The ASRS-5 was assessed positively in terms of feasibility, acceptability, and credibility by interviewed general practitioners. Potential problems were raised for “treatment options,” “stigmatization,” and “knowledge gaps.” In conclusion, the German version of the ASRS-5 offers a promising tool to improve adult ADHD patients’ diagnosis and healthcare.Adult attention-deficit/hyperactivity disorder (ADHD) is common, but often undiagnosed. A valid and time-efficient screening tool for primary care is needed. Objective of this study is to evaluate the German version of the Adult ADHD Self-Report Scale for DSM-5 (ASRS-5) and its feasibility, acceptability, and reliability as a screening tool for adult ADHD in primary care. A multi-centered prospective, diagnostic study was performed. We recruited 262 patients in primary care practices and at an ADHD Outpatient Service of a department of psychiatry in Germany. Patients from 18 to 65 years with suspected or diagnosed ADHD were included by medical doctors, as well as non-ADHD patients as “negative controls.” Participants filled in the ASRS-5 and a sociodemographic questionnaire. The Integrated Diagnosis of Adult ADHD, revised version (IDA-R) performed by trained interviewers was used for validation. Feasibility, acceptability, and credibility in primary care practices were examined through a semi-structured interview. The German version of the ASRS-5 showed comparable psychometric properties to the English original version (sensitivity 95.6% and specificity 72.3%). For factor structure, a parallel analysis suggested one latent dimension. Performing confirmatory factor analysis, the best fit was achieved for a general factor with one correlated error. Internal consistency results in Raykovs Omega = 0.86 and Cronbach’s  Adult attention-deficit/hyperactivity disorder (ADHD) is common. In at least half of the children affected by ADHD, symptoms persist until adulthood , 2021. AThe World Health Organization (WHO) Adult ADHD Self-Report Screening Scale for DSM-5 (ASRS-5) is a six-item questionnaire . In contThe objective of this study is to evaluate the psychometric properties of the German version of the ASRS-5, its feasibility, acceptability, and credibility as a screening tool for adult ADHD in primary care.https://www.hcp.med.harvard.edu.Translating the English ASRS-5 into German was performed according to the WHO Composite International Diagnostic Interview (CIDI) translation guideline. The developer approved the final translation after receiving report of the requested information about the process  The German translation of the ASRS-5 shows similar psychometric properties  as the English original and therefore is a valid screening tool for adult ADHD; (2) The ASRS-5 is a feasible, accepted, and credible screening tool for adult ADHD in primary care and thus might be implemented well in everyday practice.α. To evaluate the feasibility, acceptability, and credibility of the ASRS-5 as a screening tool for adult ADHD in primary care, a semi-structured phone interview was conducted with the participating GPs.Therefore, we performed a multi-centered, prospective, diagnostic study, and we examined a convenience sample of 262 patients. Patients were recruited in GP practices in South and West Germany and at the ADHD Outpatient Service of the department of psychiatry and psychotherapy at the University of Bonn. Medical doctors did the eligibility check based on the file  and included the patients. Patients filled in the ASRS-5 in paper–pencil form. To check external validity, trained interviewers validated the diagnosis by phone or in person, using the revised version of the Integrated Diagnosis of Adult ADHD (IDA-R) a semi-structured DSM-5 interview. For internal consistency, we determined Cronbach’s Patients aged 18–65 years with suspected or diagnosed ADHD  according to guidelines  or intakn = 1), non-DSM-5 symptoms of executive dysfunction (n = 2), and DSM-5 symptoms of hyperactivity and impulsivity (n = 3) with a five-point Likert scale (never/rarely/sometimes/often/very often). Patients are supposed to indicate the frequency of the queried behaviors, feelings and thoughts during the last 6 months. For scoring the ASRS-5, the developers proposed an evaluation scheme with a cutoff of ≥14 for a positive screening result. In this scheme, answer categories for questions were weighted differently. A sum score is built. If this is ≥14, the ASRS-5 is positive. The English original version of the ASRS-5 was validated within a mixed cohort of 637 participants where it showed good psychometric properties . For examination of possible influences on implementation, we chose a Determinant Framework. Here, we used the Consolidated Framework for Implementation Research CFIR; . The CFIα were computed in R. Exploratory Maximum Likelihood (ML) factor analyses and ML parallel analysis  is performed with the null hypothesis that the sensitivity is exactly 0.9 (based on the English version).The true sensitivity of the German version is equal to 0.8 .The number of participants with a positive diagnosis in IDA-R is 100.Under these assumptions, the power of this hypothesis test is approx. 0.8. Calculating a confidence interval for the true sensitivity of the German version, the expected length of the confidence interval would be approx. 0.15.The Ethics Committee of the University Hospital, LMU Munich (No. 20-0882) approved the study. Informed written consent was obtained from all individuals who volunteered to participate in the study. General practitioners received 20 € for each included patient.n = 16, Ulm n = 7). Each general practice contributed 1–28 patients to the study. Moreover, 91 patients were recruited at the ADHD Outpatients Service in Bonn. The patients’ mean age was 39  years. Around 118 (45%) patients were male, 143 (55%) were female, one was non-binary. Educational level was high with 58.8% having at least A levels. A total of 96 (36%) patients indicated previous mental disorder, 55 (21%) declared the intake of psychotropic medication during the last 4 weeks. For complete patient data, see Complete data from 262 patients were obtained for final analysis. Patients were recruited in 23 general practices  years. ASRS-5 positive results correlated significantly with previous mental disorder, previous psychotherapy, intake of psychotropic medication during the last 4 weeks (Phi/Cramer-V test p < 0.01), as well as with ADHD severity (Chi2 test p < 0.01) and age (Eta coefficient p < 0.01). There was no significant correlation with sex, and educational level (Phi/Cramer-V test). A total of 113 participants had a positive validation (IDA-R). In this group, 52 (46%) were female and the mean age was 36  years. A positive IDA-R correlated significantly with the same parameters like a positive ASRS-5 . Here, again there was no significant correlation with sex and educational level (Phi/Cramer-V test).A total of 150 (57.3%) participants were screened positive using the ASRS-5 . Of these, 67 (44.7%) were female and the mean age was 36 (α (0.88). EzCutoff , psychometric properties were 95% (sensitivity) and 70.7% (specificity). For female respondents (n = 118), psychometric properties were 96.2% (sensitivity) and 74.2% (specificity). Male and female respondents did not differ significantly in age (t-test), educational level, previous mental illness, ADHD severity, and ADHD subtype (Mann–Whitney U test).The German version of the ASRS-5 showed comparable psychometric properties to the English original version. Sensitivity was very high , while specificity was a bit lower  of the ASRS-V1.1 was a bit higher.Around 11 general practitioners were interviewed for the evaluation of the feasibility, acceptability, and credibility of the ASRS-5 as a screening tool for adult ADHD in primary care. Overall, the feedback was very positive. Being short and comprehensible, the ASRS-5 demonstrated good feasibility. The majority indicated that they would use the screening tool in future and would discuss it with others, indicating high acceptability. Positive feedback, especially from ADHD patients lends credibility to the ASRS-5. Stigmatization, accessibility of further specialist care, and knowledge gaps for ADHD appeared as potential problems in the inductive content analysis.The objective of this study was to evaluate the psychometric properties of the German version of the ASRS-5, its feasibility, acceptability, and credibility as a screening tool for adult ADHD in primary care.Here, we examined a convenience sample of 262 patients, which were recruited in general practices and an ADHD Outpatients Service. Of these 150 were screened positive (ASRS-5) and 113 had a positive validation (IDA-R). Psychometric properties showed 95.6% sensitivity and 72.3% specificity. It was the first time the German version of the ASRS-5 was evaluated. Our study differed from others by investigating in the primary care setting with its particular conditions. Process evaluation revealed a positive feedback from general practitioners about the ASRS-5.n = 119), the others were a managed care (n = 218) and a clinical sample (n = 300). The overall psychometric properties were well . For the clinical sample with a much higher ADHD prevalence, the specificity was a bit lower (74%), while sensitivity (91.9%) being similar. Our results interestingly are comparable to those of the clinical sample. Sociodemographic data in the original study were only specified for respondents of the overall cohort who met the DSM-5 criteria for adult ADHD. The mean age was 33.1 years, which is similar to the IDA-R positive patients of our cohort (mean age 35.7 years). Both cohorts differ in gender proportion . Educational level and further clinical criteria were not indicated in the original study  or without bipolar disorder or borderline disorder (n = 236), and 285 adults without ADHD who were mainly healthy volunteers (n = 248). They measured lower sensitivity (84.3%) and a higher specificity (91.9%) for outpatients without comorbidities than we did for our cohort. Their cohort was similar to ours concerning sex , age (37.9 ± 14.7 vs. 39 ± 13.6 years), and intake of psychotropic medication (20.9 vs. 21%). While we did not see a significant correlation between educational level and positive ASRS-5/IDA-R, they report a lower educational level in ADHD patients. Their study moreover differentiates from ours by determining a new cutoff instead of using the one proposed by Baggio et al. translated the ASRS-5 to French. They investigated in a sample consisting of outpatients with ADHD, which they subdivided in patients with . Their sensitivity (75%) as well as specificity (65%) using the same evaluation scheme and cutoff as we did (cutoff  ≥ 14), were both way lower than in our study. This might be because of differences in the cohorts. Younger and male patients may differ in symptom manifestation. Somma et al. also performed factor structure analysis which in contrast to our analysis strongly supports a unidimensional structure of the ASRS-5 .Genç et al. examined a convenience sample consisting of 68 patients receiving an ADHD diagnosis after applying at psychiatry outpatient clinics and 68 control patients applying to outpatient clinics other than psychiatry and do not have previous ADHD diagnosis. They were using the Turkish version of the ASRS-5. ADHD patients in their cohort were younger (mean age 29.22 ± 8.80 vs. 36 ± 12.2 years), while gender proportions were quite similar . Educational level was also very high (69.1% University), while we used a different measure (58.8% A levels). They did not asses comorbidities and intake of psychotropic medicine. The calculated cutoff of ≥10 revealed a bit lower sensitivity (85.1 vs. 95.6%) and a higher specificity (89.5 vs. 72.3%) than we do. It remains unclear which evaluation scheme weighting of the item was used. The difference in psychometric properties may reveal to a smaller cohort, younger age, or maybe existing comorbidities which unfortunately were not indicated .Moreover, note that in our cohort almost 60% of participants had a high educational level which is a significantly higher proportion in comparison to the standard population. Interestingly, we cannot find a significant correlation between educational level and positive ASRS-5/IDA-R. The most common ADHD presentation for our sample was the predominantly inattentive.While parallel analysis (which can be insensitive to correlated errors) suggested one factor, confirmatory factor analysis revealed a correlated error between items 5 and 6 . Thus, it seems that the last two items of the ASRS-5 share some content beyond the general ADHD factor. Both items ask for non-DSM-5 symptoms of executive dysfunction and we suspect that responses to both items are also affected by personality traits like conscientiousness. This correlated error should be replicated with a new data set. The fit of the one-dimensional model with correlated error was adequate. This result is not trivial because the original scale was constructed with a machine learning algorithm that optimizes predictive performance but does not consider dimensional structure in any way. Our results suggest that despite the predictive focus, the psychometric properties of the ASRS-5 are comparable to more conventional scales.General practitioners see a lot of patients each day within the whole range of diseases. For this setting, potentially even more than for others, feasibility aspects like processing time matter. The ASRS-5 was assessed positively in terms of feasibility, acceptability, and credibility by interviewed general practitioners. Upcoming topics were further treatment options, stigmatization, and knowledge gaps, all which might be connected. A brief primary care intervention combines knowledge about adult ADHD and a treatment option . This inFor this study, we choose the ASRS-5 as it showed good psychometric properties before and seems to be pragmatic for the primary care setting. We could confirm both of this with our results. Nevertheless, a specificity of 72.3% means, there is a risk especially of false positive respondents. This is why we want to underline the ASRS-5 is not an instrument for a definitive diagnosis of adult ADHD. It can be used as a pragmatic tool to confirm or reject an initial suspicion of the treating practitioner, which is the particular need for the primary care setting. If a patient is screened positive further evaluation is needed. According to the German guideline, a diagnosis needs to be confirmed by a specialist . HoweverOur study examined a convenience sample collected both at GP practices and at an outpatient clinic specialized in ADHD patients. The high base rate of ADHD in our study population  is not representative for GP settings in which the ASRS-5 scale will be mostly applied. Thus, we do not report Positive and Negative Predictive Value which both depend on the base rate of ADHD in the studied population. Additionally, we want to caution GPs against overconfidence when applying the ASRS-5 as a screening tool in primary care. For the sake of argument, assume a general prevalence of ADHD in German adults of 3%  in combiIn our study, we focused on sensitivity and specificity which do not directly depend on the base rate of ADHD. However, sensitivity and specificity can vary between populations that not only differ with respect to the base rate but also with respect to other person characteristics that affect the functional relationship between the ASRS-5 scale and a true ADHD diagnosis. Such an effect can be seen in the original publication where specificity was noticeably lower in the clinical sample (74 vs. 96%) that was collected in a slightly different setting . Wide inIn this study we choose the ASRS-5 as it showed good psychometric properties before and seems to be pragmatic for the primary care setting. Please note that some points of the ASRS-5 can be seen critically. It is based on DSM-5, but the wording is quite different. Besides, two out of six items relate to non-DSM-5 symptoms of executive dysfunction. Moreover only one item relates to DSM-5 symptom of inattention which is known to often be predominant in adults with ADHD .For validation, we used the IDA-R which consists of the ASRS-V1.1, the WURS-k, and a semi-structured DSM-5 interview. It can be criticized that ASRS-V1.1 refers to DSM-4, while the examined ASRS-5 refers to DSM-5. Furthermore, the WURS-k assesses childhood ADHD symptoms by retrospective self-report. References show, that this might not be reliable . One morRegarding factor analysis, note that polychoric correlations or estimators for discrete ordered responses categories could not be used because response categories were not fully utilized. The choice of response categories could be therefore reconsidered.In this study, we used the evaluation scheme proposed from A time-efficient screening tool for adult ADHD validated within the primary care setting may help to improve quality of care. The ASRS-5 meets the criteria of a capable screening tool. Here, we reported positive evidence with regard to the psychometric properties of the German version of the ASRS-5, as well as to its feasibility, acceptability, and credibility in the primary care setting. The German version of the ASRS-5 offers a promising tool to improve adult ADHD patients’ diagnosis and healthcare.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The Ethics Committee of the University Hospital, LMU Munich (No. 20-0882) approved the study. The patients/participants provided their written informed consent to participate in this study.CB: designed and delivered the study and wrote the manuscript. MK and IB-G: delivered the study. FW: contributed to the study design, delivered the study, and contributed to the final manuscript. FP: did the statistics and contributed to the final manuscript. AB and AP: contributed to the study design and final manuscript. JG: designed the study and contributed to the final manuscript. All authors contributed to the article and approved the submitted version.This study was funded by Stiftung Allgemeinmedizin  and intramural funding (University of Bonn).AP: advisory activity for Shire/Takeda, Medice, Boehringer, Janssen-Cilag; Lecture fees from Medice, Takeda; research funding through Medice; behavioral therapy supervisor and DBT supervisor; and author of book articles and books on ADHD.The remaining 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.


Children with ADHD tend to achieve less than their peers in school. It is unknown whether schools moderate this association. Nonrandom selection of children into schools related to variations in their ADHD risk poses a methodological problem.We linked data on ADHD symptoms of inattention and hyperactivity and parent–child ADHD polygenic scores (PGS) from the Norwegian Mother, Father, and Child Cohort Study (MoBa) to achievement in standardised tests and school identifiers. We estimated interactions of schools with individual differences between students in inattention, hyperactivity, and ADHD‐PGS using multilevel models with random slopes for ADHD effects on achievement over schools. In our PGS analyses, we adjust for parental selection of schools by adjusting for parental ADHD‐PGS (a within‐family PGS design). We then tested whether five school sociodemographic measures explained any interactions.SE = 0.009), but in 2.5% of schools with the weakest effects, the value was −0.07 or less. ADHD has a weaker effect on achievement in higher‐performing schools. Schools make more of a difference to the achievements of students with higher levels of ADHD, explaining over four times as much variance in achievement for those with high versus average inattention symptoms. School sociodemographic measures could not explain the ADHD‐by‐school interactions.Analysis of up to 23,598 students attending 2,579 schools revealed interactions between school and ADHD effects on achievement. The variability between schools in the effects of inattention, hyperactivity and within‐family ADHD‐PGS on achievement was 0.08, 0.07 and 0.05 SDs, respectively. For example, the average effect of inattention on achievement was β = −0.23 (Although ADHD symptoms and genetic risk tend to hinder achievement, schools where their effects are weaker do exist. Differences between schools in support for children with ADHD should be evened out. Complex outcomes such as educational achievement result from exchanges between individual characteristics and environmental contexts such as families, schools and neighbourhoods, over time  is of particular interest in this context. Its characteristic symptoms of hyperactivity and inattention loom large at school. ADHD symptoms are common, typically appear in early childhood and are associated with profound impairments in achievement  adjusted for parents' ADHD‐PGS. ADHD is strongly genetically influenced (70–80% in twin studies) .Standardised national test results for maths and reading at grades 5, 8 and 9 , and English at grades 5 and 8 were obtained through linkage to Norway's National Education Database. Introduced in 2007, these tests are mainly used to monitor school development over time. Tests are compulsory, with 96% of all students in Norway taking them; students with special needs and those following introductory language courses may be exempt. Results are conveyed to teachers and parents but have no direct consequence for students. We residualised students' test scores for sex, current age (to capture birth cohort effects) and the exact age when they took the tests. We created ‘core achievement’ measures as mean scores at each grade across available subjects  categories and measured when students were 16. The second sociodemographic indicator was the average parental pretax annual income from gainful employment including self‐employment but not capital income or social welfare transfers. We averaged the income of both parents across the years that children were aged 11–15, and ranked their income compared with other parents in the same birth cohort. Third and fourth, we measured socioeconomic inequality by calculating Gini coefficients in reported levels of parental education and income, respectively. Gini is a widely used single measure of inequality and ranges from 0 to 1, with 0 indicating absolute equality and 1 indicating absolute inequality. Fifth, we calculated the proportion of children who are non‐Western immigrants and/or who are the children of non‐Western immigrants. We created these broad measures in the absence of more detailed school data. Notably, the measures could capture effects intrinsic to specific schools (e.g. peer effects) or broader social stratification (e.g. composition of the school catchment area). If the latter is true, then these variables could be considered additional controls for selection into schools and neighbourhoods.We used the same measures of parental educational attainment and earned income as individual‐level control variables to ensure that interactions are not confounded by differences in family socioeconomic background.https://www.fhi.no/en/studies/moba/for‐forskere‐artikler/questionnaires‐from‐moba/). We summed the items for the inattention and hyperactivity subscales. For individuals with less than 50% missing data on either scale, missing item values were imputed by the sample mean. The remaining individuals were excluded from analyses. We then centred sum scores to have mean zero and standard deviation 1. Inattention and hyperactivity subscales were analysed separately, due to differences in their aetiologies  , call rate < 98%, reported sex mismatching SNP‐based sex, duplicates , derived from nine batches of participants, who make up four study cohorts. Within each batch, parent and offspring genetic data were quality‐controlled separately. Preimputation quality control criteria have been described in previous publications and are detailed in the Appendix p‐value threshold of 1), with clumping parameters kb = 500, p = 1, r2 = .25  and mid‐parental PGS  were then centred to have mean zero and standard deviation 1. In all PGS analyses, we included parental PGS as controls, such that effects of offspring PGS are within‐family direct genetic effects. These within‐family PGS effects reflect random genetic segregation, holding any parental and wider ancestral differences constant, including population stratification, assortative mating and general social background effects. Notably, within‐family designs based on siblings or adoptees rather than parent–offspring trios can also be used to distinguish direct genetic effects from parental genetic effects  estimated the association between achievement and ADHD (symptoms or within‐family PGS). We pooled data across grades by including individual identification number as a random intercept, and time point as a fixed effect to account for mean differences in scores across time. Time point was coded as a continuous variable centred with 0 for grade 9, −1 for grade 8 and − 4 for grade 5. Note that the grade 9 composite only includes maths and reading, whereas achievement composites for grades 5 and 8 include all three subjects.In Model 2, we tested the degree to which achievement varied between schools, by adding a random intercept for schools.slope) between schools than expected by chance. Since random intercepts were already included in Model 2, improved fit of Model 3 must only reflect schools interacting with ADHD, and not mean differences between schools.In Model 3, we tested for ADHD‐by‐school interactions by adding random slopes for the effects of ADHD on achievement across schools. Improved fit relative to Model 2 is evidence that there is more variation around the average effect of ADHD . These fixed effects are meant to account for intercept variance, that is average differences between schools in student achievement. We then added environment‐by‐ADHD interaction terms (Model 6) to see whether the covariates could explain ADHD–school interactions, beyond any main effects that they have on achievement . The five school sociodemographic measures were tested jointly. If covariates account for interactions between ADHD and schools, then the fit of Model 6 would be improved relative to Model 5, and the standard deviation of slopes for ADHD measures between schools would be reduced.Since we used maximum‐likelihood estimation, we could compare fit of models before and after the inclusion of fixed effects, not only of models that differ in their random‐effects structure. Specifically, this allowed us to test whether model fit improved upon inclusion of random slopes for ADHD effects across schools (i.e. an ADHD–school interaction) and upon inclusion of specific school variables as fixed effects  that could explain any interactions.Multilevel models allow the inclusion of all schools in analyses, even those only attended by one individual. Although having larger numbers of individuals per group increases power  on whether a formal administrative decision had been made about their child being eligible for special education. By comparing the fit of further multilevel models, we tested whether the effect of ADHD on achievement depended on receiving special educational support, and whether this interaction varied between schools  were approximately normally distributed, with no indication of skewness of <−1 or >1 or of ceiling effects . The average number of students participating in MoBagenetics per school at grade 5 was 11, with a minimum of 1 (in 221 schools) and a maximum of 65 (in one school). For the analyses with ADHD symptoms, the sample included 11,737 individuals, from 2,383 schools. Table p‐values were <2e−16 for inattention and hyperactivity, and 0.001 for the within‐family ADHD‐PGS. For Model 4 compared with Model 3 , chi‐squared p‐values were <2e−16 for all three ADHD indicators. We now describe the estimates for the best‐fitting model (Model 4). Full results for all tested models are in Table To explore between‐school differences in the effects of ADHD on achievement, we compared models as outlined in Table x‐axis) vary considerably between schools. On average (dashed lines), the association between inattention and achievement is β = .23 (SE = 0.009), while the association between hyperactivity and achievement is β = .09 (SE = 0.009). For children's within‐family ADHD‐PGS, the association with achievement is β = .07 (SE = 0.013). These effects varied between schools  on achievement is more extreme than double the school‐average effect (i.e. β = −.16) in 2.5% of the schools with the most strongly negative slopes, while negligible for schools in the opposite tail of the distribution of effects. Between‐school differences in within‐family ADHD‐PGS effects reflect gene–environment interaction, controlling for selection into schools. The parent ADHD‐PGS has an effect of only β = −.002, reduced from −.037 without controlling for parents' education and income (Model 3). This suggests that the indirect genetic effect of parental ADHD‐PGS on offspring achievement is mediated by family socioeconomic status. Here, parental education has a stronger association with student achievement than parental income .Note that results were similar for maths, reading and English outcomes Table , and forx‐axis = 0 in Figure The ADHD–school interaction that we identified implies that not only do ADHD effects vary between schools but that school effects vary according to student ADHD levels. Figure r = .36, .38 and .10 for inattention, hyperactivity and within‐family ADHD‐PGS, respectively). This positive correlation means that ADHD has less of an impact on achievement in higher‐achieving schools. Indeed, as ADHD effects increase between schools from strongly to weakly negative, overall achievement increases. As with the school intercept, the intercept–slope correlation is interpreted for average values of ADHD variables. We found that the correlation becomes more strongly positive with increasing values of student ADHD symptoms and PGS . This suggests that differential quality of special support between schools may explain our interaction results , we provide new insights into how achievement in this sample is shaped by the interplay between school contexts, and individuals' ADHD symptoms and genetic risk. The availability of parent–offspring ADHD‐PGS allowed us to take advantage of the ‘natural experiment’ of random segregation of parental genetic variation at conception. Using such a within‐family ADHD‐PGS design is equivalent to randomising children to schools, meaning that the genetic analyses  are unlikely to be confounded by selection into schools.We detected an interaction between schools and ADHD, whether ADHD was measured by symptoms of inattention, hyperactivity or within‐family ADHD‐PGS. This indicates that the educational consequence of ADHD depends on which school ADHD is expressed in. For example, the average effect of inattention on achievement is β = −.23, but in the 2.5% of schools where inattention matters the least for achievement, the effect is β = −.07 or less. Our estimates of ADHD‐PGS associations with achievement (β = −.11 crude and −.07 within‐family) were similar to those from a prior study, although the proportion of the ADHD‐PGS association due to direct child‐led genetic effects was weaker for their Swedish GPA outcome (β = −.12 crude and −0.04 within‐family)  corresponds well with prior evidence from Norway and the United Kingdom  appeared to be involved. These measures are likely too broad to capture how schools moderate the effect of ADHD on achievement. Future work should use the framework introduced here to identify the total latent moderation effect by schools, and then see what fraction of this can be captured by more detailed school environmental measures. Candidate school measures should include institutional, practical, social and community domains, for example, not only the qualifications of teachers and psychologists to cater to children with cognitive and behavioural difficulties , and will be difficult to account for even in within‐family gene–environment interaction studies. However, selection into schools is an interesting phenomenon that can be understood better using multilevel genetically sensitive methods.variability in ADHD  vary by ADHD levels (x‐axis).Click here for additional data file.Table S1. Intraclass correlations indicating variance in ADHD measures due to variation between schools.Table S2. Phenotypic descriptive statistics for analysis variables within the MoBa genetics cohort.Table S3. Fit statistics for main models (1–6).Table S4. Results for main models (1–6).Table S5. Results for maths, reading and english separately.Table S6. Results for boys and girls separately.Table S7. Results for special educational support analyses.Click here for additional data file.


Our present study aimed to explore the symptomatic structure in children with attention-deficit/hyperactivity disorder (ADHD) using network analyses. Symptom network based on 18 items of ADHD Rating Scale-IV was evaluated in 4,033 children and adolescents with ADHD. The importance of nodes was evaluated quantitatively by examining centrality indices, including Strength, Betweenness and Closeness, as well as Predictability and Expected Influence (EI). In addition, we compared the network structure across different subgroups, as characterized by ADHD subtypes, gender and age groups to evaluate its invariance. A three-factor-community structure was identified including inattentive, hyperactive and impulsive clusters. For the centrality indices, the nodes of “Distracted” and “Fidget” showed high closeness and betweenness, and represented a bridge linking the inattentive and hyperactive/impulsive domains. “Details” and “Fidget” were the most common endorsed symptoms in inattentive and hyperactive/impulsive domains respectively. On the contrary, the “Listen” item formed a peripheral node showing weak links with all other items within the inattentive cluster, and the “Loss” item as the least central node by all measures of centrality and with low predictability value. The network structure was relatively invariant across gender, age and ADHD subtypes/presentations. The 18 items of ADHD core symptoms appear not equivalent and interchangeable. “Distracted” and “Fidget” should be considered as central, or core, symptoms for further evaluation and intervention. The network-informed differentiation of these symptoms has the potentials to refine the phenotype and reduce heterogeneity.The  Attention-deficit/hyperactivity disorder (ADHD) is conceptualized as a neurodevelopment disorder, characterized by age-inappropriate levels of inattention, hyperactivity and impulsivity associated with impairments across settings. According to the DSM-5  and ICD-To address phenotypic heterogeneity, one current available method is to subclassify caseness based on one of the three “presentations” defined by DSM-5, such as “combined,” “predominantly inattentive,” or “predominantly hyperactive/impulsive” presentations. Within these subcategories, all symptoms are still weighted equally without hierarchical ranking, while the patterns of interaction and co-occurrence amongst symptoms are considered as irrelevant—aside the threshold of symptom count. Contrasting with the assumptions made by DSM-5 and ICD-11, empirical findings indicate the contrary to be true. A recent study reported that 18 items contribute independently to the clinical diagnosis of ADHD, with some of them carrying more weight . Moreovenetwork theory of mental disorders, which conceptualizes psychiatric symptoms as networks of symptoms that causally interact  planning/organization  and (ii) sustaining attention . Of these, “lose things” was the node with the highest “betweenness centrality.” In addition, “does not listen” was found to be mostly isolated , gender and age distribution , 17. WouThe present study aimed to evaluate the network structure of ADHD symptoms in a large clinical sample of Chinese Han participants with ADHD age 6-16), in order to address the aforementioned gaps in the literature. In particular, it aimed to probe for evidence against the equal-weight and interchangeability assumptions of ADHD symptoms. We hypothesized that 6, in ord the netwChildren and adolescents with ADHD were recruited from Peking University Sixth Hospital/Institute of Mental Health. ADHD, subtypes and comorbidity were classified based on a semi-structured diagnosed interview conducted by a child psychiatrist was conducted using the Clinical Diagnostic Interview Scale (CDIS);  accordinADHD Rating Scale-IV (ADHD RS-IV) was used to assess the psychopathology of ADHD. It was rated by parent or primary carer with best knowledge of the child on a 4-point Likert-type scale . It consists of 18 symptom items according to the DSM-IV criteria for ADHD.Fails to give close attention to details or makes careless mistakes in schoolwork, coded as “Details”; (2) Has difficulty sustaining attention in tasks or play activities, coded as “Span”; (3) Does not seem to listen when spoken to directly, coded as “Listen”; (4) Does not follow through on instructions and fails to finish work, coded as “Follow”; (5) Does not follow through on instructions and fails to finish work, coded as “Finish”; (6) Avoid tasks  that require sustained mental effort, coded as “Avoid”; (7) Loses things necessary for tasks or activities, coded as “Loss”; (8) Is easily distracted, coded as “Distracted”; (9) Is forgetful in daily activities, coded as “Forget”.Nine inattentive symptoms were: (1) Fidgets with hands or feet or squirms in seat, coded as “Fidget”; (2) Leaves seat in classroom or in other situations in which remaining seated is expected, coded as “Seat”; (3) Runs about or climbs excessively in situation in which it is inappropriate, coded as “Run”; (4) Has difficulty playing or engaging in leisure activities quietly, coded as “Noisy”; (5) Is “OnTheGo” or acts as if “driven by a motor”, coded as “OnTheGo”; (6) Talks excessively, coded as “Talk”; (7) Blurts out answers before questions have been completed, codes as “Blurt”; (8) Has difficulty waiting turn, coded as “Wait”; (9) Interrupts or intrudes on others, coded as “Interrupt.”Nine hyperactive/impulsive symptoms were coded as: (1) https://cran.r-project.org/) was used for network analysis in this study, R-package “qgraph”   in combi“qgraph”  was usedstrength, betweenness, and closeness (predictability and expected influence (EI). A node with high betweenness means it occupies frequently in the shortest paths between pairs of the other nodes. High closeness indicates close connections with all the other nodes in the network. Strength is calculated by summing the absolute weights of all the edges connected to the node. To account for negative edges that suppress other nodes contrasting with positive edges that activate other nodes, EI assesses the strength of a node accounting for the negative edges , genders  and among four age groups , we estimated these networks in samples stratified by these parameters respectively; and examined the invariance of network structure, global strength, and edge-weights using two-tailed permutation tests  . The tesHochberg  method i5 implemented in R statistical software was used to estimate the network stability.The stability of each estimated network, including the accuracy of edge-weights and centrality were evaluated according to the method published by Epskamp, Borsboom and Fried . FirstlyA total of 4,033 children and adolescents with ADHD  were recruited for analyses; and their demographic and clinical characteristics are summarized in Details” as the most frequently endorsed symptom followed by “Distracted” in the attentive domain, while “Fidget” as the most frequently endorsed symptom followed by “OnTheGo” in the hyperactive/impulsive domain.Fidget” and “OnTheGo” were the most frequently endorsed items, except for the 12-years group in which “Talk” was the second most endorsed symptom. As predicted by developmental maturity, the endorsement of hyperactive symptoms declined with age.This pattern across respective subgroups, based on subtypes, gender or age groups, was similar generally. However, some minor anomalies deviated from the overall pattern were noted. For the hyperactive/impulsive domain, “Talk,” which bridged hyperactive and impulsive clusters, was more closely linked with impulsive symptoms, rather than hyperactive symptom – a pattern more aligned with ICD-10 conceptualization  than DSM classification. Notably, the edge-connection between “Distracted” and “Fidget” represented a bridge linking inattentive and hyperactive/impulsive domains , which was consistent with its diffuse but weak links with other items as shown in Run” item in the hyperactive/impulsive domain (56.6%), which might be mainly due to its strong connection with “Seat” and “Noisy” as shown in r = 0.316, p = 0.201 for Betweenness; r = 0.282, p = 0.257 for Closeness; r = −0.204, p = 0.417 for Strength; r = −0.218, p = 0.386 for Expected Influence), indicating that the network parameters were more influenced by the rating level.For the centrality indices , the nodInattentive” factor as one community and (ii) the merged “Hyperactive/Impulsive” factor as the second community  the “ommunity . Howeverommunity . In otheM = 0.09; p = 0.482). A nominally stronger global strength was found in ADHD-C than ADHD-I   . HoweverM = 0.12, P = 0.137) or global strength   . To minip-values > 0.1) and global strength invariance  when all permutations of pairing among four strata were compared. Our detailed analyses suggested that the ADHD symptom network structures are consistent across age spanning childhood to adolescent (6–16 years old in this sample).Network structure invariance across age groups was estimated for four age strata  within the whole sample . The resStability analysis for each estimated network  showed relatively narrow bootstrapped CIs, suggesting reliable edge-weights. All the CS-coefficients for strength [CS (cor = 0.7)] were larger than 0.5, which suggests that the centrality indices were quite stable. More details of the results on network stability can be found in the Talk” showed strong links with impulsive symptoms, which is more in accordance with the designation in ICD-10. However, the community detected using the Clique Percolation method suggested two sub-clusters in inattentive domain, implicating potential novel substructure or a chance finding or an artifact arising from the Clique Percolation method. In our findings, “Finish,” “Follow,” “Span,” and “Details” formed the one inattentive community, whilst “Loss,” “Forget,” and “Details” formed a different inattentive community. “Listen” and “Distracted” were not assigned to any community. To our knowledge, no such inattentive substructure has been reported before. Secondly, the two most commonly endorsed symptoms, “Distracted” and “Fidget” (for inattentive and hyperactive/impulsive domains respectively), showed important bridge effects, which represented critical nodes for further evaluation. Thirdly, as hypothesized, the network structure was relatively invariant across ADHD subtypes, gender and age, indicating its robustness for generalization.There were three key findings in our study. Firstly, a three-factor-community structure was identified for 18-item ADHD core symptoms, including inattentive, hyperactive and impulsive domains. Interestingly, “Talk” (classified as a hyperactive symptom by DSM systems) showed stronger links with impulsive symptoms, and not with hyperactive symptoms, which is more in accordance with the designation in ICD-10 ; in contrast, it was the lowest  in the study reported by Silk et al. (Listen” symptom (71.5%) was ranked 6th in our sample, which was much lower than that in Silk et al. . For the hyperactive/impulsive domain, the difference seems were more extensive. The most frequently endorsed symptom reported by Silk et al.  followed by “Fidget” . In our findings, “Fidget” was also found to be common ; however, the “Interrupt” was with lower frequency . Other differences were noted for “Seat” , “Noisy” (Ranked 3rd vs. Ranked 9th), “OnTheGo” (Ranked 2nd vs. Ranked 7th) and “Wait” (Ranked 8th vs. Ranked 4th) between these two studies.For the frequency distribution of each item, we found “k et al.   and also that of Silk et al. (Distracted” was the most informative parent- and teacher-rated ADHD symptom with relatively lower severity threshold (Distracted” is one of the three DSM-5 items used for screening in the research gold-standard diagnostic instrument—“kiddie-schedule for affective disorders and schizophrenia-present and lifetime version” (K-SADS-PL)  and that in Silk et al. . It would be very interesting to investigate such difference, which might arise from cross-cultural difference  . Taken tfference .Listen” showed diffuse but weak links with other symptoms in both inattentive and hyperactive/impulsive domains, and the lowest predictability value. In the community detected using the Clique Percolation method, the node “Listen” was not assigned to any community. In the existing literature, evidence from factor analyses has indicated a weaker mean factor loading of “Listen,” weaker than that of any other inattentive symptoms , which is therefore present only in those individual embodying higher level of ADHD latent traits  symptoms within the network. In the maintenance phase, the network becomes self-sustaining and self-perpetuating once fully activated; and the psychopathology become stuck in an active state in the network, despite the removal of the initial triggering external event; and characteristically, the removal of the initial trigger does not lead to recovery as the pathological network has now become autonomous   . OverallDistracted” and “Fidget” might need to be given higher weight than others, while inversely for “Listen” and/or “Loss.” Instead of summing all items together equally, exploration on whether some key symptoms or their connections might refine the phenotype to decrease the heterogeneity, such as the use of weighted symptoms counts as more informative phenotypes for the investigation of the neurobiological underpinnings of ADHD (Loss” as a “difficult item,” suggesting this item embodying greater “weight” in ADHD latent traits (Distracted” symptom and investigate its related brain alteration, cognitive impairment and the genetic background. Recently, some researchers have attempted to combine the symptomatic data with the neuropsychological (Our present findings have some clinical implications. First, both DSM-5-TR and ICD-11 utilize the polythetic system for disease classification. In the current diagnostic criteria of ADHD, none of the 18 diagnostic criteria is designated as “essential” or ranked as “more essential” for diagnostic classification. Our findings suggest that not all the ADHD 18 items should be evaluated in equal weight. For example, “t traits . IRT anat traits , albeit t traits . Future ological  or genetological  to constological .This study has several limitations. First, as mentioned above, our analyses were based on cross-sectional data. Therefore, we could not examine the dynamic changes of the network structure, and therefore could not explore the dynamic relationship between symptoms in the network overtime and development. Longitudinal data could help to illustrate the dynamic change of ADHD symptom network over developmental windows to avoid age cohort effects by using cross-sectional data of participants from different age groups, as in our study and other published studies. Second, we only included 18 items of ADHD symptoms in our analyses based on the current DSM-5 criteria. In addition to the inattentive, hyperactive and impulsive domains, other important features such as emotion dysregulation, internalizing and externalizing symptoms are potential informative candidates for inclusion in the future analyses, given emotion dysregulation symptoms have been proposed to be a core component of ADHD symptoms , or sentDistracted” and “Fidget” to be the core symptoms for ADHD. The network-informed differentiation of ADHD symptoms highlights the potential to refine the phenotype and reduce heterogeneity in this clinical group.Our present study utilized network analysis to identify novel symptom structures in children with ADHD. Our findings confirm the invariance of symptom networks across age, gender and ADHD subtypes, and suggest “The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Peking University Sixth Hospital/Institute of Mental Health. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.LL, YiW, QQ, and RC conceptualized the idea and designed the study. LL and HL organized the database. LL, YiW, WC, YG, and YuW analyzed and interpreted the findings and wrote up the drafts of the manuscript. RC and QQ interpreted the findings and commented the drafts critically. All authors contributed to manuscript revision, read and approved the submitted version.


Belatacept is probably associated with an increase in both risk and severity of some infectious diseases, including EBV-linked post-transplantation lymphoproliferative disorders, and with a decreased response to vaccines. Most studies on belatacept are observational, retrospective, and non-comparative. Consequently, high-quality data about the safety and efficacy profile of belatacept, as compared with the current gold standard for maintenance regimens (tacrolimus-based), is uncertain. Our review will therefore focus on the most recent published data aiming at evaluating the evidence-based or the “true” benefits and risks of belatacept-based regimens in kidney transplantation.The current gold standard to prevent allograft rejection for maintenance immunosuppression in kidney transplantation currently consists in glucocorticoids, an antiproliferative agent and a calcineurin inhibitor (CNI), with better outcome for tacrolimus than cyclosporin. Although, CNI drastically improved early graft survival, so far, CNI have failed to significantly improve long-term survival mainly because of nephrotoxicity. In addition, CNI carry several other side effects such as an increased risk for cardiovascular events and for diabetes mellitus. Therefore, seeking alternatives to CNI remains of paramount importance in kidney transplantation. Belatacept is a fusion protein composed of the human IgG1 Fc fragment linked to the modified extracellular domain of cytotoxic T lymphocyte–associated antigen 4. In kidney transplant recipients, pivotal phase III randomized studies suggested clinical benefits of belatacept as an initial maintenance regimen, as compared with cyclosporine, mainly on kidney function. Recently, a randomized study also suggested a clinical benefit on renal function of a conversion from a CNI-based to a belatacept-based maintenance regimen in patients. However, conversion from CNIs to belatacept is probably associated with an increased risk of biopsy-proven acute rejection and should prompt close clinical surveillance. On the other hand, other studies suggest a decrease in  The current gold standard to prevent allograft rejection in kidney transplantation currently consists in a maintenance treatment based on glucocorticoids, an antiproliferative agent and a calcineurin inhibitor (CNI) . Among cBelatacept was designed as an alternative to calcineurin inhibitors-based regimens to prevent rejection–and consequently, graft loss–in recipients of kidney allografts. Belatacept is a recombinant immunoglobulin fusion protein, combining the modified extracellular B7-binding domain of Cytotoxic T-Lymphocyte-Associated protein 4 (CTLA4) with the constant fragment portion (Fc) of IgG1 . Due to de novo kidney transplant recipients (KTRs) in 2011  were not original studies .We retrieved 80 basic science studies and 164 clinical studies. Among clinical studies, 90/164 (54.9%) were non-comparative studies, meaning that no comparison was made between belatacept and other treatments.We retrieved 38 published articles on RCTs comparing belatacept with at least one other treatment. Among these, 22/38 (57.9%) concerned Belatacept Evaluation of Nephroprotection and Efficacy as First-line Immunosuppression Trial (BENEFIT) trials—either BENEFIT, BENEFIT-Extended Criteria Donors (BENEFIT-EXT), or both.post-hoc analyses, subgroup analyses or meta-analyses of these RCTs.We will consider, for each RCT, the publication describing the longest follow-up for each RCT in the intention-to-treat population. In general, unless there is a significant contribution, we will not discuss results from publications describing short-term analyses, Overall, 13 distinct RCTs were identified, 11 of which were trials directly comparing CNI- and belatacept-based regimens . One stude novo kidney transplant recipients (KTRs), and 2/11 evaluated it when started in stable kidney transplant recipients already receiving CNI. Studies in de novo KTRs included 2018 patients, 1208/2018 (59.8%) of whom were in BENEFIT and BENEFIT-EXT trials.Among those 11 RCTs, 9/11 (81.8%) evaluated belatacept in Control groups included 1001 patients who received CNI: in 3 trials, 478 patients received only cyclosporin A; in 6 trials, 211 patients received only tacrolimus; in 2 trials, 312 patients received either cyclosporin A or tacrolimus.de novo KTRs , used in all studies, consists in i.v. belatacept 10 mg/kg for 5 injections in 84 days (one every 2 weeks), then 5 mg/kg every month subsequently. This regimen is US Food and Drug Administration- and European Medicines Agency-approved. An alternative regimen  consists in i.v. belatacept 10 mg/kg for 11 injections in 6 months, then 5 mg/kg every month subsequently, and was evaluated in three studies.Standard regimen for Two studies using cyclosporin A as a comparator (BENEFIT and BENEFIT-EXT), and none using tacrolimus, appeared to have sufficient power to perform statistical comparisons for this outcome. In these, no significant difference in the risk of death with a functioning graft were observed between patients receiving belatacept or cyclosporin A, regardless of belatacept dose.Here also, only BENEFIT trials appeared to have sufficient power for this outcome. In those, no significant difference in the risk of loss of allograft function were observed between patients receiving belatacept or cyclosporin A, regardless of belatacept dosage.Three studies using cyclosporin A as a comparator, and none using tacrolimus, appeared to have sufficient power for this outcome .In BENEFIT, belatacept at a standard dose (“less intensive”) was associated with a significant decrease in the risk of graft loss, with a hazard ratio of 0.57 [95% CI: 0.35-0.94] during a 7-year follow-up, when compared with cyclosporin A, in patients receiving a kidney from a Standard Criteria Donor (SCD). All patients were treated by basiliximab at induction, and glucocorticoids and either mycophenolic acid or mycophenolate mofetil for maintenance.In BENEFIT and the phase II trial, belatacept at a higher dose (“more intensive”) was associated with a significant decrease in the risk of graft loss when compared with cyclosporin A.In BENEFIT-EXT, in KTRs receiving a kidney from an Expanded Criteria Donora (ECD), regardless of the dose, belatacept was not associated with a significant difference in the risk of graft loss in comparison with cyclosporin A.In 9 trials out of 11, belatacept was associated with a higher rate of rejection compared with CNI. Statistical comparisons were not systematically performed in these studies but, since this difference is consistently observed across trials in various settings, it most likely reflects a true difference.de novo KTRs receiving an induction with basiliximab, the risk for biopsy-proven rejection within 7 years following KT using a kidney from an SCD is approximatively 15% higher with belatacept than with cyclosporin A; and 60% higher when using a kidney from an ECD.Based on data from BENEFIT studies, we can estimate that, in Based on data from two RCTs , 8, we cOverall, most rejection episodes occurred within a year following KT (in de novo KTRs) or switch (in stable KTRs).No study had sufficient power to detect a significant difference in death from cardiovascular cause, and no study presented a survival analysis for this outcome.In BENEFIT studies in general, observed rates of serious cardiovascular events were lower in patients treated with “less intensive” belatacept compared with CsA. In BENEFIT-EXT especially, a trial in which the absolute number of events is high (elderly patients with comorbidities), the rate of serious cardiovascular events was 5.2 per 100 patient-year with cyclosporin A and 4.1 per 100 patient-year with belatacept .In the study by Kaufman et al. , in 209 In the initial phase II study, then in BENEFIT and BENEFIT-EXT, a notable decrease in the risk of serious infectious events was noted in patients treated with belatacept, compared with cyclosporin A. For instance, in BENEFIT, the risk of serious infection was 13.3 per 100 patient-year on cyclosporin A and 10.7 per 100 patient-year on belatacept .Subsequent studies, that used tacrolimus as the main comparator, did not find such a high decrease in the risk of infection. For instance, in the study by Kaufman et al., the risk of serious infection during the 2-year follow-up was 22/105 (20.9%) on tacrolimus and 24/104 (23.1%) on belatacept. In the study by Budde et al., the risk of serious infection during the 2-year follow-up was 44/222 (19.8%) on CNI and 37/221 (16.7%) on belatacept.No study was powered to detect significant differences in specific types of infection , etc..). However, in the initial phase II study, three patients randomized to receive belatacept developed EBV-induced PTLD, vs. none among cyclosporin A-treated controls. In two of them, the disease was the consequence of a primo infection. In BENEFIT, among EBV-seronegative patients, 5/369 developed EBV-induced PTLD on belatacept, vs. 0/184 on cyclosporin A. Consequently, due to an increase in risk for PTLD in case of EBV primo infection, belatacept is contraindicated for EBV-seronegative patients.The same limits about statistical power apply for cancers. In BENEFIT-EXT, a trial in which elderly patients were included and, consequently, in which the absolute risk for cancers was high, there was no obvious difference in the risk for cancer between belatacept- and cyclosporin A-treated patients . In the study by Budde et al. , during No study had sufficient power to detect differences on the risk for specific cancers .2 on belatacept, and decreased from 52.5 to 44.9 on cyclosporin A. In the study by Budde et al., mean eGFR increased by 5.2 ml/min/1.73 m2 on belatacept and decreased by 1.9 on CNI.In most studies, belatacept was associated with an increase in estimated glomerular filtration rate (eGFR) compared to CNI. This is likely a consequence of differential renal hemodynamic effects between both drugs. In BENEFIT, after a 7-year follow-up, mean eGFR increased from 66 to 72.1 ml/min/1.73 mde novo donor specific antibodies (DSA). In BENEFIT, 4.6% of patients on belatacept developed de novo DSA during follow-up vs. 17.8% on cyclosporin A. In the study by Budde et al., 1% of patients switched to belatacept developed de novo DSA during follow-up vs. 7% on tacrolimus.Belatacept was also associated with a decrease in the risk to develop de novo DSA are determined on the subgroup of patients alive, with a functioning graft and with available data, notably excluding patients that lost their graft after a rejection (an event that is probably more frequent with belatacept), thus creating a potential differential bias. Furthermore, since rejections are more frequent with belatacept than with CNI, one cannot exclude that, on the long term, more patients would lose their grafts because of a rejection occurring on belatacept than because of a CNI-mediated nephrotoxicity.These results must be interpreted with caution as they do not necessarily mean that, on the long term, there would be differences on hard, clinically pertinent outcomes (such as graft loss or death). Indeed, eGFR slopes and Surrogate endpoints, developed to predict hard, clinically pertinent outcomes based on intermediate outcomes, have been validated in kidney transplantation . As theypost-hoc study based on data from BENEFIT and BENEFIT-EXT, Dobbels et al. (p < 0.05 for both comparisons) but not in Mental Composite Scores.In a s et al.  found thNo study compared quality of life between patients receiving belatacept and tacrolimus.Hereafter, we will review non-randomized clinical studies involving belatacept in KT. We will only consider studies that add significant contribution to data from RCTs, either because they strongly comfort their findings or because they make new ones. We will distinguish between comparative  and non-comparative studies. Among comparative studies, we will distinguish between those providing an adjusted analysis  and those providing none .de novo KTRs in the US, 458 of whom received belatacept, Wen et al. . Of note, all patients were CMV-seronegative patients receiving kidneys from CMV-seropositive patients, and all received valganciclovir in primary prophylaxis for 6 months following KT. Among patients that developed CMV viremia, the rate of resistance to ganciclovir was higher on belatacept than on tacrolimus .In a cohort study of 168 e et al.  found thde novo KTRs treated with belatacept in France, and on 74 controls treated with tacrolimus, Leibler et al. (p = 0.003). There was no difference in the risk for acute antibody mediated rejection. Of note, all patients had pre-formed donor specific antibodies (median fluorescence intensity 500 to 3000), received thymoglobulin as an induction therapy and had protocol biopsies at 3 months and 12 months.In a cohort study on 49 r et al.  found thde novo KTRs treated with belatacept in Atlanta, USA, and on 44 controls treated with tacrolimus, Parsons et al. . Overall, beneficial effects on glycemic control were found whether patients had preexisting diabetes at the time of conversion or not.In a cohort study of 103 KTRs switched from CNI to belatacept in Grenoble, France, Terrec et al.  found thIn an international randomized controlled study of 260 liver transplant recipients, 153 of whom received belatacept, Klintmalm et al.  found thIn a randomized controlled study of 27 lung transplant recipients in the US, 13 of whom received belatacept, Huang et al.  found thIn a randomized controlled study of 43 kidney-pancreas transplant recipients in the US, 22 of whom received belatacept, Stock et al.  found thIn a multicenter retrospective non-comparative cohort study of 40 heart transplant recipients in France switched from CNI to belatacept, mainly due to impaired renal function on CNI, Launay et al.  found thBased on these studies, the increase in risk for rejection with belatacept seems more problematic in non-kidney solid organ transplantations than in kidney transplantation, with less clear benefits on renal function. So far, belatacept use in daily practice is restricted to few patients with very specific indications .A synthesis of the current state of the medical literature on belatacept in kidney transplant recipients is provided in Belatacept is a non-nephrotoxic non-diabetogenic immunosuppressive drug developed to increase graft survival, as compared to the current gold standard, tacrolimus—which is a nephrotoxic and diabetogenic drug. Despite proven beneficial effects of belatacept on glomerular filtration rate, glycemic control, and the appearance of de novo donor specific antibodies, there are, currently, no truly evidence-based benefits on renal graft survival, as compared with tacrolimus.This can be the consequence of insufficiently powered studies to detect a better graft survival. On the other end, a lack of effect of belatacept is also possible since its benefits  may be undermined by adverse effects (higher rate of rejection and of CMV disease) which impair graft and patient survival.de novo kidney transplant recipients, the current state of the medical literature does not support the use of belatacept instead of tacrolimus. This is a direct consequence of the lack of RCTs with enough statistical power to compare belatacept against tacrolimus, in this setting, on hard, clinically pertinent outcomes. Such trials are urgently needed.For de novo DSA, better glycemic control) will result in differences on clinically pertinent outcomes .For stable kidney transplant recipients already receiving tacrolimus, additional RCTs and long-term follow-up of previous trials are needed to determine whether the observed differences in surrogate endpoints favoring belatacept  are unanswered from an evidence-based medicine perspective. RCTs using tacrolimus as a comparator with long term follow up are essential to definitively establish the true benefits of belatacept in kidney transplantation.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.YL: methodology, conceptualization, data curation, visualization, investigation, and writing–original draft. HF: project administration, supervision, methodology, conceptualization, investigation, and writing–review and editing. Both authors contributed to the article and approved the submitted version.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.


Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Many previous studies have shown that the comorbid status of disruptive behaviour disorders (DBD) was a predictor for ADHD persistence into adulthood. However, the brain mechanisms underlying such a relationship remain unclear. Thus, we aim to investigate whether the brain functional alteration in adults with ADHD could also be detected in children with ADHD co-occurring with disruptive behaviours from both quantitative and categorical dimensions.CD−, subthreshold ADHDCD+ and cHC groups, and among ADHDODD−, ADHDODD+ and cHC groups. Finally, we repeated the above analysis after controlling for other comorbidities and core symptoms to diminish the potential confounding effects.A total of 172 children with ADHD (cADHD), 98 adults with ADHD (aADHD), 77 healthy control children (cHC) and 40 healthy control adults (aHC) were recruited. The whole-brain spontaneous fluctuations in brain activity of each participant were recorded using functional near-infrared spectroscopy (fNIRS), and the functional connectivities (FCs) were calculated. We first compared the FC differences between aADHD and aHC. Then, for the regions with significantly abnormal FCs in aADHD, we further compared these features between cADHD and cHC. In addition, the correlation between these FCs and the conduct disorder (CD)/oppositional defiant disorder (ODD) symptoms were analysed in cADHD. Moreover, to render the results readily interpretable, we compared the FC differences among ADHDCD+ group even exhibited a tendency of adult-like increased FCs compared with the cHC. The results held after controlling for other comorbidities and core symptoms.We found that compared with aHC, aADHD showed significantly increased FCs in the VN, DMN, SMN, and DAN. The aforementioned abnormal FCs were also detected in cADHD, however, in an opposite orientation. Notably, these abnormal FCs were positively correlated with CD symptoms. Finally, the subthreshold ADHDCD+ from ADHD and inspiring further understanding of brain development in ADHD.This study provides functional neuroimaging evidence that CD might be a risk factor for ADHD persistence into adulthood. Our work highlights the importance of differentiating ADHDThe online version contains supplementary material available at 10.1186/s13034-022-00486-7. Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder associated with many adverse life events and creates a substantial burden for individuals, their families, and the community. The ADHD persistence rate is in the range of 5.7–77%, and there are many factors associated with the course of ADHD .DBD+) have additional impairments and worse prognosis than children with ADHD alone or DBD alone [ADHD in children often co-occurs with many comorbidities, such as oppositional defiant disorder (ODD) and conduct disorder (CD), which are collectively referred to as disruptive behaviour disorders (DBD). DBD is a common and highly impairing psychiatric disorder characterized by conduct problems, irritability, and oppositional defiant behaviour . ChildreBD alone , 4. In pBD alone . Later, BD alone . SimilarBD alone . AnotherBD alone . RecentlBD alone . DespiteDBD+. Similarly, although few functional brain studies have been performed in ADHDDBD+ patients, Uytun et al. detected higher connectivity in children with ADHDDBD+ than in healthy controls [DBD+ already exhibit similar brain abnormalities to adult patients as early as childhood, which might be the mechanism behind the persisting ADHD symptoms. However, to date, no studies have simultaneously considered children and adults with ADHD and the effect of DBD symptoms. That is, this conjecture has not been specifically tested.In recent decades, several neuroimaging studies have been conducted on individuals with ADHD and DBD, which have produced additional insight into the pathophysiological mechanisms of ADHD and DBD. Therefore, can these studies provide some hints and tips about the above-mentioned phenomenon? The answer is yes. For example, for structural morphology, many studies found more significantly or more extensively decreased fractional anisotropy (FA), white matter (WM) volume and grey matter (GM) volume when the effect of comorbid DBD was taken into account, including the basal ganglia, cerebellum, and frontal cortices , 10. Sigcontrols , which wcontrols , 15. ThiCD+ and ADHDODD+, we did not have a specific prediction for these two groups.Over the last decade, the attention of neuroimaging research in ADHD has shifted to the role of distributed neural circuits, and the importance of understanding the function, organization, and development of interacting brain regions has been recognized. Thus, herein, we aim to investigate whether the altered brain functional connectivities (FCs) exhibited in adults with ADHD would be also observed in children with ADHD that co-occurs with disruptive behaviours from quantitative (correlations with disruptive behaviours) and categorical dimensions (comparisons for ADHD with and without DBD). We hypothesized that (1) the more DBD symptoms there are, the more adult-like functional abnormalities there will be in cADHD, and (2) cADHD comorbid DBD might show an adult-like pattern compared with cADHD without DBD. Given the scarcity of studies investigating the differences between ADHDAdditional file A total of 138 adults were recruited for the present study. Ninety-eight drug-naïve adults with ADHD (aADHD)  were recruited from the clinics of Peking University Sixth Hospital/Institute of Mental Health. Forty healthy controls (aHC)  matched for age, sex, and intelligence quotient (IQ) were recruited from nearby communities and universities.Conner’s Adult ADHD Diagnostic Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) was used to confirm the diagnosis of ADHD  by trainAs in our previous research on adults , the incA total of 172 children with ADHD (cADHD)  were recruited from the clinics of the Peking University Sixth Hospital/Institute of Mental Health. Seventy-seven HC (cHC)  were obtained from a primary school in the local community. The diagnosis and comorbidities of cADHD were diagnosed by an experienced psychiatrist according to the criteria of the DSM-IV by a semistructured interviews using the Clinical Diagnostic Interview Scale (CDIS) . ADHD syAs in our previous research on children , the incThe parents of the children with ADHD were asked to fill out the NICHQ Vanderbilt ADHD screen Assessment Scale on a 4-point scale . The item scores under the oppositional defiant disorder (ODD) and conduct disorder (CD) dimensions were summed separately for further analysis.There are various approaches for studying the brain mechanism underlying the pathogenesis of ADHD. Among these, ecologically valid and straightforward measures based on resting-state connectivity with large sample sizes strike a balance between highly specialized paradigms  and less-sensitive measures  . FunctioThis study used a multichannel continuous-wave near-infrared optical imaging system  with 24 light sources (wavelengths: 670 and 830 nm) and 28 detectors. It generated 80 measurement channels with a fixed source-detector distance of 3 cm covering the frontal, occipital and parietal lobes. According to the international 10–20 system, the cap was placed with the external auditory canals and vertex as the reference points. Data were collected at a sampling rate of 17 Hz. Each participant underwent an  ~ 12 min brain activity recording while at rest. Participants were asked to sit still and keep their eyes closed without falling asleep. Meanwhile, the surrounding environment remained unchanged.To identify the positions of each measurement channel on the brain surface, we randomly selected a child and an adult for structural MRI scanning. The participants lay supine while wearing the fNIRS cap with every channel labeled a vitamin E capsule. Then, their T1-weighted structural image was acquired using a General Electric; Discovery MR750 3.0 Tesla scanner. Next, the MR image was normalized into the Montreal Neurological Institute (MNI) space using SPM12. Then, the MNI coordinates for each channel on the brain scalp were projected to the brain surface via NIRS_SPM to obtain the MNI coordinates of each channel on the brain surface. Finally, the resulting channel coordinates were grouped into different brain networks based on Yeo et al.’s seven network template . The raw intensity signals were then converted into optical density signals. Next, we applied the spline interpolation algorithm to the resulting signals to correct the motion artefacts by channels. Motion artefacts were detected over a sliding window of 2 s. Any signal change beyond 5 standard deviations of the entire time series was considered a motion artefact. The resulting signals were then bandpass filtered (0.01–0.1 Hz) to remove the effect of low-frequency drift and high-frequency neurophysiological noise. Next, the relative hemoglobin concentration changes in oxygen-hemoglobin (HbO) and deoxygen-hemoglobin (HbR) were calculated via the modified Beer–Lambert Law. Finally, we extracted a 7-min stable hemoglobin time series for each participant. Of note, the HbO signal was used for the following analysis due to its relatively high signal-to-noise ratio .The functional connectivity matrix was computed in FC-NIRS, which generated an 80 × 80 correlation matrix for each participant by conducting Pearson correlation analyses between the time series of every pair of channels. We adopted the z matrix  for the next calculation step due to its normality characteristics. Then, according to MRI coregistration, our measurement channels were grouped into six networks: the visual network (VN), somatomotor network (SMN), dorsal attention network (DAN), ventral attention network (VAN), frontoparietal network (FPN), and default mode network (DMN). After considering the brain hemisphere factor, we obtained 12 networks in total. Finally, to evaluate the FCs between and within networks, the z values of the functional connectivity matrix were averaged separately, resulting in a 12*12 functional connectivity matrix.pFDR < 0.05).Based on our conjecture, we first calculated the difference between aADHD and aHC. Differences in age, IQ, sex, and core symptoms between aADHD and aHC were estimated using two-sample t tests or chi-square tests . The differences in FCs were determined using a univariate general linear model (GLM), with age, IQ, and sex as covariates. The FDR correction method was used for multiple comparisons (pFDR < 0.05).Similarly, differences in age, IQ, sex, and core symptoms between cADHD and cHC were estimated using two-sample t tests or chi-square tests . Then, for the abnormal FCs in aADHD, we compared their differences between cADHD and cHC using a univariate GLM, with age, IQ, and sex as covariates. The FDR correction method was used for multiple comparisons  and cHC, we randomly selected one group of cHC that was 1:1 sex and age- matched with ADHDCD+/ADHDODD+ using R.Finally, to render the results readily interpretable, we compared the FC differences among ADHDThe group differences in IQ and ADHD core symptoms were compared using one-way ANOVA. FC differences were detected using univariate GLM, with age, sex, and IQ as covariates.To rule out the potential influence of other comorbidities and core symptoms on our results, we included comorbidities other than CD/ODD and total symptoms as covariates and repeated the analyses.Group comparisons in the demographic and clinical variables between aADHD and aHC are listed in Additional file p = 0.142)  exhibited increased FCs compared with the aHC group (0.65 ± 0.25), albeit not significantly p = 0.42 -DAN(R) and VN(L)-DAN(R), post hoc comparisons showed decreased FCs in ADHDCD− compared with subthreshold ADHDCD+. For the comparison between subthreshold ADHDCD+ and cHC, the mean values of FCs in subthreshold ADHDCD+ were visually larger (the number is larger) than those of cHC in DAN(L)-DAN(R), VN(L)-SMN(R), and VN(L)-DAN(R), although these difference was not statistically significant. Descriptive statistics can be found in Additional file Detailed information on the demographic variables is presented in Additional file ODD− and ADHDODD+ compared with cHC, but there was no difference between ADHDODD+ and ADHDODD− in the DAN(L)-DAN(R), VN(L)-SMN(R) and VN(L)-DAN(R). In DAN(L)-DMN(R), post hoc comparisons showed decreased FCs in ADHDODD− compared with cHC , and thODD+ subgroup showed decreased FCs compared with cHC, which was different from the increased FCs in the subthreshold ADHDCD+ group. Interestingly, Caye et al. carried out the first meta-analysis of longitudinal studies assessing the risk markers for the persistence of ADHD and found that comorbid CD emerged as a predictor for ADHD persistence from childhood to adulthood. However, comorbid ODD was investigated by four studies with divergent results [CD+ was associated with multiple adverse outcomes, including bipolar, psychoactive substance use disorders, and smoking [ODD+ may form an intermediate subgroup between ADHDonly and ADHDCD+ [In contrast, there was no significant correlation between ODD symptoms and these FCs. The ADHD results . Similar smoking . Further smoking . Childre ADHDCD+ , 39. SomCD+ from ADHDODD+, most of them still revealed a significant difference between ADHDCD+ and ADHDODD+. For example, van Ewijk et al. found that comorbid ODD is associated with altered WM microstructure, and there was an interaction between ODD and  CD, which indicated that ODD and CD should be treated as separate constructs [CD+. Interestingly, although most task fMRI studies found decreased DMN activity in CD-only adolescents [CD+ compared with cHC [CD+ and ADHDODD+ from a etiological insight.At the neuroimaging level, most studies included mixed samples of cADHD comorbid with both ODD and CD. Although only a few small studies distinguished ADHDnstructs . This aglescents , 42, thiwith cHC . The autwith cHC . These sCD+ patients was relatively small. Although we used “subthreshold ADHDCD+,” we only obtained 7 children who met the criteria. However, considering the robust findings from quantitative analyses for CD symptoms, we anticipate that further categorical studies with a larger sample size will exhibit more compelling results. Similarly, the number of samples from female subjects is low in children due to the lower prevalence of ADHD in females. Future studies with large sample sizes are needed to validate our results. Third, this work is a cross-sectional study. It is unclear whether ADHDCD+ in children would certainly persist throughout development and into adulthood. In addition, we should note that ADHDCD+/ADHDODD+ in children may continue to develop into ODD and/or CD in the future. Thus, longitudinal studies are required to verify the mechanism in the future.Our current findings should be viewed in light of some limitations. First, fNIRS can only examine the cortical surface within 2–3 cm of the cortex. Deep structures  cannot be measured with fNIRS . ADHD neCD+ from ADHD, and children with this condition should receive more specialized care, as they are more likely to persist with throughout development.Using resting-state fNIRS data, we investigated the relationship between aADHD-related functional abnormalities and disruptive behaviours in cADHD. This study suggested that CD symptoms in children with ADHD, rather than ODD, could be more closely correlated with the risk of persisting ADHD from a neurobiological perspective. Our work provides some evidence for the brain development of ADHD. This highlighted the importance of differentiating ADHDAdditional file 1: Appendix S1. Tables and Figures. Appendix S2. FCs differences of ADHDCD+/ADHDODD+, ADHDCD−/ADHDODD- and cHC.


To understand whether the mental health of children and young people (CYP) with and without attention-deficit/hyperactivity disorder (ADHD) and/or autism spectrum disorder (ASD) were differentially affected by COVID-19. We analysed data (n = 6507) from the Co-Space study, a UK web-based longitudinal survey. CYP with ADHD , ASD , and ADHD + ASD  were compared with a reference group  using parent-completed questionnaires [Strengths and Difficulties Questionnaire (SDQ) & Pandemic Anxiety Scale (PAS)]. Baseline to 1-month follow-up differences were compared using linear regression models. CYP with ADHD and/or ASD had higher scores at baseline than other CYP. At follow-up, CYP with ASD showed small but significant improvements in symptoms (SDQ), compared with the reference group. CYP with ASD experienced a worsening of disease anxiety (PAS) and CYP with ADHD a deterioration in functional impairment. These findings indicate a mixed pattern of pandemic-related impact for CYP with ADHD and/or ASD. To control and minimise the rapid transmission of the Coronavirus disease 2019 (COVID-19), the United Kingdom (UK) government implemented lockdown restrictions, including home confinement and school closures at the end of March 2020. Consequently, the COVID-19 outbreak involved a rapid shift in social rules , as well as major changes to daily routines. Initial findings suggested that lockdown was associated with poor mental health for children and young people (CYP) [The UK National Health Service (NHS) highlighted CYP with neurodevelopmental disorders [NDDs such as attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD)] as being particularly vulnerable to the negative impact of COVID-19 . ADHD anCross-sectional studies and reports have highlighted the impact of COVID-19 on families living with ADHD and ASD. Pandemic mitigation responses such as home confinement or lockdown are reported to have contributed to an exacerbation of conduct problems and externalizing behaviours, increased irritability, and low mood for CYP with ADHD , 12 and Although there is a growing body of literature on the impact of home confinement for CYP with ADHD and ASD, the research in Europe remains limited. In a cross-sectional study, using the Strengths and Difficulties Questionnaire (SDQ) at the start of the UK pandemic lockdown 371 CYP with ASD and ADHD were compared with data from previously published norms and a UK mental health cohort. Compared with neurotypical controls, CYP with NDD were more likely to show emotional symptoms (15%/42%), conduct problems (9%/28%), and fewer prosocial behaviours (22%/54%). Children and young people with ADHD showed greater conduct problems and CYP with ASD showed fewer prosocial behaviours than neurotypical CYP . This stThe Co-Space project  has beenhttps://osf.io/8zx2y/). The Co-SPACE study gained ethical approval through the University of Oxford Medical Sciences Division Ethics Committee (reference R69060), and full details of these ethical considerations can be found in the OSF protocol. Participants completed a baseline survey and a follow-up, approximately 1 month apart (data collected between 30th March and 31st May 2020). All data were collected within the first UK lockdown, which saw the most stringent social restrictions between 23rd March 2020 and 1st June 2020. Parents reported on whether their child had any medical conditions including autism spectrum disorder (ASD), attention-deficit disorder or attention-deficit hyperactivity disorder (ADD/ADHD), clinically diagnosed anxiety or depression, or another clinically diagnosed mental health condition. Other UK research suggests that parent-reported diagnostic rates of ASD and ADHD approximate to clinical administrative prevalence  are initially presented for the observed scores at baseline (whole sample) and 1-month follow-up. Changes in the measures from baseline to 1-month follow-up (using multiply imputed datasets) were then compared across the four groups using linear regression models, adjusting for child age, child gender, timing of the questionnaire, pandemic anxiety measured via PAS disease and consequence subscales at baseline, time spent outside doing physical activity, and keeping to a similar or regular routine factors , 34–38. The assumptions of homoscedasticity and normality were checked using descriptive data and plots, without formal statistical hypothesis testing. Homoscedasticity was checked by informally comparing standard deviation of change scores in each group, while the normality of change scores was inspected using histograms.The results from the imputed models are presented as differences in means for the change scores over the follow-up period, with the no/other mental health disorder group is the reference group. A positive score in the imputed model means that the average change (between the baseline and follow-up time-points) is greater in the diagnostic group of interest compared with the reference group. To elaborate, a positive score indicates that the diagnostic group of interest has done less well over time (in terms of the difference between baseline and follow-up scores) than the reference group. Conversely, a negative score means that the average change is less in the diagnostic group than in the reference group., i.e. a negative score indicates that the diagnostic group of interest has done better over time (in terms of the difference between baseline and follow-up scores) than the reference group.In terms of the direction of within-group change (i.e. whether the diagnostic groups of interest improve or deteriorate over the follow-up period), the outputs from the imputed models should be interpreted with reference to the observed mean scores at baseline and follow-up.The sample size was 6507 CYP, with a mean age of 9.4 years; 51% were male and 90% were White British/Irish ethnicity. Approximately 2.5% (n = 160) of the sample were reported as having ADHD, 7% ASD (n = 465) and 2.4% (n = 155) both ADHD and ASD,  are shown in Fig. For conduct problems, observed scores showed slight increases for the ADHD-only and reference groups, whereas slight reductions were noted for the ASD-only and ADHD + ASD groups. Imputed analysis confirmed that there was a modest reduction in conduct symptoms in these two ASD groups compared to the reference group, where there was a slight increase.For hyperactivity/inattention, observed scores suggest a slight reduction for the ADHD + ASD group, and an increase for the reference group. Imputed analysis revealed greater changes in scores for the reference group compared with all three diagnostic groups. Similarly, for total symptoms, observed scores suggested a deterioration amongst the reference group. The imputed analysis confirmed that over time, scores reduced more in ASD only and ADHD + ASD groups than in the reference group.In contrast, for impairment, observed scores suggested a deterioration among all four groups. However, the imputed analysis showed that the ADHD-only group appeared to show a greater reduction in scores over time than the reference group.It should be noted, that overall, despite a tendency for greater reduction in scores in the diagnostic groups of interest, scores remained higher in these groups than that of the reference group.Table Results from the imputed analysis demonstrated that parents of CYP with ASD-only reported greater change in their own anxiety (p = 0.016) and also that of their child (p < 0.037) than the reference group in relation to the disease sub-scale. Observed scores show a greater deterioration for the ASD group.With reference to the consequence sub-scale of the PAS Fig. , observeGiven the uncertainty about the mental health impacts of the pandemic for potentially vulnerable people with neurodevelopmental disorders such as ADHD or ASD, we investigated outcomes following the onset of the utilising data from the Co-Space longitudinal study . There wDespite concerns about the potential vulnerability of CYP with neurodevelopmental disorders, our findings did not indicate a significant worsening of emotional or behavioural symptoms over the initial 1-month period. Although it is difficult to draw definitive comparisons with other studies given the heterogeneity in timings, sample characteristics and analysis, our findings appear in keeping with other population-based studies which suggest little/no deterioration and/or possible improvements in mental health symptoms during the initial pandemic period , 39. GivThe findings that CYP with ADHD and/or ASD showed some small improvements in emotional and behavioural difficulties compared with the reference group may reflect possible differential impact between the groups of lockdown and school closures. It has been proposed that school closures may reduce academic and social pressures for children and young people , particuIn terms of study strengths, this study is amongst the first to present longitudinal data explore COVID-19 impact over time. The large sample size strengthens the study findings. The study also combined both validated and novel pandemic-specific measures to explore changes on established measures and COVID-19 changes. The study is also unique in controlling for a range of important confounders (such as routine changes and activity). However, there are also certain study limitations with the data that are important to recognise to inform cautious interpretation of the results. The sample were not a representative sample as they were self-selected, predominately white, British, employed and the responders were typically female parents, limiting generalisability of the findings. We do not have pre-pandemic data for the sample so baseline scores may reflect both pre-pandemic and in-pandemic difficulties. We therefore use our two time-points (baseline and 1-month follow-up) as an insight into short-term longitudinal changes in the early stages of the pandemic. As participants could sign-up to the Co-Space study over a given time period, the baseline and 1-month follow-up were not at exactly the same point in time for all participants. To mitigate this, we adjusted for questionnaire timing in the analysis. Additionally, we relied on parent-reported information and there was considerable attrition over time, although there was no evidence of selection bias in terms of follow-up responders. The primary analysis relied upon multiple imputation of missing data. Because of the limitations of multiple imputation in the presence of considerable attrition, guidelines recommend that these findings should be considered as hypothesis generating . We alsoIn terms of clinical and service implications, the findings from this longitudinal study highlight that CYP with neurodevelopmental disorders showed some small improvements in emotional and behavioural symptoms during the initial period of the pandemic, despite enduring levels of pandemic disease anxiety. Despite this small improvement, scores for emotional and behavioural symptoms remained higher for CYP with a neurodevelopmental disorder compared to those without. There was also an increase in functional impairment among CYP with ADHD. Given the exploratory nature of our study, these findings should be interpreted with caution and further research is required to fully understand the longer-term impact of the pandemic. As the possibility of further lockdowns or school closures remains, it is important for key adults such as parents, teachers, and clinicians to be aware of these findings while keeping in mind the importance of both individual and group-level vulnerabilities. It is also crucial that practitioners continue to remain mindful of, and sensitive to, the possible longer-term impacts of pandemic-related confinements and subsequent expectations around re-adjustments to pre-pandemic routines; where appropriate, asking CYP about their perceptions of these experiences.This study investigated differences in mental health and pandemic anxiety during the first UK lockdown for the COVID-19 pandemic, for CYP with and without ADHD and/or ASD. Baseline and 1-month follow-up data were analysed from the Co-Space study, a UK web-based longitudinal survey investigating the impact of the pandemic for 4–16-year-olds. The measures included the parent-completed questionnaires [Strengths and Difficulties Questionnaire (SDQ) & Pandemic Anxiety Scale (PAS)]. The study found that CYP with ADHD and/or ASD had higher scores on the measures at baseline than CYP without ADHD/ASD. Over the 1-month follow-up period, in general CYP with ASD showed a small but significant improvement in symptoms (SDQ), compared with CYP without ADHD/ASD. Despite this improvement, SDQ scores were still higher. CYP with ASD also reported to have experienced a worsening of disease anxiety (PAS) and CYP with ADHD a deterioration in terms of functional impairment. Although these findings should be interpreted tentatively, they highlight a mixed pattern of pandemic-related impact, with CYP with ADHD/ASD faring better in some domains but worse in others. Clinically, these findings highlight considerable heterogeneity and the need for practitioners to be mindful of individual, rather than group-level, vulnerabilities. Improved awareness and understanding of this heterogeneity in vulnerabilities is important for future pandemic preparedness, particularly in the event of possible further lockdowns or school closures.