Working memory deficits and associated neurofunctional abnormalities are frequently reported in attention-deficit/hyperactivity disorder (ADHD). Methylphenidate and atomoxetine improve working memory performance and increase activation of regions under-functioning in ADHD. Additionally, methylphenidate has been observed to modulate functional networks involved in working memory. No research, however, has examined the effects of atomoxetine or compared the two drugs.This study aimed to test methylphenidate and atomoxetine effects on functional connectivity during working memory in boys with ADHD.We tested comparative effects of methylphenidate and atomoxetine on functional connectivity during the n-back task in 19 medication-naïve boys with ADHD (10–15 years old) relative to placebo and assessed potential normalisation effects of brain dysfunctions under placebo relative to 20 age-matched neurotypical boys. Patients were scanned in a randomised, double-blind, cross-over design under single doses of methylphenidate, atomoxetine, and placebo. Controls were scanned once, unmedicated.Patients under placebo showed abnormally increased connectivity between right superior parietal gyrus (rSPG) and left central operculum/insula. This hyperconnectivity was not observed when patients were under methylphenidate or atomoxetine. Furthermore, under methylphenidate, patients showed increased connectivity relative to controls between right middle frontal gyrus (rMFG) and cingulo-temporo-parietal and striato-thalamic regions, and between rSPG and cingulo-parietal areas. Interrogating these networks within patients revealed increased connectivity between both rMFG and rSPG and right supramarginal gyrus under methylphenidate relative to placebo. Nonetheless, no differences across drug conditions were observed within patients at whole brain level. No drug effects on performance were observed.This study shows shared modulating effects of methylphenidate and atomoxetine on parieto-insular connectivity but exclusive effects of methylphenidate on connectivity increases in fronto-temporo-parietal and fronto-striato-thalamic networks in ADHD.The online version contains supplementary material available at 10.1007/s00213-023-06422-7. Attention-deficit/hyperactivity disorder (ADHD) is characterised by developmentally inappropriate levels of hyperactivity, impulsivity, and/or inattention  studies of working memory in youth with ADHD relative to neurotypical individuals show consistent increases in fronto-parietal coupling  with a diagnosis of ADHD combined presentation and 20 neurotypical control boys (10–15 years old) were included in this study. Patients were recruited from South London Child and Adolescent Mental Health Services. ADHD diagnosis was confirmed by an experienced child psychiatrist using the standardised Maudsley Diagnostic Interview , learning disability, reading, speech, or language disorder. Data for additional 11 participants were available  but were not included in the current study due to excessive motion (NADHD = 1), poor functional data normalisation (Ncontrol = 1), and control participant’s age exceeding the age range of patients (Ncontrol = 9).Exclusion criteria for all participants were MRI-related contraindications, mean framewise displacement during scanning >1mm, IQ <70 on the Wechsler abbreviated scale of intelligence  were mean imputed.Welch’s Participants were reimbursed £50 for each session. Parental/child written informed consent/assent were obtained. Ethical approval was granted by the Joint South London and Maudsley/Institute of Psychiatry, Psychology & Neuroscience Research Ethics Committee (07/H0807/84).Boys with ADHD were scanned in a double-blind, placebo-controlled, cross-over design. On each scanning session (1 week apart), they received a single dose of either placebo , methylphenidate , or atomoxetine  in a pseudo-randomised order. Dosages were determined following National Institute for Health and Care Excellence guidelines at the time of the study . This requires both storage and continuous updating of stimuli held in working memory  with an 8-channel head coil at the Centre for Neuroimaging Sciences, King’s College London. Functional T2*-weighted data comprised 39 interleaved slices acquired with a gradient EPI sequence bottom-to-top over 186 volumes depicting BOLD contrast covering the whole brain . Whole-head structural image was acquired at the beginning of each scanning session using an MPRAGE protocol using parameters based on ADNI .Dependent variables were percentage accuracy in identifying targets, mean reaction time (MRT), and intra-subject variability of reaction time indexed by standard deviation of reaction time (SDRT). Data were analysed using R  method  and each of the seeds were conducted in the control group  with a cluster-forming threshold of puncorrected < 0.001 was applied to account for multiple comparisons.For hypothesis-testing, independent samples normalisation of function. An absence of a significant difference, however, cannot be considered as evidence of normalisation .Sensitivity analyses were conducted on performance and fMRI data excluding participants with comorbid oppositional defiant and/or conduct disorder . No other statistically significant effects were observed . One-way ANOVA showed no significant group difference between controls and patients under each drug condition in mean FD  = 1.14, p = 0.338, ƞ2= 0.04; control, mean = 0.18mm, SD = 0.08; ADHDplacebo, mean = 0.22mm, SD = 0.19; ADHDmethylphenidate, mean = 0.17mm, SD = 0.08; ADHDatomoxetine, mean = 0.23mm, SD = 0.12).FD was calculated according to Power et al. , 2014 ust-tests showed no significant differences for any seeds in within-patients comparisons.Paired samples t-test showed that participants with ADHD exhibited greater connectivity between rSPG and left-hemispheric insula/central operculum relative to controls. This effect was due to more negative beta values during 2-back compared to 0-back in controls, but no such difference in participants with ADHD under placebo  bilateral: insula, ACC, Heschl’s gyrus, putamen, supramarginal gyri (SMG), parietal operculum; 2) left: postcentral gyrus and planum temporale/operculum; 3) right: thalamus, paracingulate gyrus, and temporal occipital fusiform cortex. Additionally, greater connectivity in participants with ADHD under methylphenidate between rSPG and bilateral ACC, as well as right parietal operculum/SMG was found compared to controls. Mean beta values indicated that neurotypical controls exhibited lower beta values during 2-back than 0-back. In contrast, participants with ADHD under methylphenidate showed the opposite effect, with higher beta values during 2-back compared to 0-back  was entered into group-level models showing case-control differences as a covariate of interest. Small volume correction was applied to restrict the test to regions showing significant differences between individuals with ADHD and controls. No statistically significant associations between accuracy and functional connectivity were observed.and individuals with ADHD under methylphenidate > individuals with ADHD under placebo and (ii) controls > individuals with ADHD under placebo and individuals with ADHD under atomoxetine > individuals with ADHD under placebo. Small volume correction using a mask defined based on the insula/central operculum cluster of case-control differences under placebo was applied to both analyses. The conjunction analyses revealed no common areas of connectivity within this cluster in individuals with ADHD under either drug and controls, thereby failing to support full normalisation of rSPG-insula/operculum hyperconnectivity.To assess whether the lack of significant case-control differences in connectivity between rSPG and left-hemispheric insula/central operculum (observed under placebo) under methylphenidate and atomoxetine reflected drug normalisation effects, we conducted confirmatory conjunction analyses. Given that the within-patient comparisons of methylphenidate/atomoxetine and placebo did not reveal any statistically significant differences across the whole brain, here we restrict our search only to voxels within the left insula/central operculum that showed abnormally high connectivity with rSPG under placebo. In the absence of a separate ADHD group, we acknowledge the potential of bias of this approach. Two conjunction analyses were performed for the comparisons of (i) controls > individuals with ADHD under placebo and individuals with ADHD under methylphenidate > controls. Small volume correction using masks of regions showing case-control differences when ADHD individuals were under methylphenidate was applied. Conjunction analyses revealed common upregulation with methylphenidate in ADHD relative to placebo and relative to neurotypical controls in connectivity between rMFG and SMG  and rSPG and SMG . Beta values revealed that while the change between vigilance and high working memory load was similar under both placebo and methylphenidate, under methylphenidate those regions had more negative values across task conditions.Additional conjunction analyses were conducted to test whether regions showing heightened connectivity in ADHD under methylphenidate relative to controls during 2-back > 0-back were also upregulated with methylphenidate relative to placebo within patients. Two conjunction analyses were conducted, one for connectivity with rMFG and another one for the connectivity with rSPG. These analyses included individuals with ADHD under methylphenidate > individuals with ADHD under placebo Sensitivity analyses revealed no impact of oppositional defiant and/or conduct disorders on results of performance and fMRI analyses.F = 0.15, p = 0.858, ƞ2 < 0.01), MRT  = 0.41, p = 0.667, ƞ2 < 0.01), or SDRT  = 0.553, p = 0.58, ƞ2 = 0.01).No scan order effects were observed for accuracy


The Medicare Modernization Act (MMA) has provided an opportunity for quality improvement organizations (QIOs) to partner with Medicare Part D plan sponsors. These new relationships have developed into a set of diverse projects, each approved by the Centers for Medicare Medicaid Services.To provide information about the scope of the projects being conducted by the QIOs and their partners.The document describes a variety of quality improvement projects addressing medication use by beneficiaries enrolled in Medicare Part D.Private Medicare QIO contractors are implementing these projects in each state. Descriptions of each project were developed by individual QIOs with the assistance of lead staff for the Physician Practice/Pharmacy QIO SupportCenter for all QIOs nationwide. These projects vary in their complexity, in the quality measures used, and in the clinical processes and economic impact they seek to improve. The summaries in this supplement were prepared 6 months into the current 3-year contract period, which began August 2006. Accordingly, the summaries reflect varying stages of development, funding reductions could occur that necessitate project redesign, and projects have not yet been evaluated. With few exceptions, these projects are not designed as research but as quality improvement projects following the “Plan, Do, Study, Act” model for speeding acceptance of evidence-based practice.This survey describes the promise of partnerships whose value will be fully realized in future years. The results of these early QIO initiatives will not be available until projects are evaluated, but QIOs and many Medicare Part D plans have established promising partnerships and have begun to share data for the purpose of assessing and improving plan and practitioner performance as well as patient engagement.Most projects are focused on ambulatory care, but some QIOs are addressing nursing home care and continuity of care between settings.Most ambulatory care projects are limited to prescription drug claims data,but a few plans are providing medical and lab data to QIOs in addition to drug claims. QIOs have historically worked almost exclusively with physicians and nurses but in many states are now engaged with colleges of pharmacy as well as with managed care and community pharmacists. QIO partnerships will provide managed care organizations and pharmacists with the opportunity for innovative quality improvement initiatives that might not otherwise be possible because of limitations of available data or resources.Pharmacists can use this document to review a wide array of options for working with QIOs and other partners in their market to design or strengthen their organization's medication therapy management and quality improvement programs. Managed care pharmacists may be particularly interested in the ability of QIOs to assist them in comparing their plans' performance with other national and regional plans.


Functional connectivity is scaffolded by the structural connections of the brain. Disruptions of either structural or functional connectivity can lead to deficits in cognitive functions and increase the risk for neurodevelopmental disorders such as attention deficit hyperactivity disorder (ADHD). To date, very little research has examined the association between structural and functional connectivity in typical development, while no studies have attempted to understand the development of structure-function coupling in children with ADHD. 175 individuals  participated in a longitudinal neuroimaging study with up to three waves. In total, we collected 278 observations between the ages 9 and 14 . Regional measures of structure-function coupling were calculated at each timepoint using Spearman’s rank correlation and mixed effect models were used to determine group differences and longitudinal changes in coupling over time. In typically developing children, we observed increases in structure-function coupling strength across multiple higher-order cognitive and sensory regions. Overall, weaker coupling was observed in children with ADHD, mainly in the prefrontal cortex, superior temporal gyrus, and inferior parietal cortex. Further, children with ADHD showed an increased rate of coupling strength predominantly in the inferior frontal gyrus, superior parietal cortex, precuneus, mid-cingulate, and visual cortex, compared to no corresponding change over time in typically developing controls. This study provides evidence of the joint maturation of structural and functional brain connections in typical development across late childhood to mid-adolescence, particularly in regions that support cognitive maturation. Findings also suggest that children with ADHD exhibit different patterns of structure-function coupling, suggesting atypical patterns of coordinated white matter and functional connectivity development predominantly in the regions overlapping with the default mode network, salience network, and dorsal attention network during late childhood to mid-adolescence. Brain development during childhood and adolescence is a highly dynamic process characterized by rapid changes in structural and functional connections within and between different regions of the brain . In thisCross-sectional studies suggest that the degree of structure-function coupling is inversely proportional to the complexity of the function each brain region serves. For instance, lower structure-function coupling has been reported in brain regions responsible for higher-order executive functions and self-control like the frontal and limbic systems, whereas higher structure-function coupling has been reported in regions involved in lower-order sensory processing like the visual system . Cross-sTwo cross-sectional studies examined associations between age and structure-function coupling during childhood and did not identify any age-related effects in the association between structural and functional connections in default mode, frontoparietal, or salience networks , 20. TheADHD is a prevalent neurodevelopmental disorder that has been associated with aberrant structural and functional network organization during development, predominantly within higher-order cognitive and sensory regions –27. ExamThe goal of the current study was to investigate the development of structure-function coupling between late childhood and mid-adolescence, in a longitudinal sample of typically developing children and those with ADHD. As there has only been one longitudinal study that has examined the development of structure-function coupling in typically developing children, the first aim of this study was to examine the longitudinal changes in structure-function coupling in typically developing children. The second aim was to be the first to compare longitudinal changes in structure-function coupling in children with ADHD to typically developing children. We hypothesized that structure-function coupling would increase with age in higher-order cognitive regions in typically developing children. We also hypothesized that there would be significant differences between children with ADHD and typically developing children in structure-function coupling in higher-order cognitive and sensory regions, including differential developmental trajectories in these regions.This study used data from a community-based sample of 175 children (91 children with ADHD and 84 non-ADHD controls) between the ages of 9 and 14. All participants were a part of the longitudinal neuroimaging cohort, Neuroimaging of the Children’s Attention Project (NICAP) , in Melbn = 10), scans missing field maps (n = 25) and poor-quality DWI scans  were excluded from the final analysis. No significant differences were observed between included and excluded participants in the age distribution of control or ADHD groups in one, two, or three waves (range p = 0.062–0.960). However, those children with ADHD who were excluded had more severe ADHD symptoms than included ADHD subjects (p < 0.05).To ensure the quality of imaging data, functional scans with excessive head motion The final sample with both structural and functional data comprised 278 scans  across the three assessment waves  data were acquired using a multi-band factor of three with the following parameters: b = 2800 sec/mm2, 63 slices, matrix size = 110 × 100, voxel size = 2.4 mm3, FOV=260 × 260 mm, bandwidth = 1748 Hz, acquisition time = 3 min 57 s. T1 weighted images were acquired using a multi-echo magnetization prepared rapid gradient-echo (MEMPRAGE) sequence along with navigator-based prospective motion correction with parameters: TR = 2530 ms, TE = 1.77, 3.51, 5.32, and 7.20 ms, FOV = 230 × 230 mm, FA = 7 deg, axial slices = 176, matrix size = 256 × 232, voxel size = 0.9 mm3, acquisition time = 6 min 52 s [All participants underwent a 30 min mock (practice) scanner session to get familiarized with the MRI environment. Subsequently, MRI scans were acquired using a 3-Tesla Siemens scanner at a single site. However, waves 1 and 2 were collected on a TIM Trio scanner, and wave 3 was collected after an upgrade to a MAGNETOM Prisma scanner . Using a 32-channel head coil, functional images were acquired using multi-band accelerated EPI sequences (MB3), with the following parameters: repetition time (TR) = 1500 ms, echo time (TE) = 33 ms, field of view (FOV) = 255 × 255 mm, flip angle (FA) = 85 deg, 60 axial slices, matrix size = 104 × 104, voxel size = 2.5 mmmin 52 s .http://fsl.fmrib.ox.ac.uk/fsl/fslwiki). Standard pre-processing steps such as discarding of four initial volumes to account for initial signal inhomogeneity, motion correction using MCFLIRT (FMRIB’s Linear Registration Tool), B0 unwarping, spatial smoothing using 5 mm FWHM, spatial normalization to the MNI template using a 12-parameter affine transformation and registration of fMRI images to MNI space via high-resolution T1 images using FSL FLIRT and FNIRT were undertaken [Pre-processing of resting-state fMRI images was done using FSL 5.0.9 , a fork of the MRtrix software [Diffusion-weighted imaging (DWI) data was pre-processed using MRtrix3tissue  atlas (360 distinct regions) . The volhttps://github.com/shaniasoman/SC_FC_coupling/blob/main/SC_FC_coupling.R.The structural and functional connectome of 278 datasets  were used to examine structure-function coupling between late childhood and mid-adolescence , to account for longitudinal data and the possibility of linear and nonlinear trajectories. All models included mean frame-wise displacement of structural and functional connectivity of each subject, scanner effect (pre vs post upgrade), sex, and medication as covariates. GAMMs were implemented in R 4.0.3, with the package ‘mgcv’ .p < 0.05) and AIC units <2 [p < 0.05) was used to test the statistical significance of coefficients. All the whole brain maps and trajectory plots were created using Pysurfer v0.10.10 (https://pysurfer.github.io/) and RStudio [First, we examined age-related changes in structure-function coupling in typically developing children. We compared (i) a null model to (ii) a main effect of age, in predicting structure-function coupling. Next, we included children with ADHD. To estimate the differential developmental trajectories in children with ADHD relative to typically developing children four different models were used: (i) a null model, (ii) main effect of age (iii) main effect of group, and (iv) the interaction of group and age. For all models, the basic dimension for the smooth term was set to 4 (maximum degrees of freedom for smooth term) as recommended by Wood . Each mounits <2 . Further RStudio  respectiFirst, we evaluated how structure-function coupling develops in typically developing children between the ages of 9 and 14. Age-related differences in structure-function coupling were distributed across the cortex, including the prefrontal, anterior cingulate, mid cingulate, posterior cingulate, precuneus, inferior parietal, middle temporal, and visual cortex Fig. . NotablyNext, we examined differences in structure-function coupling in children with ADHD compared to typically developing controls. Across 9–14 years, children with ADHD showed weaker structure-function coupling in the left superior temporal gyrus, right inferior parietal cortex, and right medial prefrontal cortex Fig. . They alThe present study examined longitudinal changes in structure-function coupling with typical development and highlighted developmental differences in children with ADHD. We observed a significant change in structure-function coupling in typically developing individuals between late childhood and mid-adolescence in various regions implicated in higher-order cognitive and sensory processes, including the prefrontal, anterior cingulate, mid cingulate, posterior cingulate, precuneus, inferior parietal, middle temporal and visual cortex. We also observed that children with ADHD exhibited differential developmental trajectories to typically developing controls in brain regions such as bilateral inferior frontal gyrus, left medial prefrontal cortex, left superior parietal cortex, left precuneus, left inferior temporal cortex, right inferior parietal, right mid cingulate, right medial temporal cortex, and right visual region.Our longitudinal investigation demonstrated that the typical development of structure-function coupling from late childhood to mid-adolescence was predominantly distributed in brain regions such as prefrontal, anterior cingulate, mid-cingulate, posterior cingulate, precuneus, inferior parietal, middle temporal, and visual cortex. These regions mainly overlap with the areas of DMN, SAL, FPN, sensorimotor, and visual network. Notably, the regions that overlap with higher-order networks  showed increased structure-function coupling from 9 to 14 years of age, while regions that overlap with the sensorimotor networks  showed increased structure-function coupling from 9 to 12 years of age followed by a plateau to 14 years of age. These findings are consistent with the only prior longitudinal study examining developmental trajectories of structure-function coupling from childhood to adulthood, which noted increased coupling of DMN and FPN regions over this time .Studies have observed that protracted changes in coupling are crucial for the development of complex cognitive functions across childhood to adolescence , 61. SevMoreover, there could be some other underlying factors such as myelination or axon diameter that cause strong association between structural-functional connections. For example, while we examined fiber count as our measure of structural connectivity, it is possible that the development of myelin on those fibers or change in axon diameter could facilitate improved functional connectivity , 66. StrN = 210 ) or different metrics  used in their work [We also observed group differences in structure-function coupling between children with ADHD and their typically developing counterparts. Across late childhood to mid-adolescence, those with ADHD showed reduced coupling in brain regions involved in SAL and DMN  compared to controls. Abnormalities in these regions and networks have been consistently reported in prior cross-sectional structural and functional connectivity studies of ADHD compared to controls –81, witheir work . OverallGiven the profound changes in the brain across childhood to adolescence, it is important to examine how structure-function coupling changes with age. We found differential development of structure-function coupling in children with ADHD compared to controls, predominantly in the regions overlapping with the DMN, SAL, DAN, and visual network . In particular, those with ADHD showed increasing structure-function coupling with age in these regions, whereas typically developing children showed no change from late childhood to mid-adolescence. Increased structure-function coupling in ADHD for age and group interaction could reflect changes in the neural mechanisms underlying ADHD over time . As indiThese findings should be considered in light of certain limitations of our study. Firstly, although we accounted for medication status in statistical models, differences in trajectories between medicated and non-medicated individuals with ADHD were not examined due to the small number of individuals taking medication in our sample. Moreover, we did not examine how changes in structure-function coupling are associated with changes in neurocognitive functioning and changes or remission of symptoms. Future studies examining such relations between structure-function coupling and cognitive and clinical measures would help improve our understanding of the implications of these neural trajectories for developmental outcomes.In conclusion, our results provide a further understanding of the developmental changes in structure-function coupling in typically developing children, as well as aberrations in these neural patterns in those with ADHD. Findings suggest protracted development of structure-function coupling of higher-order regions in typical development, as well as differential developmental trajectories in structure-function coupling in children with ADHD relative to their peers.Supplementary Material


ADHD commonly co-occurs in children and parents. When ADHD is untreated in parents, it contributes to negative child developmental and treatment outcomes. Screening for parent and child ADHD co-occurrence in pediatric primary care may be an effective strategy for early identification and treatment. There is no data on whether this screening model can be implemented successfully and there exists limited guidance on how to effectively approach parents about their own ADHD in pediatric settings. Even greater sensitivity may be required when engaging with families living in urban, low SES communities due to systemic inequities, mistrust, and stigma.The current pilot study described the first 6 months of implementation of a parent and child ADHD screening protocol in urban pediatric primary care clinics serving a large population of families insured through Medicaid. Parents and children were screened for ADHD symptoms at annual well-child visits in pediatric primary care clinics as part of standard behavioral health screening. Independent stakeholder group meetings were held to gather feedback on factors influencing the implementation of the screening and treatment strategies. Mixed methods were used to examine initial screening completion rates and stakeholder perspectives  on challenges of implementing the screening protocol within urban pediatric primary care.Screening completion rates were low (19.28%) during the initial 6-month implementation period. Thematic analysis of stakeholder meetings provided elaboration on the low screening completion rates. Identified themes included: 1) divergence between provider enthusiasm and parent hesitation; 2) parent preference versus logistic reality of providers; 3) centering the experiences of people with marginalized identities; and 4) sensitivity when discussing parent mental health and medication.Findings highlight the importance of developing flexible approaches to screening parent and child ADHD in urban pediatric health settings and emphasize the importance of cultural sensitivity when working with marginalized and under-resourced families.NCT04240756 (27/01/2020).The online version contains supplementary material available at 10.1186/s12887-023-04082-2. Attention-Deficit/Hyperactivity Disorder (ADHD) is a common disorder that affects both children and adults. Given the high heritability of ADHD , multiplDisparities in diagnosis and treatment related to socioeconomic status (SES) exist for individuals with ADHD. Primary care providers working in under-resourced urban settings with higher poverty rates report more challenges in conducting appropriate diagnostic assessments for ADHD compared to those in suburban settings , which mImplementation of ADHD interventions in community and primary care settings face several barriers that may be distinct from private, suburban clinics, including limited primary care provider education on ADHD, lack of resources and time involved in diagnosing and treating a complex disorder such as ADHD, and the need to coordinate with others  to manage the disorder . FamiliePediatric primary care represents an opportunity for the early identification of multiplex ADHD, given that the American Academy of Pediatrics (AAP) recommends routine evaluation and treatment of ADHD in children beginning at age 4 . DespiteNo study, to date, has examined screening for parent and child ADHD in pediatric primary care. Although screening for parent mental health in pediatric primary care has benefits, there are challenges to implementing screening protocols in this setting. For example, parents may not feel comfortable discussing their own mental health symptoms with their child’s provider due to lack of trust or worries about being judged . ProvideAt present, there is little guidance on how to effectively approach parents about their own ADHD in a pediatric care setting, and broaching this topic with under-resourced families may require even greater sensitivity due to systemic inequities, mistrust, and stigma. The current pilot study describes initial efforts of implementing a protocol to screen for parent and child ADHD in urban pediatric primary care clinics and stakeholder perspectives on challenges and strategies to effectively engage with families living in under-resourced communities around topics of parent mental health, ADHD screening, and treatment of ADHD in multiplex families. The study period spanned from August to November 2020, during the COVID-19 pandemic and the Black Lives Matter movement following the police murder of George Floyd in May 2020.https://www.dchealthmatters.org) comparing the service areas of the primary care clinics to all of DC. In the U.S., the AAP recommends well-child visits at regular intervals, which are regular exams for children beginning from age 0 to 21. Visits allow for comprehensive assessments and focus on the child’s development. Parents and children were screened for elevated ADHD symptoms at annual well-child visits in pediatric primary care clinics via questionnaires as part of standard universal behavioral health screening. The Strengths and Difficulties Questionnaire (SDQ)  ‘I don’t wanna do any of this stuff.’”—PediatricianProviders reported similar observations of screening fatigue among families that they serve, particularly for families with young children due to the large number of health and developmental screening recommended by the AAP.“The doctor and the parent have a good relationship. I don’t think if someone else told me about it, I know I probably wouldn’t have done it, ‘cause I don’t know you, I don’t trust you.”—ParentInstead of completing screening questionnaires, participants expressed favorable attitudes towards having conversations with trusted providers to engage parents about their mental health. Providers’ established relationship with parents made them well-equipped to have these sensitive conversations. Additionally, parents and providers described the benefits of considered and careful conversations with a trusted provider for introducing new treatment approaches, such as integrated care.“'Cause just to give you an idea, on the schedule, we could be scheduled for, you know, up to 21 patients a day on a typical well-visit schedule. So you're seeing a lot of physicals back-to-back and you really don't have that much wiggle room for kind of these more delicate conversations for a study that could be extremely helpful.”—PediatricianHowever, engaging parents in sensitive conversations with trusted providers require time, which providers may not have. Although pediatricians, behavioral health providers, and parents repeatedly noted the importance of these conversations, the time investment for carrying out such deliberate conversations seemed at times incompatible with pediatricians’ workflow  during typical well-child visits. Faced with these competing demands on time, pediatricians acknowledged the challenges of taking such an approach.“I think that, it is something that has been a part of our work if you work with Black and African American families that this has always been part of our treatment and our sensitivity but is definitely heightened right now. I think yes, when talking about medication we have to recognize the immense history of mistreatment in the medical field towards Black and African American patients.”—Behavioral Health ProviderAnother major theme was the importance of centering mental health treatment around the historical and current negative experiences faced by many marginalized communities as a whole and as individuals. Explicitly eliciting, attending, and listening to the experiences of individuals with marginalized identities was viewed as critical. For example, providers noted the need for sensitivity to the historical mistreatment of Black people by medical professionals, especially in light of the Black Lives Matter movement and elevated focus on the patterns of systemic racial discrimination and racially motivated violence experienced by Black individuals across the country.“I see so many parents and mothers specifically, but also fathers of kids with ADHD, who their fears about their kid’s behavioral challenges and their impulsivity is so much more heightened because they know what the reality is that Black boys and Black children face in the world.”—Pediatrician“My son being Black, you know, a lot of Black kids have been diagnosed with ADHD. So that’s just tough on its own, you know, being a mom and having a Black son and oh, he has ADHD, so basically just trying to change and break the barrier and supporting my son …"—ParentParents and providers emphasized discrimination faced by Black boys with ADHD. Parents expressed concerns about the overdiagnosis of ADHD in Black boys, as well as fears about how others perceive or react to their behaviors. The reality of the negative consequences  disproportionately experienced by Black children was cited as a major source of concern:“When it comes to mental health in the Black community, it’s something that people don’t like to discuss because that can trigger to other things.”—ParentThis theme centered around the sensitivity required when speaking with parents about their mental health as well as treating mental health with medications due to stigma. Significant stigma related to mental health and seeking help from a psychologist or psychiatrist remains prevalent, especially among underserved and marginalized communities.“'Cause a lot of people may have felt difficulty focusing or juggling responsibilities and things like that. A lot of people could relate to that. Versus not as many people could definitely say, "Oh, I think I have ADHD and so does my child."—PediatricianParents and providers described various strategies for effectively reaching parents who may be facing these hesitations. They recommended using straight forward language and avoiding clinical labels for parents who may have been previously misdiagnosed or undiagnosed. Specifically, when asking about ADHD symptoms, parents and providers shared that it may be more effective to describe symptoms of ADHD rather than use the term “ADHD”:“With the stigma against medication because like [Parent]’s mentioning, majority of parents that we see are still hesitant about medication for their own child versus even for themselves because they’ve had such poor experience with mental health.”—Behavioral Health ProviderSensitivity is also required when addressing medication for treating ADHD, exemplified by statements such as “I don’t believe in medication.” Parents’ unfavorable attitudes towards being medicated or having their child medicated were echoed by providers in their experiences working with families in an urban primary care setting.when you find something that works, [I’ve] seen kids go from failing to getting into Ivy League schools, [gaining] confidence, self-esteem.”Parents described personal negative experiences with medications, which may have contributed to their current hesitation around ADHD medication for themselves and for their children. These prior negative experiences with medications appear to have a global effect on medication hesitation, such that the negative experiences were not specific to ADHD medications. For example, parents described experiencing significant side effects with antidepressants and generalized the experience to medications for other conditions, such as ADHD. Providers recounted similar experiences they have heard from the families that they work with and acknowledged that early classes of medications indeed often had severe side effects, which understandably contribute to parents’ continued hesitation regarding medications. Suggestions for discussing ADHD medications included a shared decision-making approach in which providers ask parents about their concerns regarding medication in order to address them directly. Providers also discussed the value of sharing positive anecdotes of medication use, such as “In the current pilot study, a protocol to screen multiplex ADHD families was implemented in urban pediatric primary care clinics serving predominantly racially minoritized families and families insured through Medicaid. In the first 6 months of implementing the screening protocol, approximately 1 in 5 families attending well-child visits who completed the screeners had elevated parent and child ADHD symptoms. However, overall screening completion rate was low (18.28%). Stakeholder input provided context and offered a deeper understanding of factors that may have contributed to the low ADHD screening completion rates. Themes largely converged between the types of stakeholders, but divergence was also observed between parents and providers/staff. Although the inclusion of multiple types of stakeholders provided important perspectives from an array of individuals who play a role or are impacted by the implementation of multiplex ADHD screening and treatment, we had a small number of participants within each type of stakeholder, limiting generalizability of our findings. As such, current findings represent preliminary data on an understudied topic.First, although providers in the study expressed enthusiasm for integrating parent mental health with pediatric care, parents expressed significant hesitation about this approach. Furthermore, there is tension between parents’ preference for having conversations with trusted providers about parent mental health and the structural and logistical reality of limited time for pediatric providers to have these sensitive conversations during a well-child visit. On the one hand, the relationship built between providers and parents offers providers the unique opportunity to inquire about more sensitive and potentially uncomfortable topics, such as parent’s own ADHD. This aligns with previous literature identifying Black and/or Latino communities and low-income groups preferring to receive mental health information from a credible, trusted source and someone that is known to them, such as a family doctor, and a preference for receiving mental health information in a familiar setting , 40. PedAside from logistical considerations, stakeholder input also provided insight on how to sensitively broach the topic of parent ADHD within a pediatric primary care setting given the continued inequities in mental healthcare and research with under-resourced families and challenges related to stigma. A key clinical takeaway is to attend to historical and continued oppression and negative experiences of individuals with marginalized identities and how these experiences impact their decision-making around ADHD care for themselves and their child. Significant stigma around mental health persists among communities of color and communities with socioeconomic disadvantages , 45. ParThis cultural sensitivity is particularly important if part of the treatment plan for ADHD includes the potential for medication which is associated with more mistrust and stigma. Parents in the study expressed concerns about medication for ADHD for themselves or their children based on past experiences. This finding is consistent with Glasofer et al.  describiCurrent findings must be considered in light of the following. This study represents initial implementation efforts and screening completion and rates of identifying multiplex ADHD families may vary with additional implementation supports and inclusion of a larger sample. Although the involvement of the stakeholder group provided the opportunity to gather perspectives of individuals occupying diverse roles within the pediatric primary care system, the group format precluded us from more in-depth interviews with individuals to fully understand their varying perspectives. Further, having a combined advisory group may have inadvertently created power differentials and impacted participants’ comfort level with sharing within the larger group. The stakeholder group was also limited in its sample representation , which may limit the generalizability of qualitative themes.Like many other psychological disorders, ADHD runs in families and pediatric primary care represents a promising context for routine screening of multiplex ADHD families. Yet, many issues are at play, both attitudinal and structural, when engaging with families living in under-resourced settings due to continued systemic inequities, mistrust, and stigma. The qualitative themes generated from the current pilot study represent a first step in understanding the perspectives and experiences of stakeholders – parents of children receiving care and providers and staff providing care at urban pediatric primary care clinics. This work and future research inspired by it can lead us closer to discovering the best way to identify and treat familial ADHD.Additional file 1: Supplemental Table 1. Washington DC Study Context.


BackgroundA common psychiatric problem called attention-deficit hyperactivity disorder (ADHD) is characterized by impulsivity with resultant behavior issues and a very short attention span. The purpose of this study was to evaluate and compare the management of dental procedures in children with and without ADHD employing various behavior modification techniques.Materials and methods2) were measured during each of these sessions. The study was conducted to evaluate the Tell-Show-Do (TSD) method, audiovisual distraction, and pharmacological management of children with and without ADHD during the dental procedure. IBM SPSS Statistics for Windows, Version 22  was used to statistically analyze the findings. The mean values of the parameters from the three sessions were analyzed and compared using the Z-test.The study consisted of 121 children divided into two groups with 60 children diagnosed with ADHD and 60 children without ADHD between 7 and 15 years of age. Each of the three sessions, which were spaced a week apart, included a dental examination, oral prophylaxis, and a minor restorative procedure. The pulse rate (PR) and oxygen saturation . The change in the mean PR score for the ADHD children revealed a declining trend from sessions one through three for all the techniques evaluated (p<0.05), demonstrating a statistically significant effectiveness of the various techniques between the two groups and thereby revealing a decreased level of anxiety. Between sessions one and three, all of the three techniques showed a decreasing trend of SpO2 scores, with the exception of the pharmacological management of ADHD children (p<0.01) indicating that the uncontrollable ADHD children feel less anxious than in the other two approaches.The children with ADHD included 39 (65%) boys and 21 (35%) girls, and the children without ADHD consisted of 27 (44.26%) boys and 33 (54.09%) girls. The mean values of the PR during sessions two and three were found to be statistically highly significant between the children with and without ADHD for TSD and audiovisual aids. In both groups, the mean SpOConclusionThe findings of the study demonstrated that behavior management techniques were found to be effective at reducing anxiety in ADHD children than in children without ADHD. Our study further suggests that scheduling dental appointments into a series of short visits could enhance the effectiveness of the therapy and better cooperation of the children.  Attention-deficit hyperactivity disorder (ADHD) is characterized by impulsivity, hyperactivity, and inattention. ADHD is the most widespread neurobehavioral problem in children and one of the most common chronic illnesses affecting school-age children. It also affects every element of a child's life, including behavior, academic performance, and interpersonal connections with peers and family . A thoroChildren with ADHD are more prone to have severe anxiety before receiving dental care . The DMFThe purpose of the present study was to evaluate and compare the management of dental procedures in children with and without ADHD employing various behavior modification techniques.The study protocol was approved by the Institutional Ethics Committee of Yenepoya University with IRB number YUEC/140/3/12/12. Participants were chosen using a consecutive sampling technique from a clinical sample of children aged 7 to 15 years who had been sequentially sent to an outpatient list of a clinic for child and adolescent psychiatry. The estimation of the sample size was performed using the formula:n = [DE*Np(1-p)]/ [(d2/Z21-α/2*(N-1)+p*(1-p)] where DE is the design effect assumed to be one, N is the finite population size, p represents the percentage frequency of the factor under study accounted as 7±5% based on a recent study report, and d is the marginal error (5%). The estimated minimum sample size was 101. After accounting for the potential dropouts, the final sample size of the study was increased to 121.The study was carried out between May 3, 2021, and April 2, 2022 at Mangalore, using a control group of children from a government high school, who had not been diagnosed with ADHD or any other psychological issues according to the DSM-V criteria  . WrittenInclusion criteria for the study groupChildren between 7 and 15 years old of both genders identified as having ADHD of DSM-V diagnostic criteria (diagnosis confirmation given by two independent psychiatrists on a standardized and structured interview) willing to provide consent either from parents or legal guardians were included in the study group.Inclusion criteria for the control groupChildren of both genders between the ages of 7 and 15 years without genetic or relevant mental illnesses willing to provide consent either from parents or legal guardians were included in the control group.Exclusion criteriaChildren with disorders of the central nervous system (CNS) such as epilepsy, serious injuries, and CNS infections co-existing with schizophrenia, bipolar affective disorder, any serious somatic disorders, chronic somatic diseases, persistent pharmacotherapy, and hormonotherapy were excluded. Children whose parents or local guardians were not willing were also excluded.Study groups2) using a pulse oximeter to evaluate the anxiety of the patient. During the second session, oral prophylaxis was performed, and from the previous visit, the cooperative attitude of the child was analyzed. The third session consisted of a restorative procedure which included a sealant placement. After each session, the child was given a stuffed toy or a stress-relieving smiley ball as a present for being cooperative during procedures and for following the instructions. The study was conducted to analyze the management of children with and without ADHD during a dental procedure by the tell-show-do (TSD) method, audiovisual distraction, and pharmacological management by examining the PR and SpO2.The study consisted of 121 children with 60 children diagnosed with ADHD and 60 healthy children who have neither psychiatric diagnosis nor systemic illness. After psychological assessment, the children were referred to the dental college. There were three sessions of dental procedure, each scheduled a week apart. The first session consisted of dental examination and monitoring the pulse rate (PR) and saturation of oxygen . Another type of management was the pharmacological behavior management. The dentist should be vigilant about the use of sedative drugs as these ADHD children on stimulant drugs may antagonize the sedative effect [Next was the audiovisual distraction, performed by showing the child’s favorite cartoons or animated videos on laptops using earphones. The videos included were a set of famous cartoons that are popular among their age groups. The behavior change was analyzed and recorded. The anxiety level was monitored based on the PR and SpOe effect ,18. Befoe effect .Statistical analysis2 between the two groups. p< 0.05 value was considered statistically significant. The effectiveness of behavior management techniques was also compared by utilizing the difference in the mean score of PR and SpO2 from session one to session three.The results were statistically analyzed by using IBM SPSS Statistics for Windows, Version 22  software. The Shapiro-Wilks test was used to evaluate the normality of the distributions of parameters observed. The Z-test was applied for comparing the PR and SpOThe study sample comprised 121 children, out of which 60 (49.58%) children comprising 39 boys (65%) and 21 girls (35%) were with ADHD. On the other hand, 60 (50.41%) children were without ADHD encompassing 27 boys (45.90%) and 33 girls (54.09%). Mean values of the parameters obtained from the three sessions were examined and compared using the Z-test. Table 2 values were also found to be statistically highly significant in both the groups from sessions one through three (p<0.01). Table While the mean values of the PR during dental examination of session one were found to be insignificant between the groups (p>0.05), those of the PR during sessions two and three were found to be statistically highly significant between the children with and without ADHD (p<0.01). The mean SpO2 values from sessions one through three were found to be statistically highly significant (p<0.01). Table The difference in the PR between the two groups during session one was found to be statistically insignificant. Children with and without ADHD were found to have statistically highly significant PR values for sessions two and three indicating a difference in the anxiety level particularly in children with ADHD. The normal child without ADHD did not show an effective change in the PR as they were more on verbal control than the other group. In both the groups, the mean SpO2 scores were observed across the three sessions between the groups (p<0.01). The Z-test was used to compare the differences in mean values of all parameters between sessions utilizing various techniques, such as TSD, audiovisual aids, and pharmacological management  sedation. It makes sense to assume that a stimulant and sedative taken together would have a negative impact on one another. In a study conducted by Kerins et al., approximately 76% of dental professionals advised their patients to take the regular dose of ADHD medication before the consultation . Success2 with the decrease of heart rate, and the children were found to be more attentive. Another similar study by Marshall et al. explained that the ADHD children who were given Midazolam for oral sedation showed little advantage [The outcome of a sedation appointment may also depend on the level of invasiveness of the planned dental procedure. The depth of sedation will be influenced by the pharmacologic differences between medication classes, but it is also important to consider the patient's inherent physiology. In our study, it was found that there is a slight change in SpOdvantage . The chaIt is advisable to give appointments in the morning so that the ADHD children will be more attentive and the effectiveness of medicine will be high, as it gets late its rebound effect may cause odd behavior . The appThe dental surgeon and the pedodontists in particular should be trained to be at the frontline for the successful management of children with ADHD using appropriate behavior management approaches, rendering quick treatment with recurrent follow-up and for competent referrals to the pediatrician and neurologists if needed for the general wellbeing of the patient.Various behavior management techniques have been used. They all have some advantages and disadvantages and hence have to be utilized based on the patient's psychology. The findings of the study demonstrated that TSD, audiovisual aids, and pharmacological management were found to be effective at reducing anxiety in ADHD children than in children without ADHD.


Attention-deficit/hyperactivity disorder (ADHD) is a prevalent, persistent, and costly mental health condition. The internet is an increasingly popular source for information related to ADHD. With a nationally representative sample (2018 NSCH), we aimed to separate individual- and state-level effects to examine inequities in ADHD diagnoses. We extracted state-level relative search volumes using “ADHD,” “ADHD treatment,” “ADHD medication,” and “ADHD therapy” from Google Trends, and sociodemographic and clinical variables from the 2018 National Survey of Children’s Health . We examined state variation in ADHD-related information-seeking and applied multilevel modeling to examine associations among individual-level race/ethnicity, state-level information-seeking patterns, and ADHD diagnoses. Online information seeking related to ADHD varies by state and search term. Individual-level racial/ethnic background and state-level information-seeking patterns were associated with ADHD diagnoses; however, their cross-level interaction was not significant. This study adds to the strong body of evidence documenting geographical variation and diagnostic disparity in mental health and the growing literature on the impact of the digital divide on population health, indicating an urgent need for addressing inequities in mental health care. Increasing public interest in and access to empirically supported online information may increase access to care, especially among people of color. Attention-deficit/hyperactivity disorder (ADHD) is a persistent, costly, and prevalent neurodevelopmental disorder, more commonly diagnosed in males Barkley, . ADHD isDocumenting the true prevalence of ADHD remains challenging in light of problems of overdiagnosis  and underdiagnosis . State-level diagnostic prevalence of ADHD varies largely  vary and relate to individual-level ADHD diagnoses among youth. Specifically, the impact of income, insurance/benefits, and employment on access to mental health information seeking and service utilization may vary corresponding to variation in federal and states’ legislative landscape  and multilevel analyses to examine geographical variation specific to online information seeking related to ADHD. Specifically, we were interested in the degree to which population-level findings across states were related to individual-level diagnostic and sociodemographic information. We applied multilevel modeling to examine 3 hypotheses: (1) youth of color will be less likely to receive ADHD diagnoses than White youth (reference group), (2) state-level online information seeking (state variation of Google search interest) related to ADHD will be associated with ADHD diagnoses, and (3) there will be a cross-level interaction between individual-level race/ethnicity and state-level online information-seeking patterns, such that youth of color will be even less likely to receive an ADHD diagnosis when residing in a state with less relative search interest in ADHD.Data from public repositories do not require approval from Institutional Review Board or collection of informed consent. We extracted, integrated, and analyzed data in R 4.0.3 . State-level RSVs were standardized and scaled, after filtering duplicate searches (repeated searches from the same person over a short time). They represent the scaled proportion of searches containing a specified (set of) search term(s); in this study, state-level RSVs represent the number of searches for “ADHD” divided by the number of all searches within each state and scaled in relevance to all other states. RSVs account for differences in internet access and population size, ranging from 0 (very low search interest within the state) to 100 ; the state with the highest search interest out of all states has an RSV = 100.Our measures of information seeking included state-level relative search volumes (RSVs) for 50 states and Washington DC  for “ADHD,” “ADHD treatment,” “ADHD medication,” and “ADHD therapy” in 2018 from Google Trends  by these three conditions in the current sample are presented in Table https://www.childhealthdata.org/learn-about-the-nsch/). The number of respondents averaged 513 per US state and Washington DC, ranging from 396 in DC to 672 in Arkansas. Individual responses (level 1) were nested in states of residency .We extracted data from the 2018 National Survey of Children’s Health . The study did not require Institutional Review Board approval or collection of informed consent, as data are publicly available. The corresponding author completed the data use agreement from the Data Resource Center and CAHMI. A national representative sample of caregivers of youth aged 0 to 17 years completed questionnaires via mailed packets and online surveys to provide demographic and health information; one child was randomly selected in families with multiple children. Details of the survey instruments are available at Applying hierarchical multilevel modeling (MLM) regression models using the “glmer” function in the “lme4” package in R  an unscaled weighted model: using the “FWC” variable from the dataset; (2) a scaled weighted model using weights adjusted by a factor that represents the proportion of cluster size divided by the sum of sampling weights within each cluster; (3) a scaled weighted model using weights adjusted by the sum of sample weights within each cluster divided by the sum of squared sample weights within each cluster. Weights were scaled using the “scale_weights” function in the sjstats (version 0.18.0) package in R  and control variables . Our second model included all variables in Model 1 and online search interest (Google RSV) as the level-2 predictor. Our third model added cross-level interactions between race/ethnicity and state-level search interest to the second model. For model comparison, we computed Akaike information criterion  are commonly used in the medical field as a metric to reflect geographical variation in public interest and information-seeking behaviors online . Caregivers were asked, “Has a doctor or other health care provider EVER told you that this child has Attention Deficit Disorder or Attention Deficit/Hyperactivity Disorder, that is, ADD or ADHD?” Caregivers who responded yes to this initial question were asked, “Does this child CURRENTLY have the condition?” Given all level-1 and level-2 predictors were extracted for 2018, we focused on current diagnosis in 2018; children without current ADHD diagnoses included those who had never been diagnosed with ADHD  and those who were ever diagnosed but do not currently have a diagnosis of ADHD (n = 233).The dependent variable was State variation in searches for “ADHD” is illustrated in Fig. AIC=16,322, BIC=16,543) fit data significantly better than Model 1 , X2 = 15.58, df = 1, p<.001). Model 3, which added the cross-level interaction to Model 2, did not outperform Model 2, AIC=16,331, BIC=16,617, X2 = 7.22, df = 8, p=.513. Thus, Model 2  was selected as the final model. Parameters of all three models are presented in Table We computed intraclass correlation coefficients Bliese, . Model centclass1pt{minimaentclass1pt{minimaentclass1pt{minimaentclass1pt{minimab = 0.40, OR = 1.49, SE = 0.07, z = 5.54, p < .001; 100–199% FPL: b = 0.17, OR = 1.19, SE = 0.07, z = 2.63, p = .008) were more likely to have an ADHD diagnosis; such results were not significant in scaled weighted analyses  was, mostly, associated with higher likelihood of ADHD diagnosis for children; however, this association was not reported for families with “Less than high school” education at level 1. Instead, youth were more likely to receive an ADHD diagnosis in states where there was a higher percentage of households with less than high school education (level-2 specific effect), b = 6.95, SE = 2.63, z = 2.64, p = .008; and this association was not significant in scaled weighted analyses , Latinx/Hispanic , and Asian  youth were less likely to have a current ADHD diagnosis, compared to White youth, after controlling for poverty status, highest education in household, child’s sex, and child’s age. Compared to White youth (most likely to receive an ADHD diagnosis), Black youth were 22% less likely, Latinx youth were 32% less likely, and Asian youth were 73% less likely to receive an ADHD diagnosis.As shown in Table b = 0.01, OR = 1.01, SE = 0.00, z = 3.97, p < .001  reveals that higher levels of state-level RSV were associated with a higher likelihood of ADHD diagnoses, Contrary to our predictions, there was no significant interaction between individual-level (level-1) race/ethnicity and state-level level-2) search interest in Model 3  and nationally representative sample (2018 NSCH), we separated individual- and state-level effects to examine inequities in ADHD diagnoses. Specifically, we applied multilevel modeling to examine the extent to which inverted-U curve.Findings may be traced to community outreach efforts in areas with major healthcare systems, such as the Oregon Health and Science University Center for ADHD (opened in 2019) that sparked media coverage and, perhaps, searches for ADHD. Except for Oregon, lower interest in ADHD-related information reflected lower prevalence of ADHD diagnoses in the West. States with more youth with ADHD diagnoses  displayed relatively high search interest in ADHD and ADHD treatment. Specific to medication, search interest was high in Maine and low in Nevada, corresponding to their difference in state averages of methylphenidate consumption in 2016 , supporting hypothesis 2. Note the relatively low OR = 1.01  may result from (1) the small sample size at level 2 (n = 50 US and Washington DC) and (2) relatively low variability of data at level 2 (ICC = 0.01). Despite the small changes of OR, online search interest explained almost all of the variance at level 2. Also, the predicted odds ratios corresponding to RSV (range = 0 to 100) ranged 0.025 to 0.125 (odds ratios), holding all other model predictors constant at their means Fig.  and mostrelative interest in “ADHD” compared to all other states rather than the absolute search volumes of identifiable individuals. Thus, we were unable to examine temporal relations between information-seeking behaviors and sociocultural beliefs at the individual level, which may affect seeking and/or reporting an ADHD diagnosis.There was no interaction between individual-level racial/ethnic background and state-level information-seeking patterns, contrary to hypothesis 3, which may be due to the lack of variance at level 2 (ICC = 0.01). Specifically, the state-level online information-seeking variation did not affect the odds that youth of color would have a current ADHD diagnosis over and above other included characteristics. The variable (Google Trends RSVs) measuring information-seeking patterns is not available at the individual level  the Covid-19 global pandemic. States and school districts responded differently to the Covid-19 outbreak, regarding structure and support for virtual learning, and timeline of mandating school closures and reopening; thus, geographic variation in access to mental health information and academic support may have increased  and their association with specific state-level policies .Second, despite the significant associations reported at individual and state levels, we note the nature of Third, we did not include information about cultural identities beyond race and ethnicity – such as nation of origin, immigration status, enculturation and language preference – due to concerns of collinearity. However, it is important to consider intersectionality Hays, , and espempirically supported information and care. Increasingly, studies have demonstrated that quality of health information online varies considerably , but not necessarily high-quality, information on the internet. Additionally, our analyses focused on current ADHD diagnoses (dependent variable); the NSCH also includes information about ADHD medication use and receipt of psychosocial treatment for ADHD, which can be analyzed to examine the multilevel relations among individual demographic characteristics, state-level information seeking, and service utilization.Fourth, we are not able to draw conclusions specific to seeking https://www.statista.com/statistics/697310/pediatricians-minutes-with-patients-us/). More research is needed to understand whether and how online information seeking helps or hinders science-informed decision-making processes, particularly for marginalized populations.Fifth, the NSCH did not ask caregivers to report the circumstances of their child’s ADHD diagnosis, such as who gave the diagnosis  or on what information it was based . Gold-standard research assessment recommendations for ADHD . Carle  utilizedscience-informed care. There is potential to leverage public search engine data to enhance access to empirically supported mental health information and care.Persistent racial/ethnic inequities warrant systematic changes in policy and clinical care that can attend to the needs of underserved communities. The digital divide adds complexity to persistent racial/ethnic and socioeconomic inequities in ADHD diagnosis; we found information-seeking patterns varied across states and by search terms. Equitable online information may increase access to mental health diagnoses and in turn, resources and services. Future research is needed for understanding individual pathways and the extent to which online information inspires seeking


We studied β diversity of grasses in a subtropical grassland over 60 years in South Africa. We examined the effects of burning and mowing on 132 large plots. We sought to determine the effects of burning and mowing, and mowing frequency, on the replacement of species and the species richness. We conducted the study at Ukulinga, research farm of the University of KwaZulu‐Natal, Pietermaritzburg, South Africa  from 1950–2010. Plots were burned annually, biennially, triennially, and a control (unburned). Plots were mowed in spring, late summer, spring plus late summer, and a control (unmowed). We calculated β diversity, with a focus on replacement and richness differences. We also used distance‐based redundancy analyses to examine the relative effects of replacement and richness differences on mowing and burning. We used beta regressions to test for the effect of soil depth and its interactions with mowing and burning. There was no significant change in grass beta diversity until 1995. Thereafter, there were changes in β diversity that demonstrated the primary effects of summer mowing frequency. There was no significant effect of richness differences but a strong effect of replacement post‐1995. There was a significant interaction between mowing frequency and soil depth in one of the analyses. Changes in grassland composition took a long time to manifest themselves and were unapparent prior to 1988. However, there was a change in sampling strategy prior to 1988, from point hits to nearest plants, that may also have influenced the rates of changes in replacement and richness differences. Using β‐diversity indices, we found that mowing was more important than burning that burning frequency was unimportant, and there was a significant interaction effect between mowing and soil depth in one of the analyses. We studied β diversity of grasses in a subtropical grassland over 60 years with different burning and mowing frequencies. Changes in grassland composition took a long time to manifest themselves. We found that summer mowing was the primary driver and that there was a significant interaction effect between mowing and soil depth. Trees and Hyparrhenia hirta (L.) Stapf, Aristida junciformis Trin. & Rupr., Themeda triandra Forssk. and other grass species. At a smaller spatial scale (as on the escarpment of Ukulinga), the vegetation is tall grassveld  Roem. & Schult. also being common  in a point‐intercept frame , about 80% of which falls during summer as convective storms (October–April). Mean monthly maximum and minimum temperatures range from 26.4°C in February to 8.8°C in July, respectively. Winters are mild with a mean maximum of 13.2°C in July (43‐year mean), with occasional frost. There has been no grazing on the experimental sites for >70 years. The experiment was situated on top of a small escarpment, ranging in altitude between 838 and 847 m. Soils are fine‐textured and derived from shales and were classified as Mispah  and Westleigh  and the other two were quantitative (Ružička and percentage difference). The Jaccard index Jaccard, , 1912 tage Jost, . The Ružge Jost,  and percge Jost,  are quange Jost, . Followige Jost, , we usedge Jost,  correctige Jost, . We usedge Jost,  in R Stuge Jost,  for all We primarily used a two‐dimensional (2D) simplex diagram  and replacement (LCBDrepl) consider the effects of each individual sample to richness and replacement gradients  is beta distributed, varying between 0 and 1 , regardless of whether the plots were assessed by Jaccard, Sørensen, Ružička, or percentage difference. However, there was a slight change among a few plots in 1988, followed by a substantial change in many plots in 1995 and 2010 Figure . The majp values. In 1988, 1995, and 2010, there were up to 17 species that had significantly higher values than the mean contribution of species to β diversity , Diheteropogon amplectens, Eragrostis curvula, E. racemosa, Heteropogon contortus, Themeda triandra, and Tristachya leucothrix , based on Holm's correction of 3.1z = 8.287, p < .001). The maximum likelihood pseudo‐R2 for the Jaccard index of β diversity was .01346. However, there was a significant relationship between the Bray–Curtis (percentage differences) index and the explanatory variables for the main effects  (Table R2 was .1408 (p < .001). The relationship between the Bray–Curtis (quantitative) index and the explanatory variables for the main effects and the mowing*burning frequency interaction had a pseudo‐R2 value of .144 (p < .001). There was no significant difference between the main effects only and the main + interaction effects . The only significant explanatory variable was mowing (Table There was no significant relationship between the Jaccard (presence–absence) index of β diversity and the three explanatory variables, with the exception of the intercept .When we included the effect of soil depth in each plot, we found that there was a significant interaction effect between mow frequency and soil depth, but there were no other significant main or interaction effects Table . Signifi3.2F = 0.255, p = .90, error df = 128, n = 999 permutations). However, we found that there was a significant effect of replacement .We ran a multivariate distance‐based redundancy analysis for 2010. There was no significant effect of richness difference . Based on the dbRDA1 biplot score for constraining variables, most of the variance was explained by mowing frequency (dbRDA1 = 0.8664), followed by burn time (0.4064), and burn frequency (−0.2936). On the 2nd dbRDA axis, burn time explained most of the variance (−0.9021), followed by burn frequency (−0.4538), and then by mowing frequency (0.3016) . The direction of the effect of Soil Depth was very close to that of Burn Frequency and opposite that of Mowing.The proportion of the constrained variance (“partitioning of squared unknown distance”) was 20.25%, and the unconstrained variance was 79.75% for replacement. The first dbRDA axis for replacement explained 87.78% of the variance , followed by 8.82% of the variance for dbRDA2 . There was a significantly adjusted 4Harpochloa falx was common at the beginning of this experiment in 1950 but disappeared by 1955. Eragrostis curvula appeared in 1955 (but not prior to that) and increased steadily throughout, reaching 8% in the BME in 2010. Cymbopogon nardus was absent until 1968 and increased in relative abundance to a value of 8% by 2010. Indeed, C. nardus became the dominant species in triennial burns , Jacaranda mimosifolia , Melia azedarach , Lantana camara (American tropics), Tagetes minuta , Solanum mauritianum (South America), Bidens pilosa , as well as some indigenous encroaching trees (Acacia (Vachellia) nilotica, Acacia (Vachellia) karroo, Lippia javanica, and Dichrostachys cinerea). Morris and Tainton , despite the fact that subtropical ecosystems might respond more rapidly than temperate ecosystems . Diheteropogon amplectens, Eragrostis curvula, E. racemosa, and Heteropogon contortus also changed in the last three periods. Cymbopogon nardus responded most strongly to triennial burns in 2010 but not prior to that , this resulted in altered grass composition and diversity. For example, tall grasses, such as 3 Figure  and unde3 Figure ; these l3 Figure . In our 3 Figure , but our3 Figure  found th3 Figure  found th3 Figure . Similar3 Figure  found th3 Figure . We foun3 Figure , but the3 Figure . Dominan3 Figure  and freq3 Figure . McGrana3 Figure  found inThemeda triandra at Ukulinga by 14% when compared with no clipping in the following summer. Coughenour et al. (The predominant effect of summer mowing frequency (particularly zero mow versus one or two mows) is inconsistent with several previous studies, including a meta‐analysis, that indicated that mown sites supported a greater number of plant species than sites that were either grazed, or grazed and mown  than on promoting environmental heterogeneity per se. In our study, soil depth was not unduly convincing as an important variable controlling β diversity, and only had an effect as an interaction with mowing, although we must concede the topography at Ukulinga was slight.The environmental heterogeneity hypothesis (EHH) could also partially explain the effects of soil depth, with variance in soil depth being one of the parameters considered ; data curation ; formal analysis ; funding acquisition (lead); investigation (lead); methodology (lead); project administration (lead); resources (lead); software (lead); supervision ; validation ; visualization (lead); writing – original draft (lead); writing – review and editing (supporting). Kevin Kirkman: Conceptualization ; data curation ; formal analysis (supporting); funding acquisition (supporting); investigation (supporting); methodology (supporting); project administration (supporting). Craig Morris: Conceptualization (supporting); data curation ; formal analysis (supporting); funding acquisition (supporting); investigation (supporting); methodology (supporting); project administration (supporting); resources (supporting); software (supporting); supervision (supporting); validation (supporting); visualization (supporting); writing – original draft (supporting); writing – review and editing .Table S1.Click here for additional data file.


ADHD commonly co-occurs with ASD without ID in young people. It has been difficult to obtain accurate prevalence estimates of ADHD in this population, as a dual-diagnosis was not permitted until DSM-V. We systematically reviewed the literature on the prevalence of ADHD symptoms in young people with ASD without ID.9,050 articles were identified through six databases. Articles were reviewed against inclusion and exclusion criteria and 23 studies were included.ADHD symptom prevalence varied from 2.6% to 95.5%. We discuss these findings according to the ADHD assessment measure, informant, diagnostic criteria, risk of bias rating and recruitment pool.ADHD symptoms are common in young people with ASD without ID, but there is substantial variance in study reporting. Future studies should recruit participants from community sources, provide information on key sociodemographic sample characteristics and assess ADHD with standardized diagnostic criteria, using both parent/carer and teacher report. Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder with a global prevalence estimate of 1% . ASD is The Diagnostic and Statistical Manual of Mental Disorders only allowed for a dual-diagnosis in its fifth edition . Prior tDiagnostic constraints have limited the evidence on the impact of co-occurring ADHD and ASD, where studies employing DSM-IV criteria have often excluded individuals with co-occurring psychiatric conditions . It has Neuropsychological difficulties shared by ASD and ADHD have been reported as similar due to comparable genetic loads and endophenotypes, despite a lack of overlap in the diagnostic criteria of both disorders . RommelsLiterature and systematic review studies have attempted to estimate the prevalence of co-occurring ADHD and ASD, but are limited by the inclusion of adults and those with ID. To date there have been no reviews providing estimates of ADHD prevalence in young people with ASD without ID specifically. It is important to separate out this group when estimating ADHD prevalence, because evidence suggests low IQ may be a potential confound when assessing ADHD prevalence in young people with ASD. This review examines the prevalence of ADHD symptoms in autistic children and adolescents without ID. Given that a dual-diagnosis of ADHD and ASD was not permitted until DSM-V, we include studies which focused on the prevalence of ADHD symptoms, alongside those where participants meet criteria for a clinical diagnosis of ADHD.Our review addresses the limitations of previous studies estimating the prevalence of ADHD in ASD in a number of ways. We are the first review to provide estimates of the prevalence of ADHD in young people with ASD without ID specifically. Second, the review compares estimates of ADHD prevalence provided by (i) parents or caregivers (ii) teachers, (iii) both (mixed). This breakdown of prevalence by type of informant was not included in the reviews conducted by Specifically, this review aimed to:Identify the prevalence of ADHD symptoms, as well as a clinical diagnosis of ADHD, in young people with ASD without ID aged 5 to 19 years.Appraise the methodological quality of included studies, including the measures used to assess ADHD symptoms in this population.Make recommendations for future studies looking to assess the prevalence of ADHD in this population.This review was conducted and written in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyzes (PRISMA) Checklist . The proThe search strategy was defined by identifying four key terms from the research question: “autism,” “ADHD” “prevalence” and “child/adolescents.” Common synonyms and Medical subject headings (MESH) for these terms were extracted from previous reviews on the prevalence of ADHD  and ASD The four search lines below were combined with the Boolean operator “AND”:autis* OR asperger* OR “ASD” OR “ASC” OR “high functioning ” OR “HFA” OR “pervasive developmental disorder*” OR “PDD”“Attention Deficit Hyperactivity Disorder” OR “ADHD” OR “attention deficit disorder” OR “ADD” OR “hyperkinetic syndrome” OR “hyperkinetic disorder” OR “attention deficit” OR “attention disorder” OR hyperactiv* OR inattent* OR impulsiv*“prevalence” OR “epidemiology” OR “rate” OR “frequency”child* OR adoles* OR youth* OR minor* OR girl* OR boy* OR teen* OR pediatr* OR paediatr* OR “young person”These terms were searched in six databases: Cinahl, EMBASE, ERIC, MEDLINE, PsychINFO and Web of Science, and limited to studies conducted after 1992, when the WHO defined Asperger’s Syndrome . The seaTitles and abstracts of articles obtained from the database search were screened against the inclusion and exclusion criteria , with 20% being independently reviewed by a second reviewer (C.E.). Agreement was 96%. Articles which met the inclusion criteria at the screening stage were then reviewed in full  and 20% were independently reviewed (C.E.). Agreement was 91%. All discrepancies at each stage were resolved until 100% consensus was met. A senior reviewer was consulted if final decisions remained unclear (S.R.). In order to identify additional relevant articles not captured by the database search, backward citation searching was performed using the reference lists of articles which met the inclusion criteria at full-text review. Full details of the selection process are provided in All data were independently extracted by two reviewers (K.R. and C.E.). Disagreements were resolved until 100% consensus was made. Missing information was recorded as not reported (NR). Where available, data were extracted for children with ASD without ID unless stated otherwise. The data extracted was: (1) country of study, (2) study type  (3) number of participants with ASD without ID, (4) recruitment pool, (5) mean age, standard deviation (SD) and range, (6) percentage of male participants, (7) ethnicity, (8) socio-economic status, (9) medication status, (10) co-occurring conditions, (11) diagnostic criteria utilized for ASD assessment, (12) who provided ASD diagnosis, (13) specific ASD diagnosis given, (14) additional ASD research diagnosis measures, (15) when the participant's IQ was assessed, (16) full scale intelligence quotient (FSIQ) mean, SD and range, (17) measure used to assess FSIQ, (18) diagnostic criteria for ADHD diagnosis, (19) who provided ADHD diagnosis, (20) tool used to assess ADHD symptoms, (21) who provided information on ADHD diagnosis, (22) psychometric properties reported in the ADHD tool for ASD without ID sample, and (23) the prevalence of ADHD symptoms in the ASD without ID group. The prevalence rate was extracted by assessing the number of children with ASD who displayed co-occurring ADHD symptoms, divided by the total number of children with ASD, expressed as a percentage.Supplemental Materials for the quality appraisal tool used in this review, with details of adaptations made.The quality of included studies was independently assessed by two reviewers (K.R. & C.E.), according to validated frameworks which addressed questions on prevalence , and theThe included studies differed in sample size, age range and diagnostic criteria when classifying ADHD symptoms. Studies also used very different assessment tools to measure ADHD. These ranged from questionnaires designed to screen for ADHD specifically  to more general psychiatric interview tools , to unspecified clinical interviews and DSM checklists, reviewed by psychiatrists. In addition, none of the included studies were rated as low risk of bias across all quality assessment scales see  and the Firstly, 9,050 articles were identified from searching all databases. A total of 3,075 duplicates were removed, leaving 5,975 articles. At title and abstract screening, 5,549 articles were removed. The full texts of 426 articles were read and 21 met the inclusion criteria. An additional two articles were identified from background citation searching, yielding a total of 23 articles included in this review.Characteristics of included studies are displayed in The results of the risk of bias assessment are displayed in In total, 16 studies administered interviews. Of these, 10 used the Kiddie Schedule for Affective Disorders and Schizophrenia, Present and Lifetime  includiA total of 11 studies administered questionnaires. Seven assessed ADHD symptoms using the CBCL ; these wNo study reported on the psychometric properties of measures used to assess ADHD symptoms in young people with ASD without intellectual disability.The prevalence of ADHD symptoms ranged from 2.6% to 95.5% . PrevaleThe prevalence of ADHD symptoms in studies using interviews ranged from 26.7% to 95.5% . StudiesEleven studies provided prevalence estimates based on separate reports from parent or caregivers . The preTeacher reports were explicitly mentioned by four studies. Of the 11 studies applying DSM-IV criteria, prevalence ranged from 26.7% tο 95.5% . DSM-IV-For studies rated as low risk of bias, prevalence estimates ranged from 26.7% to 95.5% , althougFourteen studies recruited from a clinical sample, with prevalence ranging from 2.6% to 75% . CommuniThis review examined the prevalence of ADHD symptoms in children and adolescents aged 5 to 19 years with ASD without ID. Prevalence estimates ranged from 2.6% to 95.5% and varied according to salient study characteristics, including the assessment tool, the informant, the risk of bias rating, the study recruitment pool, and the diagnostic criteria used. Even when considering those studies rated as low risk of bias , prevalence estimates still varied widely, from 26.7% to 95.5%. Across studies, there was a dearth of consistent reporting of variables which may feasibly affect prevalence estimates such as SES and ethnicity. It is clear however that the co-occurrence of ADHD is common in autistic young people without ID.Prevalence estimates were generally higher in studies administering interviews. Whilst some studies administering questionnaires reported some of the highest prevalence estimates for example, 70.6%  and 67.5The importance of using multiple informants has been emphasized when assessing ADHD symptoms  and is pThe majority of studies rated as low risk of bias reported prevalence estimates of 50% and above. The majority of medium risk studies reported prevalence estimates of less than 50%. In this review, ADHD assessment was considered to be gold-standard if a clinical diagnosis was made using standardized diagnostic criteria , using reports from both parents and teachers. The detail of how ADHD was assessed varied across studies. It is therefore possible that some studies were given a higher risk of bias rating than if detailed information about ADHD assessment been provided. Future studies should provide clear details including the ADHD assessment measure, the informant and whether a diagnosis was given, the criteria used and who gave the diagnosis .The majority of studies recruited participants either exclusively, or partially, from clinical sources. Referral patterns into services can introduce bias when using clinical samples to estimate prevalence . Research into the prevalence of mental health conditions in young people has shown that clinical samples are likely to be more impaired and have higher levels of co-occurrences than community samples . In addiSeveral confounding variables such as SES, ethnicity, geographic region, and gender should be considered when comparing prevalence rates of ADHD symptoms in young people with ASD without ID. All studies reported information regarding the age and gender of their sample, however ethnicity, SES, and geographic region were inconsistently reported. Country of study and ethnicity are particularly important, considering that clinical practice varies largely between cultures . Within This review has several limitations. Firstly, we made several adaptions to the risk of bias assessment tool; developed from the tools used in This is the first review to examine the prevalence of ADHD symptoms in children and adolescents with ASD without ID. This review shows that whilst the co-occurrence of ADHD symptoms in this population is common, prevalence estimates vary considerably. We highlight the heterogeneous nature of methodology across studies in this area, , the lack of clear reporting of salient characteristics such as SES and ethnicity, and the lack of data on psychometric properties of ADHD assessment tools when used with autistic young people without ID. To ensure more accurate prevalence estimates, future studies should endeavor to recruit large samples from community sources and to diagnose ADHD using standardized diagnostic criteria, using information from both parents and teachers. It is also important that key sociodemographic characteristics about the sample are accurately reported, as these may be important when considering the generalizability of prevalence estimates for ADHD in children and adolescents with ASD without ID.Click here for additional data file.Supplemental material, sj-docx-1-jad-10.1177_10870547231177466 for The Prevalence of Attention Deficit/Hyperactivity Disorder Symptoms in Children and Adolescents With Autism Spectrum Disorder Without Intellectual Disability: A Systematic Review by Christopher Eaton, Kayley Roarty, Nimisha Doval, Smitarani Shetty, Karen Goodall and Sinead M. Rhodes in Journal of Attention Disorders