This pilot study assessed the feasibility and potential effectiveness of asingle-session workshop in modifying parental beliefs/knowledge aboutattention-deficit/hyperactivity disorder (ADHD) in children and impact ontreatment acceptance/utilization. Concerns raised by school professionals aboutlack of treatment follow-through after ADHD diagnosis and parentalmisinformation about medication usage catalyzed this project. A single-grouppre-post quasi-experimental design was used. Sixty-eight parents completed ADHDknowledge/belief scales and stress inventories, and pre-ADHD and post-ADHDinformation workshop. Follow-up calls were made after the workshop to assesstreatment utilization. Parents/caregivers experienced significant knowledge andbelief changes regarding medication efficacy, willingness to accept physiciantreatment recommendations, and rejection of non-empirically based treatments.Follow-up data showed that 41% of contacted participants met with physicians todiscuss medication utilization and behavioral treatments. Brief, one-sessionpsycho-educational workshops were feasible and impacted parental beliefs andbehaviors regarding scientifically supported interventions for ADHD. Attention-deficit/hyperactivity disorder is the most commonly diagnosed child andadolescent psychiatric disorder,5with a 5% to 7% prevalence rate among youths.Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disordercharacterized predominantly by symptoms of inattention, impulsivity, andhyperactivity.8 Although the use ofstimulant medications for the treatment of ADHD is well established,10 acceptance of and adherence tostimulant treatment remain low, with nonadherence to treatment ranging from 13% to 64%.Research supports the use of both pharmacological and behavioral treatments forADHD. Approximately half of youths diagnosed with ADHD do not begin stimulanttreatment, and of those who do, roughly half discontinue it within a year. Furthermore, hesitation among parents regarding medication usage has beenattributed to information presented in the media. In addition, some parents believe thattoo many children receive medication for ADHD, despite evidence to the contrary. This ambivalence persists in the face of strong evidence supporting the efficacyof stimulant medications in the short-term treatment of the core symptoms ofADHD.18When asked about their perspective on the decision to initiate medication treatment forADHD, parents describe ambivalent feelings regarding the decision to use stimulants withtheir children, as well as fears of side effects, lack of family support for thedecision to medicate, and guilt specific to social pressure about medicating children.20Underscoring the need to bridge negative parental views and treatment acceptance isessential as this combination can result in untreated ADHD. Although parents often express a preference for behavioral treatments, adherencerates for behavioral therapies are also low due to issues including the time commitmentrequired or difficulty accessing services.The negative attitudes held by many parents about the acceptability of medication as partof an optimal course of treatment likely impact both treatment-seeking and adherencebehavior. that “shared decision-making” (SDM), in which parental preference and goals areassessed as part of the clinical evaluation, led to higher treatment initiation of bothpharmacological and behavioral treatments. Although findings suggest that parents trustinformation presented to them by their child’s physician, their concerns about treatment may not be elicited in a way that keeps themengaged in the treatment process.An examination of parental treatment preferences found Factors that influence parental stress include the parents’ awareness ofpsychological, academic, emotional, and behavioral problems in ADHD. In addition, parental stress has been linked to willingness for acceptance of andadherence to child ADHD treatment. Through parent education, perceptions about treatment may be modified tofacilitate wider treatment acceptance and engagement.Previous research demonstrated a relationship between parenting perceptions, practices,and increased familial stress. with the objectives identified and informed by interviews with local teachers andschool administrators who indicated that parents needed increased and currentinformation about treatments for ADHD. School personnel indicated that they feltparental misinformation regarding ADHD, their recommendations for evaluation, andpotential treatment for ADHD or follow-through with already prescribed medication washampering their student’s functioning in the school setting. This project assessedchanges in parental knowledge, attitudes, and beliefs about ADHD and gathered data aboutchanges in treatment utilization subsequent to the intervention.This pilot study sought to assess the feasibility and potential effectiveness of asingle-session workshop in modifying parental beliefs and knowledge about thecharacteristics, diagnosis, and treatment of ADHD in children. A secondary aim was toassess whether these changes in knowledge and beliefs lead to any actual changes intreatment engagement or use. A school of medicine, university-based ADHD researchprogram partnered with a local city school system to identify relevant issues to target.A community-based participatory approach was taken in this projectA total of 68 parents and primary caregivers participated in this study.  Studyinclusion criterion was parental interest in learning more about ADHD for achild who was attending the local, city school district; there were no exclusioncriteria. Study participants included parents of children considered at-risk ofADHD via parent report or who had already been diagnosed with ADHD. The childrenranged in age from 4 to 15 years, of whom 50 children  alreadyhad been diagnosed with ADHD. Of those, 50% had been prescribed medicationand/or tried a behavioral therapy intervention. The local school system invitedfamilies of elementary and middle school children in the district by postingflyers and leaving telephone messages to alert them to the workshop opportunity.Childcare was provided for the children of participants. The universityInstitutional Review Board (IRB) approved the study, and the researchersobtained informed consent from participants at the beginning of each workshop.Caregivers were given $30 for their time.The study employed a single-group, quasi-experimental design. The phases of thisstudy included a Pre-Workshop Assessment, Workshop Presentation, immediatePost-Workshop Assessment, and Follow-up Assessment to assess changes intreatment engagement or utilization. Parents attended 1 of 4 two-hour workshops,held over a 4-month period using a standardized protocol format to ensureconsistency between workshops. Workshop content included information onoccurrence rates, diagnostic criteria and state-of-the-art evaluationprocedures, myths, treatment approaches, and evidence to support differenttreatments for ADHD. The presenters each gave their respective talk using aformal slide presentation followed by a question-and-answer format for eachtopic. Presenters at each workshop included the same 2 PhD-level clinicalpsychologists and a developmental and behavioral pediatrician with expertise inADHD. Suggestions were given to parents on how to prepare for evaluations oftheir children. Information on the effect of the workshop on parents’ attemptsto engage in subsequent services for their children was gathered. To facilitatecommunity participation, the workshops were held in sites easily recognizable tothe parents including the school district office (3 workshops) and a universitysite engaged in participatory work, adjacent to the community (1 workshop).Follow-up information from participants employing standardized phone interviewswas gathered 12 weeks to 17 months (median approximately 10 months) followingthe final workshop to assess for any changes in diagnostic status, professionalconsultation, or treatment utilization. Initial attempts were made to contactthe participants within 3 to 4 months after the workshops. However, nonresponseof the participants proved challenging, and thus, we continued to attemptfollow-up data well beyond the planned period if the participant did notinitially respond to increase the sample size and data on service use. Thefollow-up data were deidentified due to IRB constraints, such thatpretest/posttest questionnaire data were not linked to follow-up with specificsubjects. The PSI assessed relative stress via parent self-report assessment. The shortversion of the scale contains 36 items and is composed of 3 subscales: ParentalDistress, Difficult Child Characteristics, and Dysfunctional Parent-ChildInteraction. A total summary stress scale was also calculated. The internalconsistency for the PSI is 0.85. This measure allowed us to look at the relationship between parentingstress and shift in ADHD beliefs.We collected demographic information including age of child, parental age,marital status, level of education, race and/or ethnicity, and previous usage ofADHD treatments (if any). At the commencement of each workshop, caregiverscompleted the Parenting Stress Index (PSI)–Short Form. before and after the workshop. It consists of 27 items rated on a Likertscale from 1 to 7 , which togetheridentify knowledge and opinions about the possible causes of ADHD,characteristics of children with ADHD, and treatments of the disorder. TheJohnston et al scale was used to determine a baseline of current knowledge about ADHD,beliefs and treatment options, modality acceptance, satisfaction with thecurrent treatment regimen, and parental stressors related to child management.The scale is composed of 4 subscales: Beliefs in Behavior Management, Beliefs inMedication, Beliefs in Psychological Causes/Treatments, and Beliefs inDiet/Vitamin Treatments. In preliminary findings, the internal consistency forBeliefs in Behavior Management was 0.73 and for Beliefs in Medication 0.77. Changes in this measure served as the primary outcome variable.Parents also completed the standardized ADHD Beliefs and Attitudes ScaleAs noted above, for the follow-up data collection, a standardized phone interviewassessed for changes in diagnostic status and whether parents soughtprofessional consultation for ADHD and whether their child began treatment forthe disorder.P <.05 (2-tailed). If a factor showed a significant pre-workshop to post-workshopchange, we performed an exploratory analysis to determine whether this changewas being driven by one or more of the individual items making up the factor.For the PSI, means, standard deviations, and standard error were calculated tobetter assess summary scores across each of the subscales . Finally, Pearsoncorrelation coefficients were used to examine relationships between the ADHDBeliefs Scale and the PSI. Dependent-samples t test mean andstandard deviation values were used to compare the changes from pre-workshop topost-workshop across each major subscale of the ADHD Beliefs and AttitudesScale. Furthermore, to compare item-specific changes from pre-workshop andpost-workshop ratings by parents in each of the major subscales of the ADHDBeliefs and Attitudes Scale, we employed a Wilcoxon signed-rank test usingnegative ranks. The strength of the relationship between these 2 scales was alsoassessed with the aim of identifying any potential relationships that could leadto testable hypotheses for future studies.All analyses were computed using SPSS software  for the 3 factors from the PSI and the 4 factors from the ADHD Beliefs andAttitudes Scale. The significance threshold was set at We performed Wilcoxon signed-rank test analyses for individual item responses ofthe ADHD Beliefs and Attitudes Scale as well as for subscale scores on the ADHDBeliefs and Attitudes Scale and PSI. Subscale scores reported here representaverage item responses: items from the ADHD Beliefs and Attitudes Scale wererated on a Likert scale from 1 to 7 .Items from the PSI were presented as percentile scores. Listwise deletion wasused to handle missing data.Data derived from the follow-up phone interview were categorized and summed.Fifty-five parents (81%) completed both pre-workshop and post-workshop questionnairesto assess beliefs and knowledge about ADHD. Thirteen subjects were ineligiblebecause they failed to complete the pre-workshop and post-workshop questionnaires.Fifty-eight parents (85%) completed the PSI. Thirty-seven (51%) participantsprovided post-workshop follow-up data. Mean grade of ADHD diagnosis for children wassecond grade. The parents were well educated (an average of 14 years of education)and most were in a “Married /Remarried /Partnered” relationship (see disagree) to post-workshop(agree) for this item was significant . Similarly, item 23—“I would not hesitate tomedicate my child if a doctor recommended it”—also shifted fromdisagree to agree post-workshop. Item 19—“Vitamintherapy is useful in treating ADHD”—was part of the Beliefs in Diet/VitaminTreatments subscale and shifted toward a belief that this is not an effective formof treatment . Followingthe workshop, parents were more likely to see medication as effective, less hesitantto explore medication treatment, and less likely to believe that vitamin therapy iseffective. These findings are particularly important, as concern about medicationimplementation was an impetus for this study.Two factors from the ADHD Beliefs and Attitudes Scale showed a significant change.These included the Beliefs in Medication factor and Beliefs in Diet/VitaminTreatments see . Movemen participants in this sample uniformly reported moderate to high levels ofparenting stress. The mean for Parental Distress was at the 53rd percentile,Parent-Child Dysfunctional Interaction was at the 79th percentile, Difficult Childwas at the 81st percentile, and Total Stress was at the 77th percentile.Correlations were performed (using arcsine-transformed percentile data) to explorethe relationship between change in beliefs and parental stress. The results did notreveal any significant correlations between belief change and total parentingstress. However, there was a significant correlation between changes in beliefs ofBehavioral Management and pre-workshop levels of Parental Distress such that higherlevels of parental distress were associated with larger positive changes in beliefsabout the effectiveness of behavioral management .Consistent with reports in the literature,The original study design called for participants to be contacted 12 weeksfollowing workshop attendance by phone to assess what changes, if any, they madeabout their child’s ADHD diagnosis and treatment. However, subjects proveddifficult to reach  and the length of follow-upstretched to 17 months in an attempt to interview as many participants aspossible. Thirty-seven participants (55.2%) provided follow-up data. (Nineteenfollow-up interviews were completed 6 months post-workshop and 18 were reached14-17 months post-workshop. An average of 3-4 contacts were needed to reachparticipants.) Of the contacted participants, 28 (75.7%) already had a diagnosisof ADHD at the beginning of the study. Twenty-three of the 28 were alreadyreceiving medication. Of the 5 children not already on medication, 2 familiessubsequently obtained a medication consultation and began medication followingthe training group.There were 9 contacted participants (24.3%) for whom the family suspected ADHD,but they did not have a formal diagnosis at the beginning of the trainingworkshop. Of these, 5 subsequently obtained evaluations and received a positivediagnosis of ADHD.Following the parent education workshop, 15 participants (40.5%) consulted afamily physician or pediatrician. Of these, 13 met to discuss medication issuesspecifically. Seven participants began taking medication following this consult,1 discontinued, 1 switched medication, and 4 families met with their physicianbut did not make medication changes. Twelve families sought out behavioralinterventions such as child-focused individual therapy or behavioral familytherapies. This is an important finding as this represents 32% of ourparticipant subjects and follows a single workshop. In the general ADHDpopulation, only about 30% to 45% of children become engaged in any behavioral intervention.31 These findings support the conclusion that a single workshopcan improve the ability of parents to participate more fully in their child’streatment by initiating discussions with their physician because they haveevidence-based data to draw upon. The ultimate hope is that parents will becomebetter potential partners for shared decision-making with physicians. In addition,although our parent participants reported moderate to high levels of parentingstress, this did not seem to impair their ability to shift their beliefs, againsuggesting that accurate and well-presented material can be delivered across a rangeof diverse families. Twelve out of 37 families indicated that they sought outbehavioral interventions following the workshop, suggesting that parents may havebecome more aware of the availability of behavioral interventions through theworkshop. Notably, there were frequent questions about where to obtain theseservices in the question-and-answer phase of the workshop, and the facilitators wereable to provide suggestions for obtaining these services. However, without thepresence of a control group, this is difficult to ascertain.The results suggest that a single workshop session delivering current, evidence-basedinformation about ADHD to a culturally and ethnically diverse parent group canmodify parental beliefs to align with state-of-the-art evidence on ADHD. Resultsindicated that our parent group was already knowledgeable about the course andtreatment of ADHD as was reflected in their overall endorsement of appropriatebehavioral interventions and medication treatment. They understood the psychologicalunderpinnings of ADHD and the limitations of dietary interventions. However, areaswhere parents’ beliefs shifted following workshop training included beliefs aboutthe efficacy of medication treatment and their willingness to use this as atreatment strategy, as well as their willingness to accept a treating physician’srecommendations about treatment. Immediately following the workshop, parents hadmore positive beliefs regarding medication interventions. Post-workshop parentreports shifted in that they were less likely to endorse diet and vitamin therapiesas effective. This is particularly important as parents often seek nutrition-basedtreatments because they see these as potentially less harmful than pharmacologicalagents. One of the first steps in treatment efficacy is the willingness to engagedirectly with a treating professional and to accept the recommendation to initiate acourse of treatment. Of our sampled families, a substantial portion of the familieswe reached initiated consultation visits with their physician to discuss theirchild’s treatment following workshop participation. Such actions bring us closer tothe optimal goal of greater treatment engagement. Notably, several parents commentedat the end of the workshop that they had not felt comfortable asking theirphysicians for further information about treatment, but that they would now, havingparticipated in the workshop. Parental perception that their child’s physician wouldnot welcome questions about treatment for ADHD is critical for physicians torecognize as this may lead to lower adherence to treatment recommendations.Therefore, it is also important for physicians to discuss shared decision-making sothat treatment recommendations might be initiated earlier.The literature states that efficacy for all treatments is determined to a largeextent by treatment adherence.Several limitations of this pilot study should be noted. While this single-session,pre-post assessment of a workshop model served as an efficient method of informationdissemination, there were limitations in the design and scope of the approach.Future studies can build upon our preliminary work by testing the effectiveness of asingle-session workshop by using a randomized design with comparisons between anactive educational session versus a control group receiving no education. Adding amore interactive, participatory, group discussion format may also lead to higherbehavioral change than just receiving standard educational information. In thefuture, it would also be important to assess other contextual barriers to treatmentengagement . Potential selection biasrelated to our sample is also a significant concern. Parents who elected to attend asession led by clinicians may already have some commitment to learning aboutefficacious treatments and approaches to ADHD. The parents were well educated. Ourgroup expressed a desire to engage in treatment and appeared to take medical adviceseriously. Strengths of this study included use of a community-participationapproach, such as selection of topics identified as important by teachers and schoolstaff; using a workshop format that was reasonable for busy families ; and workshopfacilitators representative of both psycho-educational and medical profession.33 A review ofthe literature showed that multiple attempts are required to keep participants engaged, withsome studies showing averages of 8 contact attempts, and that this is not unusual.Reconnecting with busy parents of children with behavioral disorders is a particularconcern. The participants with whom we were able to engage in the follow-up periodmay not be representative of the larger group, that is, they may demonstratenonrandom attrition. Many of the contacted families indicated that they were usingmedication as a part of their child’s treatment regimen. Parents who did not makethis choice are clearly underrepresented in this sample. It is possible that parentswho were experiencing greater difficulty managing their child’s ADHD and greaterstress may have greater challenges responding to the follow-up calls as they mayhave had other priorities.33 The length of time for follow-up with some families waslengthy, and there may be fundamental differences between families we were able toreach at 12 weeks and those we did not reach until 17 months. Because follow-up datawere deidentified, we were not able to distinguish what group differences may havebeen present in the sample we were unable to reach. To increase parent response tofollow-up interviews, we recommend that future studies reimburse parents for theirtime and participation in efforts to obtain follow-up data. Future research shouldsystematically evaluate methods for maintaining engagement in studies, includingtesting different types of social networking communications.Our success with contacting only about 50% of our original participants is alimitation of the study. Recent studies indicate maintaining research participantengagement is challenging, particularly for research in behavioral health.A strength of our project is its inclusion of a diverse sample of parents, althoughwith a sample size insufficient to explore the relationship between intervention anddiversity. Future research should explore whether the effects of psycho-educationalworkshops are moderated by socioeconomic status and ethnic group membership ontreatment participation. In summary, this study moves us closer to understandingwhat factors may contribute to a parent’s willingness to engage in treatment forADHD. It demonstrates the potential of a group format for modifying parental beliefsabout issues school professionals consider a high priority. Notably, knowledgegained through the workshop increased willingness of parents to partner withtreating professionals.J.F. Dixon took responsibility for supervision of all aspects of the study and wrotethe first draft of the manuscript. J.B. Sweitzer and R. Akins facilitated workshopsand reviewed and revised manuscript. E. Bisi participated in the literature reviewand reviewed and revised manuscript. S. Gill scored the study measures and reviewedand revised manscript. E. Miller and J. Breslau reviewed and revised manuscript.


There is an ongoing debate about the restrictive inattentive (RI) presentation of attention deficit hyperactivity disorder (ADHD). The current study aimed to systematically investigate the clinical, neuropsychological, and brain functional characteristics of children with ADHD restrictive inattentive presentation.A clinical sample of 789 children with or without ADHD participated in the current study and finished clinical interviews, questionnaires, and neuropsychological tests. Those individuals with a diagnosis of ADHD were further divided into three subgroups according to the presentation of inattentive and/or hyperactive/impulsive symptoms, the ADHD-RI, the ADHD-I (inattentive), and the ADHD-C (combined) groups. Between-group comparisons were carried out on each clinical and neuropsychological measure using ANCOVA, with age and sex as covariates. Bonferroni corrections were applied to correct for multiple comparisons. Two hundred twenty-seven of the subjects also went through resting-state functional magnetic resonance imaging scans. Five ADHD-related brain functional networks, including the default mode network (DMN), the dorsal attention network (DAN), the ventral attention network, the executive control network, and the salience network, were built using predefined regions of interest (ROIs). Voxel-based group-wise comparisons were performed.Compared with healthy controls, all ADHD groups presented more clinical problems and weaker cognitive function. Among the ADHD groups, the ADHD-C group had the most clinical problems, especially delinquent and aggressive behaviors. Regarding cognitive function, the ADHD-RI group displayed the most impaired sustained attention, and the ADHD-C group had the worst response inhibition function. In terms of brain functional connectivity (FC), reduced FC in the DMN was identified in the ADHD-C and the ADHD-I groups but not the ADHD-RI group, compared to the healthy controls. Subjects with ADHD-I also presented decreased FC in the DAN in contrast to the control group. The ADHD-RI displayed marginally significantly lower FC in the salience network compared to the ADHD-I and the control groups.The ADHD-RI group is distinguishable from the ADHD-I and the ADHD-C groups. It is characterized by fewer externalizing behaviors, worse sustained attention, and better response inhibition function. The absence of abnormally high hyperactive/impulsive symptoms in ADHD-RI might be related to less impaired brain function in DMN, but potentially more impairment in the salience network. Attention-deficit/hyperactivity disorder (ADHD) has a relatively high prevalence among children and adolescents, making it one of the most common neurodevelopmental disorders. Worldwide estimations of its prevalence in children ranged from 3 to 7% . The corThe ADHD symptoms do not have developmental stability. In preschool years, the hyperactive/impulsive symptoms dominated, while the inattention symptoms became more obvious by the age of 6–7 years . A previNevertheless, previous studies investigating the difference between the ADHD-PI and the ADHD-C subtypes generated inconsistent results. Some studies revealed that those patients with ADHD-C had more severe clinical impairments, albeit less cognitive dysfunction, than the ADHD-PI patients in some cognitive domains , 10, e.gn = 145) adolescents with or without ADHD demonstrated more impaired early-stage attention control and less impaired late-stage response inhibition in individuals with ADHD-RI than the ADHD-C subjects (n = 301) also detected lower psychomotor speeds, and longer reaction time during neuropsychological tests in individuals with ADHD-RI, compared to healthy controls, the ADHD-C, and the ADHD-I type (n = 96), the ADHD-RI group was found to activate more attention-related posterior brain regions  compared to healthy controls and the ADHD inattentive type , that is, hyperactivity and learning problems . A studysubjects . Anothern = 789, with brain imaging n = 297). We hypothesized that patients with ADHD-RI displayed fewer clinical problems, more impaired sustained attention, less impaired inhibition function, and a different functional connectivity pattern compared to patients with ADHD-I, patients with ADHD-C, and the healthy controls.Although we have noticed the value of investigating the ADHD-RI presentation, there are few studies doing so. In addition, the sample sizes of existing studies are relatively small. Some of the studies utilized non-clinical samples, which might restrain the generalization of the findings. The current study, therefore, aimed to systematically explore the clinical, neuropsychological, and brain functional characteristics in a relatively large sample size clinical cohort of children with and without ADHD  were recruited in the child health care and mental health center of Shenzhen children’s hospital. Another 108 typically developing children were recruited from local elementary schools. All of the participants and their parents were interviewed before enrollment. The diagnosis of ADHD and/or any other psychiatric disorder was confirmed or excluded through a clinical interview and a semi-structured interview based on the Schedule for Affective Disorders and Schizophrenia for School-Age Children -present and lifetime version (K-SADS-PL)  years we. The incThis work was approved by the Ethics committee of Shenzhen Children’s Hospital. Informed consent was obtained from parents and children.Besides the clinical and semi-structured interviews, a battery of clinical and cognitive assessments was carried out on both ADHD patients and healthy controls. The Child Behavior Checklist  was filThe Child Behavior Checklist (CBCL) : it contThe Wechsler Intelligence Scale for Chinese Children-IV (WISC-IV): it has been widely used to evaluate the intelligence of children aged 6–16 years . All admThe CANTAB: the CANTAB has been widely used in scientific research about all kinds of psychiatric disorders, including ADHD . In the Spatial Working Memory (SWM) is a test of retention and manipulation of visuospatial information. There are a number of boxes shown on the screen, and a “token” will be hidden in one of the boxes at a time. The “token” will not be hidden in the same box twice, which means the participants have to remember the positions of the boxes where the token has been taken. The major outcome measures include SWMS , and SWMBE .Stop Signal Task (SST) is a test of response inhibition. This test asked the participants to inhibit their responses to an arrow stimulus once they hear the stop signal (a beep). The major outcome measures include the SSTSSRT , the SSTDEG , and the SSTDES .Rapid Visual Information Processing (RVP) is a test of sustained attention and information processing speed. Generally, the participants are asked to hit on the screen when they spot the targeted sequence of digits in a box, where digits appear one by one in pseudo-random order. The major outcome measures include the RVPA , RVPML (the mean response latency), the RVPPFA , and the RVPPH [probability of (correct) hit].Reaction Time (RTI) measures sustained attention and motor and mental response speeds. The participants are asked to hold a button at the bottom of the screen. There are one (the simple mode) or five circles (the five-choice mode) presented above. A yellow dot will appear in one of the circles from time to time. The participants are required to release the button and select the circle with a yellow dot inside as soon as possible. The major outcome measures include the RTISMDRT (reaction time of the simple mode), the RTIFMDRT (reaction time of the five-choice mode), the RTISRTSD (the standard deviation (SD) of reaction time of the simple mode), and the RTIFRTSD (the SD of reaction time of the five-choice mode).A total of 297 individuals participated in the resting state functional magnetic resonance imaging scans (RS-fMRI), including 87 with ADHD-I, 71 with ADHD-C, 46 with ADHD-RI, and 93 healthy controls. The MRI images were acquired using the 3 T Siemens Skyra scanner with a standard 12-channel head coil located in Shenzhen Children’s Hospital. Single-shot echo-planar imaging (EPI) sequences were applied: TR = 2000 ms, TE = 30 ms, flip angle = 90°, thickness/skip = 3.5/0.7 mm, matrix = 64 × 64, field of view (FOV) = 200 × 200 mm, 33 axial slices, 240 volumes, and 3 mm × 3 mm in-plane resolution.All the RS-fMRI images were preprocessed in FSLp-values corrected for whole-skeleton family-wise error (FWE). Only those significant clusters larger than 10 voxels were reported. Although we have mainly adopted a categorical concept of ADHD and examined the between-group differences, alternative dimensional models (with symptom severity as independent variables) and hybrid models (with symptom severity and the interaction between diagnosis and symptom severity as independent variables) were also tested. In addition, sensitivity analyses were performed with age^2 or head motion parameter as an additional covariate. The potential interaction between diagnosis and age was also evaluated. In addition, the brain-behavior and brain-cognition relationships were also investigated. More details about these alternative models can be found in the supplementary material.All brain networks were built using predefined regions of interest (ROI). (1) the default mode network (DMN): this network was built using the posterior cingulate cortex (PCC) as ROI, which was created from the Harvard-Oxford atlas;All of the statistical analyses were performed in R. Group-wise comparisons of the behavioral and cognitive data were finished by performing ANCOVA, with age and sex as covariates. Bonferroni’s correction was applied by dividing 0.05 by the number of measures from the same scale or tasks. Therefore, the significance level was set to 0.05/8 = 0.00625 for all CBCL factors, 0.05/4 = 0.0125 for measures from the WISC-IV, the RVP task, and the RTI task, 0.05/3 = 0.0167 for the measures from the SST task, and 0.05/2 = 0.025 for the measures from the SWM task.p < 0.05). There are more males in all of the ADHD groups compared to the healthy control . In addition, there are also more males in the ADHD-C group in contrast to the ADHD-I and the ADHD-RI groups (both p < 0.001). As expected, the ADHD groups had more inattentive and hyperactive/impulsive (H/I) symptoms than the control group . Among all the ADHD groups, the ADHD-C group had the highest score in both symptom domains . Note that, in terms of inattention symptoms, there was no significant difference between the ADHD-RI and the ADHD-I groups (p = 0.262). As for the WISC-IV indicators, all of the ADHD groups have lower FIQ, VCI, PRI, WMI, and PSI scores . There is no significant group-wise difference among the three ADHD groups in any of the indicators from WISC-IV . More details can be found in In general, the ADHD-RI group was older than the ADHD-C group, and the control group was older than both the ADHD-I and the ADHD-C groups . The ADHD-C group scored higher than the control group in the thought problems factor (p < 0.001). None of the ADHD groups had a higher or lower score in the somatic complaint factor compared to the control group . Among the three ADHD groups, the ADHD-C group had a higher score than the ADHD-RI group in the attention problems factor, the delinquent behaviors factor, and the aggressive behaviors factor (both p < 0.00625). The ADHD-C group also scored higher than the ADHD-I group in the aggressive behaviors factor (p < 0.001). None of the other group-wise comparisons of the CBCL factors among the three ADHD groups yielded significant results . More details can be found in In all of the eight indicators from CBCL except for the somatic complaint and the thought problems factor, all three ADHD groups scored higher than the control group , and the ADHD-RI and the ADHD-I group had a higher RVPML (p = 0.0072 and 0.013). In the SST task, compared to the control group, the ADHD-I and ADHD-C groups had higher SSTDEGs (both p < 0.001) and SSTDESs (p = 0.012 and 0.0077 respectively). In the RTI task, compared to the control group, the ADHD-RI group scored higher in RTISMDRT (p < 0.001), and RTIFMDRT (p < 0.0001). The ADHD-C and ADHD-I group also had higher RTIFMDRT scores than the control group (both p < 0.001). The ADHD-C group had a marginally significantly smaller RTISMDRT than the ADHD-RI group (p = 0.0176). No other significant group-wise differences were detected. More details can be found in In the RVP task, compared to the control group, the ADHD-C group had a smaller RVPA score (p < 0.1) lower functional connectivity in the right temporal lobe compared to the ADHD-C group within the dorsal attention network. Within the salience network, the ADHD-RI group showed marginally significantly (0.05 < p < 0.1) decreased functional connectivity in the left occipital pole compared to the control group, as well as in the left superior frontal gyrus, and the left paracingulate gyrus compared to the ADHD-I group. As for the executive control network, the ADHD-C group showed marginally significantly (0.05 < p < 0.1) decreased functional connectivity than the control group, mainly in the right thalamus, the right pallidum, the right accumbens, the right frontal lobe, the left occipital lobe, and the left caudate. Details can be found in In terms of functional connectivity within the DMN, compared with the control group, the ADHD-I group showed decreased functional connectivity mainly in the left frontal lobe, the right insular, the right thalamus, and bilateral putamen, and the ADHD-C showed decreased functional connectivity mainly in the right postcentral gyrus, the right precentral gyrus, the posterior cingulate gyrus, and the left insular. As for the dorsal attention network, the ADHD-I group showed decreased functional connectivity, mainly in the right frontal lobe, compared to the control group. The ADHD-I group also displayed marginally significantly  had fewer clinical problems than those with ADHD-C presentation . Those ir = 0.31)  . Therefo = 0.31) , 14. Unl = 0.31) . Note th = 0.31) , seems t = 0.31) .The default mode network, the salience network, the executive control network, and the dorsal and ventral attention networks have been suggested to be involved in the pathophysiology of ADHD –37. The Besides the DMN, the ADHD-I group also presented altered brain functional connectivity in the dorsal attention network (DAN). Previous study comparing individuals with ADHD-PI and those with ADHD-C to healthy controls has identified reduced functional connectivity in the left inferior occipital gyrus and right superior occipital gyrus of the DAN in the ADHD-C group and the right superior parietal gyrus of the DAN in the ADHD-PI group . We did The current study explored the clinical, neuropsychological, and brain-functional characteristics of the ADHD-RI presentation in comparison to healthy controls, the ADHD-I, and the ADHD-C presentations. In our sample, the ADHD groups have more male subjects than the control group, which might restrain the generalization of the results of the current study. The ADHD and control groups differed significantly in terms of age, and our exploration analyses of the interacting effects of diagnosis and age have revealed that the between-group differences might be affected by age. Future study with more age-matched sample or longitudinal design is warranted.In summary, the current study demonstrated fewer clinical problems, weaker sustained attention, better response inhibition, fewer alterations in the functional connectivity in the DMN, and potentially more impaired brain function in the salience network. The current study contributes to the ongoing debates on ADHD-RI presentations. The results supported the notion of ADHD-RI being an independent presentation. We also noticed the complicated interactive effects, rather than simply additive or aggregative effects, of the two ADHD symptom domains regarding cognition and brain functional connectivity. It is not a severity continuum. Aggregation, compensation, and additive and interactive effects of these two symptom domains may all play a role in causing functional brain alterations in patients with ADHD. Future studies using brain structural and functional information to subtype ADHD patients might provide more insights. In addition, future studies exploring the neurological underpinnings of ADHD symptoms in the general population and clinical samples, embracing both the categorical, dimensional, and hybrid models, are also warranted.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by the Ethics committee of Shenzhen Children’s Hospital. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.Z-MW and PW contributed significantly to the data collection, data analysis, and manuscript preparation. JL and X-LC helped to conduct the study. LL and LS helped with the data analysis, as well as the writing and reviewing of the manuscript. LY, Q-JC, B-RY, and Y-FW contributed to the design of the study, the data analysis, and the manuscript preparation. All authors contributed to the article and approved the submitted version.This work was supported by the National Natural Science Foundation of China (82101613 and 82071537) and the SANMING Project of Medicine in Shenzhen “The ADHD research group from Peking University Sixth Hospital” (SZSM201612036).This work was also supported by the Guangdong High-level Hospital Construction Fund.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


P < 0.01) than those fed the high-energy rye diet or the low-energy diet without rye, which was caused by a reduced weight gain during the initial 17 d of the trial. Final BW and overall feed intake were not affected by rye inclusion or NE level. The NE intake was greater (P < 0.05) and feed efficiency (G:F) was reduced (P < 0.05) in pigs fed rye diets compared to those fed diets without rye, whereas there was no effect of NE level on NE intake or G:F. There was no effect of rye inclusion or NE level on lesion scores. In conclusion, pigs can be fed diets including 40% hybrid rye with only minor changes in growth performance. Increasing the NE level of the first phase diet in the grower-finisher barn may be useful to avoid a reduction in growth performance when feeding hybrid rye.Previous research has shown reduced feed intake and growth rate in pigs fed diets with hybrid rye replacing wheat. A reduction in growth rate caused by reduced feed intake will conceivably be counteracted by increasing the dietary energy level. Our objective, therefore, was to determine the effects of 40% hybrid rye inclusion replacing wheat in diets formulated to be either low or high net energy (NE) on growth, feed intake, energy digestibility, and lesion scores in growing-finishing pigs. We hypothesized that pigs fed 40% hybrid rye would perform better on the high than the low energy diets. A total of 160 pigs (body weight [BW] 70.1 kg) housed in 32 pens, 5 pigs per pen, were fed diets with 0% or 40% hybrid rye , either with low  or high  kcal NE per kg of diet over two growth phases . The BW, and feed disappearance were measured on days 0, 8, 17, 28, 42, and 50. Fecal samples obtained in phase 2 (~100 kg BW) were used to calculate apparent total tract digestibility (ATTD) of gross energy (GE). Lesion scores were measured weekly. The ATTD of GE was unaffected by rye inclusion and was reduced in low vs. high NE diets. Overall, (days 0 to 50), pigs fed the low-energy rye diet gained 0.08 kg/d less ( The inclusion of 40% hybrid rye in diets for growing-finishing pigs resulted in only minor changes in growth performance. Increasing the energy level of the first phase diet in the grower-finisher barn may be useful to avoid a reduction in growth performance when feeding hybrid rye. Access to a variety of grains and grain co-products allows the formulation of swine diets at the lowest cost. While it has been known for many years that rye can be used in swine feeds, the low acreages planted and susceptibility of rye to mycotoxins, specifically ergot, have limited its inclusion . HoweverRecent research has demonstrated that the new hybrid rye varieties can replace wheat  or corn Our objective was to determine the effects of 40% hybrid rye inclusion in diets formulated to be either low or high NE on growth, feed intake, energy digestibility, and lesion scores of growing pigs. We hypothesized that growing-finishing pigs fed 40% hybrid rye would perform better on the high than the low-energy diets.Study procedures were reviewed and animal use was approved by the University of Saskatchewan Animal Research Ethics Board and followed principles established by the Canadian Council on Animal Care . The stuA total of 160 pigs  with an average initial body weight (BW) of 70.1 kg, were placed into two rooms, 16 pens per room, and five pigs per pen. Pens measured 2.4 m × 1.7 m. Flooring of each pen was fully slatted concrete, back, and sides of pens were concrete, with a front gate made of polyvinyl chloride planking. Each pen was equipped with a single-space dry feeder. A nipple drinker was located on the back wall of the pen. The room was ventilated using negative pressure and temperature was maintained within the thermo-neutral zone for pigs. Artificial light was provided for 12-h (0700 to 1900 h) followed by 12-h of darkness.The trial utilized a randomized complete block design with a 2 × 2 factorial arrangement of treatments. Within an area block of four pens, barrows, or gilts were randomly allotted to diets with either 0% or 40% hybrid rye replacing wheat , and witExperimental diets were fed to slaughter weight over two growth phases . Diets had similar inclusion of barley and canola meal. Rye NE value was estimated based on previous research conducted at the Prairie Swine Center (unpublished) that provided a value of 3,509 kcal/kg for DE and chemical analysis of the hybrid rye was used to calculate the NE value using equation 1.8 of Pigs were weighed at the initiation of feeding the experimental diets (day 0), and on days 8, 17, 28, 43, 50, and 57. Feed was weighed and delivered to pigs by hand and feed remaining in the pen feeder on weigh days was weighed back. Collected data were used to calculate pen average daily feed intake (ADFI), average daily weight gain (ADG), and feed efficiency expressed as ADG/ADFI (G:F).Fecal samples were obtained by obtaining freshly excreted samples over a 24-h period, a minimum of one sample per pen, when pigs had received the phase 2 celite-containing diets for one week (~100 kg BW). Samples were only collected if defecation was observed and were immediately frozen (−20 °C). Apparent total tract digestibility (ATTD) of energy was calculated based on the indicator method using AIA as a marker and using the following NF is the nutrient concentration in feces; ND is the nutrient concentration in the diet; MD is the marker concentration in the diet; and MF is the marker concentration in feces.Where NE of the diets was estimated according to Where DE is DE, EE is ether extract, crude protein (CP) is CP, and acid detergent fiber is acid detergent fiber.Lesion scores were measured on the face, ear, body, and tail of each pig weekly in the morning and afternoon of the same day to distinguish between old lesions (morning score) and new lesions (afternoon minus morning score). The scores for the different body parts were summed to create one score per animal. The lesion scoring system, adapted from Fecal samples were dried in a forced-air draft oven at 55 °C for about 72 h minimizing N loss . The feeS and R epimers combined.Rye samples were analyzed for moisture (AOAC 930.15), CP (AOAC 990.03[M]), ether extract (AOCS Am 5-04), ash (AOAC 923.03), acid detergent fiber (Ankom method 12[M]), neutral detergent fiber (Ankom method 13[M]), and amino acids  at the Central Testing Laboratories, Winnipeg, MB, Canada. Diets and rye samples were analyzed for mycotoxins and ergot alkaloids (EA) using UHPLC-MS/MS following solvent extraction at Prairie Diagnostic Services . A total of six EA were determined, Pen was the experimental unit for all variables. Because the sampling unit for BW and lesion scores was individual pigs, an average for each pen was calculated prior to statistical analyses.Growth performance and energy digestibility were analyzed using the GLIMMIX procedure of SAS using a normal distribution. Models included the fixed effects of rye level (0% or 40%), energy level (low or high), sex (barrows or gilts), and interactions. Block was considered a random effect in the model. Overall ADG, ADFI, NE intake, and G:F were analyzed using closeout data. BW, ADG, ADFI, NE intake, and G:F were analyzed as repeated measures including growth phase as repeated term. Growth phase was added as a fixed effect and the interactions of growth phase with the other fixed effects were analyzed. An appropriate covariance structure was selected by comparing the goodness-of-fit measures of different structures. The Kenward-Roger correction was used for the denominator degrees of freedom. Since many pigs had already been sent for slaughter by day 57, growth performance data are only reported until day 50 on test.Lesion scores were analyzed using the GLIMMIX procedure of SAS using a Poisson distribution and Log link function. The repeated measures analysis for lesion scores was overparameterized, so the model was simplified. The lesion score data for both old and new lesions was analyzed for each week separately.P < 0.05 was considered significant and P < 0.10 was a trend.To test the hypotheses, The hybrid rye fed in this experiment had relatively low levels of mycotoxins, including EA. Ergocristine  was the most common EA measured, followed by ergotamine 15%, . IncludiP ≤ 0.001) in the low relative to the high-energy diets. The ATTD of GE and the DE content on a dry matter basis were unaffected by rye inclusion; however, DE content on an as fed basis was greater (P < 0.05) in the 40% rye diets compared to the 0% rye diets  between hybrid rye inclusion and NE level for ADG; pigs fed the low-energy rye diet gained 0.08 kg/d less than those fed the high-energy rye diet or the low-energy diet without rye, with those fed the high energy diet without rye being intermediate (P < 0.05) and feed efficiency (G:F) was reduced (P < 0.05) in pigs fed rye diets compared to those fed diets without rye, whereas there was no effect of NE level on NE intake or feed efficiency , there was an interaction (rmediate . For theficiency .P < 0.001) between hybrid rye inclusion and NE level for BW at days 8, 17, and 28. Pigs fed the low-energy rye diets weighed less than those fed high-energy rye diets or diets without rye  between hybrid rye inclusion and NE level for ADG for the days 0 to 8 and days 8 to 17 periods; pigs fed the low-energy rye diets gained less than those fed the high energy rye diet or the diets without rye. For the days 17 to 28 period, the interaction (P < 0.001) between rye inclusion and NE level for ADG was reversed; pigs fed the low-energy rye diet gained the most weight, and those fed the high-energy diet without rye gained the least, with the other two treatments being intermediate (There was an interaction (rmediate . There wP < 0.01), whereas ADFI was not affected by rye inclusion in any of the other growth phases. Feed intake was 0.14 kg/d greater (P < 0.01) during the days 17 to 28 period and tended (P = 0.082) to be 0.13 kg/d greater during the days 28 to 43 period in pigs fed low relative to high NE diets. Energy level did not affect ADFI for the days 0 to 8, 8 to 17, and 43 to 50 periods . There was no effect of NE level on NE intake throughout the trial .P < 0.001) in pigs fed the low-energy rye diet compared to pigs fed the high-energy rye diet or diets without rye. For the days 17 to 28 period, pigs fed rye diets had better G:F than those fed diets without rye (P < 0.001), whereas, for the days 43 to 50 period, pigs fed the low-energy rye diet tended to have lower feed efficiency compared to pigs fed the wheat diets, while the high energy rye diet was intermediate (P = 0.084). For the days 28 to 43 period, pigs fed low NE diets tended to have worse G:F compared to pigs fed high NE diets  was reduced (NE diets .P > 0.38) or NE level (P > 0.37) on lesion scores for old and new lesions throughout the experiment (data not shown).Minimal aggression occurred throughout the trial, resulting in low lesion scores for old lesions  or new lesions . Overall average lesion score for old lesions was 1.05 both for pigs fed diets with or without rye, and 1.04 and 1.06 for pigs fed diets low or high in energy, respectively. Overall average lesion score for new lesions was 0.21 and 0.17 for pigs fed diets without or with rye, respectively, and was 0.23 and 0.16 for pigs fed diets low or high in energy, respectively. There was no effect of rye inclusion , yet the analysis did not find a significant effect of sex. For this reason, a larger sample size may need to be considered in future trials.Due to its lower NE value compared to wheat, when hybrid rye is replacing wheat in the diet the oil inclusion level needs to be increased. As a result, the price of not only wheat and hybrid rye but also oil needs to be considered when determining whether to formulate diets with hybrid rye. The low NE diets were much cheaper than the high NE diets. This large difference in feed cost per tonne translated to lower feed cost per pig and per kg BW gain for pigs fed low vs. high NE diets. This finding is in agreement with our previous research that has consistently shown lower feed cost per pig and per kg BW gain, as well as higher income subtracting feed cost when pigs are fed lower energy diets .In conclusion, feeding 40% hybrid rye replacing wheat to grower-finisher pigs resulted in similar overall feed intake and final BW, slightly lower overall feed efficiency, and lower overall growth rate for pigs fed the low NE but not the high NE rye diets. The lower overall growth rate was caused by reduced BW gain during the initial 17 d of the trial and it may be useful to consider increasing the NE level of the first phase diet in the grower-finisher phase when including hybrid rye to avoid this reduction in growth performance.


Anorexia Nervosa (AN) and Attention Deficit Hyperactivity Disorder (ADHD) are frequent mental disorders in child and adolescent psychiatry. Comorbidity of these disorders is, however, rare among minors. Thus, little is known about their mutual impact on illness development as well as diagnostic and therapeutic influencing factors. We report the case of a 10-year old girl with AN and massive underweight. At the age of 5, ADHD had been diagnosed. Application of ADHD-specific medication had been refused by her caregiver. As of 3rd grade, hyperkinetic symptoms were significantly reduced, which was later linked to beginning AN-induced weight loss. At inpatient admission, no clinically relevant ADHD-related symptoms were present. Accompanying weight gain, rather ‘sudden’ appearance of attention difficulties, motoric hyperactivity and impulsivity were reported, widely impairing our patient’s schoolwork and further daily life. Methylphenidate medication showed good clinical response and tolerability. We hypothesize that the former massive underweight had suppressed ADHD-specific behaviour. AN with significant weight loss could possibly mask hyperkinetic symptoms in children. Thus, sufficient clinical diagnostics and intense monitoring during ED treatment are required. Physicians and therapists should be sensitized for interactions in the joint occurrence of these mental disorders among minors. In child and adolescent psychiatric healthcare, AN and ADHD are frequently treated disorders. In the past few years, rising numbers and higher symptom severity of EDs, particularly AN, were reported in the international literature, not least as a consequence of the COVID-19-pandemic. In Germany, the prevalence of eating disorders among female adolescents has increased by 54% (9.8/1000) from 2019 to 2021 .In addition to multiple somatic complications , formal thought disorder (FTD) with rumination on eating, weight and body image as well as body image disturbance are among the psychiatric symptoms of AN. AN-specific behaviour includes self-imposed diets, excessive physical activity and possibly vomiting or purging  .ADHD is a neurodevelopmental disorder characterized by the main symptoms of inattention, motoric hyperactivity and impulsivity. Worldwide prevalence of ADHD is around 5%, peaking at childhood age . DSM-V dComorbidity of ADHD and AN is, however, very rare in clinical cases of younger children, particularly in females. Thus, little is known about mutual pathogenesis, impact on illness development or diagnostic and therapeutic influencing factors. Literature links ADHD mostly to EDs with impulsive behaviour, like Bulimia Nervosa (BN), Binge Eating Disorder (BED), AN with self-induced vomiting and obesity among youths or adults ,10. ‘PicThe objective of this article is to present the clinical case of a 10-year old girl with previously diagnosed ADHD who developed AN with weight loss and thereby suppressed her hyperkinetic disorder symptoms. We intend to outline the effects of underweight on ADHD-specific behaviour and its change throughout weight regain during child and adolescent psychiatric therapy.A 10–11-year-old female patient was presented at our Department for Child and Adolescent Mental Health at University Hospital of Erlangen, Germany. Previously, she had undergone paediatric hospital treatment after her parents and day caregivers at school had recognized growing food and fluid refusal. They reported a self-induced weight loss of 7 kg during the past 3 months via selective and restrictive eating. She was admitted to hospital at 27 kg, 1st BMI age percentile . The patAdditionally, depressive symptoms like low and dysphoric mood, avolition and anhedonia were present. Her mother reported an affective lability with frequent crying and anger as well as permanent feelings of guilt and insufficiency in the girl. Previously to hospital treatment, the girl had socially withdrawn from peer contacts. She further reported sleep disturbances with frequent night awakenings. She showed anxiety symptoms like social phobia, performance and separation anxiety at admission, which had developed since the beginning of weight loss. The girl suffered from recurring states of high tension particularly connected to eating and tube feeding situations. In this context, she had repeatedly injured herself deliberately via slamming her head against walls or objects.At the age of 5, ADHD (combined presentation) had been diagnosed due to inattention, hyperactivity and impulsivity. The girl had suffered immensely from low performance at school. She was avoided by peers and repeatedly involved in conflicts with peers and adults, particularly due to her impulsive behaviour. Criteria of oppositional defiant disorder were not met. Administration of stimulant medication had previously been recommended yet refused by her caregivers. The patient had received ergotherapy, motopedic and occupational therapy during early childhood. After attending special school for first two classes, the change to regular elementary school was followed by improvement and ‘disappearance’ of hyperkinetic symptoms, later being linked to the beginning of AN-specific weight loss. This development was also verified by evaluating the girl’s school reports, where improvement of her grades had been noticed. At inpatient admission, no clinically relevant ADHD-related symptoms were present at all. The German questionnaires ‘Diagnosesystem für psychische Störungen nach ICD-10 und DSM-5 für Kinder und Jugendliche’ (DISYPS-III)  yielded Our patient received a highly structured AN-specific cognitive-behavioural treatment program with 3 main and 2 to 3 snack meals per day in an inpatient setting. The girl and her caregivers signed a therapy agreement, through which a target weight (‘minimum weight’) at the 25th age BMI-percentile (35 kg) was defined. Body weight was measured every morning, 3 times per week during later treatment stages. We addressed eating behaviour via contingency management and token economy. Portion sizes were adapted to a weekly checked average weight-gain progress. Due to initially constant rejection of any food or drink intake, feeding via nasogastric tube was required for 3 weeks. After that, food alimentation was initially possible only via sip feeds, before our patient started gradually tolerating oral nutrition. The refeeding process was accompanied by AN-specific psychotherapeutic sessions in individual and group settings several times per week. These sessions comprised, among others, psychoeducation and cognitive restructuring, as well as training of social and emotional skills and body image interventions. During residential and later day-care treatment at our ED-specific ward, our patient was able to gain weight up to her target weight and flexibilize her eating structure. Her mood and anxiety symptoms subsided. She became more open and was able to build up social contacts with peers and adults under constant weight gain. States of high tension decreased and vanished completely. There was no deliberate self-injury during our treatment. Her heart rate normalized, digestion restored under gradual reduction of the laxative dose and her hair and nails revitalized. Our patient attended daily lessons at our Hospital School during her treatment.Accompanying weight gain, particularly with the 10th age BMI-percentile (31 kg) after about 1.5 months of treatment, the healthcare team, teachers and caregivers reported rather ‘sudden’ clinical (re-)appearance of constant attention difficulties, motoric hyperactivity and impulsivity. The girl was increasingly distractible and unable to pursue executive tasks, at which she had shown good endurance for a longer time span during the first weeks of treatment . Careless mistakes were becoming more frequent. She increasingly showed disruptive behaviour during lessons at the Hospital School by interrupting her teachers or shouting out loudly during class. She was increasingly unable to sit and stand still, stood up frequently during lessons and moved around the classroom. Further, she was almost run over by a car when following a cat onto the streets. This had to be differentiated from the urge to move in order to lose weight, which is typical for AN. As our patient was also significantly less anxious about increasing body weight, this was interpreted as a hyperkinetic symptom. ADHD-specific clinical ratings showed significant increases in values . Symptom® retard (dosage: 30–0–0–0 mg/d), hyperkinetic symptoms significantly reduced . We hypothesize that former massive underweight had suppressed (‘numbed’) ADHD-specific behaviour through as-yet-unknown neurocognitive mechanisms.Possible appetite-suppressing and thus weight-reducing adverse side effects of stimulant medication have to be considered . BecausePathophysiologic consequences of underweight include central nervous atrophy and thus neurocognitive impairment. Underlying somatic pathologies, e.g., cerebral malignancy, should be ruled out, particularly in ED cases with unusual age onset or atypical symptom presentation . Thus, oContrary to these findings, our patient’s pre-existing deficits in attention and self-control were reduced during AN-induced underweight. Third-party interviews and her school reports suggested better performance, contrasting the typically seen intellectual damage in AN . HoweverThis report has several limitations: As we can only report one clinical case, the level of evidence is low. Further, observations during the diagnostic and treatment progress were made by a single hospital institution, which might limit objectivity. Yet, standardized diagnostics were applied and therapy progress was evaluated via multi-view sources , to provide assessments as independent as possible. Further, we accompanied our patient during inpatient and day-care treatment stages, which allowed us a detailed evaluation of symptom changes during her weight increase.Our case report shows that AN can have a significant impact on ADHD symptomatology in young patients. AN-induced weight loss might suppress/mask hyperkinetic behaviour, as demonstrated in our case report. Underlying neurobiological explanatory models still have to be investigated. Despite low comorbidity of AN and ADHD among female minors, clinicians should be aware of possible masking effects, particularly in female patients.


Neurodevelopmental disorders (NDDs), such as attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), are examples of complex and partially overlapping phenotypes that often lack definitive corroborating genetic information. ADHD and ASD have complex genetic associations implicated by rare recurrent copy number variations (CNVs). Both of these NDDs have been shown to share similar biological etiologies as well as genetic pleiotropy.n = 7920), ASD (n = 4318), or both , as well as 19,993 controls. Cases and controls were matched by genotype array . Three case–control association studies each calculated and compared the observed vs. expected frequency of CNVs across individual genes, loci, pathways, and gene networks. Quality control measures of confidence in CNV-calling, prior to association analyses, included visual inspection of genotype and hybridization intensity.Platforms aimed at investigating genetic-based associations, such as high-density microarray technologies, have been groundbreaking techniques in the field of complex diseases, aimed at elucidating the underlying disease biology. Previous studies have uncovered CNVs associated with genes within shared candidate genomic networks, including glutamate receptor genes, across multiple different NDDs. To examine shared biological pathways across two of the most common NDDs, we investigated CNVs across 15,689 individuals with ADHD . Additionally, we uncovered PRLHR deletions in 40 ADHD cases and 12 controls  as well as clinically diagnostic relevant 22q11.2 duplications and 16p11.2 duplications in 23 ADHD + ASD cases and 9 controls  and 22q11.2 duplications in 34 ADHD + ASD cases and 51 controls ; those control samples were not with previous 22qDS diagnosis in their EHR records.Here, we report results from CNV analysis in search for individual genes, loci, pathways, and gene networks. To extend our previous observations implicating a key role of the metabotropic glutamate receptor (mGluR) network in both ADHD and autism, we exhaustively queried patients with ASD and/or ADHD for CNVs associated with the 273 genomic regions of interest within the mGluR gene network (genes with one or two degrees protein–protein interaction with mGluR 1–8 genes). Among CNVs in mGluR network genes, we uncovered CNTN4, 22q11.2, and 16p11.2 are overrepresented in NDDs that constitute patients predominantly suffering from ADHD and ASD.Together, these results suggest that disruption in neuronal cell-adhesion pathways confers significant risk to NDDs and showcase that rare recurrent CNVs in ClinicalTrials.gov Identifier: NCT02286817 First Posted: 10 November 14, ClinicalTrials.gov Identifier: NCT02777931 first posted: 19 May 2016, ClinicalTrials.gov Identifier: NCT03006367 first posted: 30 December 2016, ClinicalTrials.gov Identifier: NCT02895906 first posted: 12 September 2016.The online version contains supplementary material available at 10.1186/s11689-023-09483-z. Attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) have overlapping phenotypes and shared associations at several genetic loci. Microarray and sequencing platforms aimed to address genetic-based inquiries have allowed for the application of groundbreaking techniques in fields aimed at elucidating the underlying disease biology associated with these neurodevelopmental disorders (NDDs), as well as other neuropsychiatric diseases such as anxiety, depression and oppositional defiant disorder (ODD) to name a few –5. AnalyIn addition to individual loci, significant CNV enrichments in specific gene networks have been associated with NDDs. In this regard, our group and others have identified significant CNV enrichment within the in metabotropic glutamatergic receptor (mGluR) network among independent ASD and ADHD cohorts –15. ThesThis study examines the shared biological pathways in the mGluR network in individuals diagnosed with ADHD and/or autism. It defines the mGluR network as those 273 genes that demonstrate 1 or 2° protein–protein interaction with the mGluR 1–8 genes , 13  is of exploratory interest, where emerging evidence suggests an association with developmental delay (DD) and/or intellectual disability (ID). There are also 3 canonical regions of interest within the 16p11.2 locus that have been shown to be strongly associated with DD and NDDs. Most pertinent to this study are regions, 16p11.2 deletion syndrome, distal  (BP2-BP3), and 16p11.2 deletion syndrome  (BP4-BP5). Patients with CNVs within these clinical regions have been characterized by DDs , ID, and/or ASD. The CNTN4 locus is also of high interest as previous findings have associated CNVs implicating disruption to normal neuronal cell–cell adhesion functions, evidenced by deletions in the CNTN4 gene –20. ThusWe analyzed 7920 individuals with ADHD, 4318 individuals with ASD, and 3,416 with both ASD and ADHD, in comparison with 19,993 control samples from the Center for Applied Genomics (CAG) biobank  were identified as significant for CNV risk burden for ADHD, ASD, or both Table .Table 2CPRLHR deletions were associated in both the ADHD and NDD cohort . ADRB2/SH3TC2, CACYBP, and FSCN1 deletions were exclusively enriched within the ADHD cohort while PCBP3 duplications were enriched within the NDD cohort; ADRB2, SH3TC2 deletions were observed in 50 cases and 5 controls , FSCN1 deletions in 32 cases and 2 controls . Finally, PCBP3 duplications were observed in 37 cases and 3 controls .p = 1.03E − 8, Reactome term GPCR ligand binding p = 5.39E − 7; GO Process term modulation of chemical synaptic transmission p = 3.14E − 5; GO Function term G protein-coupled receptor activity p = 4.97E − 5; GO process term behavior p = 1.5E-4, and; GO Process term Adenylate cyclase-modulating g protein-coupled receptor signaling pathway p = 1.8E − 4, suggesting high level of complexity among the gene signaling networks involved in NDD.To further refine our list of 273 genes interacting with mGluR1-8, we ran functional annotation enrichment analysis on the most significant genes identified here. Significant functional annotation enrichment was observed in KEGG term Neuroactive ligand-receptor interaction N = 15,654 cases N = 19,993 controls) improves our ability and confidence of accurately capturing rare recurrent statistical events, such as the CNVs reported herein. Among the 18 CNVRs uncovered, representing the highest levels of CNV enrichment in any affected NDD population, 4 CNVRs support previously validated associations and 4 represent novel CNVRs with no prior associations to ADHD or ASD.Our results demonstrate increased burden of rare CNVs in NDD disease biology, both novel and known in keeping with previous reports , 17, 20.CNTN4 deletions we uncovered are similarly highly enriched in the ADHD and autism cases and corroborate previous reports [Our results corroborate the biological significance of the 22q11.21 and 16p11.2 regions in the pathophysiology of neurodevelopmental disorders as reported in previous studies , 11, 22. reports , 11, 20.PRLHR and ADRB2 genes are highly enriched in ADHD cases suggesting that functional pathways ancillary to the pituitary and noradrenergic systems may play greater roles in the pathophysiology of ADHD and potentially other NDDs than previously recognized. PRLHR is required for normal anterior pituitary function and plays a key role in G protein-coupled receptor activity by encoding the prolactin-releasing peptide receptor (PrRPR) also known as G-protein coupled receptor 10 (GPR10). The pathophysiology underlying ADHD has been shown to be more sensitive to normal anterior pituitary function in comparison to other NDDs, such as schizophrenia [ADRB2, is a cell membrane-spanning beta-adrenergic receptor that interacts and binds with epinephrine , a hormone and neurotransmitter. Epinephrine stimulates adenylate cyclase through trimeric Gs proteins, increasing cAMP, and downstream L-type calcium channel interaction, mediating physiologic responses such as smooth muscle relaxation and bronchodilation. ADRB2 has been implicated as a risk factor for ASD, with no current association reported with ADHD [We investigated more deeply the functional roles of the mGluR interacting genes showing significance in our present study. The CNV deletions we uncovered in the ophrenia . The betith ADHD .ADRB2, SH3TC2), 10q26.11 (PRLHR), 1q25.1 (CACYBP), 7p22.1 (FSCN1), 18q21.32 (MC4R), although there is a trend toward significance at the FSCN1 locus for individuals with both ASD and ADHD. For both the strength of the association, and the absence of a similar signal for ASD, the ADRB2/SH3TC2 locus is perhaps the most noteworthy. The SH3TC2 (SH3 domain and tetratricopeptide repeats-containing protein 2) protein is thought to be expressed in Schwann cells, protective glia that support neuronal function, and is best known for its association with the childhood neurodegenerative disease Charcot-Marie-Tooth disease type 4C as well as sensory and motor neuropathy [ADRB2 has previously been identified as an ADHD candidate gene [In ADHD cases but not ASD cases, we found deletions significantly enriched at 5 CNVRs-5q32  than the ADHD subjects (p = 0.006 OR = 4.54). An expression study of expression pattern of the broader poly(C)-binding protein (PCBP) family  in zebrafish offers some evidence of a role in the early development of neural as well digestive systems [PCBP3 duplications had more robust significance in the ASD subjects  in patients with ASD plus 22q11.2DS, 22q11.2DupS, or Trisomy 21 accounted for about one third of the patients with Syndromic ASD + mGluR network changes. Relatedly, a CNV study of the etiological overlap between ASD and schizophrenia features PCBP3 [Interestingly, a study from our group previously identified an association between the locus and syndromic autism , which ies PCBP3 .P = 1.38 × 10−8; OR = 12.19). We observed 16p11.2 duplications in two separate regions with the most significant association demonstrated at the canonical 16p11.2 deletion syndrome  (BP4-BP5) region with CNVs present in 31 cases and 1 control . Duplications were also observed downstream to syndromic sites in 6 cases and 0 controls . Our findings also replicated previously associated CNTN4 deletions with ADHD and other NDDs [CNTN4 deletions enriched in both the ADHD cohort with deletions in 134 cases and 17 controls  and the NDD cohort with deletions in 175 cases and 43 controls .Duplications overlapping diagnostic regions in 22q11.21  and 16p11.2 (ALDOA*) were most significantly associated with comorbid ADHD and ASD phenotypes. Microduplications in known syndromic regions, including 22q11.2 and 16p11.2, were found to be most significantly overrepresented among comorbid patients diagnosed with both ADHD and ASD. In total, we observed 22q11.2 duplications in 41 cases and 3 controls .SNP genotyping was performed using the Infinium II assay using HumanHap550, Human610Quad, and HumanOmni2.5 M arrays at the (CAG) at CHOP. CNV calling was done using PennCNV using a combination of values including Log R Ratio, B Allele Frequency, SNP spacing, and population frequency of the B allele (PFB) into a hidden Markov model (HMM)  was usedn = 273) in the ADHD and autism cases versus controls. CNVs passing visual review were then examined for association testing and the most significant p-value genes/genomic regions are presented, minimizing false positive CNV calls.Apart from new discovery, our technical aims were focused on reducing false discovery rate by limiting false positive input prior to performing association analysis. This challenges the existing ParseCNV analysis paradigm of “visualize last”, as previously described , 3. We eAll reported calls made by PennCNV were carefully curated prior final association by ParseCNV. Predicted CNVs were visually evaluated for expected Log R Ratios (LRR) and BAF values associated with corresponding copy number states Figs.  and 3. CP values ≤ 0.05, or simpleM P values ≤ 0.05 were considered to be significant. FDR, Bonferroni, and simpleM-based corrections identified the same CNV regions as significantly associated [The Bonferroni correction for multiple testing was used on all discovered CNVR associations detected by ParseCNV. False discovery rates correction was also applied and tested using qPCR validation. CNV association tests with FDR ≤ 0.05, Bonferroni adjusted sociated , 51.We experimentally validated 616 CNV calls using qPCR. Five hundred twenty samples were confirmed to be true positives, while 96 samples turned out to be false positives. qPCR was performed using TaqPath ProAmp Master Mix (ThermoFisher Scientific). Taqman assays targeting the desired regions were identified using the ThermoFisher Scientific website tools and were selected to be compatible with the hTERT reference Taqman assay. Ten nanograms of genomic DNA was included in each reaction, along with the indicated Taqman assay and the hTERT reference assay in a reaction volume of 10 ml. Each reaction was run in triplicate. For each assay, three controls were run along with subject samples: a no template control , and commercial sources of male and female genomic DNA (Promega). PCR was performed on a Viia 7 Real-Time PCR system (ThermoFisher Scientific), using cycling conditions recommended for the TaqPath ProAmp master mix for copy number variant detection . Data were exported to text file using the QuantStudio Real-Time PCR Software v1.2 (ThermoFisher Scientific) and imported to Copy Caller v2.1 for analysis (ThermoFisher Scientific). Analysis of each Taqman assay was performed in Copy Caller using the commercial male DNA as the calibrator sample. Normal copy number of the commercial female DNA was confirmed as a control, as was failure of amplification in the no template control sample.Additional file 1: Supplementary methods. ADHD and Autism Phenotype Query Parameters. Supplementary Table S1. ADHD Inclusion/ Exclusion Table. Supplementary Table S2. Autism Inclusion/ Exclusion Table. Supplementary Table S3. mGluR Interacting Genes (n=273). Supplementary Table S4. CNVs in mGluR interacting gene regions significantly associated in ADHD cases vs. controls. Supplementary Table S5. CNVs in mGluR interacting gene regions significantly associated in ASD cases vs. controls. Supplementary Table S6. CNVs in mGluR interacting gene regions significantly associated in ADHD & ASD cases vs. controls. Supplementary Figure S1. DeepCNV Probability in mGluR CNVs Passing Prior Visual Inspection. Supplementary Figure S2. mGluR CNV Association Study Manhattan Plot.