fit with the data  compared to the 1-factor model , as confirmed by difference testing  compared to headstrong behaviors at 14 months , whereas the headstrong behaviors dimension at baseline was a significantly better predictor of headstrong behaviors at 14 months  than irritability at 14 months . This supports the idea that these constructs are distinct from each other  as well as at the end of treatment (irritability: β = 0.35 [95% CI = 0.23–0.47] versus headstrong behaviors: β = −0.03 [95% CI = –0.15–0.08]). Conversely, the headstrong behaviors measure was a significantly stronger predictor of the Externalizing Scale at baseline (irritability: β = 0.29 [95% CI = 0.21–0.38] versus headstrong behaviors: β = 0.47 [95% CI = 0.38–0.55]) but not at the end of treatment (irritability: β = 0.22 [95% CI = 0.10–0.33] versus headstrong behaviors: β = 0.29 [95% CI = 0.18–0.40]) .Finally, irritability and headstrong behaviors each contributed independently to impairment . As shown in There were no differences in the level of parent-reported irritability at baseline in the 4 treatment groups ; the variable was therefore excluded in a subsequent, more parsimonious model, which included time and treatment group only as predictors of change (p = .021), but not the CC group . Those in the Comb group were more likely to improve than those in the Beh  and CC  groups, but there was no difference between the MedMgt only and Comb . It is important to note that the effect sizes of difference between treatments are more modest compared to the effect sizes between pre- and posttreatment for each group. For example, the effect size of the difference between the Comb and CC arms is 0.34, whereas the difference between CC and Beh is −0.05. However, it is worth noting that the magnitude of the difference between ADHD treatments is best accounted for by the random-effects regression model which, unlike the effect sizes, takes into account the heterogeneity across individuals in their responses over time. Effect sizes are displayed in The random-effects regression model included time, treatment group, and site as predictors of change in irritability. Omnibus Wald tests for the effect of site did not reach significance , for which the variable was excluded in a subsequent, more parsimonious model, which included time, treatment group, and irritability only as predictors of change  and a main effect of time (indicating that ADHD scores decreased significantly over time). The effect of site (but not of the interaction site×treatment) was also significant. As shown in 2 [5] = 5.33, p = .377; site×treatment: χ2 [15] = 12.54; p = .638) and therefore was dropped from the model. As can be seen in the lower part of Additional analyses looked at teacher-rated ADHD as an outcome in the previous model. This was to ensure that the paper's main findings held across informant sources, but also because teachers were more likely to be blinded to the treatment condition. As in the case of the parent-rated ADHD, the variable site did not reach significance p = .095). However, combining MedMgt with Beh treatment was superior to both the Beh treatment alone and the CC intervention, but not compared to MedMgt alone. Beh treatment was not significantly different from the community care intervention. These results show a partial overlap with previous MTA findings regarding other disruptive symptoms. Jensen et al.Our second aim was to test the hypothesis that symptoms of irritability would diminish with medication. We found that irritability levels decreased in all treatment arms after 14 months. However, the magnitude of the effect sizes for the irritability response to treatment was approximately half of the magnitude for ADHD symptoms in the original study.Finally, we wanted to examine whether high levels of irritability diminished ADHD treatment response. We found that the combined and medication-only treatment arms were superior to the behavioral treatment and the community care interventions at reducing ADHD symptoms, regardless of the level of irritability. This is in keeping with previous reports on the MTA data showing that the comorbidity of ADHD with ODD or CD rarely interacted with treatment response or outcomes.Limitations of this study include the fact that the MTA was not originally designed to examine irritability in children with ADHD, and therefore patient randomization was not stratified by irritability status. Second, the parents in the MTA study were not blinded to treatment group assignments. As such, the extent to which differential outcomes as a function of treatment group were influenced by parental expectations cannot be determined. However, teacher reports of ADHD symptoms were also used as outcomes, and the results were similar to those obtained when using the parent reports. Therefore, considering that teachers were probably blinded ,•Irritability is a separable dimension within the ODD construct in children with ADHD.•Standard ADHD treatments are helpful for reducing irritability in children with ADHD.•Irritability symptoms do not seem to influence ADHD treatment outcomes. Clinicians can proceed with confidence that ADHD treatments will be effective even in the presence of irritability.These results have 2 important clinical implications. First, stimulants—a commonly used and relatively safe class of drugs for ADHD—are also helpful for improving irritability in children with ADHD. Moreover, the combination of stimulants and behavioral treatment could help reduce these symptoms further. Second, irritability symptoms did not have a negative effect on ADHD treatment outcomes. Clinicians can proceed with confidence that ADHD treatments will be effective even in the presence of irritability. These 2 aspects had not been demonstrated in major randomized controlled trials in the field and have long remained an area of clinical uncertainty. Our results may also have etiological implications. Based on the fact that irritability improves with treatments that are effective for ADHD symptoms, it would be tempting to assume that common pathophysiology underlies the overlap between irritability and ADHD. Further research should therefore explore this possibility. Also, future studies should investigate whether ADHD treatment in children with irritable symptoms has a beneficial impact on mood symptoms in the medium-to-long term, given the links between irritability and mood disorders.


Autism spectrum disorder (ASD) traits are continuously distributed throughout the population, and ASD symptoms are also frequently observed in patients with attention-deficit/hyperactivity disorder (ADHD). Both ASD and ADHD have been linked to alterations in reward-related neural processing. However, whether both symptom domains interact and/or have distinct effects on reward processing in healthy and ADHD populations is currently unknown.n = 136), their unaffected siblings (n = 83), as well as healthy controls (n = 105) performed an MID task in a magnetic resonance imaging (MRI) scanner. ASD and ADHD symptom scores were used as predictors of the neural response to reward anticipation and reward receipt. Behavioural responses were modeled using linear mixed models; neural responses were analysed using FMRIB’s Software Library (FSL) proprietary mixed effects analysis (FLAMEO).We examined how variance in ASD and ADHD symptoms in individuals with ADHD and healthy participants was related to the behavioural and neural response to reward during a monetary incentive delay (MID) task. Participants  from the NeuroIMAGE study with a confirmed diagnosis of ADHD  ADHD and healthy participants. Our findings therefore suggest that both symptom domains affect reward processing through distinct mechanisms, underscoring the importance of multidimensional and multimodal assessment in psychiatry.The online version of this article (doi:10.1186/s13229-015-0043-y) contains supplementary material, which is available to authorized users. Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder characterized by social, communicative and behavioural deficits . ASD traADHD, a neurodevelopmental disorder characterized by inattentiveness and/or hyperactivity and impulsivity, has been associated with high ASD comorbidity and elevated levels of ASD symptoms compared to the general population –7. The hOne area where ASD and ADHD effects could interact is during the processing of reward. Both disorders have been linked to abnormalities in the frontal-striatal neural circuits associated with reward processing; whether this is the result of similar pathophysiological mechanisms is unclear , 11. SumIn ADHD, both hypoactivity and hyperactivity in reward circuits in response to reward have been reported. The current consensus is that ADHD is characterized by decreased striatal activation during reward anticipation , but incOnly a few neuroimaging studies on reward processing to date have included participants with ASD and ADHD , 26, 27.The previous studies therefore suggest that ASD and ADHD can have both shared and distinct effects on reward processing. In addition, some evidence suggests that the cognitive dysfunctions of comorbid ASD and ADHD are not simply a combination of those of ADHD and ASD, but can be qualitatively different and/or more severe , 27, 28.Hence, in the current study, we investigated these effects in a large well-described sample that included individuals with ADHD, their unaffected siblings and healthy control participants. Unaffected siblings were included as they are known to present with increased ASD symptom levels compared to healthy controls . Reward We expected that higher levels of ASD symptoms would be associated with activity changes in fronto-striatal regions and the insula during reward anticipation and receipt based on previous studies , 26, 27.Based on our analyses, we can report two main findings in this article. First, we observed that participants with more ASD symptoms showed increased activity in the insula during reward anticipation. Second, we found that higher ADHD symptom levels were associated with decreased activity in the dorsolateral prefrontal cortex during reward anticipation. We found no effects during reward receipt or any interaction between the ADHD and ASD effects.http://www.neuroimage.nl/). The NeuroIMAGE study was approved by the local ethics committee . For details on recruitment of participants and a description of all study procedures in NeuroIMAGE, see  > [Non-Reward Hit–Non-Reward Miss]). Estimated beta maps for both contrasts were normalized to MNI152 standard space for each participant for subsequent group comparisons.Group-level analyses modeled neural activation across the full sample of participants . Second-level activation maps were calculated with FSL FLAME using the normalized beta maps from the first-level analyses. Neural responses during reward anticipation and reward outcome were modeled separately at the second level and included the first-level variance estimates to account for between-subject differences in the quality of parameter estimation. The second-level model included the participant-specific ASD symptoms, ADHD symptoms, the ASD × ADHD interaction (the element-wise multiplication of the previous two variables), age, sex, IQ, scan site and ODD/CD comorbidity as explanatory variables (EVs). The factor Group  was only present as EV in post hoc sensitivity analyses. Additional models including separate regressors for ADHD hyperactive/impulsive and inattentive symptoms were run as supplementary analyses .All results reported were based on an initial uncorrected voxel-level threshold of p = 0.05 for all post hoc analyses.The mean time-series of each cluster that survived cluster-level correction were extracted for each participant using FSL for post hoc analyses in SPSS. In these analyses, results were corrected for familiality . Time-series for each cluster were entered as the dependent variable in a linear mixed model that included ASD symptoms, ADHD symptoms, the ASD × ADHD interaction, age, site and sex as fixed effects and Family ID as a random effect. Moreover, this analysis was repeated for the subset of participants for whom medication data was available, additionally including their total stimulant use duration as a random effect to control for the effect of medication use. This extra model served as a sensitivity analysis to investigate whether our findings were influenced by medication usage. Finally, the presence of interactions between any CSBQASD or CPRS-R-L effect and experimental group  was checked by running separate models that included Group and a CSBQASD by Group interaction in addition to all previous fixed and random effects. These models served to test whether the observed effects of ASD and ADHD symptoms and the parameter estimates in the regions under investigation differed in the three experimental groups. Alpha was set at t217 = 1.33, p = 0.186; ADHD vs CON t239 = 1.35, p = 0.179); unaffected siblings were older than controls . IQ was similar in participants with ADHD and their siblings , but was higher in controls than the two other groups . Scores on the CPRS-R-L were highest for ADHD, as expected , but were also elevated in siblings compared to controls . Finally, CSBQASD scores were higher in the ADHD group and their siblings compared to controls , but not significantly different between the former groups . In summary, participants with ADHD showed on average the highest severity of both ADHD and ASD, their unaffected siblings were similar to the ADHD group in ASD but not ADHD severity, and the healthy controls scored lowest on both ADHD and ASD dimensions.Table t test on the log transformed data: t323 = −12.73, p < 0.001). Subsequent mixed model analyses  showed no significant association between the CSBQASD or CPRS-R-L scores and any RT measure . In summary, although we found that reward trials showed the expected speeding of responses for all participants, we found no evidence that ASD or ADHD symptoms modulated the behavioural response of our participants in the MID task.Correct responses were faster for Reward versus Non-Reward Hits (Reward Hit RT ± standard error of the mean (SEM) = 287.41 ± 3.1 ms; Non-Reward Hit RT ± SEM = 317.18 ± 3.8 ms; paired All fMRI analyses were controlled for effects of age, sex, IQ, scan site and ODD/CD comorbidity. Reward anticipation (Reward Cue > Non-Reward Cue) was associated with significant activation in a network of brain areas including the ventral striatum, amygdala, insula, cingulate cortex and visual areas Fig. . Non-rewASD scores were positively correlated with activity in bilateral insula and the left superior frontal gyrus during reward anticipation. However, only the association between left insula activity and ASD scores remained significant after correction for familial non-independence and medication use Fig. . This efThe neural response to reward outcome was investigated using the contrast between Rewarded and Non-Rewarded outcomes (Reward Hit-Miss > Non-Reward Hit-Miss). Rewarded hits were associated with significantly stronger activation than non-rewarded hits in the ventral striatum, anterior cingulate and orbito-frontal cortex, posterior cingulate and parietal cortex and posterior visual areas Fig. . Non-rewIn this study, we present evidence that variation in ASD and ADHD symptoms is related to specific changes in the neural signatures of reward processing in patients with ADHD, their unaffected siblings and healthy controls. We found that ASD symptoms were positively related to left insula activity during reward anticipation across the three experimental groups. In contrast, ADHD symptoms were negatively related to activity in left dlPFC during reward anticipation. Both findings could not be explained by effects of age or sex. No effects of either ASD or ADHD were found during reward outcome.Neural hyperactivity during the processing of reward in ASD is not a common finding, but has been demonstrated previously , 18, 16.ADHD symptoms were associated with reduced left dlPFC activity during reward anticipation. ADHD has previously been linked to hypoactivity during anticipation of monetary reward, although primarily in striatal regions , 51, 52.Against expectation, we found no evidence for striatal effects of ASD symptoms in our study. Although striatal deficits related to reward processing have been observed in multiple ASD studies , other sWe did not find evidence for effects of ASD or ADHD symptoms during reward receipt, in the outcome phase of the MID task. Although it is difficult to speculate about the reasons for a null-finding, it could be in part due to the lower number of trials available for the outcome condition. However, we believe that our large sample offers substantial protection against this potential problem, and we do find strong reliable reward outcome-related neural responses. It could nevertheless be that dimensional effects of ADHD and ASD during the reward outcome phase are smaller than those during reward anticipation.In addition to the expected positive effects of reward anticipation in fronto-striatal regions, we also observed significant activation differences in the reversed contrast (i.e. stronger activity for anticipation of no reward versus reward). These effects were localized in brain areas previously associated with the so-called default mode network and could therefore reflect reduced task engagement (and increased mind-wandering) during non-reward versus reward anticipation .www.eu-aims.eu).The results of this study should be seen in the context of some strengths and limitations. First, although a large part of the autistic spectrum was covered in our experiment due to the inclusion of three groups of participants with varying degrees of ASD symptoms, we did not measure the extreme end of the spectrum by including participants with a clinical diagnosis of ASD. This makes it difficult to translate our findings to more severely affected populations. However, our results remain relevant for individuals with ADHD and the general population, where milder forms of ASD are commonly observed. To extend our findings and provide converging evidence for the results of the current study, we are currently conducting research using participants with a clinical diagnosis of ASD who are also evaluated for ADHD symptomatology in the EU-AIMS project  symptoms affect social (and other types of) reward differently from monetary reward. Further research is needed to investigate the specificity of our findings. Follow-up research could clarify whether social reward paradigms show similar effects. Given the ongoing discussion about the special relevance of social reward deficits in ASD and ADHD, such studies could provide valuable novel insights , 9.Since data were available from participants with ADHD (who scored high on ADHD and ASD), their unaffected siblings (who scored high on ASD but not ADHD) and healthy controls (who scored low on ADHD and ASD), our sample included a wide range of ASD and ADHD symptoms. This design, in combination with our large sample size, enabled us to separate effects of ADHD and ASD and study whether both symptom dimensions interacted. We found no evidence for an interaction between ADHD and ASD symptom scores, nor did we find that the neural effects of ASD and ADHD symptoms differed in the three experimental groups. Our findings therefore suggest that ASD and ADHD symptoms affected all types of participants equally (at a given level of severity) and that ASD and ADHD did not have multiplicative effects in our sample. Practically, this would mean that ASD and ADHD affect reward processing in distinct ways and via different  mechanisms. Our findings thus do not directly support theories of a shared aetiology between ASD- and ADHD-related reward dysfunction, nor do they point towards a qualitative difference in reward abnormalities in individuals who score high on both ASD and ADHD symptom measures. However, our sample did not include individuals with clinical levels of both ADHD and ASD, so we cannot rule out that such individuals would show specific abnormalities in line with previous studies , 27, 28.With this study, we provide evidence that variation in ASD- and ADHD-related symptomatology can modulate the neural response to reward anticipation in participants with ADHD, their unaffected siblings and healthy controls. Taken together, these results underscore the importance of multidimensional assessment for clinical and healthy populations in general and for the characterization of ADHD- and ASD-related effects on reward processing in particular.


The use of transcranial direct current stimulation (tDCS) in patients with attention deficit hyperactivity disorder (ADHD) has been suggested as a promising alternative to psychopharmacological treatment approaches due to its local and network effects on brain activation. In the current study, we investigated the impact of tDCS over the right inferior frontal gyrus (rIFG) on interference control in 21 male adolescents with ADHD and 21 age matched healthy controls aged 13–17 years, who underwent three separate sessions of tDCS  while completing a Flanker task. Even though anodal stimulation appeared to diminish commission errors in the ADHD group, the overall analysis revealed no significant effect of tDCS. Since participants showed a considerable learning effect from the first to the second session, performance in the first session was separately analyzed. ADHD patients receiving sham stimulation in the first session showed impaired interference control compared to healthy control participants whereas ADHD patients who were exposed to anodal stimulation, showed comparable performance levels  to the control group. These results suggest that anodal tDCS of the right inferior frontal gyrus could improve interference control in patients with ADHD. Attention deficit hyperactivity disorder (ADHD) is a childhood-onset psychiatric disorder which is characterized by developmentally inappropriate levels of inattention, impulsivity and hyperactivity (DSM-IV). It has a worldwide prevalence of 5.3% in children  and in mIn ADHD cognitive control, the ability to control sensory processes and actions in a goal-directed manner , is seveSuccessful interference control has been associated with the integrity of the right inferior frontal gyrus (rIFG) . In chilTranscranial direct current stimulation (tDCS) is a non-invasive tool for modulating cortical excitability. To conduct tDCS a weak current is passing through the scalp mostly via two conductive rubber electrodes in sponges soaked in saline solution or covered with conductive gel. The modulation of cortical excitability depends on the polarity of electrodes. In general, the positively charged anode increases cortical excitability while the negatively charged cathode decreases it . This moStudies showed tDCS induced improvements of symptom severity already in different psychiatric and neurologic disorders, for example depression , schizopStudies testing modulatory effects of tDCS in ADHD are, however, sparse. Using oscillatory tDCS during slow wave sleep, In the current study, we aimed to improve interference control in adolescents with ADHD using tDCS. In healthy adults, tDCS over of the rIFG and the pre-supplementary motor area has been successfully used to improve response inhibition , thus, tForty six male adolescents aged 13–17 years participated in the study. Three ADHD patients and one control participant were not included because behavioral data suggested that they did not comprehend the task (see Statistics for exclusion criteria).Participants and their parents were interviewed with the Revised Schedule for Affective Disorders and Schizophrenia for School-Age Children: Present and Lifetime Version  or lisdexamfetamine (n = 1) for the treatment of ADHD, refrained at least 24 h before each experimental session from taking their medication.Intelligence was assessed by the Culture Fair Test – Revised Version CFT, . HandednNo participant reported contraindications to receiving tDCS. The study was approved by the local ethics committee of the University of Magdeburg and followed the ethical standards of the Helsinki declaration. All participants and their parents gave written informed assent/consent before participating. Each participant received a voucher (10€) for a local shopping center per session.Figure 1C). Participants had to indicate the direction of the target arrow (right/left) by a button press with the index finger of their right or left hand, respectively. Flanking arrows pointed in the same (congruent stimuli) or opposite direction (incongruent stimuli) as the target arrow. Four resulting arrays were randomly presented with equal frequency. Stimuli were presented with a visual angle of 3.8° with Presentation software .Each participant received anodal, cathodal, and sham tDCS, separated by at least 1 week, while completing a modified Eriksen Flanker task . The ordFigure 1, each trial started with a fixation cross, presented for 100, 200, 300, or 400 ms followed by a blank screen for 100 ms. Then stimuli were presented for 60 ms followed by a blank screen for 300 ms and a fixation cross for 1000 ms. Participants had a total time of 1360 ms to respond to the target stimulus. The interstimulus interval varied between 1560 and 1860 ms. Participants were instructed to react as accurately and as fast as possible. The task consisted of three runs à 156 trials and had a total duration of 15 min. Before the task started, a short training was conducted for 1 min .As illustrated in 2) covered with saline soaked sponges. The stimulation electrode was centered on electrode site F8 , according to the 10–20 International EEG system which corresponds to the rIFG . Anodal and cathodal tDCS were applied for 20 min (with a 30 s ramp up and down). For sham stimulation electrode arrangement was identical to active stimulation but the stimulator was turned off after 30 s with a 30 s ramp up and down. To ensure stable stimulation effects according to Figure 1D). In the first 5 min of stimulation instruction was given to the participants and a short training block was conducted. Afterward, stimulation continued for the 15 min duration of the experimental task. At the end of each session participants indicated the strength of skin sensations caused by tDCS and their subjective ability to concentrate on a 5-point Likert-scale.A battery driven DC stimulator  delivered a direct current with an intensity of 1 mA via two conductive rubber electrodes ; las MNI, . The mullas MNI, . Two elelas MNI,  was emplFrom the original sample, three ADHD patients and one control person were excluded from the analysis because their commission error rates were more than two standard deviations above the mean of their respective group  indicating that they did not entirely comprehend the task.Rates of commission errors  and omission errors (no button press), mean of reaction times and reaction time variability  were analyzed in SPSS (version 22.0). Incongruent trials were considered for all analyses, as the performance in these trials serves as an indicator for quality of interference control. Only the first reaction of participants was analyzed and only correct trials were considered for reaction time analyses. Trials with reaction times less than 200 ms were excluded from all analyses. Repeated measures analyses of variance (ANOVA) were conducted with the factors tDCS type  and group (ADHD vs. control) for all dependent measures. In order to control for learning effects across sessions, we separately analyzed session number (1 vs. 2 vs. 3) and group (ADHD vs. control) in a further repeated measures ANOVA. Mean comparisons of directed hypotheses are reported one-sided.Figure 2A, Supplementary Table F = 15.71, p < 0.001], reaction times  and reaction time variability . Participants of both groups made more errors in the first session compared to the second  and the third session  . Reaction times and reaction time variability decreased also from the first to the second session . See Supplementary Table n = 7 in each group) as well as the three control groups did not differ in age or intelligence. Symptom severity did not differ between ADHD groups and the distribution of clinical subtypes and medication was comparable .The overall ANOVA did not show effects of tDCS regarding commission errors, omission errors, reaction times and reaction time variability, although descriptive data suggested diminished commission errors in the ADHD group after anodal stimulation  = 2.71, p = 0.08] . ADHD patients who received sham stimulation made more commission errors (mean: 20.57%) than controls (mean: 12.08%)  and ADHD patients receiving anodal stimulation had lower commission error rates (mean: 9.82%) than those who received sham stimulation . In the control group, there was no effect of tDCS . Thus, the commission error rate in ADHD patients who received anodal tDCS was at the same level as in healthy controls. Cathodal tDCS did not differ from sham tDCS in both groups .A marginally significant interaction between tDCS stimulation and group showed that patients tended to respond more strongly to stimulation than controls  showed that in patients reaction time variability was reduced during anodal stimulation compared to sham stimulation . Whereas ADHD patients who received sham stimulation showed higher variability of reaction times than control participants , ADHD patients in the anodal condition did not differ from the control group. In the control group, reaction time variability was lower during sham tDCS than during anodal tDCS . Cathodal tDCS did not differ from sham tDCS in both groups.The same pattern occurred for reaction time variability  = 2.83, p = 0.07]. Skin sensations (Table 2) were rated higher during cathodal tDCS compared to sham tDCS .Participants judged their ability to concentrate similarly for all different tDCS types. For skin sensations, there was a trend toward a main effect of tDCS [Figure 4 shows that the computer model predicted current density concentrations over right frontal/temporal regions. In more detail, the anodal current flew through scalp tissue, while a fraction entered skull/CSF to reach brain tissue at right frontal/temporal areas. The stimulation estimated higher current density concentrations at brain stem/lower cerebellum close to the foramen magnum. Some amount of that current might have left the cranium through the foramen magnum, as indicated in The aim of this study was to demonstrate the impact of tDCS over the rIFG on interference control in ADHD patients. Accordingly, adolescents with and without ADHD underwent anodal, cathodal and sham tDCS while completing a Flanker task. In contrast to our prediction, the overall analysis did not reveal a significant tDCS effect in either group. However, a significant learning effect from the first to the second session suggested that effects of learning and stimulation could have overlapped or interacted. When only the first session of each participant was analyzed, ADHD patients receiving anodal tDCS showed significantly lower commission error rates and reaction time variability than patients who obtained sham stimulation. Moreover, task performance in the anodal ADHD group did not differ from the healthy control group whereas performance in the sham ADHD group did. It is conceivable that while errors were diminished, reaction times were not increased, indicating that anodal stimulation was not associated with a speed accuracy trade off. Cathodal tDCS did not influence performance of participants. It is worth noting that significant results in the overall analysis were most likely made more difficult by the considerably large variability in performance and tDCS effects between participants. Different studies have recently shown  that notAnalyzing the first session, error rate considerably differed, by approximately 50%, between the sham and the anodal ADHD group equaling the extent of error reduction in a Flanker task by methylphenidate . ContrarIn contrast to existing studies which achieved improvements in a broad range of cognitive abilities in healthy persons  we did n2) produced widespread changes in cortical excitability. This might have led to changes in the general arousal (We assume that improvement of interference control is caused by an enhanced activity of the rIFG. The computer simulation supports our experimental results and suggests that we succeeded in targeting this area. However, since we did not exclusively stimulate the rIFG, effects could also be based on other physiological mechanisms. Using large electrodes (surface of 35 cm arousal  or could arousal . It is uOne limitation of our study is the small sample size in our exploratory analysis of the first session. A small sample size bears the risk that confounding variables are not equally distributed between groups and could therefore add to the experimental effect. To control for confounding variables, participants were assigned randomly to experimental conditions. Moreover, experimental groups of this study did not differ in age, intelligence, ADHD symptom severity and ADHD subtypes. Nevertheless, it cannot be stated with certainty that randomization was successful for all possible confounding variables. Therefore, to assess genuine pre-stimulation differences between groups, a stimulation naïve session should be included in future investigations.Since simple learning effects can mask effects of stimulation, the use of tasks with the prospects of small learning or practice effects would be essential. Commission error rates in the flanker task have been actually shown to provide satisfactory test–retest reliability . AlternaBetween participants, there was a considerable variability of error rates, especially in ADHD patients. ADHD symptoms improve with ongoing age  but thisCurrently, the view that sham stimulation is an appropriate method for blinding participants is questioned . As a coTranscranial direct current stimulation studies with young participants have reported only mild and transient side effects, like tingling and itching  and the Our results suggest that the used tDCS assembly could be suitable for improving interference control in ADHD patients. In further investigations results have to be confirmed and extended. For example, it needs to be clarified whether targeting specific functions such as interference control via tDCS leads to amelioration of clinical symptoms such as general behavioral control or impulsivity. For the development of an effective therapy it will be essential to investigate how long-term effects can be accomplished and maintained. In this context, it is important to further investigate potential learning or carry-over effects, since clinical treatment efficacy is often assessed in cross-over designs which could underestimate effects of stimulation.Finally, anatomic inter-subject variability is a particular challenge for the development of stimulation protocols because factors like the topography of the cortex, subcutaneous fat and distribution of cerebrospinal fluid determine current flow  and can All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The most common neuropsychiatric condition in the in children is attention deficit hyperactivity disorder (ADHD), affecting ∼6–9% of the population. ADHD is distinguished by inattention and hyperactive, impulsive behaviors as well as poor performance in various cognitive tasks often leading to failures at school. Sensory and perceptual dysfunctions have also been noticed. Prior research has mainly focused on limitations in executive functioning where differences are often explained by deficits in pre-frontal cortex activation. Less notice has been given to sensory perception and subcortical functioning in ADHD. Recent research has shown that children with ADHD diagnosis have a deviant auditory brain stem response compared to healthy controls. The aim of the present study was to investigate if the speech recognition threshold differs between attentive and children with ADHD symptoms in two environmental sound conditions, with and without external noise. Previous research has namely shown that children with attention deficits can benefit from white noise exposure during cognitive tasks and here we investigate if noise benefit is present during an auditory perceptual task. For this purpose we used a modified Hagerman’s speech recognition test where children with and without attention deficits performed a binaural speech recognition task to assess the speech recognition threshold in no noise and noise conditions (65 dB). Results showed that the inattentive group displayed a higher speech recognition threshold than typically developed children and that the difference in speech recognition threshold disappeared when exposed to noise at supra threshold level. From this we conclude that inattention can partly be explained by sensory perceptual limitations that can possibly be ameliorated through noise exposure. Attention deficit hyperactivity disorder (ADHD) is the most common neuropsychiatric condition in children, affecting ∼6–9% of the youth population and 3–5% of adults e.g., . ADHD isThe aim of the present study is to investigate if performance in speech recognition thresholds differs between children with ADHD symptoms and typically developed children (TDC) performing a speech recognition task in two different noise conditions, no noise and in 65 dB slightly modulated noise (that resembles white noise). The hypothesized difference between groups in speech recognition thresholds will here be further investigated. A reason for this is that prior research on ADHD has mainly focused on executive functioning where differences in performance are explained by deficits in pre-frontal cortex activation e.g., . Less noper se. Noise can be detrimental for attention but when investigating efferent auditory system the ability to suppress contralateral noise between an ADHD- and a control group was reported as equal  in the no noise condition the inattentive group demand a higher speech signal level as compared to controls in order to perceive the speech signal correctly due to a smaller signal-to-noise ratio; (ii) in the noisy condition (65 dB SPL modulated noise) these differences will disappear while noise strengthens the speech signal for the inattentive group and they will perform in parity with the TDC group.M = 10,2) participated in the study. Girls were not included in the study since a vast majority of the clinical group were boys and gender could therefore be a confounding variable. Initial testing and parent- and teacher ratings of ADHD-symptoms were performed before the speech recognition task. In the ADHD group 10 boys were recruited by the staff (nurses and psychologists) at neuro-psychiatric units within the pediatric healthcare in the Stockholm catchment area, all having a clinical diagnosis set by a pediatrician. One participant was excluded due to incomplete test data. The 39 participants recruited for the control group came from a school in a mixed demographic suburb of Stockholm. One participant was excluded due to incomplete test data and one due to low general ability (IQ < 80). According to the initial teacher and parent ratings of ADHD symptoms, six of the participants had significant ADHD-symptoms  and were moved from the control group to the ADHD symptom group. Thus in all 15 participants were included in the ADHD symptom group and the remaining 31 participants constituted the typically developed control group. Of note is that ADHD is a behavioral diagnosis, i.e., certain behaviors make up criteria for the diagnosis. To get a diagnosis the symptoms should not be explained by a general cognitive deficit and symptoms should be present in childhood , social skills, hearing and hearing sensitivity, language spoken at home, and medication. All participants had normal hearing according to self-report, parent and/or teacher reports. To rule out peripheral hearing loss, exclusion criterion was set to binaural hearing threshold of 37 dB SPL  or below according to the result in the no-noise condition. No participants were excluded for this reason. ADHD symptom rating were based on the SWAN scales , the TTIThe signal-to- noise ratio , where it is comfortable to listen to speech is about 15 dB, i.e., when the signal is 15 dB louder than the noise. Noise levels can thus be as high as 40–50 dB SPL without affecting speech intelligibility if the signal is presented at about 65 dB SPL. A comfortable level for listening to speech in quiet or low levels of background noise is about 60–65 dB SPL, which corresponds to the level of normal conversational speech heard at 1 m . The abiSpeech-in-noise tests, where the speech signal is imbedded in background noise, are mainly used for evaluation of the benefit of hearing aids but also for assessing auditory functioning in individuals that report difficulties in perceiving speech in noisy surroundings despite good peripheral hearing . In the present study we used the Hagerman sentences test that is one of the Swedish speech recognition tests in noise used in clinical settings. The test has a fixed noise level where the speech signal is attenuated. The noise sounds like a continuous noise but is slightly modulated to resemble the temporal variations of speech , 2002. Tno word was recognized, the signal was increased 2 dB, if only one word was recognized the speech signal was increased by 1dB, if two words were recognized the signal remained at the same level and if all three words were recognized the signal was decreased with 1 dB. The speech level of the last sentence in the first test list decided the level at which to begin the second test list. The program calculated a mean of the 10 sentences for the last list.In the present study the test was presented binaurally with headphones. The equipment for the speech recognition test consisted of a lap-top, headphones Sennheiser HDA 280, and an external audiocard Behringer UCA 222 with the software calibrated at the department of Technical Audiology at Karolinska Institute in Stockholm. Thresholds in quiet (no noise) for the minimum audible level in dB SPL were tested in order to compare this condition with the noise condition at a well audible level. In addition, both speech and noise were presented simultaneously in both ears, in order to get a more natural hearing situation. The computer-based adaptive method adjusted the speech level after each sentence depending on how many words that was repeated correctly. In the first condition (noise), the sentences  were presented at suprathreshold level at 85 dB SPL and then attenuated in slightly modulated noise at 65 dB SPL, in order to identify the threshold for the correct recognition, a criterion of 67% words, i.e., two out of three words correctly recalled. In the second condition (no- noise), the sentences were presented at 50 dB SPL and then attenuated until the minimum audible level using the same criterion as above. The test comprised in all 12 lists with 10 sentences in each list. From these 12 lists three randomized lists were chosen for each participant in each condition, one list for practicing and two for the actual test. Each participant was exposed to 30 sentences in each condition  in total 60 sentences. In some cases one, two and in the odd case three sentences occurred twice during a condition. The exposure to repeated sentences, were very similar to each group with slightly more repetitions in the ADHD-symptom group and in the no-noise condition. For the assessment of thresholds, the training list was used to make participants familiar with the task and the test situation and to set a suitable speech signal level to start the first test list from. The two test lists was built on a computer-based adaptive method that adjusted the speech level after each sentence depending on how many words the participant recognized correctly. If The design was a 2 × 2 mixed design. The within group manipulation was binaural speech recognition in two conditions no-noise vs. noise. Threshold in the no nose condition was set in dB SPL at minimum audible level (attenuated from 50 dB SPL). Speech recognition threshold in noise was set in dB SPL at well audible level (attenuated from 85 dB SPL) in noise at 65 dB SPL. The between group variable was children with ADHD symptoms vs. controls. Dependent variable was binaural speech recognition thresholds dB SPL in the no- noise condition vs. the noise condition.Table 1). They were carried out in the same succession and administrated according to the manuals and took ∼40 min to administer. After 15 min of testing a short break with juice and fruit followed. After taking part in the testing, the boys received a movie voucher.The testing was conducted at the child’ s school to minimize drop-out rate and participants were tested individually in a room during the school day by the same licensed psychologist and took part in the participants’ schools for optimal participation rate. The test session began with the modified Hagerman test for children. The two speech recognition conditions (no noise vs. noise) were given in counterbalanced order and took ∼10 min to perform in all. The test session also included tests for participant characteristics  = 6852.6, p < 0.0005] and an interaction between speech condition and group . This means that 65 dB noise affected groups differently; in the no noise condition TDC children displayed a lower speech recognition threshold as compared to the ADHD symptom group. The overall differences between groups was significant . In the noise condition both groups had similar recognition thresholds. Post hoc testing, an independent samples t-test showed that the difference between groups in the no noise condition was significant  the TDC group perceived correctly at 27.6 dB while the ADHD symptom group needed 29.6 dB for correct performance. In the noisy condition this difference disappeared , see Figure A 2 × 2 mixed analysis of variance (ANOVA) was conducted to asses speech recognition threshold with one between subjects factor, group (ADHD symptoms vs. TDC) and one within subjects factor, noise condition (no noise vs. 65 dB SPL modulated noise). A criterion of 67% words correct was used, two out of three words were correctly recalled for a correct response. We found a main effect of noise  and a t-test showed that the mean difference still was significant . ADHD children now require 30.4 dB for a correct recall and there was still no difference between groups in the noisy condition still . Only one participant had a threshold just below the level for inclusion . However, if excluding this participant from the ADHD group, the difference between groups still remained significant .We conducted an alternate mixed ANOVA that only included the originally clinically diagnosed ADHD group of nine children and the TD group of 31 control children. Data displayed that the interaction between groups increased further [Figure  Data showed a significant correlation between attention ability as rated by teachers  and parents . Hyperactivity by parent’s ratings and speech recognition was only significantly correlated , see Table 2 for all figures. However, there were no further correlations between cognitive ability and speech recognition thresholds as measured by similarities  and picture completion .The relationship between speech recognition threshold in silence and attention ability was further investigated in a Pearson product-moment correlation, see The current study tested the hypothesis that children who differ in attention (ADHD symptoms vs. TDC children) will have different speech recognition thresholds, which could be diminished in noisy conditions following the MBA model . Firstlyper se in the ADHD group, but found reduced processing efficiency for signal recognition, in particular in noisy environments. This is of great interest for the present study while it provides arguments for distinguishing between signal detection and signal recognition in ADHD when discussing results on auditory perception. Present results could also indicate deficits in the auditory pathways in ADHD; however, Central Auditory Processing Deficit (CAPD) is a complex and heterogeneous group of auditory-specific disorders, usually associated with a range of listening- and learning deficits, including auditory discrimination. There is a huge overlap between language processing disorders and ADHD, in particular in the inattentive subtype  tasks it shows that ADHD patients have a reduced left hemisphere specialization, i.e., larger right hemisphere contribution, which leads to impaired word processing among ADHD patients when word processing is normally dedicated to the left hemisphere . FurtherStimulant medication in ADHD seems to have a robust effect on ADHD behaviors  and on cMoreover, stimulant medication has been found effective to reduce susceptibility to auditory noise as well . On the The working mechanisms of noise benefits are not yet known, but apart from SR, auditory masking is a good candidate in speech recognition, as a masker different from the signal, the noise can facilitate signal detection . FurtherIn future studies a sub-threshold noise condition should be added to determine the threshold speech signal. In this setting it is possible to investigate whether the relative benefit of noise for inattentive persons is apparent in threshold SR as well. This study should be regarded as a pilot insofar that no firm conclusions could be drawn from it because of the small number of participants; there were only 15 in the clinical, ADHD symptom group. Our findings have to be corroborated in a follow-up study. We do not know if these findings are valid for girls either since only boys participated.Importantly, further studies should include testing in a sound proof setting rather in a school setting which involves a lot of ambient noise. Tone audiometry thresholds as well as speech recognition thresholds should be measured in the lab monaurally to further evaluate binaural speech recognition thresholds. Although all participants had hearing within normal range, the difference between the groups could be due to subtle differences in the peripheral transmission, e.g., in the middle ear or in the cochlea. However the correlation between hearing thresholds and the rating of ADHD symptoms speaks against this, implicating that the difference is due to a neurocognitive dimension rather than a perceptual peripheral deficit.Shared first authorship, both authors have contributed to the outlining, the design, and planning of the study. Both have contributed significantly to the writing of the manuscript. ENJ had the main responsibility for data collection and test battery. GS has been responsible for the statistical assessment, figures, tables and the outlining of the discussion. Both authors have collaborated through the revision process and the final version of the discussion.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.The reviewer Staffan Hygge and the handling editor declare their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review.


In Germany, the coverage of officially recommended vaccinations for the elderly is below a desirable level. It is known that advice provided by General Practitioners and Physician Assistants influences the uptake in patients ≥60 years. Therefore, the predictors of advice-giving behavior by these professions should be investigated to develop recommendations for possible actions for improvement.We conducted a postal cross-sectional survey on knowledge, attitudes and advice - giving behavior regarding vaccinations in the elderly among General Practitioners and Physician Assistants in 4995 practices in Germany. To find specific predictors, we performed logistic regressions with non-advising on any officially recommended vaccination or on three specific vaccinations as four separate outcomes, first using all participants, then only General Practitioners and lastly only Physician Assistants as our study population.p < 0.001), General Practitioners displayed higher odds to not advise specific vaccinations (ORs: 1.8–2.8).Participants consisted of 774 General Practitioners and 563 Physician Assistants, of whom overall 21 % stated to have not advised an officially recommended vaccination in elderly patients. The most frequent explanation was having forgotten about it. The habit of not counselling on vaccinations at regular intervals was associated with not advising any vaccination (OR: 2.8), influenza vaccination (OR: 2.3), and pneumococcal vaccination (OR: 3.1). While more General Practitioners than Physician Assistants felt sufficiently informed  contains supplementary material, which is available to authorized users. Recommendations of the German Standing Committee on Vaccination (STIKO) include influenza vaccination (IV), tetanus vaccination (TV) and pneumococcal vaccination (PV) for individuals who are 60 years or older . These oVaccination coverage for PV in the elderly is as low as 31 % in Germany ; for IV,We developed two KAP-questionnaires , and piloted them, using cognitive pretest-interviews as think-aloud, comprehension, category selection and information retrieval probing and confidence rating  in 16 peWe evaluated the representativeness of our study population by chi-square tests, using the atlas of physicians  for age-n = 107). We included all variables with p < 0.25 in bivariate analyses  and applied backward selection with p < 0.2 as model inclusion criteria. If more than 5 % of missing values in predictor variables occurred, we used chain-multiple imputations with five datasets for multivariable analyses. Otherwise and in bivariate analyses, we conducted complete case analyses. For multivariable analysis, we used the GP answer for the PA when GP and PA from the same practice stated to work in different parts of Germany (n = 272). We report associations with p < 0.05 as statistically significant. All analyses were carried out using Stata 12.We performed logistic regressions for each of the four outcomes, i.e., reporting not having recommended any vaccination/TV/IV/PV despite official STIKO-recommendation and in the absence of contraindication in the elderly. Each regression was modelled three times: including all participants, only GP, and only PA, excluding PA that did report to be not responsible for vaccination counseling in their practice  corresponding to 13.4 % eligible participants (1337/9990) : 48–61), median time working as GP was 17 years (IQR: 10–24), 47 % of the respondents were female and 77 % worked in the Western part of Germany. Median age of PA was 43 years (IQR: 30–51), median time working with a GP was 20 years (IQR: 10–30), and 97 % of the respondents were female.p > 0.05); regarding location of practice, we found no difference for GP (p > 0.05), while more female GP  and more male PA  participated.Regarding age-distribution, we found no significant difference between our study population and the source population for both professions , i.e. 15 % of all participants involved in counseling on vaccinations, or 19 % (148/774) of GP respectively. Most participants reported to know  and to trust  the STIKO-recommendations. Whereas 85 % (1140/1337) of the respondents felt in general sufficiently informed about vaccinations in the elderly, 66 % (880/1337) required better information on changes of STIKO-recommendations. Respondents supported  discussions about vaccinations being initiated by patients and utilized this as an opportunity to counsel   stated to have not advised at least one vaccination to an elderly patient despite STIKO-recommendation and absence of a contraindication. PV was the vaccination most frequently not being suggested n = 83, i.e. The most common explanations given by respondents for not advising was for all three investigated vaccinations forgetting to advise 53–72 %), followed by the perceived low risk of the patient to catch the respective disease (23–28 %). Uniquely for IV, 19 participants (14 %) stated to not have advised it due to safety concerns and 21 (15 %) due to doubts on its effectiveness  >1 imply that the influencing factor increases the chance of not having advised a vaccination to elderly, while OR <1 signify an increasing chance that a vaccination is always advised when medically indicated and recommended by STIKO.Most prominent predictor for any  and tetanus vaccination  is not trusting the STIKO-recommendations; although this concerns only 2 % of respondents (25/1337). For influenza  and pneumococcal vaccination , the negative perceived benefit-harm-ratio of the respective vaccine showed the most substantial association for not advising it to the elderly. While working in West-Germany more than doubles the odds for not advising any vaccination , IV  and PV , this association is not significant in the model for TV. Not counseling on vaccinations at regular intervals, e.g. at the first visit of a patient within an accounting period, is associated with not advising any vaccination , IV , and PV . GP exhibit about two times the odds for not having advised specific vaccinations compared to PA  , stated to know STIKO-recommendations (97 % of GP (752/774) vs. 86 % of PA (483/563), p < 0.001), and to use them as a source of information (85 % of GP (662/774) vs. 69 % of PA (388/563), p < 0.001). For all investigated vaccinations, less PA than GP believed the benefit to exceed potential harms  (Table PA supported GP regarding counseling on vaccinations in 79 % 612/813) of responding practices. Despite the higher chance of GP to not have advised all investigated vaccinations in the elderly compared to PA, more GP than PA felt sufficiently informed regarding vaccinations in adults (90 % of GP (696/774) vs. 79 % of PA (444/563), 2/813 of Modelling GP and PA separately indicates that e.g. location of the practice in the Western part of Germany, and not counseling routinely at regular intervals increases the chance for not advising on any vaccination only in GP, whereas e.g. age-structure of practices’ patients is only a significant predictor in PA Table .Table 3MOver 20 % of the participants stated that they had not advised at least one officially recommended vaccination, even in absence of any specific contraindication; with 26 % of the GP and 14 % of the PA, significantly more physicians than assistants reported a vaccination-advise practice deviating from recommendations. By far the most frequent explanation in both professions was “having forgotten to advise”. More than 20 % of PA did not feel sufficiently informed regarding vaccinations in adults (vs. 10 % of the GP); 90 % of the respondents stated that they trusted the official STIKO-recommendations, and very few were general opponents of vaccination. Only 17 % of the participants counsel routinely at regular intervals and just 23 % use a recall-system. In general, the chance of not advising is higher in practices in West-Germany and with younger patients. Also, those who do not counsel routinely at regular intervals, those with a neutral attitude towards counseling, and who do not trust the STIKO-recommendations have a higher chance of not advising. Overall, associations with KAP-variables were rather similar across different vaccines, while we observed some significant distinctions between GP and PA. The high proportion of GP and PA working in the Western part of Germany can be explained by the general high proportion of the German population living there (~16 million in the Eastern part versus ~65 million people in the Western part ).There are only few vaccination-related KAP-surveys among GP that address vaccinations in the elderly. A German study, published 16 years ago, found the same geographic difference in following the official recommendations as we did, with GP in the Western part of Germany vaccinating/advising less often than in the east . This maSo far, PA have been neglected in public health vaccinology in Germany; however, as they also counsel and administer vaccinations , 22, it The evaluation of the representativeness regarding age, sex and location of practice by chi-square tests did not indicate any bias in recruitment or response within the German population of GP and PA, despite the low response with 11.3 % in PA and 15.5 % in GP. Still, the variables available for investigating representativeness do not necessarily represent characteristics relevant for the research question at hand. Furthermore, using other statistical test methods might result in different findings. The generalizability of our results is therefore limited.not been recommended to a person of at least 60 years, despite the absence of a contraindication. We also provided the option to state that the participant did not know about above-mentioned recommendations. Still, due to social desirability or recall problems an underestimation of not advising vaccinations by GP and PA is possible.Due to known difficulties in recruiting GPs for such studies in Germany , we chosBy far the most frequent explanation given for not advising a vaccination was forgetting about it, matching the substantial association of not advising any, influenza and pneumococcal vaccination with not counseling routinely at regular intervals. Still, despite improvements in this field (compared to 2000 ), only aEmpowering PA, installing and promoting mechanisms to reduce the risk of forgetting to give vaccination advice and include special vaccination hours in public health services in the vaccinations procedure may open up new avenues to improved vaccination coverage in the elderly.GP, general practitioner; IV, influenza vaccination; P, practice; PA, physician assistant; PV, pneumococcal vaccination; SD, socio-demographic and practice-characteristics; STIKO, German standing committee on vaccination; TV, tetanus vaccination.


Investigators from the Division of Developmental Medicine and Clinical Research Center, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, studied the relationship between the timing of Attention Deficit Hyperactivity Disorder (ADHD) diagnosis in children with Autism Spectrum Disorder (ASD) and the age at ASD diagnosis. Investigators from the Division of Developmental Medicine and Clinical Research Center, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, studied the relationship between the timing of Attention Deficit Hyperactivity Disorder (ADHD) diagnosis in children with Autism Spectrum Disorder (ASD) and the age at ASD diagnosis. Prior studies have suggested that symptoms of ADHD may overshadow or mask the symptoms of ASD but none has examined the relationship between the age at ADHD diagnosis and the age at ASD diagnosis. Data were drawn from the 2011-2012 National Survey of Children's Health, which asked parents to provide the age at which their child received a diagnosis of ADHD and/or ASD. There were 1496 children with a current diagnosis of ASD reported by parents of children between ages 2 to 17 years; approximately 20% of these children had been initially diagnosed with ADHD. Children diagnosed with ADHD before ASD were diagnosed with ASD ~3 years  after children in whom ADHD was diagnosed at the same time or after ASD. The children with ADHD diagnosed first were 30 times more likely to receive their ASD diagnosis after age 6 . The disparity in delay of age for ASD diagnosis for the ADHD before ASD group was maintained across all severity levels. The findings support implications that children with ADHD before ASD may exhibit unique dimensional traits that could bias clinicians toward an ADHD diagnosis. Diagnostic criteria and screening measures for ASD may need to reflect the overlapping symptomatology between ASD and ADHD. [COMMENTARY. The new DSM-5 restructuring of the ASD and ADHD diagnostic categories has caused concern about how these changes may impact prevalence rates, and rates of comorbid psychopathology. Under the DSM-5, symptoms of ADHD should be present before age 12, not 7 years, and the number of symptoms required is 5, not 6. To investigate the prevalence of inattention and impulsive symptoms, 1722 infants and toddlers were separated into three diagnostic groups for analyses: DSM-5 ASD group, an atypically developing group, and a DSM-IV-TR ASD group. Significantly elevated rates of inattention/impulsive symptoms were identified in toddlers meeting DSM-5 criteria for ASD. ASD symptom severity was positively correlated with inattention/impulsive symptoms regardless of the primary diagnosis. The expression of impulsive and inattentive symptoms did not differ significantly within diagnostic groups . ASD pre


Attention-deficit/hyperactivity disorder (ADHD) is a severe mental illness, associated with major impairment and a high comorbidity rate. Particularly undiagnosed ADHD in adulthood has serious consequences. Thus, a valid diagnosis is important. In adulthood, the diagnostic process for ADHD is complicated: symptoms may overlap with comorbid disorders, and the onset and progression of the disorder must be reconstructed retrospectively. Guidelines for the diagnostic process recommend the inclusion of additional informant ratings. Research into the relation between self- and informant ratings shows extremely heterogeneous results. The levels of agreement range from low to high. The focus of this study is the concordance and differences between self- and informant ratings on ADHD symptoms and impairments. In this regard, two possible influencing factors (gender and relationship type) are also examined. 114 people participated in this study, 77 with an ADHD diagnosis and 37 without a diagnosis. For all participants, either parents or partners also rated ADHD symptoms and impairments. Small to moderate concordance was found between self- and informant ratings, with females being slightly more concordant than males, particularly for ratings of problems with self-concept. Examination of the consistency within a particular perspective showed that people with ADHD seemed to be unaware of the causal relation between ADHD symptoms and their impairments. A close investigation found almost no influence of gender and relationship type on differences within perspectives. Based on these results, the implications for the diagnostic process are that additional informant information is clearly necessary and helpful. Attention-deficit/hyperactivity disorder (ADHD) is a severe developmental disorder, appearing in childhood and frequently persisting into adulthood , 2. In ainattention, hyperactivity, and impulsivity—and additional symptoms such as emotional symptoms [ADHD is characterized by three core symptoms—symptoms , 8. Thessymptoms , 10. Peosymptoms , 11–13. symptoms –6. Additsymptoms .Concerning the wide range of functional impairments and the high rate of comorbidity, an early and valid diagnosis of ADHD is important , 15. ParIn many studies, people with ADHD retrospectively rate symptoms in childhood lower than their relatives do , 29. In Differences in perspectives between people with ADHD and their relatives are rarely discussed in literature. So far, no consensus on the validity of the different perspectives has been reached. There is a lack of objective criteria to evaluate the statements, so it cannot be determined with any certainty which ratings are more precise. Nevertheless, there are some indications as to which perspectives are more valid. In retrospective ratings of childhood symptoms, statements of parents highly correlate with daily impairments in childhood and childhood diagnosis of ADHD, and parents were also better at estimating the time of onset of the disorder , 29. ForThese different findings are discussed by various researchers. Some tried to find explanations for the higher symptom self-ratings: one possibility could be an overestimation of the minor executive power limitation found in ADHD . AnotherSome studies address factors influencing the concordance between the different perspectives. These factors include age, gender, ADHD diagnosis, and the identity of the informants (type of relationship they have with the ADHD person). Zucker et al. , for exaA deeper investigation of the concordance between perspectives seems necessary and might help to examine their usefulness for diagnostic purposes and therapy. A precise diagnosis is important for the effective treatment of ADHD . PerspecEthikkommission Nordwest- und Zentralschweiz (EKNZ”). The EKNZ approved the entire study for the clarification of our research questions with the use of routine data of the special consultations unit.Data of patients of the ADHD Special Consultations Unit of the Outpatient Department of the University of Basel Psychiatric Clinics, collected between July 2013 and December 2014, were used for this study. The collected routine data was retrospectively used to investigate the research questions of this study. According to the standard approach of the University of Basel Psychiatric Clinics for routine clinical data, informed consent was given verbal, that data may be used for research. Data were collected in anonymous form in a clinical intern data base. None of the authors had contact with the participants and the data was entered anonymized by researcher assistants of the research group. This procedure was approved before the start of the study by the ethics committee in Basel , structinattention and/or five symptoms of hyperactivity/impulsivity must coexist in adulthood. Important components of the process were the Conners Adult Rating Scales , in selWRAADDS; ). Functi Adults; ). Formernterview  and the . Diagno with an age range from 18 to 75 years. In our sample, 77 participants received an ADHD diagnosis, while 37 did not (ADHD and Non-ADHD group). Demographic characteristics for these two groups are the following: In the Non-ADHD group 24 participants were male (64.9%) and 13 were female (35.1%), while in the ADHD group 53 participants were male (68.8%) and 24 were female (31.2%). The group differences for gender were not significant (t(112) = .42; n.s.). Both groups did neither differ significantly in their mean age  = .45, n.s.), nor their education: In the Non-ADHD group 21 participants (56.8%) finished secondary school and 16 (43.2%) finished grammar school, while in the ADHD group 50 participants (64.9%) finished secondary school and 27 (35.1%) finished grammar school (t(112) = 1.42, n.s.). There were also no significant differences for relationship status, number of children, and the informant identity between both groups.This study includes a clinical sample which was routinely diagnosed in the ADHD Special Consultations Unit. A total of 114 persons participated in the study. Of these, 77 were men (67.5%) and 37 women (32.5%), the mean age was 32.19 years  participants, also partners rated symptoms and impairment, while for the rest (43.0%) parents did.t(107) = 2.40, p < .05), more anxiety problems (t(105) = 3.32, p < .01), more thoughts about suicide (t(112) = 2.87, p < .01), more alcohol abuse (t(109) = 3.19, p < .01), and more substance abuse (t(111) = 2.79, p < .01).In the ADHD group, 47 people (61.0%) had a current comorbid disorder such as a mood disorder, anxiety disorder or a substance use disorder. People in the ADHD group had significantly more former depressions . Th. ThConne . The interobserver agreement for each item was between .44 and .77. Till now, there is no published German version of this questionnaire available. Therefor we used a translation, made by our research group. Because of the small participants’ number, a validation of the questionnaire based on our data was not advisable. For the assessment of functional impairment in our study, four domains of impairment were formed out of cluster analysis results: family life, social life, work, and organization. Cronbach`s alphas for the mean impairment score and the subscales can be found in the results section.s . The BFs . This iInternal consistency was assessed with Cronbach`s alpha. Values were calculated for all subscales of ADHD symptoms and all domains of impairments for self- and informant ratings.Concordance between clinical diagnosis and the diagnosis based on self- and informant statements was examined with Spearman correlations and cross tabulations. Thereby the percent of similarity between the diagnosis  were calculated.mean impairment score (BFIS) and ADHD index (CAARS) were used to test for consistency of symptoms and associated impairment within self- and informant perspectives. The ratio of explained variance should be an indicator for consistency of the perspectives.Regression analyses with the scales of General differences between self- and informant perspectives were examined for both groups separately through t-tests. For differences, also effect sizes (Cohen`s d) were computed.In-depth analysis of the relationship between self- and informant perspectives in ADHD was assessed with the ADHD group only: Spearman correlations for intra-class concordance of self- and informant ratings and Multivariate Analysis of Covariance (MANCOVA) to test the influence of gender and relationship type were used. Via Fisher z-transformations the intra-class correlations were normalized and t-tests conducted. Restricted sample size demanded separate MANCOVAs for the influence of gender and for the relationship type, controlled for comorbidity. Direction, significance, and effect size for the different subscales are reported.ADHD index, the five ADHD symptoms, the functional impairment domains, and the mean impairment score were assessed with Cronbach`s alpha. The following values are the results for (a) self- and (b) informant ratings. For the ADHD index scale, Cronbach`s alpha (a) was .93 and (b) .93. Results for separate ADHD symptoms were as follows: for inattention/memory problems Cronbach`s alpha (a) was .87 and (b) .90, for hyperactivity/restlessness Cronbach`s alpha (a) was .89 and (b) .90, for impulsivity Cronbach`s alpha (a) was .80 and (b) .83, for emotional lability Cronbach`s alpha (a) was .85 and (b) .84, and for problems with self-concept Cronbach`s alpha (a) was .87 and (b) .84. The mean impairment score showed Cronbach`s alpha of (a) .84 and (b) .93, while for the different impairment domains the following results were found: for family life Cronbach`s alpha (a) was .79 and (b) .80, for social life Cronbach`s alpha (a) was .81 and (b) .81, for work Cronbach`s alpha (a) was .57 and (b) .71, and for organization Cronbach`s alpha (a) was .82 and (b) .82. Taken together, internal consistency showed good to excellent values for the total scales, the subscales of ADHD symptoms, and almost all separate domains of impairment for both ratings. An exception was work, which showed low values for self-ratings but acceptable values for informant ratings.Reliability of the r = .53) and a general similarity of 80% (44% for no diagnosis and 97% for diagnosis) were revealed for an ADHD diagnosis based on clinical diagnosis and self-ratings. For informant ratings and clinical diagnosis correlation was small (r = .27) and a general similarity of 68% (51% for no diagnosis and 76% for diagnosis) was found. The agreement between self- and informant diagnosis was also small: r = .22 and general similarity was 70% (56% for no diagnosis and 72% for diagnosis).A moderate correlation  = 99.85, p < .001), and for informant ratings the symptom scale explained 52% of the total variance  = 37.21, p < .001). Findings for the ADHD group were different: self-ratings of symptoms explained only 16% of the total variance  = 13.80, p < .001), while for informant ratings the symptom scale explained still 41% of the total variance  = 50.57, p < .001). To rule out comorbid diseases as the basic cause for lack of consistency within the ADHD self-ratings, a subgroup of ADHD patients without comorbidity was retested (n = 30). In self-ratings of this group, symptoms explained 7% of the total variance  = 2.09, n.s.), while for informant ratings the symptom scale explained 41% of the total variance  = 17.77, p < .001).To examine the consistency of a perspective, hierarchical multiple regression analyses were used. Thus, the prediction of ratings for impairment through symptom ratings was tested separately for the participants and their relatives in both groups (ADHD and Non-ADHD group). For this purpose, the ADHD index subscale of the CAARS-S:L and CAARS-O:L and the mean impairment score of the BFIS, also self- and others-rating form. No significant differences were found in the Non-ADHS group: ADHS index: Participants with ADHD  and informants  = 0.27, n.s.; Cohens d = .04); Mean impairment score: Participants with ADHD  and informants  = 1.19, n.s.; Cohens d = .24). In the ADHD group significant group differences were found: ADHS index: Participants with ADHD  and informants  = 3.91, p < .001; Cohens d = .47); Mean impairment score: Participants with ADHD  and informants  = 2.62, p < .05; Cohens d = .33).Independent-samples t-tests were used to evaluate ratings of ADHD symptoms and functional impairments between participants and their relatives. Comparisons between both perspectives showed significant differences for ADHD symptoms and general impairment in the ADHD group, while in the Non-ADHD group no significant differences were found. Calculations were made with the ADHD index, ADHD symptom subscales, and the mean impairment score were tested with mean Spearman correlations  women were more concordant with their relatives than men. This difference was only significant for ratings of problems with self-concept.Concordance of the elations . To thisThe gender of the ADHD person and the relationship type (parents vs. partners) were investigated as possible factors influencing the differences in perspectives between people with ADHD and their relatives. For the purpose of these analyses only the ADHD group was used. Two MANCOVAs were calculated: one with perspectives and gender Tables  and 3, thyperactivity/restlessness and impulsivity: people with ADHD themselves rated their symptoms higher than their relatives did.There was a main effect on perspectives found in hyperactivity/restlessness and problems with self-concept was found. For hyperactivity/restlessness males rated their symptoms significantly higher than females, while for problems with self-concept the contrary was found. The biggest effect was found on problems with self-concept.For gender, a main effect on ratings of hyperactivity/restlessness, there was a significant correlation between perspective and relationship type: while participants rated similar symptoms in both groups, parents rated the problems of their adult children higher than partners did.For relationship type, no main effects were found. For The main goal of this study is the investigation of the self- and informant ratings on symptoms and impairment in ADHD. For this purpose, concordance and differences between the two perspectives were addressed. While concordance measured the similarity of patterns of both perspectives, with differences the levels of agreement between both perspectives were considered. Additionally, the consistency within a perspective and also influencing factors for differences between ratings were observed.Examination of the agreement between self-ratings and clinical ADHD diagnosis revealed higher similarity compared to agreement between informant ratings and clinical diagnosis. This is hardly surprising, bearing in mind that judgments of clinicians mostly depend on the statements of patients. Nevertheless, participants rated their symptoms as clinically relevant more often than did their clinicians, which indicates that although clinicians depend on the statements of patients, they interpret this information carefully. Furthermore, this probable overestimation of ADHD symptoms by patients themselves leads to the conclusion that informants may be important for a second perspective within the diagnostic process.only people with ADHD failed to see these connections. In contrast, a review of Gordon et al. [Results about consistency within the perspectives reveal that in the Non-ADHD group severity of symptoms predicted severity of impairment in self- as well as informant rating, while in the ADHD group only the informant ratings achieved this result. Self-ratings in the ADHD group only explained a small amount of the variance in impairment. These results became even more pronounced after excluding the influence of comorbidity: while informant ratings stayed the same, self-ratings became insignificant. In general people with ADHD rated more symptoms and impairments, compared with their informants. But our results suggest that these ratings are very variable: While some participants with ADHD rated higher symptoms, but lower impairments, others rated lower symptoms, but higher impairments. This indicates that people with ADHD seem to be unaware of the connection between their symptoms and associated impairment. Also an unawareness of a causal connection between psychological symptoms and impairments is documented for some other disorders , it is nn et al.  showed an et al. , 36, 37.problems with self-concepts. While females showed moderate concordance for this subscale, ratings of males with ADHD hardly correlated with those of their relatives. Higher concordance between females and their relatives corresponds with our hypothesis and findings of former studies [Correlations between self- and informant ratings indicate a small to moderate concordance between perspectives, testing the whole ADHD group. The following gender differences in concordance were found: for most ratings females were slightly more concordant than men, which was significant for  studies .hyperactivity/restlessness and impulsivity. The modification of these two groups of symptoms with increasing age can be seen as an explanation: both become more internal with increasing age [inattention symptoms do not decline with age and thus may be relatively better recognized in adulthood. Another explanation for these results may be the negative view people have of inattention in other people: negative feelings in relationships and social dysfunctioning are more closely connected with inattention symptoms than with hyperactive behavior [impulsive and hyperactive or impulsive behavior is less negative for flirting partners: in contrast to inattention, it is perceived more as an interesting personality trait, useful in dating and social relations. However, also an overestimation of symptom severity by people with ADHD themselves cannot be ruled out as explanation for the differences [Differences between self- and informant ratings were also examined. General differences in mean scores indicate that people with ADHD estimate their total symptoms and impairments significantly higher than their relatives. Further investigations for single ADHD symptom subscales revealed that these differences were significant for sing age –55. Thussing age . Consequbehavior , 57. Alsbehavior  reportedferences , 38, 39.ferences , for exageneral impairment score were found, while the separate ratings of the four domains of impairment  did not differ between self and informant. Thus, patients and their relatives generally tell of similar problems in different domains of daily life. Results are in line with former studies, showing high impact of ADHD on daily life [For functional impairment, significant differences for the ily life , 7, 11.hyperactivity and problems with self-concept. For hyperactivity, males had significantly higher values, while for problems with self-concept females rated higher. An explanation for the higher ratings in men may be the differences in symptoms between females and males: according to former studies, men show more symptoms of hyperactivity than women in adulthood . In converview: . Thus, thyperactivity/ restlessness were differences found: parents seem to estimate the severity of symptoms of their adult children higher than partners did. The higher ratings by parents may be because they remembered former childhood problems instead of restricting their rating to current symptoms in adulthood only. Another explanation may be personal perception: as already described above, partners may see these symptoms as personality traits they like, while parents see them in terms of clinical relevance. At the beginning, we hypothesized that partners’ views may be more useful because of a closer personal relationship between partners in adulthood. This hypothesis was disproved: both calculations of concordance and of differences showed similar results, which indicates that relationship type bears no significant influence on similarities or differences between perspectives. It is noteworthy that particularly for people under the age of 30 it tended to be parents who provided the informant ratings. Accordingly, depending on the age of the person with ADHD, parents as well as partners are important sources and can and should be used for the diagnostic process.Outcomes also revealed that the relationship type seems to be unimportant for general accordance between people with ADHD and their informants. Only for For the purpose of this study, two questionnaires in self- and informant report forms were used. This has its strengths and limitations. This procedure enabled perspectives to be compared in detail: the same questions were used for participants themselves and their informants and the same subscales were examined. Other instruments to assess perception of severity of symptoms and impairments in more detail were not included. For future studies, therefore, inclusion of more such measurements may be appropriate.or partners only. This limits the group sizes. Accordingly, a MANCOVA containing gender and relationship type as influencing factors could not be conducted. For future investigations more participants should be assessed. Also, the inclusion of parents and partner ratings for all participants would be meaningful. This procedure would allow a closer comparison of perspectives and enable possible significant differences between partners and parents to be detected.A second limitation is our sample size. In the Non-ADHD group, only 37 participants and their relatives were tested, while the ADHD group consisted of 78 people. In both groups, others’ perspectives were assessed for either parents Finding a valid external criterion for the accuracy of ratings is a considerable problem in studies on self- and informant ratings. For future research, methods such as the ones used by Adler et al.  might beThe last limitation emerges from the assessment of comorbidity. Only a background interview, asking participants for their psychiatric backgrounds, former /actual therapies, and former /actual disorders was used. For further research comorbidity should be evaluate more closely by employing a structured interview for mental disorders. Also the assessment of other neurodevelopmental disorders, like autism, and for seizures should be included. This approach may help to better understand connections between ADHD, perspectives, and comorbidity. Despite these limitations, results show that self- as well as informant ratings should be an important part of the ADHD diagnostic process. Results revealed a low consistency within self-ratings and an overestimation of symptoms in comparison with the clinical diagnosis. Thus, both perspectives are pertinent for clinicians to better understand the individual person with ADHD.Furthermore, impairments in family and social life indicate that including family members in therapy might be reasonable. Former research showed that medication for ADHD has no effect on social and family impairment , 63. By In conclusion, people with ADHD and their relatives are important sources for assessment of symptoms and functional impairment. Nevertheless, there are some significant differences between their respective perspectives of symptoms and impairments. So far, no objective measurement for symptoms and impairments is available, wherefore the level of accuracy of information obtained from patients and other informants remains uncertain. People with ADHD themselves make no causal link between their symptoms and their impairments. The resulting inconsistency within their ratings can be an indication for misjudgment. Accordingly, the additional information informants can give in support of the diagnostic process would appear to be essential.