At 5 years, maternal expressed emotion (using the Five Minute Speech Sample) and positive regard of child (using a standardized at-home observation procedure) were assessed. At 5 and 8 years, symptoms of ADHD, oppositional defiant disorder (ODD), and callous-unemotional (CU) behaviors were measured using a multi-informant approach. Multiple linear regression analyses revealed that positive regard specifically predicted a decrease in ODD symptoms between preschool and school age. The expression of high negative emotion specifically predicted an increase in CU behaviors. The development of ADHD symptoms was not predicted by parenting. Knowledge on these specific links can help to elaborate diagnostic and counseling processes in preschoolers with high ADHD symptoms. Underlying mechanisms and the role of neurocognitive deficits of the preschool child should be further analyzed.Parental expressed emotion and positive reinforcement are assumed to affect the development of oppositional and callous-unemotional behaviors in children at risk of attention deficit hyperactivity disorder (ADHD). As longitudinal research on this issue is scarce, we analyzed the respective links between preschool and school age. 138 five-year-old ( There is broad evidence on an association between behavior problems in childhood and coercive, harsh parenting as well as low positive parental regard/reinforcement, and there is consensus on the notion that these parenting characteristics play an important role in the development of problem behaviors in childhood. In the present study, we focus on the developmental pathway from parenting to child behavior problems as one component of a more complex transactional process model in parent and child behavior development . As outlIn past decades, research focused on attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD) and conduct disorder (CD), and the development of co-morbid ODD/CD in ADHD. More recently, so-called callous-unemotional (CU) traits have been distinguished within the ODD/CD spectrum, and regarded as a sub-dimension with specific etiology and developmental precursors. The three psychopathological dimensions, i.e. attention deficit/hyperactivity, oppositional, and CU symptoms are correlated and occur co-morbidly. In the course of development, however, ADHD symptoms often manifest first (mostly in preschool ages) and may be followed by the development of ODD/CD with or without CU behaviors –5. The aRegarding ADHD, several studies have investigated associations with parental “expressed emotion” (EE), i.e. parental criticism, warmth, and a positive relationship with the child, usually assessed by a short qualitative interview . It was assumed that the expression of high negative and low positive emotions towards the child indicate family stress, low parental support, low parental coping resources, and a negative parent–child relationship, which in turn affect the developmental course of the disorder including an increase in ADHD symptoms and the development of co-morbid ODD/CD –9. LongiRegarding ODD/CD and externalizing problems, associations with coercive/harsh and low positive parenting are well established. A recent meta-analysis found the strongest  cross-sectional associations between externalizing problems and “harsh control” including criticism and verbal violation/punishment . In chilRecent research has pointed to the relevance of the sub-dimension of CU traits with respect to the link between parenting and ODD/CD development. CU traits, i.e. lack of empathy, guilt or remorse, shallow or deficient affect, and limited prosocial emotions , may accSeveral longitudinal studies have analyzed the prediction of CU traits by parenting in high-risk aggressive as well as representative samples . The stTaken together, the findings of many well-controlled longitudinal studies suggest that low positive regard/reinforcement and harsh parenting/criticism likely affect the development of psychopathological symptoms. However, several questions still remain open. As symptoms of ADHD and ODD often manifest for the first time in the preschool years and show relative instability until school age, they might be particularly malleable at this early stage, and parenting behaviors might play a significant role in this period. However, very few longitudinal studies have addressed this time period. Moreover, while ADHD symptoms often precede the development of ODD/CD/CU and may be involved in the psychopathological mechanisms of ODD/CD development, there is no longitudinal research on the predictive effect of these parenting characteristics in preschool children at risk of ADHD. Furthermore, it is possible that specific parenting components predict specific psychopathological processes, but only a small number of longitudinal studies have controlled for co-morbid symptoms. Therefore, it is not clear whether negative expressed emotion/criticism, low warmth and low positive regard/reinforcement precede the development of oppositional and CU behaviors in preschool children with elevated symptoms of ADHD. To the best of our knowledge, the present longitudinal study is the first to analyze these questions, i.e. the prediction of ADHD, ODD, and CU development by negative expressed emotion and low positive reinforcement in mother–child interaction in preschoolers with elevated ADHD symptoms.We hypothesize that low positive regard/reinforcement and high criticism  predict an increase in ODD and in CU symptoms between preschool and school age in preschool children with elevated ADHD symptoms. Moreover, we explore whether ADHD symptom development can be predicted by these parenting characteristics and whether specific parenting characteristics uniquely predict the development of a specific psychopathological dimension.n = 138 five-year-old  children  with elevated ADHD symptoms was recruited from child care centers. At recruitment, parents completed an ADHD screening questionnaire . Children who scored in the upper quartile (i.e. exceeded the lower bound of the 95% CI of the 75th percentile of the reference sample) were considered. Exclusion criteria from the study sample were IQ < 80, chronic diseases involving brain functions, any continuous pharmacological treatment, and insufficient German language skills of parent or child. Table t-scores between − 1.17 and 1.30), gender of child (2 (1) = 0.29), and paternal education level (2 (3) = 0.30). However, children who did not attend the 8-years assessment had mothers with a lower education level (2 (3) = 8.48, p = 0.037). At 8 years, three children who had been diagnosed with ADHD in the interim were medicated with stimulants. In 41 cases, non-pharmacological interventions  targeting the ADHD and/or externalizing symptoms of the child had been conducted. In the following analyses, we carefully controlled for the effects of these treatments (see below). Parents gave their written informed consent to participate in the study, and received an expense allowance of 50 Euros at the preschool assessment and 70 Euros at the school-age assessment. The study was approved by the Ethics Committee of the Medical Faculty, University of Marburg.A sample of Lehmkuhl ,). ChildAt the 5-years assessment wave, data were collected within the scope of a home visit and a telephone interview with the mothers. During the home visit, mother–child interaction episodes were observed, the Five Minute Speech Sample (FMSS) was conducted with the mother, and the child underwent an intelligence test. At the 8-years assessment, a structured clinical interview was conducted with the mother at our lab while the child participated in neuropsychological tests. An investigator (psychologist) who was blind to all 5-years data of the child conducted the clinical interview with the mother. Parents and teachers completed questionnaires on ADHD symptoms, symptoms of ODD/CD, and CU traits.Parenting behaviors. Positive reinforcement of the child by the mother was assessed by a standardized at-home observation procedure. Expression of negative emotion/criticism and perception of a positive relationship with the child were assessed by the respective subscales of the FMSS.n = 23) of cases (home visits conducted by two observers) and proved to be good (tau-b = 0.82). For further analyses, the scores of the 30-s intervals were summed up.Maternal positive reinforcement was assessed in accordance with the procedure described by Hyde et al. . Two staMaternal expressed emotion (EE) was assessed using the Five Minute Speech Sample (FMSS) by Magana et al.  in the mIn the present study, we hypothesized that the expression of critical comments and the description of a low positive relationship by the parent predict the development of ODD and CU symptoms. As summarized in the introduction, previous research revealed significant concurrent and longitudinal associations specifically between these EE components and ADHD or externalizing symptoms. To test our hypotheses, we focus on the EE scales critical comments and relationship. For reasons of completeness, however, we also explored the concurrent and longitudinal associations of the other three EE scales  with ADHD and externalizing symptoms.n = 21) of cases and proved to be good . Regarding the initial statement, warmth and number of positive comments, inter-rater reliability was Kappa = 0.84, Kappa = 0.50, and ICC = 0.84, respectively.In the present study, the tapes were transcribed and coded by a trained research assistant who was blind to the child’s ADHD and ODD symptom scores. Most mother–child relationships were coded as neutral (65%) or positive (33%) but seldom negative (2%). To avoid artifacts due to the skewed distribution, we created a dichotomous variable, i.e. distinguished between positive (scored with 1) and neutral/negative (scored with 0) relationships (EE-positive relationship). The frequency of critical comments  was used as a continuous variable. Inter-rater reliability was checked in 15%  interview [r = 0.54, p < 0.001 (Pre-PACS and FBB-ADHS-V parent), r = 0.23, p < 0.05 (Pre-PACS and FBB-ADHS-V teacher), and r = 0.30, p < 0.01 (FBB-ADHS-V parent and teacher). The Pre-PACS ADHD score and the FBB-ADHS-V parent and teacher score were significantly associated with the 8-years ADHD diagnosis  and with the 8-years ADHD summary score . We created a summary score on the 5-years ADHD symptoms by adding up the z-transformed ADHD symptom scores . Internal consistency was 0.54 (Cronbach’s Alpha). ODD symptoms were measured by the FBB-SSV questionnaire of the DISYPS-II diagnostic system. The questionnaire has shown good psychometric properties [r = 0.30, p < 0.001; r = 0.34, p < 0.001).nterview  in the mnterview  was condnterview  in the lnterview . The ADHnterview . Parentsnterview . The parnterview ). In theADHD symptoms and diagnoses. At the age of 8 years, the ADHD diagnostic module of the Child and Adolescent Psychiatric Interview  by Angold et al. [n = 29 (24%) received an ADHD research diagnosis. ADHD symptoms of the child were additionally assessed by parent and teacher questionnaires. Parents and school teachers completed the FBB-ADHS of the DISYPS-III [r = 0.70).d et al.  was condd et al. . Of the SYPS-III . The queODD symptoms. For the assessment of ODD symptoms, the conduct problems scale of the Strengths and Difficulties Questionnaire (SDQ) [r = 0.43, p < 0.001).re (SDQ)  was compre (SDQ) , 38. We CU traits. CU traits were assessed using the “prosocial behavior” scale of the SDQ and the “callous-unemotional” scale of the Antisocial Process Screening Device (APSD) [r = 0.35, p < 0.001). We built a composite score by summing up the z-transformed scores.e (APSD) . Motherse (APSD) . The CU e (APSD) –42. In tTreatment for ADHD and ODD/CU problems of child. For purposes of control, mothers were asked whether the child, the parents or the family had received any non-pharmacological treatment  targeting attention deficit or behavior problems of the child. If any treatment was reported, we recorded the number of sessions that had been received in the time period between the 5 and 8-years assessment.To facilitate the interpretation of the results of the multiple regression analyses, the bivariate correlations between the parenting measures and the psychopathological symptom scores at 5 and 8 years were calculated. These correlations and their significance levels have to be understood as descriptive statistics.To test the first hypothesis, i.e. whether parenting characteristics predict an increase in ODD symptoms and CU behaviors between 5 and 8 years, hierarchical multiple regression analyses were conducted , 44, witAn analogous procedure was used to test our hypothesis on CU behavior development. To explore the prediction of ADHD symptom development by the parenting characteristics, hierarchical multiple regression analysis was conducted. To explore whether the parenting scores predict the ADHD diagnosis, we conducted a logistic regression analysis. Hypotheses were tested with an alpha error of 5% (significance level of 0.05).As shown in Table The results of the hierarchical multiple regression analyses confirmed our hypotheses. ODD and CU symptom development was significantly predicted by parental low positive regard, EE-critical comments and EE-low-positive relationship Table . SpecifiRmodel = 0.610 (p < 0.001). The three parenting measures, however, did not contribute significantly to this prediction: Rchange = 0.004, F = 0.223 . Similarly, the logistic regression analysis on the prediction of ADHD diagnosis at 8 years was statistically significant (2 (6) = 26.4; p < 0.001; predictors: 5-years ADHD symptoms, gender of child, treatment history, and the three parenting scores) but the three parenting scores did not significantly contribute to this prediction (2change (3) = 3.19).When exploring the prediction of ADHD symptom development by the parenting measures, we found that the parenting measures did not predict the development of ADHD symptoms between 5 and 8 years or an ADHD diagnosis at 8 years. Specifically, the complete prediction model of 8-years ADHD symptoms  was significant at The present longitudinal study followed preschool children with elevated ADHD symptoms until school age, analyzing whether the development of ODD and CU symptoms can be predicted by parental positive regard/reinforcement and expressed emotion. Additionally, we explored the predictive effect of the parenting measures on ADHD symptom development. We found that an increase in ODD symptoms was significantly predicted by the parenting characteristics, and that maternal positive regard/reinforcement of the preschool child contributed significant unique variance to this prediction. The development of CU symptoms was also significantly predicted by the parenting characteristics, with the expression of negative emotion/criticism  making a unique and significant contribution to this prediction. In both cases, the findings did not change when adjusting for treatment history, gender of child and all co-morbid symptom dimensions. Thus, the respective parenting characteristics specifically predicted the ODD and CU dimension. Parenting did not predict any change in the ADHD symptoms of the child, and there was no significant prediction of the 8-years ADHD diagnosis by parenting when adjusting for the concurrent preschool ADHD symptoms.To our knowledge, this is the first study to analyze the links between parenting and ODD as well as CU symptom development in preschool children with elevated ADHD symptoms. Our finding that ODD symptom development can be predicted by positive parental regard/reinforcement is in line with the results of Chronis et al.  and HydeWhile the study by Hyde et al.  also repIn the present longitudinal study, maternal negative expressed emotion  and description of a low positive relationship (EE-relationship) with the child did not predict an increase in ADHD symptoms or an ADHD diagnosis over and above concurrent symptoms of ADHD. To our knowledge, the prediction of change in ADHD symptoms by expressed emotion measures has not yet been analyzed. Nevertheless, our findings of concurrent and longitudinal associations of maternal critical remarks and description of a low positive mother–child relationship with the ADHD symptoms of the child correspond well to previous research, which reported that the expressed emotion measures were associated with concurrent, stabile ADHD symptoms , 10. Thip < 0.001, and 0.23, p = 0.013 respectively). Therefore, we can assume that by adjusting for the ODD and ADHD symptoms at 5 years, considerable and meaningful 5-year CU variance was controlled for. Third, we have not yet assessed pathways from 5-years symptom dimensions to 8-years parenting. Although the additional analysis of these pathways would not alter the present results, such analyses would provide more complete information. In the future, analyses of the complete cross-lagged processes should be conducted. Fourth, we did not calculate the inter-rater reliability for the ADHD scores of the clinical interviews. However, all interviewers underwent careful training and supervision. The significant concurrent and longitudinal associations between the ADHD interview and questionnaire scores indicate good validity of the measurement of ADHD in the present study.Our study has several strengths, such as the longitudinal design, the use of a sample of preschool children with elevated ADHD symptoms, the use of a multi-informant approach to the measurement of the psychopathological symptoms of the child, the use of behavior observations in an at-home context for the assessment of positive reinforcement, the use of a validated version of the Five Minute Speech Sample for the assessment of expressed emotion, and the careful control for any previous and concurrent pharmacological and non-pharmacological treatment. However, some limitations of the study should also be mentioned. First, we cannot rule out the possibility that gene-environment correlation effects underlie the results, i.e. shared genes might be responsible for the mother’s and the child’s behaviors. However, the longitudinal design of the study does provide insights into the developmental succession. The predictive effects indicate possible environmental effects, which need to be confirmed in future research, e.g. by adoption studies. Second, as recommended , CU behaTo conclude, our longitudinal study revealed specific associations between parenting and behavior problem development in preschool children with elevated ADHD symptoms until school age. Maternal positive reinforcement likely buffered against and led to decreasing ODD symptom development. The development of CU behavior was preceded by the mother’s high negative expressed emotion. These links were specific for the symptom dimensions. Underlying mechanisms and the contribution of neurocognitive deficits should be further analyzed. The results can help to elaborate diagnostic and counseling processes in preschoolers with high ADHD symptoms.


To explore the influences of digital media use on the core symptoms, emotional state, life events, learning motivation, executive function (EF) and family environment of children and adolescents diagnosed with attention deficit hyperactivity disorder (ADHD) during the novel coronavirus disease 2019 (COVID-19) pandemic.A total of 192 participants aged 8–16 years who met the diagnostic criteria for ADHD were included in the study. Children scoring higher than predetermined cut-off point in self-rating questionnaires for problematic mobile phone use (SQPMPU) or Young’s internet addiction test (IAT), were defined as ADHD with problematic digital media use (PDMU), otherwise were defined as ADHD without PDMU. The differences between the two groups in ADHD symptoms, EF, anxiety and depression, stress from life events, learning motivation and family environment were compared respectively.When compared with ADHD group without PDMU, the group with PDMU showed significant worse symptoms of inattention, oppositional defiant, behavior and emotional problems by Swanson, Nolan, and Pelham Rating Scale (SNAP), more self-reported anxiety by screening child anxiety-related emotional disorders (SCARED) and depression by depression self-rating scale for children (DSRSC), more severe EF deficits by behavior rating scale of executive function (BRIEF), more stress from life events by adolescent self-rating life events checklist (ASLEC), lower learning motivation by students learning motivation scale (SLMS), and more impairment on cohesion by Chinese version of family environment scale (FES-CV). The ADHD with PDMU group spent significantly more time on both video game and social media with significantly less time spend on physical exercise as compared to the ADHD without PDMU group.The ADHD children with PDMU suffered from more severe core symptoms, negative emotions, EF deficits, damage on family environment, pressure from life events, and a lower motivation to learn. Supervision of digital media usage, especially video game and social media, along with increased physical exercise, is essential to the management of core symptoms and associated problems encountered with ADHD. China was hit by an outbreak of the novel coronavirus disease 2019 (COVID-19) at the end of 2019, and the government implemented a policy of home quarantine to control the infection rate by the end of January 2020, which required citizens to stay at home . The calADHD is one of the most common mental and behavior disorders among children and adolescents with recent estimates from a meta-analysis indicating that the prevalence in China was 6.26% . Both hoStudies have suggested that there is a close relationship between PDMU and attention deficit , behavioWe hypothesize that during the epidemic quarantine, ADHD children with PDMU would have more attention, behavioral and emotional problems, along with more EF impairments, more stress, less learning motivation, and more adverse effects on their family environment, as compared with the ADHD children without PDMU.Participants in this study were ADHD patients aged 8–16 years who had visited a medical psychological outpatient clinic at a general hospital in Shanghai, China, between April and May of 2020, when the COVID-19 epidemic broke out. All participants met the diagnostic requirements for ADHD based on the DSM-V criteria using semi-structured interview tool as clinical diagnostic interviewing scale (CDIS) , 45. ChiThe 192 participants were divided into two groups using the self-rating questionnaire for problematic mobile phone use (SQPMPU) and Young’s internet addiction test (IAT). The ADHD children with reported problematic use behavior with either the mobile phone or internet, scoring higher than the cut-off point in either SQPMPU or IAT, were defined as PDMU, and others were defined as without PDMU. The demographic data of all the subjects were collected including age, gender, living area per capita, with medication treatment or not, with comorbidities or not.Self-rating Questionnaire for Problematic Mobile Phone Use (SQPMPU) is used to estimate the dependence symptoms of mobile phone use for Chinese adolescents , oppositional defiant , conduct problem , and emotional problem , when compared with the ADHD group without PDMU. With regard to EF evaluated by BRIEF, the PDMU children presented significantly more impaired EF on shift , emotional control , initiation , working memory , plan , and behavior regulation index , metacognition , and GEC , than the group without PDMU.The results of ADHD symptoms, psychosocial behaviors and academic performances of ADHD children with and without PDMU are presented in Table p = 0.01, η2 p = 0.04]. The ADHD children with PDMU showed significantly more disturbances of life events for relationship pressure , learning pressure , being punished , adaption , and total situation  compared to the ADHD children without PDMU. Consequently, the ADHD children with PDMU had significant more problems on learning motivation , including initiative , awareness , and goal , compared to ADHD children without PDMU.The results of the family environment did not show significant differences except for cohesion  and SCARED  was significantly worse in ADHD with PDMU group, compared with ADHD without PDMU group. In the ADHD group with PDMU, children had a significantly higher positive relationship in DSRSC  and SCARED  than children in the ADHD group without PDMU. However, with regard to the diagnosis with depression disorder and generalized anxiety disorder (GAD), there were 2 children with depression disorder in ADHD with PDMU group, none in ADHD without PDMU group. Neither group had ADHD children met GAD diagnosis criteria. The diagnose differences with depression and GAD between were not significant between two groups.The total score on DSRSC  or social media software . On the other hand, the ADHD children in PDMU group spend significant less days on physical exercise , however, there were not significant differences on the days spend on artistic and music , science and culture , and other types of hobbies .Our investigation found that there were significant differences on media usage patterns and daily life arrangement between two groups. The ADHD children in PDMU group spend significantly more time on digital media use regardless of whether it was video game [F  =7.14, The study found that the ADHD children with PDMU suffered more severe core symptoms, negative emotions, EF deficits, damage of the family environment, pressure from life events and lower motivation to learn.ADHD children with PDMU showed significantly more core symptoms of inattention than ADHD children without PDMU. Previous studies suggested that there was a link between PDMU and attention deficits , 43. On ADHD children with PDMU, as compared with ADHD children without PDMU, showed an increase of emotional problems including both higher scores and abnormal rates when using the SCARED and DSRSC methods of measurement. Many previous studies, although inconclusive, had revealed that children who spend more time online were more likely to be depressed . The diaEF deficits have been shown to closely related to ADHD in many studies , 36, 48,While their family environment exhibited worsened cohesion, the ADHD children with PDMU showed severe symptoms of ODD, as compared with the ADHD children without PDMU. This indicates that there were more problems such as confrontation and disobedience, within the parent-child relationship. One study that included Chinese families found that parent-child relationship helped to mediate adolescent problematic mobile phone use and parental phubbing . The heaThe ADHD children with PDMU exhibited lower learning motivation, higher stress on life, interpersonal, and learning problems as compared with the ADHD children without PDMU. In fact, one study that included Chinese adolescents found that the participants with problematic use of mobile phone presented more stress from life events and less motivation toward school work as compared with the healthy controls . This neThe ADHD children with PDMU spend considerably more screen time on both video games and social media software, and less time on physical exercising, than the ADHD children without PDMU. Studies have revealed that both video games  and sociIt is important to manage children’s use of digital media products, making prevention and early intervention, because screen use is now so ubiquitous. Greater access to media and reduced parental supervision have contributed to prolonged leisure screen time in Chinese children with adolescents . To prevThis study was carried out during the special period of COVID-19 epidemic and due to the home quarantine policy, along with the fact that participants were families who seek medical help voluntarily, confounding factors such as comorbidities and medication use were not controlled. This special period could be seen as an extended vacation because the long break from the classroom, however, the influence of COVID-19 could still affect children’s emotion and stress. This study may reveal the relationship between PDMU and ADHD children’s symptoms, emotional and behavioral problems, parent-child relationship, and family environment, however, it is difficult to explain any causal relationship. The effects of PDMU and problematic behaviors, negative emotions, and dysfunctional family relationship might be interacted with each other. Due to the special period, our study only included ADHD children, but not healthy control children, which could not better explain the relationship between ADHD symptoms and internet use in the whole children population. Finally, although this study suggested a variety of negative influences of PDMU, feasible and effective intervention need to be further explored in future study.This study, taken as a whole, not only reveals the connection between the use of digital media and ADHD symptoms, emotions, EF, learning motivation and family environments, but also shows enhanced problems in ADHD children with increased exposure to digital media during the epidemic quarantine period. ADHD symptoms, behavioral problems, EF impairments, and family environment problems all showed increases with increased use of digital media. Although no causal relationship is shown by our study, parents should consider taking action to limit digital media exposure to prevent family, emotional, and learning disruptions. For example, during break from the classroom, parents of children with ADHD should adhered to prescribed medication for ADHD symptom management, while attempting to provide a good family environment, finding ways to manage negative emotions, increase physical exercise, and reduce the use of digital media products.


Low-birthweight  babies are at a higher risk of poor educational achievement, disability, and metabolic diseases than normal-birthweight babies in the future. However, reliable data on factors that contribute to LBW have not been considered previously. Therefore, we aimed to examine the distribution of the causes for LBW. A retrospective review of cases involving 4,224 babies whose mothers underwent perinatal care at Keio University Hospital between 2013 and 2019 was conducted. The LBW incidence was 24% . Of the 1,028 LBW babies, 231 babies were from multiple pregnancies. Of the 797 singleton LBW babies, 518 (65%) were born preterm. Obstetric complications in women with preterm LBW babies included premature rupture of membrane or labor onset (31%), hypertensive disorders of pregnancy , fetal growth restriction (24%), non-reassuring fetal status (14%), and placental previa/vasa previa (8%). Of the 279 term LBW babies, 109 (39%) were small for gestational age. Multiple logistic regression analyses revealed the following factors as LBW risk factors in term neonates: low pre-pregnancy maternal weight, inadequate gestational weight gain, birth at 37 gestational weeks, HDP, anemia during pregnancy, female sex, and neonatal congenital anomalies. HDP was an LBW risk factor not only in preterm births but also in term births. Our results suggest that both modifiable and non-modifiable factors are causes for LBW. It may be appropriate to consider a heterogeneous rather than a simple classification of LBW and to evaluate future health risks based on contributing factors. Neonates with LBW at delivery are known to have a higher risk of not only infant morbidity and mortality but also poor educational achievement, disability, and the development of metabolic diseases  in the future . A recennt women . We wereThere is no doubt that LBW should be prevented for effective lifelong healthcare in the future; however, there are still limited reliable data on causes for LBW in Japanese pregnancies. Moreover, the identification of modifiable factors responsible for LBW is important so that appropriate interventions could be administered during perinatal care. Therefore, in this study, we aimed to investigate the recent distribution of the causes for LBW in our hospital, which is located in the central area of Tokyo, Japan, to reduce the prevalence of LBW.Data associated with pregnancies in Japanese women who underwent perinatal care at the Keio University Hospital between January 2013 and December 2019 were retrospectively reviewed. The exclusion criteria were pregnancy loss before 22 weeks of gestation and intrauterine fetal death. Details regarding the maternal and neonatal characteristics and perinatal outcomes were collected from the medical records of our hospital. This research was performed in accordance with the Declaration of Helsinki, and the written informed consent was obtained from the patients. This study was approved by the Ethics committee of the Keio University School of Medicine, Tokyo, Japan .2 ≤ BMI < 25.0 kg/m2: 11.3 kg ≤ GWG ≤ 15.9 kg), overweight (25.0 kg/m2 ≤ BMI < 30.0 kg/m2: 6.8 kg ≤ GWG ≤ 11.3 kg), or obese (30.0 kg/m2 ≤ BMI: 5.0 kg ≤ GWG ≤ 9.1 kg) patients [Gestational age was confirmed during the first trimester using crown-rump length measurements. Perinatal management of pregnancy-related symptoms  was performed at the discretion of each obstetrician based on the clinical recommendations of the Japan Society of Obstetrics and Gynecology (JSOG) . In our patients . Anemia U test. Categorical variables were analyzed with the chi-square or Fisher’s exact test. The pregravid BMI and GWG trends were analyzed using the Cochran–Armitage trend analysis. In all tests, P < 0.05 was considered significant. A multiple logistic regression analysis was performed to evaluate the relative contributions of the various maternal and perinatal factors to LBW in neonates delivered at term. The control group consisted of all pregnant women who underwent perinatal care at our hospital between January 2013 and December 2019 and who delivered singleton babies with birthweights of over 2,500 g at term . The following independent variables were included in the model based on the clinical relevance and statistical significance of their association with LBW: maternal age at delivery, method of conception, pre-pregnancy BMI, GWG, gestational week at delivery, mode of delivery, presence of HDP, anemia during pregnancy, neonatal congenital anomaly, and offspring sex. Odds ratios (OR) and their 95% confidence intervals (CI) were evaluated for the associations between LBW and the aforementioned clinical features. Statistical analyses were performed using the JMP software .Data are presented as the median (range) or number of cases (percentage). Continuous data were compared between groups using the Mann–Whitney Of the 4,224 babies who were born during the study period, 1,028 (24%) were born with LBW. The flowchart for the inclusion of pregnant women who delivered babies with LBW is depicted in in vitro fertilization-embryo transfer (IVF-ET). The median gestational weeks at delivery was 35 weeks (range: 22–38), and there were 200 preterm births. Eighty-five babies (37%) from multiple pregnancies were SGA.The maternal and neonatal characteristics in the cases involving multiple pregnancies are presented in Tables The maternal characteristics of mothers who underwent preterm childbirth are shown in The comparison of maternal and perinatal characteristics between LBW and non-LBW  in the case of deliveries after 37 gestational weeks are shown in The results of the logistic regression analysis are shown in The present study has revealed the distribution of the causes for Japanese LBW through a single hospital-based investigation, and several causes for the birth of neonates with LBW were identified. Particularly, our results revealed that mothers with multiple pregnancies and HDP, both in the case of preterm and term birth, were at a higher risk of delivering babies with LBW.The association between LBW and future health problems among preterm infants was analyzed in several previous articles, but these studies did not address the causes for preterm birth ,18, and In the present study, 22.5% of the LBW babies were from multiple pregnancies and 202 babies (87%) were born before 37 gestational weeks owing to various causes. The higher prevalence of LBW in multiple pregnancies than in a singleton pregnancy is owing to the higher risk of preterm birth, HDP, and preeclampsia . NeonateIn the present study, HDP was found to be the most important cause for LBW not only in preterm birth but also in term birth. Offspring born to mothers with HDP might be at a higher risk of autism spectrum disorder and attention-deficit/hyperactivity disorder because maternal inflammation might be associated with these neonatal diseases . FurtherThe cause for LBW in babies born at term is the most important concern because it could potentially aid in reducing the prevalence of LBW. In this study, it was found that the proportion of babies who were SGA was 39% among singleton babies born at term. Several maternal factors, such as adolescent or advanced maternal age, pre-pregnancy maternal underweight, inadequate GWG, smoking during pregnancy, and maternal complications, have been reported to be associated with SGA .Recently, the ideal body image for young women has been impacted by the widespread use of social networking sites and by the media . Japan hNakashima et al. reported that the birthweight of babies conceived by frozen-thawed ET (FET) was significantly higher than those by fresh ET or by other Japanese births . Since Fin-utero, and neonates with fetal congenital anomalies might require medical, socioeconomic, and educational support. These factors were identified as non-modifiable factors. However, among the 92 elective CS cases planned at 37 gestational weeks in the present study, 56 cases (61%) had no specific indications for the timing of delivery. Though elective CS should be scheduled before labor onset to prevent uterine rupture, the timing of elective CS is controversial globally [The present study suggests that the risk factors for LBW consist of both modifiable and non-modifiable factors. Some clinicians attempt to control or prevent HDP or preeclampsia using several medicines, for example, aspirin , metformglobally . The Natglobally . To prevglobally ,40. Pregglobally –43. Furtglobally –46.There are some limitations associated with this study. First, this is a retrospective study. However, there are limited data on the distribution of the risk factors for LBW; previous reports with warnings regarding increasing numbers of babies with LBW do not include explanations as to why this number is increasing in Japan. Since our hospital is a tertiary care institution in the central area of Tokyo, Japan, several pregnant women with severe complications are referred from other clinics, thereby resulting in a higher LBW incidence than that indicated in the national data of Japan (approximately 10%). We considered that conducting the study in our hospital would be suitable for evaluating the causes for LBW and that the evidence generated in the study would add to the limited data on the causes for LBW. Second, in previous reports, women with preeclampsia had a higher risk of delivering babies with LBW than those with HDP ,48. HoweThe distribution of the background factors responsible for LBW revealed in this study suggests that LBW babies are a heterogeneous population. Strategies to reduce LBW as well as to evaluate future health risks for LBW should be considered based on the causes for LBW. An important risk factor for LBW development in both preterm and term births is HDP, a non-modifiable factor without an established effective preventive treatment. It may be difficult to achieve a rapid, ambitious reduction in LBW prevalence; however, educating women with regard to the importance of adequate pre-pregnancy body weight and GWG as well as reconsidering the timing of elective CS may be key factors that could aid in accomplishing this goal.


Background: Adults with attention deficit/hyperactivity disorder (ADHD) are predominantly treated with medication. However, there is also a need for effective, psychologically based interventions. As ADHD is strongly associated with reduced inhibitory control, cognitive remediation approaches should be efficient. Goal management training (GMT) aims at enhancing inhibitory control and has shown positive effects on inhibitory control in non-ADHD patient groups. The aim of the current study was to explore whether GMT would specifically enhance inhibitory control in adults with ADHD, and if such an enhancement would lead to secondary improvements in self-reported everyday functioning.Methods: Twenty-one participants with ADHD (mean age: 39.05 years [SD 11.93]) completed the intervention and assessments pre-, post- and 6 months after the intervention. Measures included neuropsychological tests and self-report questionnaires pertaining to cognitive- and executive functioning, emotion regulation, quality of life, and ADHD symptoms.Results: Compared to baseline, the participants showed enhanced inhibitory control on performance-based measures at post-assessment and 6-month follow-up. The participants also reported increased productivity and reduced cognitive difficulties in everyday life at both assessments post-treatment, as well as improvements in aspects of emotion regulation and a reduction in the severity of core ADHD-symptoms at 6-month follow-up.Conclusion: Our exploratory study showed that GMT seems to specifically improve one of the core executive dysfunctions in ADHD, namely inhibitory control, with a positive effect lasting at least 6 months post-treatment. The adults with ADHD also reported improved self-regulation in their everyday life after completing GMT, providing strong arguments for further investigations of GMT as a treatment option for this group of adults.Clinical Trial Registration: The study is registered under ISRCTN.com . Attention deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder affecting individuals of all ages with an estimated prevalence of 2.5–4.4% among adults DSM-5; . Many neThe main treatment for adults with the disorder is pharmacotherapy with stimulant drugs . DespiteThis has led to efforts aimed at exploring whether psychological interventions can ameliorate difficulties in executive functioning in individuals with ADHD. Procedures to improve working memory functioning have been investigated in children e.g.,  and aduln = 12) was compared with the effect of psychoeducation without GMT (n = 15), and it included outcome measures focusing predominantly on everyday cognitive functioning according to the Cognitive Failures Questionnaire  were recruited through an existing study of ADHD in adults at the University of Bergen (see N = 29) were recruited through local outpatient clinics in the municipality of Bergen. Recruitment was conducted by distributing a short information letter about the project, i.e., inclusion and exclusion criteria, the GMT intervention, assessments as well as a prompt to contact members of the project staff for further information. Upon contacting a project member, interested individuals were screened for eligibility and given further information about the study as well as an informed-consent form in accordance with the Helsinki declaration. The study protocol was approved by the Regional Committee for Medical and Health Research Ethics, West Norway (2015/2325). All participants were compensated with 1000 NOK (approximately 110 USD) at the completion of the follow-up assessment to cover travel expenses.In total, 36 potential participants were recruited for the present study through two different approaches. A small subset of participants . Participants on medication were asked to avoid changes in dosage during the project period unless necessary. Exclusion criteria for the project were a lifetime history of psychotic disorder or an ongoing, severe psychiatric illness , ongoing substance use disorders and a full-scale intelligence quotient (IQ) below 80.All potential participants completed the Mini International Neuropsychiatric Interview Plus  from the Delis-Kaplan Executive Function System D-KEFS;  was admiThe CWIT  was admiThe Tower Test  was admiThe Letter-Number Sequencing task from the Wechsler Adult Intelligence Scale – 4th edition  and the The Hotel task  was admiThe CFQ  is a 25-The Adult ADHD Self-report Scale ASRS;  is an 18The Wender-Utah Rating Scale WURS;  is a 25-The Adult ADHD Quality of Life inventory AAQoL;  is a 29-The Behavior Rating Inventory of Executive Function Adult version BRIEF-A;  is a 75-The Dysregulation of Emotions Rating Scale DERS;  is a 36-All tests and questionnaires, except the WASI and the WURS, were administered at all assessments. Cronbach’s αs ranged from acceptable to excellent (between 0.87 and 0.96).t-tests were conducted as preliminary analyses to compare the baseline characteristics of those participants who completed the intervention and those who dropped out with regards to self-report- and performance-based measures.Statistical analyses were conducted using R version 4.0.2  and SPSSp < d × i/n; ∗power . Little’s missing completely at random test showed that all missing items were randomly distributed. Missing items were therefore replaced using the expectation maximization algorithm in SPSS. One participants’ BRIEF-A-questionnaire from the pre-assessment was missing, assessment data from one participant was also missing for most measures of the post-assessment, and for another participant on all measures of the follow-up assessment. Complete questionnaires that were missing were not replaced.In addition, 32 scores were identified as outliers , and were replaced with ± MAD.An overview of changes in the included variables from pre- to post- and follow-up assessments among participants who completed GMT is shown in Ms = 55.55 and 62.47 at baseline, Mdif = −4.48 and −8.64 for the third condition and fourth condition, respectively). These changes were maintained at follow-up 6 months later . The participants also increased their achievement scores on the Tower test at the follow-up assessment relative to baseline  and improved their performance on the fourth condition of the TMT , thus showing further improvements in inhibition in addition to attentional control and cognitive flexibility. No significant changes were detected on the other performance-based measures of executive function. However, on the Hotel task, an improvement in general problem solving was shown in a reduction in deviation from the ideal time from pre- to follow-up assessment .Analyses of scores on the performance-based measures of executive functions and problem solving showed improved efficiency in inhibitory control from baseline to post-assessment, as evidenced by a significant reduction in completion times on the third and fourth conditions of the CWIT (ps ≥ 0.09 without correction for multiple comparisons).The exploratory analyses investigating the potential effects of age and medication status did not show any significant effects of these covariates . The participants further reported a significant reduction of ADHD symptoms on the ASRS at both time points. They also reported increased quality of life following GMT as measured by the Life productivity subscale of the AAQoL . This subscale assesses functioning in school/work and everyday task accomplishment. The remaining subscales of the AAQoL showed no significant changes, but there was a significant change to the total score . Please see As secondary effects, the participants reported a significant reduction of cognitive functioning difficulties in their everyday lives, as measured by the CFQ . Reports on the DERS questionnaire 6 months after completing GMT also showed that the participants experienced an enhanced ability to regulate emotional responses and were better able to use active strategies for helping them when they experienced negative emotions.In line with our expectations, the adults with ADHD did not show changes in working memory after completing GMT. Interestingly, however, we found that after 6 months the adults with ADHD improved their general problem-solving skills as well as their flexible control of processing speed. Although we did not expect this, we believe that this change supports the interpretation of GMT leading to functional improvements. This is in contrast to the prior pilot study of an adapted version of GMT in adults with ADHD in which no change following the intervention was found on an everyday problem-solving task . The HotAs the current study was a self-control case design, we cannot rule out that practice effects may have contributed to improved scores from pre- to post- and follow-up assessments. Important to note in this regard, is the fact that we hypothesized that inhibitory control would be improved, and found that neuropsychological test measures of this function, and not of working memory, improved after completing GMT. We believe that this supports the assumption that our primary results of enhanced inhibitory control are not due to pure practice effects. This interpretation is supported by results from available studies of practice effects. For instance, Although the findings in the current study need to be interpreted with caution, the results strongly support the notion that the participants with ADHD adopted the learned strategies and applied them in their everyday life 6 months after completing GMT. Furthermore, in line with the primary aim of the study, our findings support the use of neuropsychological outcome variables as effect measures of GMT in ADHD samples. Specifically, GMT in ADHD seems to address inhibitory control in particular more than executive functioning in general. Interestingly, newer revisions of the understanding of executive functions lean toward inhibitory control being the unitary component of executive functioning . This maThe current study indicates significant effects of GMT on inhibition among adults with ADHD. Furthermore, the current results provide support for the notion that GMT may also affect broad and important domains of functioning such as everyday cognition and productivity as well as emotion regulation. These results encourage further studies that include control conditions to examine GMT as an intervention for adults with ADHD, as replication would indicate that GMT represents an efficient and cost-effective treatment alternative.Daniel.A.Jensen@uib.no.The datasets presented in this article are not readily available because the ethical approval states that anonymized data can only be made available for registered collaborators. Requests to access the datasets should be directed to DJ, The studies involving human participants were reviewed and approved by Regional Committee for Medical and Health Research Ethics, West Norway. The patients/participants provided their written informed consent to participate in this study.LS was the project leader. DJ, LS, AL, AH, JS, and JH involved in conception and design, and approved the final version for publication. DJ collected the data. DJ and LS involved in analyses, interpretation, and writing of the manuscript. AH, AL, JS, and JH critically reviewed the manuscript.JH has received speaker honoraria from Lilly, Shire, HB Pharma, Medice, Takeda, and Biocodex. 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.


Attention-deficit hyperactivity disorder (ADHD) is associated with later depression and there is considerable genetic overlap between them. This study investigated if ADHD and ADHD genetic liability are causally related to depression using two different methods.N = 8310 individuals in the Avon Longitudinal Study of Parents and Children (ALSPAC). Second, two-sample Mendelian randomization (MR) analyses examined relationships between genetic liability for ADHD and depression utilising published Genome-Wide Association Study (GWAS) data.First, a longitudinal population cohort design was used to assess the association between childhood ADHD (age 7 years) and recurrent depression in young-adulthood (age 18–25 years) in Childhood ADHD was associated with an increased risk of recurrent depression in young-adulthood . MR analyses suggested a causal effect of ADHD genetic liability on major depression . MR findings using a broader definition of depression differed, showing a weak influence on depression .Our findings suggest that ADHD increases the risk of depression later in life and are consistent with a causal effect of ADHD genetic liability on subsequent major depression. However, findings were different for more broadly defined depression. Attention-deficit hyperactivity disorder (ADHD) is a common, childhood-onset neurodevelopmental disorder that frequently co-occurs with other neuropsychiatric disorders  .Mental health data were used from the Avon Longitudinal Study of Parents and Children (ALSPAC), a well-established prospective, longitudinal birth cohort study. Details of this study are provided in the online Supplementary Material. Individuals were included in our analyses when data were available on ADHD in childhood (see below): adult ADHD’ using self-reported SDQ ADHD data at age 25 years. There is no research to guide appropriate cut-points for adult ADHD. In line with DSM-5 guidance that fewer symptoms are needed for an ADHD diagnosis in adulthood, we used one point less for the cut-point . Individuals were coded as having ADHD that persists in adult life if they met the relevant cut-points at ages 7 and 25.ADHD in childhood was measured using the well-validated, five-item parent-rated ADHD subscale of the Strengths and Difficulties Questionnaire (SDQ) Goodman,  range 0. Total ADepression was measured at five time-points from age 18 years (in young-adulthood), using the 13-item self-rated Short Moods and Feeling Questionnaire (sMFQ) , maternal education and maternal prenatal depression were included as potential confounders for the longitudinal analyses.N = 4771) had depression data for at least one time point . Primary analyses were conducted using multiple imputation (MI) by chained equations, including all those with ADHD data (N = 8310) to minimize bias from missing depression data .Additional analyses were conducted using a larger, more recent depression GWAS (rg = 0.42 (s.e. = 0.03) for MD  for broad depression . These genetic proxies should satisfy three main assumptions: (i) strong association with the exposure, (ii) no association with confounders of the exposure–outcome association, (iii) association with the outcome exclusively via the exposure . Where SNPs were missing in the outcome GWAS, linkage disequilibrium proxies (r2 = 0.8 within 250 kb) were used. Data were harmonized across the exposure/outcome datasets and palindromic SNPs were excluded: details of the included SNPs are shown in online Supplementary Tables S2 and S3.Genetic variants  were extracted from the relevant GWAS using a Three MR approaches were conducted to estimate the exposure–outcome effect because these have different assumptions: inverse-variance weighted (IVW) linear regression, a weighted median approach and MR-Egger regression. IVW assumes that all instruments are valid and that there is no horizontal pleiotropy (i.e. SNPs are associated with the outcome exclusively via the exposure). The weighted median method estimates the median (rather than the mean) causal estimate and is therefore robust to 50% of the genetic variants being invalid. Finally, MR-Egger regression relaxes the third assumption , by allowing the intercept of the SNP–exposure and SNP–outcome regression to be non-zero; the intercept thus provides an estimate of horizontal pleiotropy and the slope provides an estimate of the causal effect of an exposure on an outcome accounting for pleiotropic effects. MR-Egger regression is therefore less well powered but is robust when 100% of genetic variants have pleiotropic effects, conditional on the assumption that the pleiotropic effects are distributed independently of instrument strength   and heterogeneity in the SNP–exposure/SNP–outcome association using Cochrane's Q : simulation extrapolation (SIMEX)-adjusted MR-Egger was used to provide bias-adjusted estimates when appropriate  scored above the ADHD cut-point in childhood (age 7) and 26.9% had recurrent depression in young-adulthood (high depression symptoms at least twice in young-adulthood). Of those included in our sample, 6.4% .ADHD in childhood was associated with an increased risk of having recurrent depression in young-adulthood: OR 1.35, 95% CI 1.05–1.73, p = 1 × 10−05). The association with recurrent depression was similar when ADHD was defined as ADHD diagnosis and more broadly defined ADHD . Finally, investigating associations with continuous depressive symptom scores at single time-points found childhood ADHD to be associated with higher depression symptoms in young-adulthood, but the evidence was weaker than when investigating association with recurrent depression (online Supplementary Table S4).ADHD defined as a continuous trait  was also associated with later recurrent depression  and using IPW found a similar pattern of results although with much wider confidence intervals when using IPW . Analyses using listwise deletion did not find evidence of an association between childhood ADHD and recurrent depression in young-adulthood, likely reflecting bias due to non-random attrition, although confidence intervals were wide and overlapped those from the MI analyses .without childhood depression . There was no evidence that ADHD conferred an additional risk for young-adult depression in those who already had depression in childhood , although the sample size was small.Approximately 7.5% of the sample had childhood depression (15.5% of those with childhood ADHD and 15.2% of those with recurrent depression in young-adulthood). Childhood ADHD was associated with an increased likelihood of recurrent depression in young-adulthood for those p = 2 × 10−04. The association with later recurrent depression for those whose childhood ADHD did not persist to adulthood was greatly attenuated: OR 0.93, 95% CI 0.67–1.29, p = 0.66.Finally, approximately 2.2% of the sample had adult (persistent) ADHD (34.1% of those with childhood ADHD). Those with adult ADHD had a higher proportion of recurrent depression in young-adulthood compared to those with childhood ADHD only (47.5% compared to 26.4%): OR 2.69, 95% CI 1.61–4.50, p = 8 × 10−06.Conversely, those with recurrent depression in young-adulthood were also at an increased risk of having adult ADHD (3.4% compared to 1.6% in those without recurrent depression in young-adulthood): OR 2.51, 95% CI 1.68–3.75, F = 31.13, MD F = 34.28). MR-Egger indicated potential violation of the NOME assumption (ADHD I2GX = 38%) so SIMEX-adjusted MR-Egger regression were conducted as a sensitivity analysis.MR results are summarized in Q = 9.22, df = 9, p = 0.42). This association was consistent across the different MR approaches  and there was very little evidence of pleiotropy .For each unit increase in log-odds genetic liability of ADHD, there was evidence consistent with an approximately 21% increased risk in odds of MD, as suggested by the IVW  with very little evidence of heterogeneity  although analyses were limited by the small number of available SNPs for MD  found less consistent evidence of association  with evidence of heterogeneity (F = 37.87). Again, MR-Egger analyses indicated a potential violation of the NOME assumption  so SIMEX-adjusted MR-Egger regression were conducted.Results using GWAS findings for a broader depression phenotype are shown in p = 2 × 10−03). Using the broader depression GWAS for MR analysis, association in the reverse direction suggested an approximately 79% increase in the odds of ADHD per log odd increase in genetic liability to broad depression  with evidence of heterogeneity . This was consistent across the different MR approaches  with little evidence of horizontal pleiotropy .We found weaker evidence for an impact of ADHD genetic liability on broad depression, consistent with an approximately 7% increase in the odds of broad depression per log odd increase in genetic liability to ADHD, in the presence of horizontal pleiotropy . Removing these SNPs revealed the same pattern of results as when they were included (online Supplementary Table S6).This study used two different designs, a longitudinal population cohort design and Mendelian randomization (MR) to investigate a possible causal relationship between ADHD and depression. Previous work has observed association and genetic overlap between ADHD and depression  (Lawlor et al., Both methods were limited by the measures used. The measure used in sensitivity analyses of adult ADHD is yet to be validated for this age-group: this needs further research given the importance of using consistent measures across time. The measures used in both of our methods also meant that we were unable to investigate whether inattention or hyperactivity–impulsivity symptoms are more likely to lead to later depression.In conclusion, we used two methods to investigate a possible causal impact of ADHD and ADHD genetic liability on depression. Our longitudinal analyses highlight ADHD as a risk factor for depression in young-adulthood and MR analyses supported a causal effect of ADHD on MD although findings were different depending on the definition of depression. Taken together, clinical follow-up studies, one quasi-experimental design and this MR study and cohort design, converge in suggesting that ADHD may have a causal effect on depression. This suggests that effective treatment of ADHD might help prevent the development of depression for some, especially when ADHD persists into adulthood, but that it is unlikely to consistently prevent the development of depression for all.


The authors wish to make the following correction to this paper :After the publication of the manuscript, the authors recognized a mismatch in the link between the microbiota sequencing data (from ADHD cases and controls) and their descriptive and behavioral data. Thus, the manuscript had to be reanalyzed and rewritten, resulting in different results and conclusion. The main difference is that the case-control comparison resulted in different bacteria differences. Moreover, we did not find an association (only at trend level) between the microbiome relative abundance and inattention score. The corrected results, discussion, and conclusion, can be found below. Due to the changes the abstract, and material and methods section had to be adjusted as well. The changes are provided below. The authors would like to apologize for any inconvenience caused to the readers by these changes.The results and conclusion in the abstract changed to:puncorrected < 0.05) between both groups  and were further tested for their association with ADHD symptom scores . Our results show that the variation of a genus from the Lachnospiraceae family (Coprococcus_2) showed a trend of being negatively associated with inattention symptoms. Furthermore, we showed that the relative abundance of four genera was reduced by ADHD medication (puncorrected < 0.05). Overall, our results may support the role of the gut microbiota in the pathophysiology of ADHD. Given the scarcity of studies on the gut microbiota in individuals with ADHD, the current results are an important contribution to this field. More studies are needed into the gut microbiota as part of the pathology of ADHD, especially with a bigger sample size across the lifespan and more detailed information about lifestyle.Alpha and Beta-diversity were not different between participants with ADHD and healthy controls. Three genera showed nominal differences  and the composition analysis using “phyloseq” R package version 1.28.0. Second, we used the nonparametric Mann-Whitney U test method in order to identify differences in genera between cases and controls. This was visualized by using a boxplot with a summary table representing the number of zeros using “ggpubr” R package version 0.4.0.999. Third, in the regression analyses, we had to adjust the number of total tests used in FDR to 6 and not 14 tests. Fourth, the new results of the “2.2.9. Correlation Analysis and Multiple Regression with All Selected Genera” are shown in the Supplementary Materials. The data had to be reanalyzed; thus, all the results changed includes all the tables and figures. For easier readability, the whole (corrected) results section is provided below: The general characteristics of the studied sample are presented in Within- and between-sample diversity metrics: None of the three alpha-diversity (within-sample diversity) measures showed significant differences between the ADHD and control groups .p = 0.08; p = 0.479, N = 89). Other variables, such as age, sex, BMI, inattention score (IA), hyperactivity-impulsivity score (HI), and medication, did not show a significant effect on beta-diversity (Beta-diversity (between-sample diversity), assessed using betadisper , showed iversity . Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria, and Verrucomicrobia, were the most frequent phyla in our data (Table S2). There were no significant differences in the relative abundance of any of these phyla between participants with ADHD and controls (Table S2).As expected from , a compop < 0.05; Coprococcus_2 showed a trend of being negatively associated (B = (−3.189), p = 0.055, Q = 0.33; corrected for multiple testing; p > 0.05); therefore, only IA was considered in further analyses.At the genus level, differences in the gut microbiota composition revealed nominal significant case-control differences for three genera (Coprococcus_2 and symptoms of inattention (B = (−2.806), p = 0.080 vs. results in We tested the effect of ADHD medication on the (regression) results by excluding medicated cases (N = 19) from the analysis. We found that medication reduced the beta coefficient from −3.189 to −2.806 in the association between Lactobacillus, Lachnospiraceae_ND3007_group, Ruminococcaceae_g__ and Ruminococcaceae_UCG.014) were decreased in medicated ADHD . Regarding the Lactobacillus results, we had to treat them with caution because we only had three non-zero values for medicated cases.We performed a post hoc exploratory analysis where we compared the relative abundance of all the genera  between the medicated (N = 19) vs. non-medicated (N = 22) individuals with ADHD. We found that four genera  discussion section is provided below:Prevotella_9 and Coprococcus_2 and higher abundance of Intestinibacter in individuals with ADHD compared to controls. Of these three genera, Coproccocus_2 related most strongly (p = 0.055) with ADHD symptoms, specifically Inattention symptoms. Excluding subjects that were using ADHD medication from the regression model slightly reduced the strength of the association. Together this indicates that differences in gut microbiome in this sample of ADHD patients compared with control subjects are subtle.This study aimed to determine the differences in gut microbiota composition between individuals with ADHD and controls and the association between the abundance of the selected genera and the severity of ADHD symptoms (inattention and hyperactivity/impulsivity) accounting for the effects of medication. Our results did not show general differences in microbiota composition (beta-diversity) between the groups. At the taxonomic level, we found nominal (uncorrected significant) differences at the genus level; lower abundance of Coprococcus to be underrepresented in individuals with ADHD [Coprococcus_2 was found altered. Here, the effect was in the opposing direction; relative abundance was increased in mice colonized with ADHD gut microbiota, wherein the current case-control comparison Coprococcus_2 abundance was higher in controls. Putting aside differences in the directions of effects, the fact that genus Coporococcus_2 surfaces in both case-control comparisons suggest that this is an interesting target for replication in gut microbiota associated with ADHD diagnosis.Our results align with the growing evidence that gut microbiome alterations might be part of the pathology of ADHD ,5,6,7,8.ith ADHD . Mice coPrevotella was also found lower in children with ADHD compared with controls [Prevotella spp. and some Coprococcus species have been identified as short-chain fatty acids (SCFAs) producers [Furthermore, an abundance of the genus controls . Functioroducers , which croducers . SCFAs producers  and autiroducers ,14 throuIntestinibacter (belonging to Peptostreptococcaceae), was defined only recently [Intestinibacter may reflect the true absence of a sub-threshold presence of this genus, which should be confirmed and extended in metagenome sequencing.The only genus with a higher rather than lower relative abundance in cases versus controls, recently ; not mucrecently . Mucus-drecently , a comorrecently  or ADHD recently . Note thBifidobacterium genus showing the largest  difference between the ADHD group and controls by Aarts et al., even though this sample overlaps with the current sample (around 40%). There are many methodological reasons contributing to a lack of replication between studies, including DNA extraction [We did not replicate the differences in the traction , 16S rRNtraction , bioinfotraction , sample A specifically novel contribution in this dataset is the exploratory comparison between medicated (N = 19) and non-medicated individuals (N = 22) with ADHD, which showed four genera with a nominally statistically significant lower relative abundance in medicated individuals. The effects of ADHD medication on gut microbiota are very scarce, especially examined at the genus level and in a sample larger than n = four unmedicated ADHD patients as was available in Prehn-Kristensen et al., 2018 . HoweverThis study should be viewed in the context of several strengths and limitations. Our strengths include the use of a sample with high-quality clinical assessment and age-matched clinically ascertained controls. The limitations of our study include (i) limited sample size  and (ii) lack of information on lifestyle, dietary patterns (including probiotics) or antibiotic use at the time of feces collection. For the former, we applied two QC steps to deal with a large number of variables (genera), their expected small effects and big interindividual variation of the gut microbiota. First, we applied an uncorrected non-parametric approach . Second, we applied an outlier detection step prior to the regression analysis to reduce the chance of false positives/negatives. For the latter, we were only able to collect information on BMI, and while we acknowledge that this is not enough to account for the effects of diet and lifestyle, it is encouraging to see that there was no BMI difference between the groups. Moreover, we looked for and removed samples with a very low bacterial diversity (high proportion of zeros) by applying a 10% genus-based frequency cut-off per sample. This step can be used as a proxy for individuals using antibiotics since they would show a smaller bacterial diversity.Prevotella and Coprococcus have also been found by others. Of the three nominally significant different genera, Coprococcus 2 showed the strongest, though trend level relation with inattention symptoms. Given the scarcity of studies on the gut microbiota in individuals with ADHD, the current results are an important contribution to this field. More studies are needed into the gut microbiota as part of the pathology of ADHD, especially with a bigger sample size across the lifespan and more detailed information about lifestyle.In conclusion, we found subtle, uncorrected differences in the microbiota composition between individuals with ADHD and controls, of which alterations in genera The Supplementary Materials were changed accordingly and were included as a separate document.Due to applied changes, we would like to add Mirjam Bloemendaal as a co-author in order to emphasize her significant contribution to this correction; this was approved by all co-authors. She should be recognized for her help in verifying the applied changes, as well as in structuring and writing the correction paper.


This study was a comparison of the thickness of the choroid in pediatric patients with attention-deficit hyperactivity disorder (ADHD) and healthy pediatric controls.This study was comparative, cross-sectional, and observational in design. The healthy controls were age- and sex-matched with the members of the ADHD group and had no history of psychosis. Choroidal thickness was determined using spectral-domain optical coherence tomography.A total of 138 patients were enrolled with a male:female ratio of 54 (69.2%): 24 (30.8%) in the ADHD group and 41 (68.3%): 19 (31.7%) in the control group (p=0.910). The ADHD patients had a mean age of 9.4±1.9 years (range: 6-12 years) and the controls had a mean age of 9.9±2.2 years (range: 6–12 years) (p=0.213). The ADHD group (n=78 eyes tested) had a significantly higher mean choroidal thickness at 1.5 mm  measurement than the controls (n=60 eyes tested) . There were no significant differences in any of the other choroidal thickness measurements (p>0.05).The choroidal thickness measurement (TTF) at 1.5 mm was significantly greater in the ADHD patients. These findings suggest that choroidal thickness alterations may have a potential role in the underlying etiology of ADHD. Attention-deficit hyperactivity disorder (ADHD) is a prevalent pediatric neurodevelopmental condition  that pre Despite phenotypic differences ADHD, autism spectrum disorder, and schizophrenia (SZ) share many components in the etiological and pathophysiological pathways . EvidencMicrovascular abnormalities appear as a potential contributor to the pathophysiology of SZ as shown by genetic, neuroimaging, postmortem gene expression, and morphological studies . RetinalReports have shown that abnormal brain structure is linked to ADHD, and comprehensive decreases in total brain volume have been observed in children with this condition -10 similOptical coherence tomography (OCT) is an imaging modality that is noninvasive, and is able to capture cross-sectional scans of the retina with high resolution . AdvanceThis non-interventional, comparative, and cross-sectional study included 78 newly diagnosed ADHD patients (6–12 years old) who were recruited from the Department of Child and Adolescent Psychiatry of the single tertiary referral hospital between August 2017 and July 2019. The hospital’s ethics committee gave its approval for this study, which was conducted following the tenets of the Helsinki Declaration. The parents or legal guardians of the included children provided informed consent for the study.This study also included 60 healthy subjects as a control group (matched for age and sex to the ADHD group) who were enrolled from the Ophthalmology Department of the single tertiary referral hospital. These healthy controls were subjected to a routine eye examination and were determined to have no ophthalmologic disorders, psychiatric complications, and/or history of medication.All subjects included in this study were assessed by a psychiatrist specializing in children and adolescents using the Schedule for Affective Disorders and SZ for School-Age Children-Present and Lifetime Version-Turkish Version (K-SADS-PL-T) , 24.All included subjects underwent dilated funduscopic examinations. Inclusion criteria were as follows: having a best-corrected visual acuity (BCVA) ≥20/20, a refractive error (SE) of ±2 diopters, and an intraocular pressure of <21 mmHg. Exclusion criteria were as follows: not being able to complete the OCT examination, previous intraocular surgery, glaucoma, organic eye diseases, strabismus, cataract, laser treatment, any conditions of the retina, and having any systemic illness, immune disorder, or neurological disease.Every included subject was given 1% cyclopentolate  every 5 min, and cycloplegic refraction was performed 45 min after the initial treatment. Each subject had 5 autorefractor readings within 0.25 D of the other via a Tonoref II autorefractor/tonometer (Nidek Co. Ltd.). The following formula was used to calculate SE: spherical sum + 1/2 cylindrical error.All subjects underwent other clinical assessments, including BCVA, extraocular movements, slit lamp examination, intraocular pressure, average central keratometry, and central thickness of the cornea . In addition, the IOL Master  was used to measure the eye’s axial length.A Heidelberg Spectralis SD-OCT imaging platform  and an EDI program were used to obtain images for measuring choroidal thickness. Poor quality scans (scores under 20) and unclear images were excluded from the analysis.As previously described, EDI-OCT was used to determine subfoveal choroidal thickness . MeasureAll analyses were made in SPSS v 22.0 . The data distribution was assessed with a Kolmogorov–Smirnov test. Parametric data were assessed via Student’s t-test and non-parametric data underwent analysis via Mann–Whitney U test. A Chi-square test was used to compare group gender distributions. Values of p≤0.05 were determined to be significant.A total of one hundred thirty-eight subjects were enrolled in this study. The male/female ratio was 54 (69.2%)/24 (30.8%) for the ADHD group and 41 (68.3%)/19 (31.7%) for the control group. There was no difference in gender distribution between the controls and the ADHD patients (p=0.910). The average age of ADHD patients was 9.4±1.9 years (range (min:max), 6:12 years) and was 9.9±2.2 years  in controls (p=0.213).In addition, differences were not significant between the ADHD patients and controls with regards to SE, mean central keratometry, central corneal thickness, or axial length .The ADHD patients had significantly higher 1.5 mm temporal to the foveal center (TTF) choroidal thickness than the controls . Although choroidal thickness values also in other locations in the ADHD group was higher than the control group’s values, the differences were not significant .Age, SE, axial length, mean central keratometry, and central corneal thickness were not associated with choroidal thickness 1.5 mm TTF in ADHD patients .In this study, SD-OCT was used to assess choroidal thicknesses of patients with ADHD. The ADHD group had increased 1.5 mm TTF thickness of the choroid compared to controls. There were no correlations between the 1.5 mm TTF choroidal thickness measurements and demographic or ocular parameters.OCT has previously been used to assess ADHD patients -15. HergTo the best of our knowledge, the current study is the first to determine choroidal thickness in ADHD subjects with SD-OCT.The choroid consists of connective tissue, melanocytes, blood vessels, ﬁbroblasts, and resident immunocompetent cells . ChoroidGrönlund et al.  reportedResults of the current study reveal an increased choroidal thickness at the 1.5 mm TTF region for the ADHD patients versus controls. It is unclear why the choroidal thickness increased at this region in ADHD patients. However, the variance may be caused by disturbances in vascular development.Beyond the CNS, blood markers of pro-/anti-inflammatory states have been reported in ADHD . It has A recent study by Tarakcioglu et al.  quantitaOther parameters were not significantly different, including FAZ area, foveal and perifoveal density, FAZ perimeter, and thickness levels. However, that study did not compare OCTA parameters between ADHD patients and healthy controls.It has also been hypothesized that blood turbulence, or varying orientations of flow, may cause variations in macular choroidal thickness in ADHD, as well as increasing the 1.5 mm TTF region choroidal thickness.OCTA is a recently developed imaging technique that reveals changes in choroidal thickness and the vasculature. OCTA may provide evidence for the increased choroidal thickness in the patients with ADHD.There are several limitations to our study. There wasn’t an independent examiner for the evaluation of the OCT scans and measurements were made manually. Measurements were taken on a single day. Making measurements on several occasions would have increased the reliability of the data. Considering the age of our study group this was not appropriately feasible. We weren’t able to evaluate the anxiety caused by the eye examination. This might also have caused an increase in choroidal thickness. The results of our study don’t allow us to establish a casual relationship between increased choroidal thickness 1.5 mm TTF and ADHD. Further studies are needed to support that choroidal thickness could be used as a marker for the ADHD.Results of the current study show increased choroidal thickness at the 1.5 mm TTF region in ADHD patients. Choroidal thickness should be considered and further investigated in a larger population and using newer imaging modalities like OCTA, so that its role in the underlying etiology of ADHD can be fully elucidated.The present study was approved by the local ethics committee and informed consent was obtained from all participants or their parents or legal representatives. This study was conducted in accordance with the Declaration of Helsinki.Externally peer-reviewed.None declared.Involved in design and conduct of the study ; preparation and review of the study ; data collection ; and statistical analysis (SA).


Children with attention-deficit/hyperactivity disorder (ADHD) are commonly affected by medical illness. The aim of the present study was to explore the risks of contracting respiratory infectious diseases (RIDs), including upper and lower RIDs and influenza, in children with ADHD. We also examined whether methylphenidate has a protective effect regarding the risk of contracting RIDs among children with ADHD who have a history of methylphenidate treatment. Children in the Taiwan Maternal and Child Health Database from 2004 to 2016 were included in the present study. Upper and lower RIDs, influenza, ADHD, age, sex, and records of methylphenidate prescription were identified. A Cox proportional hazards regression model was used to estimate the significance of the risk of RIDs among children with ADHD in comparison with that among children without ADHD after adjustment for sex and age. The self-controlled case series analysis was conducted to examine the protective effect of methylphenidate treatment against RIDs. In total, 85,853 children with ADHD and 1,458,750 children without ADHD were included in the study. After controlling for sociodemographic variables, we observed that children with ADHD had significantly higher risks of upper RIDs, lower RIDs, and influenza infection than did those without ADHD. Among the children with ADHD who had a history of methylphenidate treatment, the risk of contracting RIDs was lower during the methylphenidate treatment period than during the nontreatment period. Children with ADHD had a higher RID risk than those without ADHD. Methylphenidate might reduce the risk of RIDs among children with ADHD who have a history of methylphenidate treatment. Attention-deficit/hyperactivity disorder (ADHD) is the most prevalent neurodevelopmental disorder and manifests as hyperactivity, inattentiveness, and impulsivity ,2. ADHD Research has shown that children with ADHD have predominantly higher rates of allergic sensitization and allergic rhinitis than the general population, indicating the shared etiology of ADHD and immunological diseases ,16. HoweMethylphenidate is the most commonly used stimulant that is effective for reducing not only the severity of ADHD symptoms and ADHD-related dysfunction ,22 but aThe first aim of this population-based study was to investigate the risks of contracting upper RIDs, lower RIDs, and influenza among children with ADHD in comparison with those without ADHD. We hypothesized that compared with children without ADHD, children with ADHD would be more likely to contract upper and lower RIDs and influenza. The second aim of the study was to examine the effect of methylphenidate on reducing the risk of contracting RIDs among children with ADHD who received methylphenidate treatment. We hypothesized that for the children with ADHD who had received methylphenidate treatment, the risk of contracting RIDs would be significantly lower during the treatment period than during the nontreatment period.The present study included liveborn children with information regarding gestational age at birth in the Taiwan Maternal and Child Health Database (TMCHD), which covered 99.78% of births , from 20In the current study, the primary exposure was the diagnosis of ADHD. Children were identified as having a diagnosis of ADHD if they received more than three outpatient diagnoses of ADHD  or one inpatient diagnosis of ADHD during the study period ,For children with ADHD, we further examined whether they received methylphenidate treatment after ADHD diagnosis according to dispensed prescriptions recorded in the prescribed drug register with the Anatomical Therapeutic Chemical classification of methylphenidate (N06BA04).For all of the children in the TMCHD, the main outcomes included upper RIDs, lower RIDs, and influenza according to ICD-10 and ICD-9 in the 2 test was applied to compare categorical variables and an independent t test was used to compare continuous variables. To determine the risk of incident RIDs in children with and without ADHD, the Cox proportional hazards regression model was applied, with adjustment for age and sex. Hazard ratios (HRs) with 95% confidence intervals (CIs) were used to verify the risk and statistical significance of differences in incidence rates of upper RIDs, lower RIDs, and influenza. Children without ADHD served as the reference. An HR value greater than 1 indicated an increased risk of RIDs in children with ADHD compared with those without ADHD. If the 95% CI of the HR included the null value of 1, then no significant difference existed in the risk of RIDs between the groups.For the descriptive statistics, continuous variables and categorical variables were recorded as the mean with standard deviation and frequency with proportion, respectively. To estimate the difference between children with and without ADHD, the Pearson’s χTo determine the beneficial effect of methylphenidate on RIDs, we performed a self-controlled case series (SCCS) analysis for within-individual comparisons. For individuals with ADHD, we divided the entire follow-up period into the nontreatment period and treatment period from the first date of ADHD diagnosis to the end of the research period , and the RIDs were treated as a recurrent event in the SCCS analysis. On the basis of previous studies ,28, the In total, 85,853 children with ADHD and 1,458,750 children without ADHD were included in the study. The characteristics of demographic variables in children with and without ADHD are presented in p < 0.001), with the highest risk noted for influenza. Protective effect of methylphenidate against RIDs in children with ADHD. Based on the SCCS analysis with a conditional Poisson regression model, we discovered that the children with ADHD had lower average risks for upper RIDs , as well as for lower RIDs , influenza , and all types of RIDs  during the methylphenidate treatment period compared with during the nontreatment period . Second, the TMCHD is a database including naturalistic and clinical information, and possible confounding factors could not be controlled for to the same extent as they can be in clinical trials. For instance, prescription of methylphenidate is not randomized to groups of comparison. However, naturalistic studies can include representative individuals, enabling the results to be more reflective of real situations. Third, medication records were based on prescription data rather than actual consumption, resulting in potential misclassification because of common imperfect medication adherence. However, this may have had little impact on our results. Because of the limited drug regulations for methylphenidate and the young age of the children in this study, it is less likely that children who were not prescribed methylphenidate actually consumed it. Instead, it is more likely that children who were prescribed the medication were not adherent to it. In this case, the misclassified effect period should actually be attributed to the non-effect period, which is a bias in favor of nonmedication, and we observed a significant protective effect of methylphenidate against RIDs; thus, the true effect of methylphenidate should be more profound.The present study reveals that children with ADHD have increased risks of contracting upper RIDs, lower RIDs, and influenza compared with those without ADHD. Regular treatment with methylphenidate is beneficial for reducing the risk of RIDs among children with ADHD. Establishing adequate interventions for infection control among children with ADHD is crucial, such as hygiene education, proper behavioral modification, and adjustments to school environments for social distancing purposes. Moreover, parents can adopt specialized parenting strategies to reduce the defiant and disruptive behaviors of children with ADHD, as recommended by the European ADHD Guidelines Group for preventing the spread of COVID-19 . The res