Relatively little is known about the role of maternal functioning in terms of attention deficit hyperactivity disorder (ADHD) symptoms, attachment style and resilience as predictive factors for treatment outcome when offspring are diagnosed with ADHD.To investigate whether maternal functioning is associated with treatment outcome in children with ADHD.The study formed part of a larger naturalistic observational study of children with ADHD. A battery of self-report measures was used to assess selected factors in maternal functioning at the point of referral (baseline data); adult ADHD-symptoms, adult attachment style and adult resilience. Associations between these domains and child treatment response were subsequently examined in a 1-year follow up.Maternal ADHD-symptoms and degree of resilience were significantly correlated to symptom reduction in offspring diagnosed with ADHD. However, the association between maternal attachment style and child treatment response as measured by the ADHD-RS did not reach statistical significance.To our knowledge, this is the first study to consider potential protective factors along with risk factors in maternal functioning and the impact on child treatment outcome. The study contributes to our knowledge of the potential role of maternal functioning in treatment outcome for children with ADHD.The online version of this article (10.1186/s13034-018-0234-3) contains supplementary material, which is available to authorized users. Attention deficit hyperactivity disorder (ADHD) is the most commonly occurring neurodevelopmental disorder in childhood with a prevalence ranging from 3 to 5% and symptoms often continuing into adulthood . It is cThe etiology of ADHD is multifactorial, as both genetic and environmental factors have been evidenced in the development of ADHD , 6. For Maternal ADHD may be a potential risk factor in the development of offspring ADHD –21. MoreIn addition to the contribution of maternal ADHD symptoms to the increased risk of offspring developing ADHD, the quality of the mother–child relationship has also come under scrutiny. Indeed, both ADHD and attachment have been proposed as risk factors . ReviewiIn this study, the focus is on the significance of maternal resilience for parenting in situations where the child needs extra support.The aim of the present study was to examine associations between mothers’ functioning and treatment response in their children diagnosed with ADHD who are receiving care as usual.We hypothesized that maternal self-reported ADHD symptoms; self-reported attachment style and maternal resilience would all be significantly correlated with treatment outcome. More specifically, we anticipated the following; (1) higher maternal ADHD-symptom scores would be associated with lower ADHD symptom reduction in offspring within the first year of treatment. (2) Higher scores for self-reported anxiety or ambivalence on the attachment style questionnaire are associated with lesser symptom reduction in offspring. (3) A higher degree of self-reported maternal resilience is associated with better treatment response in offspring diagnosed with ADHD.The current study was part of a naturalistic observational study exploring different aspects of maternal functioning expected to influence treatment response in children diagnosed with ADHD.The families participating were recruited from two child psychiatric outpatient clinics in Region Zealand, Denmark. The four interviewers participating were the same at the two sites; two conducting maternal attachment interviews and two conducting child attachment interviews. Sixty-seven (N = 67) child-mother dyads were included in the follow up.Care as usual according to national guidelines [Of the 67 mothers, 64 (95.5%) provided adequate responses on the baseline questionnaires to include for analysis. Three dyads were excluded from the analysis as they had not responded to all the questions. Age, gender distribution and the diagnoses of the children, along with other sample characteristics of parents and children can be seen in Table idelines . At 3 moMaternal resilience was measured by the Resilience in Adults Scale (RSA)—a 33-item self-report scale for measuring resilience in adults. The scale covers six dimensions assessing protective factors at the personal level as well as at a family and a social level. The RSA is based on a seven point semantic differential scale with a positive attribute at the high end of the scale and a negative attribute at the low end of the scale. An example of a positive attribute in Personal Competence is ‘‘I know if I continue, I will succeed’’. Half of the items are reversed to reduce acquiescence biases. The maximum score achievable is 231 (high resiliency) and the lowest possible score is 33. The scale has been found reliable for distinguishing clinical samples versus the normal population –39.Maternal ADHD symptoms were measured using the Adult ADHD Self-Report Scale . The ASRS 1.1 is a 6-item screening version of a longer 18-item scale. It is used to assess ADHD symptoms in the previous 6 months and includes four items on inattention and two on hyperactivity. Symptoms are rated on a 5-point response scale . The total score ranges from 0 to 24. In a convenience subsample of subscribers to a large health plan in the US, the ASRS Screener was administered twice to assess test–retest reliability and then a third time together with a clinical interviewer. The ASRS Screener was found to be in high concordance with clinician diagnoses. Internal consistency reliability was in the 0.63–0.72 range and test–retest reliability (Pearson correlations) in the 0.58–0.77 range .strongly disagree) to 6 (strongly agree). In a study by Sibley and colleagues psychometric properties  of the ECR-R were investigated and documented [Maternal attachment style was measured using the Experiences in Close Relationships Scale—Revised (ECR-R)—36 items in total, 18 items assessing romantic attachment anxiety (model of self) and 18 items assessing romantic attachment avoidance (model of others). The questionnaire is a widely used self-report measure of adult romantic attachment and is based on the theoretical assumption that anxiety and avoidance are the two fundamental dimensions underlying attachment. Items are rated on a 7-point Likert scale ranging from 0 .The interview is a valid and widely established diagnostic measure and it allows clinicians to classify children and adolescents with respect to their psychiatric diagnoses according to DSM-IV systems. In a recent study, the convergent and divergent validity of two diagnostic groups, anxiety disorders and ADHD was investigated. It was concluded that the K-SADS-PL generates valid diagnoses of anxiety and ADHD including the predominately inattentive subtype .Child ADHD symptoms were measured using the revised ADHD-RS , 49  followed by a clinical evaluation in order to establish whether the family met the inclusion criteria.In order to lower the risk of selection bias, we applied consecutive recruitment, as all the families with children in the appropriate age range presenting the relevant referral diagnosis, were invited to participate.The data obtained through questionnaires and interviews in the two-stage inclusion process and a 1-year follow up period were analysed using structural equation modeling and mixed effects modeling for repeated measures  , 45.Only patients assigned an ADHD/ADD diagnosis according to DSM-V with ADHD (314.01) or ADD (314.00) in step two were included for follow up. The included families attended both a clinical and a research track separated from each other Fig. .Fig. 2OvApart from exchanging information on treatment initiation, child IQ and in the event of drop out from medical treatment, the research project was separated from the clinical track.care as usual consisting of standard medical treatment with methylphenidate as first choice for moderate and severe ADHD. The interventions were standardized and formalized according to national guidelines [The children included all received idelines .In Denmark, clinical guidelines adhere to recommendations from NICE-guidelines . RecommeMothers were asked to complete questionnaires regarding themselves. The questionnaires screened for ADHD symptoms using the ASRS 1.1, assessed attachment styles as relating to current romantic relationships using the ECR, and measured the degree of resilience using the RSA. All questionnaires were sent as links by e-mail from the online data managing system Easytrial.In order to obtain a high response rate in the follow-up period, we used the Easytrial© online clinical data management system. All questionnaires from the baseline procedure as well as the follow up sequence were sent out as links to the parents by e-mail. The system provided an opportunity to monitor non-responders and send out ‘gentle reminders’. Responses were collected directly in a secured database compliant with good clinical practice (GCP) and database security legislation.The families progressed to the follow up 3 months after the initial assessment  in ADHD-RS from baseline to the 12 month follow up represents the primary outcome’.In one-parent households, the schedule was sent to the household in which the child was residing. More than half (53%) of the families were one-parent households and only in one family was the child residing with the father.Treatment response was measured as the change in the ADHD-RS scale over the course of the 12 months of follow up. The change was calculated as the best fitting linear slope for each patient with time as a predictor of ADHD-RS. Due to some missed self-reports, this slope was in some cases based on only two observations in the follow up sequence with the other three missing (baseline and four follow up ADHD-RS measurements). A random effects linear regression was used to predict the slope of ADHD-RS change for each child. This slope is used as a continuous measure of treatment response. For instances of missing baseline measurements, the baseline score was approximated by an intercept estimate based on other measurements available. Data on missed self-reports is provided in Table The ECR, RSA and ASRS scores used are latent variable predictions derived from structural equation models. ECR and RSA items are modeled assuming multivariate normality. ASRS items are considered ordinal items and modeled using a logit link function. All three latent variable predictions are standardized with means at 0 and variances fixed to 1. The latent variable approach has the advantage of removing the residual (unexplained by the latent factor) variance for each item when predicting the latent variable. Measurement error associated with psychometric scales is minimized in this way.−1) a missing data incident . Mixed effects Poisson models were used for the missing data analysis.Because of some missing data on covariates, we used a full information maximum likelihood estimator implemented in Stata 14. Means and variances as well as covariance for exogenous variables were estimated and used as the basis for corrected regression estimates. Missing data due to non-attendance at the follow up measurements were assumed to be random, i.e. not associated with the unobserved outcome measurement. This assumption was substantiated by a missing data analysis showing no significant association between baseline ADHD-RS score and missing data  and between the ADHD-RS score preceding  had a maximum of one missed self-report.Whilst all fathers were invited to participate and all consented to do so, only a minority actually completed the questionnaires 22.4%). Consequently, the paternal response rate was too low to include for further analysis. Complete information from all planned assessments was obtained for 62.5% (N = 40) of the children. Two children were only measured twice from baseline to the 12 month follow up. Table 2.4%. ConThe following demographic variables were included in the analysis: gender, age, family history of mental illness and whether the child is living in a one or two parent household. A binary indicator of medical treatment and the number of non-attendances were also included as covariates. Table The current study was undertaken with the broad aim of attempting to shed further light on the role of maternal functioning in the treatment response of children diagnosed with ADHD. Informed by the literature and existing empirical findings we chose to evaluate three domains of potential importance in maternal functioning: self-reported ADHD symptoms, self-reported attachment style and degree of resilience. A sample of sixty-seven mother–child dyads with ADHD-diagnosed children was recruited. The children and families received care as usual, and treatment response was evaluated in terms of ADHD symptom-load measured at 3 monthly intervals over a 1-year period. We anticipated that all three maternal functioning factors would correlate with treatment response, independent of treatment strategy.The findings suggested a significant association between maternal self-reported ADHD symptoms and treatment outcome, measured by a reduction in children’s reported ADHD symptoms. Thus, mothers scoring high on ADHD symptoms had children who showed a lower reduction in ADHD symptoms at the 12 months’ follow up.Contrary to expectations, we found no significant correlation between maternal self-reported attachment style on the ECR and child outcome on the ADHD-RS.Lastly and in line with our prediction, we found a negative association between maternal resilience as measured by the RSA and offspring treatment response on the ADHD-RS. This suggested that a higher degree of resilience in mothers was associated with greater symptom-reduction in their children receiving care as usual.The correlation between maternal ADHD symptomatology and treatment outcome of children with ADHD may be increased level of conflict in the parent–child relationship and exacerbated negative parenting . Harvey Regarding ADHD and attachment, these have been found to constitute mutual risk factors and show extensive overlap in symptomatology, . HoweverIn terms of risk and resilience, numerous studies have documented the relationship between parental risk factors and child development. For example; association between family structure and mental wellbeing of children  were investigated and pointed to the significance of family trauma and family psychiatric history . FurtherResilient child development despite adversity and how to promote resilient parenting are topics of increasing interest –63. SurpAs resilience is generally regarded as a more stable trait than psychiatric symptoms  it may pSome studies in ADHD treatment have focused on parenting training and social skills training for children with ADHD. However, the evidence has not been convincing –69 whichThis study is unique in representing the first attempt at exploring the role of maternal functioning in predicting treatment response of children with ADHD; an area which has been lacking in previous studies , 16.The study is, to our knowledge, one of very few studies to address maternal resources as well as risk factors simultaneously and it clearly raises important questions for future research.Nevertheless, the current study has several limitations.Our study had a naturalistic design and applied consecutive recruiting in order to include and follow a sample representative of the population we intended to investigate. This was to keep selection bias to a minimum, and hence, we further kept the research track separated from the clinical treatment during the 1-year follow up. However, since a little more than half declined to participate, this then resulted in selection bias. When asked, the participant’s main reason for declining to participate was due to the stress of the many appointments entailed by the clinical track.Further, another limitation relates to the duration of the follow up period. As factors in the parent–child relationship are likely to emerge over time, a longer follow up would have been ideal.For example, the lack of correlation between maternal self-reported attachment style and child outcome on ADHD-RS may relate to the relatively short follow up period. This is supported by findings from other studies suggesting that the influence of medical treatment tends to wear off, making other factors more influential in long-term treatment strategies , 72.Another limitation concerns the sole reliance on self-reporting in the assessment of various aspects of maternal functioning as socially desirable responding has been shown to affect results in previous research . HoweverAlso, maternal ADHD symptomatology was assessed very specifically; other types of maternal psychopathology were not assessed and thus taken into consideration. For example, as maternal depression is known to be a risk factor for symptom severity in offspring ADHD , it woulDisappointingly, we were not able to draw any conclusions in relation to the role of fathers’ functioning in the treatment response of their children diagnosed with ADHD. The response rate of fathers was too low to include in the study. Whilst this is not unique to our study , previoCompared to other reported studies, the rate of comorbidity was very low in our study , 77. HowTaken together, our findings suggest that risk factors as well as protective factors in maternal functioning have an impact on treatment outcome in children with ADHD. This underlines the potential value of a broader assessment of maternal functioning, including screening of mothers for ADHD symptoms. This would permit the identification of parents with unmet needs for treatment and support, which might in turn lead to a better prognosis for their children. On the other hand, a greater focus on protective factors such as maternal resilience may be no less important in differentiating the subgroups of families who are at less of an immediate risk and who may therefore require less support and intervention.Additional file 1: Table S1. Correlation matrix.


Objective: Autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and anxiety are three of the most common childhood psychiatric disorders. Early trajectories of social avoidance have been linked with these psychiatric disorders in previous studies, but it remains unclear how social avoidance differentially predicts comorbid disorders in a high-risk genetic subgroup. Here, we delineate the association between trajectories of social avoidance from infancy and subsequent ASD, ADHD, and anxiety outcomes at preschool in children with fragile X syndrome (FXS), a well-characterized single-gene disorder highly associated with social avoidance as well as elevated rates of ASD, ADHD, and anxiety.Method: Males with FXS (n = 78) aged 4–62 months participated in a longitudinal study resulting in 201 assessments. The Social Avoidance Scale (SAS) documented socially avoidant behaviors from infancy in three domains—physical movement, facial expression, and eye contact during both the first minute and the last hour of an interaction. ASD, ADHD, and anxiety symptom outcomes at preschool were measured via parent-report questionnaires.Results: Increased social avoidance across infancy and preschool predicted elevated ASD symptom severity but reduced ADHD and anxiety symptom severity in males with FXS.Conclusion: ASD, ADHD, and anxiety symptoms relate inconsistently to social avoidance behaviors, providing new insight toward the debate of independence or overlap among these disorders in FXS and other disorders . The results suggest that the nuanced profile of the developmental and temporal aspects of social avoidance may inform more the accuracy of differential diagnoses of comorbid psychiatric disorders in FXS. Psychiatric disorders are debilitating and common, affecting more than one in five children . Autism not mean levels at any specific age, predict ASD outcomes  is a well-characterized single-gene disorder highly associated with co-occurring features of ASD, ADHD, and anxiety, making the disorder an ideal candidate for studying social avoidance trajectories in a “high risk,” genetically-defined sample. FXS is the most common inherited cause of intellectual disability (ID), affecting ~1 in 4,000 males and 1 in 8,000 females . FXS is  for ASD , 15 and  for ASD , 17. Anx for ASD . In addi for ASD –21. The  for ASD .The validity and independence of ASD, ADHD, and anxiety disorders in FXS has been challenged, not surprisingly, with debate regarding whether they represent “true” comorbidities or whether co-occurring symptomology shared across these disorders results in artifactual diagnostic categorization , 23. ForSocial avoidance is a core or associated feature of ASD, ADHD, and anxiety and is a hallmark characteristic of males with FXS , 26. In Using a prospective longitudinal design, we examined the relationship between trajectories of social avoidance from infancy to the severity of ASD, ADHD, and anxiety outcomes at preschool in males with FXS. We hypothesize that males with FXS who exhibit higher ASD and anxiety symptoms will exhibit higher levels of social avoidance that will intensify across age. This relationship will not be present in ADHD outcomes. This hypothesis is based on the fact that social avoidance is a core feature of both ASD and anxiety, whereas in ADHD, social avoidance may present as a secondary product of attention-related difficulties in managing social situations. Distinguishing the relationship of the level and trajectories of social avoidance to ASD, ADHD, and anxiety in FXS will provide novel information about their differential impact on these three psychiatric disorders that occur frequently and are very impairing in this population. As such, this work is critical to improve differential diagnostic processes and direct targeted treatment.FMR1 gene (>200 CGG repeats) was confirmed through genetic testing. Subsets of these data have been published previously . Participant's parents at all sites provided written informed consent prior to participation. All of these studies focused on documenting the phenotype of FXS across early development with identical procedures and a subset of common measures. The age of the samples, however, varied across studies with some focused on infants while others focused on preschoolers. Participants were drawn from these studies if they were male, under 6 years of age and had at least one assessment that included all of the measures listed below. The advantage of including data from multiple studies allows us to generalize across contexts so our findings are not restricted to one discrete age group and to increase the sample size given the relatively low prevalence of FXS. All participants with FXS were recruited from past studies, national parent listservs, social media, the National Fragile X Foundation, and the Research Participant Registry Core of the Carolina Institute for Developmental Disabilities at the University of North Carolina at Chapel Hill. The full mutation of the eviously , 26; howM = 27.31 months, SD = 15.12) while chronological age at the outcome assessment ranged from 23.28 to 70.10 months . The average time between the first and final assessment was 29.39 months (range of 11.04 to 59.64 and SD = 12.10). Nine participants only had one assessment, whereas the rest (n = 65) had 2 or more assessments.From the potential pool of participants, 74 males with FXS representing 201 assessments met criteria for study inclusion. Chronological age at the first assessment ranged from 4 to 62 months . Intra-class correlation coefficients (ICCs) reflect a moderate to high degree of reliability between raters on all of the SAS scales, with a range from 0.82 to 0.90. The capacity for the SAS to capture dynamic aspects of social avoidance is central given evidence that a decrease in avoidance between the two ratings is a core feature of FXS and one that differentiates those with and without comorbid ASD ] rbid ASD , 26. Ther = 0.90;  and ADHD . Anxiety and ADHD were moderately related . Thus, separate models were used for each outcome. We analyzed our primary research questions using random effect latent variable models, which account for variable assessment intervals. Specifically, we used 2-level random slope and intercept model with continuous child-level outcomes. The two levels of our model correspond to (1) variation within child  and (2) variation between children. Our model is represented in Analyses were conducted using SPSS 24 , R Core S, the solid circle on top of the line seen in I, the solid circle within the SAS box in In the within portion of our model , we regressed social avoidance measures  on the age of the child to estimate a) a latent slope  slopes and intercepts for each SAS predictor  for the first minute and last hour of interaction. These global scores are found in In our full models, age and SAS scores were scaled to a mean of zero and variance of one. Results from the full models supported our hypotheses that SAS levels and trajectories would predict ASD outcomes. However, our hypothesis that SAS levels and trajectories would predict anxiety and ADHD outcomes was only partially supported (see B = 5.84(1.67), z = 3.51, p < 0.001, CI), and a trajectory of increasing physical avoidance (B = 7.93(3.66), z = 2.17, p = 0.030, CI) during the last hour of interaction predicted more severe ASD symptomology at outcome. We also found that both a higher mean level (B = 3.16(0.31), z = 10.12, p < 0.001, CI) and a trajectory of increasing facial expressions of social wariness (B = 51.47(0.15), z = 355.02, p < 0.001 CI) during the first minute of interaction predicted more severe ASD symptomology at outcome. However, only the mean level, not the trajectory, of facial expression during the last hour of interaction (B = 8.51(2.50), z = 3.41, p = 0.001, CI) predicted ASD symptomology. Finally, a higher mean level (B = 8.15(2.52), z = 3.23, p < 0.001, CI) of avoidant eye contact during the first minute of interaction predicted more severe ASD symptomology at outcome, whereas the trajectory did not. However, both a higher mean level (B = 10.05(2.02), z = 4.97, p < 0.001, CI) and a trajectory of increasing avoidance of eye contact (B = 8.22(2.21), z = 3.72, p < 0.001, CI) during the last hour of interaction predicted more severe ASD symptomology at outcome.Physical avoidance in the last hour but not the first minute significantly predicted ASD outcomes. We found that both a higher mean level (B = −10.79(3.73), z = −2.89, p = 0.004, CI). No other SAS variables predicted ADHD outcomes.For ADHD, only the trajectory of increasing physical avoidance during the first minute of social interaction predicted decreased ADHD symptomology at outcome (B = −11.33(5.47), z = 2.07, p = 0.038, CI), No other SAS domains predicted Anxiety Outcomes.For Anxiety, only the trajectory of increasing physical avoidance during the first minute of social interaction predicted decreased anxiety symptomology at outcome  and parameter  with increased social avoidance predicting elevated ASD severity and, surprisingly, it also predicted reduced ADHD and anxiety severity at outcome. For ASD outcomes, we found that elevated physical avoidance, increased facial expressions of avoidance and reduced eye contact all signaled risk for the later onset of more severe ASD symptoms. Specifically, elevated levels of physical movement during the final hour and elevated levels of facial shyness and avoidant eye contact during both the first minute and final hour were associated with increased severity of ASD features. A trajectory of increased avoidance in physical movement and avoidant eye contact during the last hour and for the first minute for facial shyness also were associated with increased severity of ASD outcomes. And, while social avoidance during initial social encounters provided some signal for the later onset of ASD symptoms, it was elevated social avoidance during social encounters with familiar people that reflected the strongest indicator of more severe ASD symptomology. In contrast, only trajectories of increasing social avoidance during initial interactions were associated with reduced severity of ADHD and anxiety outcomes.Psychiatric disorders are common and impairing in children, and efforts to increase understanding of the prodromal and predictive features of these disorders represent significant impact given the known benefits of early intervention. Given the high rates of ASD, ADHD and anxiety in males with FXS, studies of the developmental trajectories of symptoms associated with these psychiatric disorders can impact the timing and targets for intervention. This work has implications not only for individuals with FXS but also for those who exhibit features of ASD, ADHD and anxiety of known or unidentified etiology. Because of the high rates of comorbidity and the monogenic etiology of FXS, this population provides a saturated model for risk that includes more “signal” for detecting meaningful associations than can be observed in studies of the general population . The oveBased on our results, increased social avoidance across infancy and preschool predicted elevated severity of ASD symptoms but reduced ADHD and anxiety symptoms in males with FXS. A nuanced set of relationships was apparent with ASD predicted by specific social avoidance features that were entirely unique from those that predicted ADHD and anxiety outcomes. Surprisingly, identical predictors  emerged for both ADHD and anxiety outcomes. The trajectory of increasing social avoidance appears to be one of the most salient features as it predicted ASD, ADHD, and anxiety outcomes whereas an elevated level of social avoidance only predicted ASD features. However, it was the trajectory of initial interactions with unfamiliar people at the beginning of the assessment (first minute) that predicted reduced ADHD and anxiety whereas the trajectory of interactions with both unfamiliar people (beginning of the assessment) and people who had become more familiar by the end of the assessment (last hour) predicted ASD. These findings highlight the importance of capturing social avoidance across multiple domains and the value of including both initial responses to unfamiliar people as well as responses to people who have become familiar over the course of the assessment. Overall, these results suggest that elevated social avoidance emerging during infancy may be a salient marker for the onset for ASD and of reduced risk for ADHD and anxiety in males with FXS.The finding that multiple indicators of social avoidance across the infant and preschool years' signal risk for the emergence of elevated ASD symptoms is of great importance. ASD is one of the most prevalent and impairing psychiatric disorders associated with FXS, and FXS is the leading identified genetic cause of ASD . DespiteTrajectories of social avoidance across infancy and preschool were also associated with ADHD and anxiety symptom outcomes, however, in the opposite direction to that expected with trajectories of elevated physical avoidance during initial social interactions predicting lower ADHD and anxiety symptom severity at outcome. These relationships were unexpected as we anticipated no relationship with ADHD as social impairment is an associated, but not core, feature of ADHD. The unexpected direction of the relationship could signal strong emotion regulation skills in these children. Per this interpretation, children who have less severe ADHD and anxiety symptom outcomes may have learned to manage their emotions by physically retreating from the source of stress, in this case, the approach of an unfamiliar person. This finding could also suggest a developmental effect in that children with less severe ADHD and anxiety outcomes may respond to social challenge differently across age with increasing physical avoidance of novel social partners more likely at preschool age with less physical avoidance during the infant and toddler years .The results reported here are consistent with a recent study, which identified unique and distinct early-life predictors of ASD and ADHD, but are inconsistent with the same study documenting overlap in predictors of ASD and anxiety . SpecifiOne of the most important findings of this study is that ASD, ADHD and anxiety symptoms relate inconsistently to social avoidance behaviors, providing new insight toward the debate of independence or overlap among these disorders in FXS and other disorders . As noted above, ASD was the only disorder in which elevated social avoidance predicted increased severity of symptoms. In fact, increased social avoidance predicted reduced symptom severity for ADHD and anxiety. Thus, elevated social avoidance is a trait that uniquely predicts ASD and not ADHD or anxiety despite social avoidance being a feature of all three disorders. Our preliminary correlational analyses confirm this conclusion as ASD was not related to either ADHD or anxiety. This finding regarding the apparent independence across these disorders is particularly striking considering the high prevalence of 48.72 and 56.41% for ASD and ADHD who are above the clinical cut-offs, respectively. These rates are generally consistent with extant literature , 17. In This study has a number of important clinical implications. First, we demonstrated that both the level and trajectory of social avoidance show meaningful individual differences in the expression of ASD, ADHD, and anxiety symptom outcomes in males with FXS. This suggests that the nature and function of social avoidance is complex, and caution should be taken to attend to the nuanced profile of social avoidance to ensure diagnostic accuracy with developmental and temporal aspects of social avoidance carefully considered. Specifically, both initial and prolonged social avoidance should be integrated into differential diagnoses, and this practice rests on clinical knowledge and observation as some tools  may not be sufficiently sensitive to these clinical factors. Second, our findings confirm that social avoidance manifests very early in development, and we extend initial work in this area by demonstrating that early trajectories of social avoidance may index risk for ASD while signaling resilience or a protective factor for ADHD and anxiety in young males with FXS. This information is critical to inform the timing and targets for treatment.(SD = 1.04), with some children having as many as five assessments, and some children having as few as one assessment. Because of this range, we modeled our trajectories using simple linear trends; however, in reality, these trends are not likely entirely linear. Thus, our understanding of how developmental changes in social avoidance influences later outcomes is constrained to linear trends , rather than more nuanced profiles that could be estimated with additional data. These are important factors for future work, as is inclusion of a contrast group to see if these findings generalize to other clinical or non-clinical groups .Despite inclusion of the largest sample of males with FXS to date in a study focused on social avoidance and integration of multiple outcomes with repeated measures, there are a number of limitations. These include failure to include females and reliance on behavioral ratings without biomarkers. We also targeted the first years of life as a critical developmental period as our focus was on early signs and symptoms vs. diagnoses. However, the focus on this early childhood period likely constrained our ability to fully detect the relationship of social avoidance to anxiety given that symptoms of anxiety emerge later in development than ASD and ADHD symptoms. Also, with regard to our models, the average amount of assessments available across children was three This study was carried out in accordance with the recommendations of Human Subjects Research University of South Carolina Institutional Review Board and the Institutional Review Board at University of North Carolina at Chapel Hill, with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the University of South Carolina Institutional Review Board and the Institutional Review Board at the University of North Carolina at Chapel Hill.JR conceptualized the study and oversaw data collection and provided leadership for producing the paper. EW and SM analyzed the data with consultation from BT and AH. HC played a key role in writing the paper with input from AH. SO, DR, and AB wrote sections of the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor declared a shared affiliation, though no other collaboration, with several of the authors, JR, EW, AH, SM, SO, AB.


Limited data exist related to low birth weight (LBW) incidence and risk factors in Western China. This paper aims to assess LBW and its relationship with antenatal care (ANC) in the poor counties of Western China. A community-based study in rural Western China was conducted in 2011. A kernel distribution was used to estimate the adjusted LBW incidence, and associations between LBW and socio-demographic or maternal factors were examined using multilevel logistic regression. Among 8,964 participants, 65.7% were weighed at birth. Crude LBW incidence was 6.6% and the adjusted rate was 9.3%. The study revealed that risk factors of LBW are being female, raised within a minority group, and with a family income below the national poverty line. For maternal risk factors, LBW was positively associated with not attending at least five or eight ANC visits, not receiving any ANC during the first trimester, and not having access to assess certain ANC content . There is urgent need to promote quality ANC in poor and rural areas of Western China and to prioritize vulnerable women and children who will benefit from quality ANC. In both developing and developed countries, low birth weight (LBW)  is the leading cause of neonatal death as well as the primary reason for childhood mortality and morbidity . GloballIn China, the incidence of LBW was 5.9% in 1998 and 6.1% in 2011, which is lower than the global average .Many studies in developing countries have provided evidence that the improvement of quality antenatal care (ANC) can significantly mitigate the incidence of LBW. Quality ANC includes accessibility to ANC, the number of ANC visits, and the content of ANC –14. To iIn this study, we assess the LBW prevalence in resource-deficient areas in Western China and examine the association of ANC quality on LBW delivery by conducting a population-based survey in forty-two counties in rural Western China.Data were collected from a community-based, cross-sectional survey conducted in forty-two counties, with a total population of 11, 000, 000, in seven Western provinces of China: Gansu, Guizhou, Qinghai, Yunnan, Sichuan, Tibet, and Xinjiang. The annual income per capita of this rural population in forty-two counties  was below the national average  in 2010 . The undA multistage sampling technique was used in each of the surveyed counties. First, fifteen administrative villages were randomly selected based on the probability proportional to size (PPS) methodology in each of the counties. Second, two rural villages in each administrative village were selected randomly with the PPS method. Third, in two natural village, ten children under three years old were randomly selected from a list of names of the local children who were younger than three-years-old. However, as the population in Tibet is sparsely distributed, only two or three children were randomly selected in each rural Tibetan village. Before the fieldwork, all interviewers had been trained using the same comprehensive standard. Face-to-face interviews with mothers or caregivers were conducted in 2011 using a structured questionnaire.The structured questionnaires were designed using UNICEF’s Multiple Indicator Cluster Survey’s (MICS) format and modified on the basis of a literature review, expert consultation, and a pilot study . The queLBW was defined as birth weights lower than 2,500 grams . The queBased on international guidelines and national basic public health service guidelines in China –23, indiCollected data was entered into a computer database and cleaned before analysis by using Epidata3.0 software package. STATA 15.0 for Windows statistical software package was used to carry out statistical analysis. Birth weights less than 250 or more than 5500 grams were classified as “missing”. The χ2 -test was used to examine the proportional differences between infants weighted and not weighted at birth. The significance level was set at p <0.05, two-tailed. To account for the abundance of infants at 2,500g (the cut-off point of LBW), the adaptive kernel smoothed cumulative distribution was fitted over the frequency distribution for birth weights and was used to estimate the adjusted LBW incidence , 25. SocIn total, 8,964 children aged 0–35 months were surveyed . After applying the sampling and age distribution weight, there was a total of 5,891 children (65.7%) who were weighed at their birth, while 3,073 children (34.3%) were not weighed, as shown in Among the 5,891 children who were weighed at their birth, the crude LBW incidence of our sample population was 6.6% (387 cases), and 4.5% children were found to have received a rounded birth weight of exactly 2,500g as measured at their birth. The histogram and kernel density distribution of birthweight after adjusting for the abundance at 2,500g are shown as Among the 5,891 interviewees of the children who were weighed at their birth, 4,311 (73.2%) of them were maternal guardians of the child. There was no significant statistical difference of LBW incidence between children with mothers as the interviewee (6.6%) and other caregivers as the interviewee (6.4%) . Additionally, Lastly, The study focused on LBW and ANC quality of impoverished rural Western China. The results revealed that about 9.3% of neonates born within the surveyed area had a LBW. Inadequate ANC visits and lack of certain ANC services were shown to be associated with of LBW after adjusting for other factors in the multilevel model. However, the ANC coverage, accessibility, and treatment quality are still low in the current poverty-stricken rural areas of Western China.According to the most recent assessment, 8.1% of children in South China had a LBW in 2017 . This prANC is crucial for detecting infant abnormalities during crucial windows of neonatal development. This is especially true for women living within resource-constrained areas. Early detection ensures timely diagnoses and therapeutic interventions which ultimately contribute to averting LBW and other general complications which may negatively impact both the mother and neonate alike. In the analysis, at least five or eight ANC visits during pregnancy were shown to have protective effects for the mitigation of LBW. The cut-off point of eight ANC visits had a stronger association with LBW (higher OR) than five visits, but only few women could reach this indicator. A study in Brazil has shown that at least seven visits were protective in reducing LBW incidence; in comparison there were no significant differences of LBW incidence between mothers who received 4 or more visits and 1–3 visits in Nepal , 12. TheThe sex ratio of our study population is skewed from the natural sex ratio at birth ; higher than the sex ratio at birth in China of the same period (1.16–1.17 in 2008–2011). Given thNumerous observational studies have demonstrated that the adequacy of ANC contents  were associated with LBW and many other pregnancy outcomes , 14, 31.Previous studies have demonstrated that taking nutritional supplements during pregnancy can mitigate the risks of gestational complications and is advantageous to pregnancy outcomes –36. Howe,. Ch. Ch,[39],. TherefoThe study notes that there are several limitations that raise concern when acquiring an estimation of LBW incidence. First, the birth weight of numerous children in this study was obtained by collecting self-reported weight from caregivers rather than from professional medical records; the memory of caregivers may not always be accurate and may lead to some recall bias, which could lead to an over or under-estimated incidence. Second, there was a large proportion of unweighted children in the study. Nearly one third of the children in this survey were not weighed at birth and were excluded in the following analysis. When comparing the unweighted children to those weighted, the unweighted children were more likely to be delivered at home and have a lower socio-economic status, which may make them more vulnerable to have a LBW. Therefore, the missing birth weights of these unmeasured children may cause an underestimation of the true magnitude of the LBW problem in the surveyed area.Another issue that raised concern in this study is that not all known risk factors, such as maternal medical conditions and behavioral factors, were considered. Several studies have provided evidence that during pregnancy, the mother’s nutritional status; behaviors ; maternal infections; and complications, such as pre-eclampsia or diabetes, may affect the growth and development of the fetus as well as the duration of the pregnancy , 41–43. In addition, this study only measured the contents of ANC and number of visits that women received during pregnancy, which only represents the overall quality of ANC in the study area to a certain extent. In China, ANC is part of the basic public health services regulated by the central and local governments, and the quality of ANC is mostly influenced by the institutions providing it. Unfortunately, we did not measure the institutional quality of ANC. Further studies regarding ANC quality should focus on both the services women receive and the institutions that provide those services.To conclude, based on our estimation, LBW is still a noteworthy public health problem in Western China. LBW is more common among female children, those born at home, rhose born within an ethnic minority, and those from a poor family. As the study suggests, adequate and quality ANC care is associated with LBW incidence. The study also revealed an insufficiency of ANC in rural Western China. LBW incidence is a crucial indicator of maternal and child health progress and is closely associated with childhood and adulthood mortality and morbidity. Currently, there are scarce data on LBW in China, especially in remote areas of the Western regions. This study and its results contribute to a broader understanding of this issue and can help improve future allocations of ANC services and strategic investments to vulnerable groups impacted by LBW.All procedures performed in the studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.Informed consent was obtained from all individual participants included in the study.


High rates of attention deficit/hyperactivity disorder (ADHD) and anxiety symptoms have been documented in autism spectrum disorder (ASD), and have been associated with social and adaptive impairments. The study examined the frequency of clinically elevated ADHD and anxiety symptoms in an ASD group in comparison to a non-clinical group, compared the clinical presentation in the ASD group with and without ADHD and anxiety, assessed which child and familial variables add to the severity of Inattention, Hyperactivity/Impulsivity (HI), and anxiety symptoms, and evaluated whether having clinically elevated ADHD and/or anxiety symptoms adds to the prediction of adaptive functioning in ASD. The study included 260 participants diagnosed with ASD (mean age: 7.5 ± 1.1), using standardized tests. The rate of clinically elevated ADHD and anxiety symptoms in ASD was 62.7 and 44.6%, respectively, and symptom severity was significantly greater than the non-clinical sample. The entire population was divided into four subgroups: ASD alone, ASD+ADHD, ASD+anxiety, ASD+ADHD+anxiety, based on the parental behavioral questionnaire. The ASD alone group showed less severe autism symptoms in comparison to the other groups. Having ASD+ADHD symptoms was associated with greater impairments in socialization adaptive skills. Only the group with ASD+ADHD+anxiety was associated with poorer daily living adaptive skills. Regression analyses for prediction of ADHD and anxiety symptoms revealed that being a female and having lower adaptive skills scores predicted higher Inattention severity; being older, having better cognition, and more severe Restrictive Repetitive Behavior symptoms predicted more severe HI symptoms; being older and having more severe social impairments predicted higher anxiety scores. A regression analysis for the prediction of adaptive skills revealed that in addition to cognition and autism severity, the severity of Inattention symptoms added to the prediction of overall adaptive skills. In light of these findings, clinicians should diagnose these comorbidities in ASD early on, and provide effective interventions to reduce their negative impact on functioning, thereby improving outcome. Autism spectrum disorder (ASD) is a neurobehavioral disorder defined by social- communication deficits and restricted and repetitive behaviors that are typically detectable in early childhood and continue into adulthood . ASD-speADHD is a common neurodevelopmental disorder with a prevalence estimated at 7.2% in the general population . ADHD isThe prevalence of anxiety disorders in the general population is 6.5% , rangingRates of anxiety in the presence of ADHD in the general population range from 13 to 50%, and these comorbidities together are associated with greater risk of long term impairments than children with either condition . HoweverIn light of this, it is possible that the clinical presentation in ASD would not be worsened by having anxiety symptoms. Therefore, is it important to further investigate the contribution of having anxiety symptoms in ASD with comorbid ADHD on various aspects of the clinical presentation.The study has several aims. First, to evaluate the frequency of ADHD and anxiety symptoms in the participants diagnosed with ASD and to compare them to non-clinical standardized samples. Second, to compare the clinical presentation in the ASD participants with and without ADHD and anxiety, in terms of autism symptom severity, adaptive skills, and cognitive ability. Third, to assess the relationships between the severity of the ADHD and anxiety symptoms and the autism severity and adaptive functioning. The fourth aim is to assess which variables  add to the severity of Inattention, Hyperactivity/Impulsivity, and anxiety symptoms individually. The fifth aim is to assess whether having ADHD and/or anxiety symptoms adds to the prediction of adaptive skills functioning in the ASD participants, beyond the role of the child's other characteristics.Clinically elevated ADHD and anxiety symptoms frequently occur in children with ASD. Rates of ADHD and anxiety in the ASD group will be significantly higher compared to the non-clinical standardized samples.The participants with ASD and clinically elevated ADHD and/or anxiety symptoms, and particularly those with ASD+ADHD+anxiety, will present with more severe autism symptomatology, lower cognition, and lower adaptive skills, in comparison to those without these comorbid symptoms.Higher cognition, more severe autism symptoms and lower adaptive skills will be associated with and predict more severe ADHD and anxiety symptoms.More severe ADHD and anxiety symptoms in ASD will be associated with and predict lower adaptive functioningWe have several hypotheses:This study is the first to examine a large group diagnosed with ASD and two major comorbidities and assesses their relationship to the clinical presentation.A semi-structured interview administered to parents, designed to make a diagnosis of autism according to DSM-IV criteria. Diagnosis of ASD was made on meeting the cutoff points of the ADI-R algorithm scores in the three domains: social interaction, communication, and restricted repetitive behavior (RRB) . Autism A semi-structured, interactive schedule conducted by skilled professionals designed to assess social and communicative functioning in individuals who may have ASD . The scoSD = 15 , each of which yields a standard score . Higher SD = 10); higher T-scores reflect greater psychopathology , anxiety, and other co-morbid behaviors. Estimates of symptom severity are obtained using T-scores  were excluded from the study. The final cohort included 260 participants , with a mean age of 7 years and 5 months (SD = 1 year and 1 month). All the participants were Caucasians, and Hebrew was the spoken language.The study was conducted at a national tertiary center for autism that is involved in diagnosis, treatment, and research in ASD. Data from clinical records were collected on 1,143 children who were assessed for a possible ASD diagnosis between January 2010 and December 2015. The children underwent a comprehensive evaluation including a neurological assessment by a pediatric developmental neurologist, and behavioral and cognitive evaluations conducted by a skilled interdisciplinary team. Information about previous diagnoses was obtained from previous assessments performed in other centers. Assessment of ASD was obtained using standardized tests, the Autism Diagnosis Interview-Revised (ADI-R)  and the The results for the ADI-R were available for all 260 participants and for the ADOS for 255 participants. Cognitive and developmental abilities (IQ/DQ) were assessed using the Wechsler Preschool and Primary Scale of Intelligence (WPPSI)  or the WN = 68); the second group, with an ADHD index ≥60, and anxiety <60, was designated as ASD with ADHD ; the third group, with an ADHD index <60 and Anxiety ≥60, was designated as ASD with anxiety ; the fourth group, with an ADHD index ≥60 and anxiety ≥60, was designated as ASD with anxiety and ADHD .In the current research, although parents' and teachers' CRS scores are presented and compared, only the parents' questionnaire was used to define the groups, in order to avoid the impact of ADHD medications given during the school day, which may affect the severity of ADHD symptoms as reported by the teachers. The study participants were divided into four groups based on the ADHD index and anxiety scales of the Conners Parents' Rating Scales–Revised: Long (CPRS-R:L) questionnaire : the first group, with an ADHD index <60, and anxiety <60, was designated as ASD alone , a one-way MANOVA with a repeated measure of coder was performed for the Inattention, HI, and Anxiety subdomain scores.post-hoc Scheffe tests were performed.Comparisons of demographic data between the four examined groups  included sex using non-parametric chi-square analysis, age using one-way ANOVAs, and parental ages and educational attainment using one-way MANOVAs. Comparisons between the four examined groups of the dependent variables—including IQ/DQ scores, ADI-R subdomain  scores, ADOS subdomain (SA- and RRB-CSS) scores, and VABS composite and subdomain  scores—were performed using one-way ANOVAs and MANOVAs. When a MANOVA yielded a significant group effect, individual ANOVAs were performed for each of the examined variables. In the analyses that yielded a significant group effect, Next we examined the correlations between CPRS subdomain  scores with IQ scores and VABS, ADI-R, and ADOS subdomain scores using Pearson correlation analyses.Finally, to identify the variables that contributed to the explained variance in the CPRS subdomains, three five-step hierarchical linear regression analyses were performed with CPRS Inattention, HI, and Anxiety scores as the dependent variables.To identify the variables that contributed to the explained variance in the VABS composite scores, another five-step hierarchical linear regression analysis was performed.All procedures performed in this study were approved by the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The Helsinki committee of the medical center waived the need for informed consent, as the study was retrospective and all the data were derived from the clinical charts.The frequency of clinically elevated ADHD symptoms as reported by the parents (CPRS ADHD index ≥60) in the entire ASD group was 62.7%. “Inattention” symptoms (CPRS DSM-IV inattentive ≥60) were reported in 67.3% of the participants, and “hyperactivity/impulsivity” symptoms (CPRS DSM-IV hyperactive ≥60) in 56.5% of the participants.The frequency of clinically elevated anxiety symptoms as reported by the parents (CPRS anxious-shy ≥60) in the entire ASD group was 44.6%.n = 194) of the study participants were not previously diagnosed with ASD. Among those participants, 52.9% had at least one previous medical, neurodevelopmental and/or behavioral diagnosis. The most prevalent diagnosis was ADHD  followed by developmental delay  and language disorder . Among the group with a previous ASD diagnosis , 10 participants (15%) received an ADHD diagnosis in addition to the principal diagnosis of ASD. Comparing the CPRS subdomain mean scores of the ASD group to the mean scores of the non-clinical group (ages 3–12) taken from the CRS manual revealed significantly higher scores in the Inattention , HI  and Anxiety  subdomains for the current study's ASD group.At the time of evaluation at the Autism Center, 74.5%  = 38.53, p < 0.001, η2 = 0.32]. For the clinically elevated ADHD symptoms (Inattention and Hyperactivity/Impulsivity), the teachers' CRS scores were lower than the parental CRS. In contrast, for clinically elevated anxiety symptoms, teachers' CRS scores were higher than the parents'. For the clinically elevated CRS Hyperactivity/Impulsivity and the CRS anxiety scores, the effect size was medium. However, for the clinically elevated CRS Inattention scores the effect size was small.As presented in Table p > 0.05]. As presented in Table post-hoc Scheffe analysis did not reveal any significant difference between each pair of the groups.We compared the four defined groups based on the CPRS ADHD index scores and the anxious-shy scores. The male:female ratio did not differ significantly among the groups in a non-parametric chi-square analysis . When examining each subdomain separately, the daily living skills and the socialization subdomains yielded a significant group main effect with medium effect size (Table p < 0.001); for the socialization subdomain, the ASD alone group had significantly higher scores than the ASD+ADHD group (p < 0.01) and the ASD+ADHD+anxiety group (p < 0.05) (post-hoc Scheffe).Regarding adaptive behavior skills, using a one-way MANOVA, a group effect was found . Separately examining each ADI-R subdomain using one way ANOVAs yielded a significant group effect in all ADI-R subdomains (Table p < 0.05) and the ASD+ADHD group had significantly lower scores than the ASD+ADHD+anxiety group (p < 0.05). For the communication and RRB subdomains, the ANOVAs yielded medium effect sizes. For the communication subdomain, only the ASD alone group had significantly lower scores than the ASD+ADHD+anxiety group (p < 0.001). For the RRB subdomain, the ASD alone group had significantly lower scores than the other three examined groups (0.001 > p < 0.01) (post-hoc Scheffe tests).We then compared autism severity in the four examined groups, using the ADI-R scores, which were based on parental reports, and the ADOS scores, which were based on professional assessments. Comparing ADI-R subdomain scores between the four examined groups using a one-way MANOVA revealed a significant group effect , however, the separated ANOVAs for each subdomain did not yield a significant main effect.Comparing the ADOS-CSS between the defined groups, the one-way MANOVA yielded a significant group main effect [We examined the correlations of all three CPRS subdomains–Inattention (IA) Hyperactivity/Impulsivity (HI) and Anxiety, with VABS, ADI-R, and ADOS CSS subdomain scores Table . We usedTo identify variables that contributed to the variance in the CPRS scores, we applied three five-step hierarchical linear regression analyses using the CPRS Inattention, Hyperactivity/Impulsivity, and Anxiety scores as the dependent variables. We used continuous scores for these analyses. The independent variables of age and sex were entered in the first step, maternal education in the second step, cognitive scores in the third step, the ADI-SI, ADI Communication, and ADI RRB scores in the fourth step, and the VABS composite score in the fifth step.As presented in Table The second regression analysis with CPRS IH scores as the dependent variable Table  explaineThe third regression analysis with CPRS anxiety scores as the dependent variable Table  explaineAn additional five-step hierarchical linear regression analysis using the VABS composite scores as the dependent variable was applied to identify variables that contributed to the variance in the child's adaptive behavior. Independent variables included age and sex in the first step, maternal education in the second step, cognitive scores in the third step, ADI-R SI, Communication and RRB subdomain scores in the fourth step, and CPRS Inattentive, HI and Anxiety scores in the fifth step. As presented in Table The current study found an increased frequency of clinically elevated ADHD symptoms 62.7%) as reported by the parents in a large, well-characterized group diagnosed with ASD. Both clinically elevated 'inattention' symptoms and 'hyperactivity/impulsivity' symptoms were documented at high rates in the ASD group (67 and 57% respectively). These findings were emphasized when comparing the current study's ASD group with the CRS manual's non-clinical group. This was in accordance with our hypothesis. The current study supported previous studies that reported higher ADHD symptom frequencies (16–85%) in ASD % as repo, 25.In addition, increased frequency of clinically elevated anxiety symptoms (44%) was found in the entire ASD group of the current study. These findings were emphasized when comparing the current study's ASD group with the CRS manual's non-clinical group. The clinically elevated anxiety symptoms are in accordance with previous reports , 27 and Differences in informant reports of clinically elevated ADHD and anxiety symptoms were also of interest. Parents reported more severe ADHD symptoms, while teachers reported more severe anxiety symptoms. This can be explained as almost one third of the study participants received medication for ADHD, which decreased symptom severity in the structured school setting. In contrast, the school environment provides more stressful social situations, which may lead to more noticeable anxiety symptoms. Therefore, we chose to use only the parental reports for the assessment of comorbidities (see Limitations).Llanes et al.  comparedWhen looking at ASD with and without specific comorbidities (ADHD and/or anxiety), the subgroup of ASD without comorbid symptoms showed less severe autism symptoms in comparison to the subgroup of ASD with ADHD and/or anxiety. These differences were noted only by parental reports on the ADI-R  with a large effect size, but were not found in the professionals' observations (ADOS). One possible explanation is that children with ASD and comorbidities (ADHD and/or anxiety) exhibit aberrant behaviors at home more than children with ASD without these comorbidities. They may be less attentive, need more support and have more difficulties in change of routines, and consequently are harder to raise. Therefore, they are potentially perceived by their parents as having more severe “autism” than children with only ASD. The professional assessment using the ADOS focuses on specific behaviors in a stimulating and interesting setting and is less affected by ADHD or anxiety-related behavior problems. In addition, the ADOS is a relatively short “snapshot” in real time of a child's observed behaviors in a quiet clinical room 1:1 with a professional. The ADI-R, on the other hand, is based on information given by the child's parents, and includes the child's overall behavior in the “real world,” providing a broader picture than the time-specific ADOS. These findings are in accordance with previous research , 37 whicRegarding adaptive skills, having ASD with clinically elevated ADHD symptoms was associated with greater impairments in socialization adaptive skills. Only the subgroup with ASD and the two comorbidities was associated with poorer daily living adaptive skills. These findings partially supported our hypothesis, as not all the adaptive skills domains were associated with the comorbidities. However, having two comorbidities was associated with more adaptive functioning domains, albeit with a medium effect size. The current research is in line with previous findings that individuals with ASD and ADHD have a tendency toward greater impairments in adaptive functioning in all the VABS subdomains as compared to those with only ASD , 37, 38.Although ASD with clinically elevated symptoms of ADHD and/or anxiety was associated with lower adaptive skills functioning, surprisingly and not in accordance with our hypothesis, it was not associated with lower cognitive ability. Other studies found more impairments in verbal and non-verbal abilities, spatial working memory, response inhibition and executive functions in ASD with ADHD , 38. A lRegarding our third aim, in accordance with our hypothesis, the severity of clinically elevated ADHD and anxiety symptoms were associated with more severe autism symptoms and poorer overall functioning.Our Forth aim was to assess which variables added to the severity of Inattention, Hyperactivity/Impulsivity, and anxiety symptoms individually. For Inattention symptom severity, the regression model explained 12.3% of the variance. Being a female and having lower adaptive skills scores were greater predictors of higher severity of Inattention symptoms, beyond the contribution of age, parental educational attainment, cognition, and autism severity. It is possible that lower functioning is associated with the severity of inattention as perceived by parents. The finding regarding females is important and should be further examined in future studies on inattention in a subgroup of females with ASD. For Hyperactivity/impulsivity symptom severity, the regression model explained 18.5% of the variance. Being older, having greater cognitive abilities and more severe RRB symptoms were greater predictors of higher severity of HI symptoms, beyond sex, parental educational attainment, adaptive skills, and autism severity in the social interaction and communication domains. It may be that ADHD is easier to diagnose in older children with greater cognitive abilities. In addition, RRB symptoms may overlap with HI symptoms , and therefore children with more RRB symptoms will be perceived as having more HI symptoms. For anxiety symptom severity, the regression model explained 21% of the variance. Being older and having more severe social impairments were greater predictors of higher anxiety scores, beyond sex, parental educational attainment, adaptive skills, and autism severity in the communication and RRB domains. This may reflect that anxiety symptoms are more easily recognized in older children. Social impairments and anxiety symptoms often overlap or augment each other. Overall our hypothesis regarding the association between the comorbidities and cognitive level, autism severity and adaptive functioning was partially supported, as each comorbidity was associated with different factors.Adaptive functioning refers to behaviors critical in everyday life in terms of communication, socialization, daily living, and motor skills. Adaptive skills are one of the most important measures in evaluating functioning in ASD, as they reflect the generalization of acquired skills in everyday life. Therefore, we thought it important to identify the variables that may predict overall adaptive skills by using regression models as outlined in our Fifth aim. For overall level of adaptive skills, the regression model explained 44% of the variance. Younger age, better cognition, less severe social and communication impairments, and less severe inattention symptoms, all as reported by parents were greater predictors of better overall adaptive skills, beyond sex, maternal education, autism severity in the RRB domain, and the severity of HI and anxiety symptoms. These findings suggest that in ASD, in addition to the role of cognitive ability and autism severity, the severity of inattention symptoms adversely relates to the overall adaptive functioning. Interestingly, only the severity of Inattention and not that of Hyperactivity/impulsivity or anxiety contributed to lower adaptive functioning, over and above other ASD-related characteristics. These findings partially support our hypothesis, as only inattention symptoms but not HI and anxiety symptoms predicted the level of adaptive skills.The current study has several strengths. One is the large sample size of a well-characterized ASD sample. The sample contained both males and females. There were no significant differences between the four examined groups in any demographic parameters. The assessment of ASD was conducted using gold standard tests  and ADHD and anxiety symptomatology were obtained using standardized questionnaires (CRS). The use of these comprehensive assessments promotes a broader understanding of the clinical presentation in the subgroup diagnosed with ASD and ADHD and/or anxiety.This study has several limitations. There is a lack of a control group of children with neither ASD nor comorbidities; in the future, it will be important to design such a study. In addition, there were missing data points for some participants in the cognitive test scores (28) and the ADOS severity scores (5). Severity of symptoms of ADHD and anxiety was based on standardized questionnaires, which allowed for the quantification of a continuous variable, and not on the clinical diagnosis of these disorders. We compared parents' and teachers' CRS scores, but used only the parental CRS to examine the relationship between the severity of ADHD and anxiety symptoms and the levels of autism severity, cognitive ability and adaptive skills. Since more than a quarter of our study participants were previously diagnosed with ADHD, and many were treated with medications during the school day, the parents' reports were used to avoid the potential effects of medication on the reported severity of the ADHD symptoms. Previous research has used only parental CRS as well . Indeed,The novelty of the current study is that it is the first to examine the relationship between having ADHD and/or anxiety in ASD and the clinical presentation in autism severity, adaptive skills and cognitive ability. In addition, the current study investigated for the first time which variables are associated with symptoms of inattention, hyperactivity/impulsivity and anxiety in ASD. Finally, the study addressed which variables may comprehensively affect adaptive skills in ASD by considering the contribution of ADHD and anxiety co-morbidities in addition to more traditional variables, such as the child's age, sex, cognitive ability, and autism severity. This led to the unique finding that only a specific ADHD symptom—inattention—contributes to lower adaptive functioning in ASD.This study has theoretical significance. The very high frequency of ADHD symptoms in over two thirds of the ASD group suggests that some of the symptoms of both disorders may overlap. ASD and ADHD are described with similar brain abnormalities in specific regions, including the medial frontal and prefrontal cortex, which play an important role in executive functions , and redThe study has several clinical implications. In light of the finding that ADHD and anxiety symptoms are related to poorer adaptive behaviors and to more severe autism symptoms as perceived by the parents, it is highly important during the ASD diagnostic process to assess ADHD and anxiety symptomatology. Since having ADHD and/or anxiety symptoms with ASD is associated with parents' negative perceptions of their child's functioning, parents should be provided with support and guidance.In addition, since many children in this study were diagnosed first with ADHD and only later with ASD, it may be that the professionals were influenced by the dominant ADHD symptoms and they associated the social communication and RRB symptoms with the ADHD diagnosis. A very important takeaway for developmental behavioral pediatricians, pediatric neurologists and child psychiatrists is to consider a possible diagnosis of ASD when a young child exhibits significant ADHD symptomatology and when there are social difficulties and evidence for sensory or repetitive restrictive behaviors too.In light of the study's findings, it will be important to diagnose these comorbidities early on in children with ASD, and to explore effective medical and behavioral interventions to reduce the impact of these comorbidities, thereby hopefully leading to improved functioning.Future studies should further explore the clinical presentation in females. In addition, it would be interesting to explore the impact of medication and specific intervention programs to lower anxiety on the clinical presentation of children with ASD and ADHD and/or anxiety symptoms. It is also important to investigate genetic and imaging differences between children with ASD alone, ASD and ADHD, and ASD, ADHD and anxiety.EA, EB-I, and DZ contributed to the design and implementation of the research, to the analysis of the results, and to the writing of the manuscript.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.


Attention deficit and hyperactivity disorder (ADHD) is a neurodevelopmental condition that affects, among other things, the movement patterns of children suffering it. Inattention, hyperactivity and impulsive behaviors, major symptoms characterizing ADHD, result not only in differences in the activity levels but also in the activity patterns themselves. This paper proposes and trains a Recurrent Neural Network (RNN) to characterize the moment patterns for normally developing children and uses the trained RNN in order to assess differences in the movement patterns from children with ADHD. Each child is monitored for 24 consecutive hours, in a normal school day, wearing 4 tri-axial accelerometers (one at each wrist and ankle). The results for both medicated and non-medicated children with ADHD, and for different activity levels are presented. While the movement patterns for non-medicated ADHD diagnosed participants showed higher differences as compared to those of normally developing participants, those differences were only statistically significant for medium intensity movements. On the other hand, the medicated ADHD participants showed statistically different behavior for low intensity movements. Attention deficit and hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting between 3 and 5% of children of school age ,2. ADHD In recent years, several studies have proposed the use of different sensors in order to assess the effect of ADHD symptoms over different physiological signals. The authors in  used an In this paper, a novel mechanism to assess the movement patterns for both medicated and non-medicated children with ADHD, as compared to typically developing non-ADHD controls, is proposed by using a Recurrent Neural Network and a similarity measure based on the Pearson Correlation Coefficient. A total of 36 children and young people (ages from 6 to 16) wore 4 tri-axial accelerometer devices (one at each wrist and ankle) during 24 consecutive hours. Half of the participants (18) were ADHD diagnosed children and young adolescents, and half were typically developing non-ADHD controls. Half of the ADHD diagnosed participants  were taking medicines while the data was recorded, and the other half did not take any medicine during the 24-hour recording (nor the day before). Of the 18 controls, half of them were used to train a Recurrent Neural Network (RNN) and the rest of the participants  were used to assess their similarity to the group of controls in the training phase. The proposed assessment method uses a Recurrent Neural Network (RNN) to learn the internal dependencies and patterns from the time series form the 9 typically developing participants used to train it. Training the RNN with acceleration data from typically developing children will allow it to learn some common traits about how normally developing children move. Using the trained RNN for new participants will detect segments in the time sequences which are badly characterized by the RNN. Due to the high complexity of the different human movements, and the high number of possible human activities, the training data will not be able to encompass all the different patterns in normally developing children and young adolescents, but a subset of them. Therefore, there are going to be segments of data from all users which will not be properly characterized by the trained RNN. However, the number of badly characterized segments is expected to be higher for participants with ADHD. This paper presents both the RNN-based architecture and the results both for non-medicated as well as for medicated children and young adolescents with acceleration data in a normal school day.This paper is divided into 5 sections. The first section presents the introduction and motivation for the research in this paper. The second section is dedicated to capturing the related previous research studies. The third section captures the materials and methods, presenting the details for the hardware used, the way in which participant were recruited, the demographic data for the participants in each group and the proposed algorithm and method used to obtain the results. The use of wearable sensors in general, and accelerometer sensors in particular, has motivated the research in new mechanisms, methods and tools to support both the diagnosis and monitoring of children with ADHD. Accelerometer sensors are able to capture movement related time series from different parts of the body and serve as a valuable information source not only to characterize the ADHD particular effects but also to monitor the impact and behavioral changes of some interventions. The authors in , for exaPrevious studies using accelerometer sensors such as ,5 have fIn this paper, we propose a novel architecture based on the use of a 2-layer Recurrent Neural Network (RNN) to learn the movement patterns from normally developing children as observed from the combination of the time series of 4 tri-axial accelerometers (one at each wrist and ankle). The RNN will be configured to minimize the reconstruction error when predicting the next 2 second acceleration data for the 4 sensors based on the past 6 seconds of data. Once trained, the RNN will be fed with data from other participants in order to assess whether the RNN is able to recognize previously learnt patterns. The Pearson Correlation Coefficient will be used to assess the reconstruction similarity. The authors in  not onlyThe participants in the experiment group were included in the study if they were children and/or young people with ages between 6 and 16 and they had already been diagnosed with ADHD. Their parents were asked to confirm that the children had been fully assessed and diagnosed by the Paediatric Neurodisability or Child and Adolescent Mental Health Services.The inclusion criteria for participants in the control group were to be in a similar age range (6–16) and to not have been diagnosed of ADHD, and were not siblings of a child with diagnosed ADHD (since ADHD is highly heritable).Members of the research team conducting this study used a convenience sample of normally developing children in order to recruit participants using a snowball sampling method. For participants diagnosed with ADHD, children living in South Yorkshire (United Kingdom) were recruited via a community group for parents who were referred to these groups by their child’s clinician.The members of the research team carried out visits to all the participants (both in the experiment and control groups) in their homes. An informed consent was provided by the parent/legal guardian to confirm their child’s participation in the study. Moreover, all the participating children also signed assent forms to agree to participate. The parents/legal guardians also had to complete a SNAP IV questionnaire to assess the current severity of their child’s hyperactive behaviors. The participants were placed a labelled sensor  had been diagnosed with ADHD and the other half (18) were typically developing participants. In the group of 18 children/young adolescents diagnosed with ADHD, half of them (9) were not taking medication for their ADHD when the data was recorded, and the other half (9) were on medication. A managing ADHD group in Sheffield was used to recruit the participants with ADHD. This group was only available to parents of children who had been diagnosed with ADHD. All the participants with ADHD had been previously assessed by the Paediatric Neurodisability or Child and Adolescent Mental Health Services in Sheffield Children’s NHS Foundation Trust. The assessment followed the NICE guidelines and the DSM 5 criteria using a standard assessment and diagnosis process. A SNAP symptom questionnaire was also completed by the participants’ parents, as previously mentioned. The SNAP questionnaire helped us to assess their current symptoms.The School of Health and Related Research (ScHARR) ethics committee at the University of Sheffield was responsible for the ethics approval (reference: 013209). To guarantee that all participants were able to understand the information provided to them, several participant information sheets were written for different age groups.A set of 4 Runscribe™ inertial sensors  were used for each participant . A tri-aTo adapt the sensed raw data to the movement pattern characterization algorithm proposed in the next sub-section, a two-step preprocessing algorithm is used as captured in The data samples recorded by each sensor represents the raw acceleration projections on the sensor anchored coordinate system  of the user acceleration sampled every 100 ms as measured in the wrists and ankles of the participants. Since the sensors move with the user, the sensor anchored coordinate system makes it difficult to compare acceleration patterns among similar movements with different sensor orientations. A preprocessing algorithm is used in order to estimate the geo-referenced vertical acceleration values  from the acceleration vector in the sensor anchored coordinate system as captured in the left part of lh for the left hand worn accelerometer, rf for the right foot’s device and rh for the right hand’s acceleration values.Each tri-axial acceleration is sampled at a particular sampling frequency The gravity acceleration vector (the acceleration due to the gravity force) at sample number posed in ): g(i)’→The acceleration caused by the movement of the user is estimated according to: The movement-related acceleration projection over the gravity vector i point to the beginning of the vertical acceleration signal.Let the index th1 is a threshold value between the maximum acceleration values before the shaking movement and the maximum acceleration value inside the shaking movement.Remove i = i + 1 and repeat the step 2 until i until the following condition is met th2 is a second threshold small enough so that the average vertical acceleration values inside the shaking movement are higher than th2.Remove The second preprocessing step in The proposed algorithm to learn the movement patterns from typically developing participants is captured in Once the algorithm is trained with data from some typically developing participants, the algorithm is used to assess the similarity of new participants to those control children/young adolescents by using the trained structure to try to reconstruct the future acceleration values from the new users’ acceleration time series and comparing the similarity of the reconstructed segments with the real data values. The Pearson Correlation Coefficient is used to assess the similarity between the real and the estimated signals.The structure of an LSTM cell in the first layer is captured in t), the The behavior of connections in The algorithm presented in The acceleration data from the 27 participants under study were divided into 8-second windows. The first 6 seconds from each window were fed into the trained algorithm in The results in To assess whether the differences between both ADHD diagnosed groups with the typically developing control group were statistically significant, the t-test was used. Changing the parameters in the architecture presented in The data fragments for each participant were divided into different categories according to the intensity of the acceleration values as measured by the standard deviation of the combined data from all 4 sensors in the fragment (the 8-second window). For low-intensity movements, the standard deviations would be small, while for more energetic movements, the standard deviations for the combined acceleration from all 4 sensors in the time window would be higher. The algorithm in For non-medicated ADHD participants , the difThe results for medicated ADHD participants  show verThe area under the curve for non-medicated ADHD diagnosed participants for movement fragments with the optimal combined standard deviation (between 0.8 and 1 in g units) is illustrated in To assess the effect of the similarity threshold value in the results, different thresholds were analyzed for each group and movement intensity interval. The results were similar for different values. This paper presents a novel architecture for characterizing movement patterns based on the use of a Recurrent Neural Network (RNN) using Long Short Term Memory (LSTM) cells. RNNs have previously been used in the characterization of time series showing optimal results for solving Human Activity Recognition (HAR) problems.The RNN part of the proposed method was used to learn the movement patterns in the control group that is used to train the network. The training was based on learning the optimal patterns in the recent past information of the time series obtained from 4 different tri-axial accelerometers (one on each wrist and ankle) in order to optimally predict the information in the near future for the same signals. A mean square optimization is used to minimize the reconstruction errors. Once trained, the acceleration data from new users will be fed into the network and a similarity measure based on the Pearson Correlation Coefficient will assess whether the new information shows similar patterns to those found in the users when training the network.9 normally developing participants used for training the network only9 different normally developing participants used in the validation part of the study9 non-medicated ADHD diagnosed participants9 medicated ADHD diagnosed participantsFor this research study, 36 recruited children were used. These children were divided into 4 groups:A comparison under the null hypothesis “there is no difference in the mean values for poorly predicted acceleration fragments between the participants in groups 2 and 3 and between the participants in groups 2 and 4” was performed using the t-test. If the total number of non-similar acceleration fragments was computed for all movement intensities together, there was no statistically significant differences between non-medicated or medicated ADHD diagnosed participants and the users in the normally developing participant control group, under the 0.05 significance threshold , although the non-medicated showed a more significant difference.Analyzing the differences by dividing the different movements according to their intensity, as measured by the combined standard deviation from the vertical acceleration signals, there were some significant differences among groups. The non-medicated participants with ADHD showed statistically significant data differences for medium intensity movements. The learned movement patterns for the 9 training controls by the algorithm in As future work, a deeper analysis of finding common patterns in ADHD diagnosed children will be performed. The effect of medication on behavioral changes over these patterns will also be studied. A more exhaustive experiment including a higher number of participants is also expected.