Poor health behaviors and variables are recently more documented in attention-deficit hyperactivity disorder (ADHD) lifestyle which might be relevant to the pathophysiology of this disorder. The objective of this case-control study was to assess the nutrient intake, dietary patterns, and anthropometric variables in children with ADHD compared to normal peers.One hundred children diagnosed with ADHD were included and compared to 100 healthy, sex-matched normal children as the control group. Anthropometric indices, macronutrients, and micronutrients were measured and compared in both groups.ADHD children were significantly consuming more simple sugars, tea, ready-made meals but less protein, vitamin B1, vitamin B2, vitamin C, zinc and calcium compared to the control group. The body mass index (BMI) and waist circumference of children with ADHD were significantly higher and were related to the severity and type of the disease.Unhealthy eating behavior is more frequent in children with ADHD, compared to normal children which might warrant lifestyle intervention in this disorder. Attention-deficit and Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder of childhood and adolescence  marked wanthropus means the human and the metric means measuring and is referred to as the measurement of human physical indices. One of the aims of anthropometric measurements is to examine the human body size and shape. In the developing population including children and adolescents, anthropometric measurements are applied as variables of growth and development [One factor related to dietary behavior is anthropometric indices. The word anthropometry consists of two parts: the elopment . Other aelopment .Some of these anthropometric variables are investigated in children with ADHD. A study in this respect investigated the changes in body and hormone levels in children with ADHD and found that several variables are either lower or higher in children with ADHD when compared to typically-developing controls , 14. In The association of dietary behavior and ADHD symptoms is important for the well-being, general health, and development of children with ADHD, however, a limited number of studies exist in this respect. Moreover, although the above-mentioned studies provide some insight about nutrients and anthropometric variables in ADHD, no comprehensive investigation of variables is available. Finally, the mixed results from previous studies warrant further investigation in carefully-controlled case studies. Accordingly in the present study, we aimed to assess the dietary patterns, nutrient intake, and anthropometric variables in ADHD children as compared with normal children. Additionally, we assessed the anthropometric variables with regard to ADHD subtype and severity of symptoms.This study adopted a case-control design and performed on children aged 5–13 years old with and without ADHD. Sample size was determined based on previous similar works and using the Cochran formula and 200 children, including 100 children with ADHD (case group) and 100 typically developing controls (control group) were recruited. To reduce the confounding factors, two groups were matched for age and sex. Considering that the sample was selected in Ardabil, all the children present in the study were Azeri and of the same race. Inclusion criteria for the ADHD group were (1) meeting Diagnostic and Statistical Manual of Mental Disorders criteria (DSM-5) . TypicalAll ethical requirements according to the declaration of Helsinki were met. The study protocol was described to parents and their children. We obtained the written informed consent form parents and oral assent from children before participation in the study. Ethical approval was obtained from the ethics committee review board of the Ardabil University of Medical Sciences (ethics code: IR.ARUMS.REC.1395.81).Participants in the ADHD group were selected from the patients referred to the Fatemi Hospital of the correspondent university and healthy controls were age and sex-matched from kindergartens and schools during the year 2018. In both groups, children were screened for ADHD by a professional child psychiatrist according to the clinical interview based on the DSM-5 diagnostic criteria. The healthy control group was also interviewed for ruling out ADHD and other neurodevelopmental disorders. The severity of the disorder was furthermore assessed by the Conners questionnaire (parent form) . Then diIn this study, anthropometric variableswere measured by a trained physician. Anthropometric parameters were measured in the standard positions. Bodyweight was measured on a calibrated digital scale, to the nearest 0.1 Kg, for this purpose the subjects wore minimal clothes without shoes. Height was measured by an un-stretchable tape on a wall with a straight body position to the nearest 0.1 cm. Waist and arm circumferences were measured by an un-stretchable tape to the nearest 0.1 cm. Body mass index (BMI) was calculated by dividing weight (kg) to height squared (m2).The children’s nutritional information was collected by the Food Frequency Questionnaires (FFQ) . The guiData analysis was conducted using the SPSS-21 software package. Descriptive statistics including mean and standard deviation were used for data overview and to compare groups (ADHD vs control) in outcome measures , independent Student’s t-test was performed. The effect of ADHD subtype  and symptom severity on each anthropometric variables was also investigated using the univariate analysis of variance (ANOVA). The assumptions of homogeneity of variances and normal distribution were examined with Levene’s test for homogeneity of variances and Shapiro-Wilk test of normality respectively.The mean age of the ADHD children in the case group was 8.33 ± 2.10 years and the mean age of the control group was 8.26 ± 2.00 years. 72% of both groups were boys and the rest were girls. There was no significant difference between the groups in these demographic variables. Demographic information and the mean and standard deviation of age, weight, height, BMI, and other anthropometric variables are summarized in Table p = 0.012) and Waist Circumference (p = 0.039) , tea (p = 0.006), and Ready-made meals (p = 0.002), and lower vitamins B1, B2, C, Zn and calcium than those in the control group.Table In this age and sex-matched case-control study, we compared nutrient intake, dietary patterns, and anthropometric variables of children with ADHD in comparison to healthy controls. The main findings of this study were lower levels of protein intake, higher poor dietary habits , and lower levels of micronutrient intake such as vitamin C, vitamin B1, vitamin B2, calcium, zinc, and iron in children with ADHD compared to typically-developing peers. ADHD children had greater BMI values as well.p = 0.006), dietary intake of zinc, protein, phosphorus, selenium, calcium, and riboflavin (p = 0.014), and the serum zinc level was negatively associated to ADHD (p = 0.003) [With regard to nutrient intake and dietary patterns, although there was no significant difference in total intake of carbohydrates and fat between the groups, consumption of simple sugars and tea was significantly higher and protein intake was significantly lower in children with ADHD. In the study by Ríos-Hernández et al. (2017),  there was no significant difference in dietary caloric intake and consumption of carbohydrate and fat between children with ADHD and normal children . However= 0.003) .In anthropometric indices, a non-significant difference was found between the arm circumference of ADHD children and normal children . AnotherWhen it comes to height, results are also mixed. A study found that the height of non-medicated children with ADHD was significantly higher than normal children but after the beginning of pharmacotherapy, the growth velocity reduced so that those who remained on stimulant medication showed an annual growth rate about 20% less than what expected . MoreoveIn this line, there is still controversy in various studies over the BMI difference between children with ADHD and their normal peers. In a relevant study, the BMI of children with ADHD was 19.6 ± 3.4 while it was 18 ± 3.3 in normal peers. Statistical analysis indicated that this difference was statistically significant . ContrarFinally, we observed differences in eating behavior between ADHD children and healthy controls. Children with ADHD had a significantly higher waist circumference which is an indicator of fat tissue accumulation in the abdomen. Weight gain and fat accumulation in ADHD may be due to the association between impulsive behavior and loss of control in eating behaviors . FurtherSome limitations should be considered in our study. Despite the instructions and guidelines delivered to parents, studied food pattern may have missed some items, including snacks used in schools, which may children provide from school buffet. Other limitations of this study include the small sample size. Furthermore, parents’ awareness of ADHD may affect the children’s dietary patterns. It is suggested that Martin’s anthropometric measuring instruments be used for weight measurement in future research.Children with ADHD have higher waist circumference and BMI than healthy children, and this difference is related to the severity of the disease and its type. The BMI and waist circumference in children with mild ADHD and mostly attention-deficit type was significantly higher than the control group. Children with ADHD consume more simple sugars, tea, and ready-made foods but lower protein, vitamin B1, vitamin B2, vitamin C, zinc and calcium compared with their normal control peers. These results suggest lifestyle and nutritional interventions in children with ADHD as early as possible.


Parents’ knowledge and misconception about attention-deficit hyperactivity disorder (ADHD) influences their children’s access to care, its management and outcome. The study aimed to investigate parents’ knowledge and perceptions of ADHD.The cross-sectional survey of 79 parents of children (aged 5–17 years) with ADHD at a specialist child psychiatry clinic in KwaZulu-Natal Province, South Africa, consisted of a socio-demographic and clinical questionnaire, and the Knowledge of Attention Disorders Scale questionnaire, was carried out.Twenty-six (32.9%) parents consulted a traditional healer, of whom 84.6% did so before consulting a medical doctor, with 61.5% reporting that the healer suggested psychiatric referral. Most parents had some knowledge of their child’s ADHD diagnosis but held various misconceptions about its treatment and associated factors: 92.4% believed that reducing sugar or food additives were effective to reduce symptoms; 78.5% that treatments focussing on punishment reduced the symptoms; 67.1% that prolonged use of stimulant medications leads to increased addiction  in adulthood.Many parents had misconceptions about ADHD’s causes and treatment, some having consulted traditional healers, indicating the need to increase awareness among health practitioners to ensure timeous treatment access. A parent focussed psycho-education programme is required that provides information about causes, symptoms, treatment and prognosis. Although the incidence of ADHD is comparable in both white and African Americans in the United States (US), fewer children of the latter were diagnosed and treated, which may be because of the complex barriers extending from the home to the health care system.11 and that medication is the mainstay of treatment,12 public controversy about it remains prevalent, being fuelled by perceptions from society, including parents, teachers and even health professionals.13 There are also many misconceptions relating to its causes, symptoms, treatment and course.10 Misconceptions commonly relate to the sources of information, for example, television and social media, parenting practices and the side effect profiles of psychotropic medications, particularly the stimulant methylphenidate. Based on these perceptions, parents tend to balance the advantages and disadvantages of using ADHD medications, with some opting for less evidence-based treatment.15Although it has been scientifically accepted that ADHD is a childhood-onset neurobiological disorder15 A community study in the US on adolescents at high risk of developing ADHD because of family history reported that, although many of their parents, teachers and health care professionals were familiar with the diagnosis, there were several misconceptions relating to its treatment and the potential addictive effect of medication.16 This has been further supported by a review of the literature on surveys among parents, teachers and professional regarding ADHD.13In an Australian community study of parents and adolescents, while many participants were knowledgeable about ADHD, there were gaps in their knowledge about its genetic aetiology and course of illness, with many caregivers expressing concerns about over-medication.17 Although a South African study assessed primary school teachers’ knowledge and misperceptions of ADHD in the Western Cape province,18 there appears to be very limited data from Africa on the subject.A study in Iran in 2007 of parents of children with ADHD found that their knowledge of the condition was relatively poor, particularly relating to its biological and genetic causation and their limited awareness led to delays in accessing care.19 Bussing et al. suggested that cultural variations may affect ADHD knowledge in the US,1 although this was not borne out in a later study.16 In a more recent (2017) study in Iran, parental knowledge in a clinical sample correlated significantly with educational level.10 In addition, parental knowledge, attitudes and awareness may also be influenced by the information sources, with patients and carers traditionally relying on the physician for psycho-education, although there is an increasing reliance on the Internet and other media.13 In the more recent Iranian study by Dodangi and colleagues, 52% of parents of affected children reported that the television was the most common source of information.10Parental knowledge of ADHD may be influenced by multiple psycho-socio-cultural factors, including educational level, race, culture, stigma, access to the Internet and mental health services.The literature therefore notes that several misconceptions about ADHD persist, specifically related to diagnosis and treatment, which may be influenced by various factors that, in turn, could affect adherence and outcome. Against this backdrop of ADHD being one of most common neuro-developmental disorders in children, and because of the reliance on parental knowledge and attitudes to its treatment to ensure an optimal outcome, it is important to investigate this aspect in the South African setting, where there are limited mental health resources.This study therefore aimed to describe the knowledge and misconceptions towards ADHD among parents of children receiving care at a public sector outpatient psychiatric hospital in KwaZulu-Natal province, South Africa. We also aimed to explore any associations between parents’ socio-demographic characteristics and the Knowledge of Attention Deficit Disorder Scale (KADDS) sub-scale scores or misconceptions.20 who were referred to study researcher. Inclusion criteria were English-speaking parents of children with ADHD at a specialist child psychiatry outpatient service and had been under treatment for a minimum of 6 months. The diagnosis of ADHD was based on the clinical assessment by using DSM 5 criteria by senior psychiatry registrars under the supervision of or by a child psychiatrist. Carers who were not biological parents were not included in this study.This cross-sectional, descriptive study involved a questionnaire interview with 79 adults (18 years and older) biological parents of children (aged 5–17 years) with an established clinical diagnosis of ADHD, as per the Diagnostic and Statistical Manual (DSM 5) criteriaAll parents were invited to participate in the study, with survey being completed on their clinical visit. All surveys were completed by the principal investigator (N.R.) after written informed consent was obtained, with data being collected from May 2017 to March 2018.Two instruments were used to obtain data: a parent socio-demographic questionnaire and the KADDS.Socio-demographic and clinical questionnaire: A socio-demographic and clinical questionnaire was used to obtain child and parent variables and consisted of three sections. Section 1 obtained the parent’s demographic details, such as age, gender, occupation, educational level, household income and the number of children. They were also asked if they had consulted a faith healer and whether they had suggested psychiatric treatment. Section 2 obtained the child’s socio-demographic  and clinical characteristics from the parents, which were confirmed by chart review for variables, such as diagnosis, duration of illness and treatment. Section 3 explored the sources of parents’ knowledge and misconceptions about ADHD and was based on a review of the literature. Data on their experience of stigmatisation, support systems, ADHD causes, sources of information and perception of the health care received were collated. Stigma was defined for parents as a mark of shame, disgrace or disapproval that results in an individual being rejected, discriminated against and excluded from main society.Knowledge of Attention Deficit Disorder Scale: The KADDS is a 36-item rating-scale questionnaire21 that uses a true, false or do not know format and enables a comparison between the parent’s knowledge and their attitudes (perceptions), that is, their misconceptions. The KADDS was developed to measure knowledge and misconceptions in three sub-scales: symptom or diagnosis (9 items), treatment (12 items) and associated features  (15 items) among parents, teachers and mental health professionals, being used in this study for the former only. Knowledge was measured by correct scores and misconceptions by incorrect responses.18 Internal consistency was found in the present study, with the Cronbach’s alpha for the total score being 0.551, possibly because of poorer proficiency in English as English may have a second language for some participants. The KADDS scale was used previously in the Western Cape Province, South Africa, in a study that assessed primary school teachers’ knowledge and misconceptions of ADHD.18 The tools were piloted on 10 parents prior to data collection to ensure that all questions were comprehensive. It provided insight on how best to phrase the survey questions and to ensure that they were all understood.The questionnaire does not make provision for a total score, with each item being assessed individually and the sub-scale scores being compared. The items in the KADDS scale have statistical reliability and validity, with research having been conducted on the internal consistency of its total score, based on the original 36 items scale (three items are still for further testing), revealing a high internal consistency, ranging from 0.81 to 0.86.t-tests or Wilcoxon rank sum test, with a p < 0.05 being considered statistically significant. The data are presented in three sections: (1) correct knowledge, (2) incorrect knowledge (misconceptions) and (3) associations between misconceptions with parent characteristics.The quantitative data from the socio-demographic questionnaire were entered and analysed by using the Statistical Package for Social Sciences version 26 software by using descriptive statistics. The variables from the KADDS questionnaire were also descriptively analysed by using the number and per cent for the categorical variables, with their frequency distribution being examined, and the means with standard deviation, medians and inter-quartiles ranges being used, as appropriate. The three sub-groups of the KADDS  were compared by conducting chi-square tests on The study was approved by the University of KwaZulu-Natal’s Biomedical Research Ethics Committee (Ref BE036/17). Permission was also obtained from the Department of Health and written informed consent from the parents.Of the 82 parents who were invited to participate, 79 agreed and 3 refused. The results were: (1) the parents’ socio-demographic and health-seeking behaviour, (2) children’s clinical characteristics, (3) the source of the parents’ knowledge, being followed by (4) the KADDS sub-scale scores (knowledge and misconceptions) and possible associations between the parent factors.n = 57, 72.2%), married (59.5%) and black (49.4%); did not have a tertiary education ; and had two children (45.6%). Seven (8.9%) of the parents had two or more children with ADHD, whereas the majority  had only one affected child (The majority of parents were 41–50 years old (49.4%), female . In terms of age, 57.7% were 10 years and older, 67.7% (n = 61) attended mainstream schools, and although 87.7% had been diagnosed at least 2 years previously, 95.5% had been on treatment for more than a year.N = 79, 100%) reported being informed of the diagnosis of ADHD by a medical doctor, with the majority being satisfied about obtaining information on the diagnosis  and treatment , but data on type and quality of information received were not collated. However, the majority reported experiencing stigma  relating to their child’s illness. Although doctors  and clinic staff  were the most common providers of information, there were other sources , such as teachers , the media  (newspaper and television), the Internet  and other parents . Fifty-seven (72.1%) parents mainly attributed the cause of ADHD to a chemical imbalance in the brain, 21 (26.5%) to genetics, 27 (34.1%) to sugar use and 21 (26.6%) to being a spoilt child.All the parents (The participants’ KADDS scores (correct responses) were assessed for the three sub-scale scores and individual items and are summarised in The most common correct knowledge and incorrect responses (misconceptions) are indicated with their respective question (Q) number and statement from the KADDS.Most common correct knowledge responses:■78 (98.7%) – ADHD children are frequently distracted by extraneous stimuli (Q 3).■75 (94.9%) – Side effects of stimulant drugs include insomnia and appetite reduction (Q 15).■73 (92.4%) – In order to be diagnosed as ADHD, a child must exhibit relevant symptoms in two or more settings  (Q 21).■65 (82.3%) – Children with ADHD are more distinguishable from normal children in a classroom setting than in a free play situation (Q 31).■53 (67.1%) – Stimulant drugs are the most common type of drug used to treat children with ADHD (Q 25).Most common incorrect responses on KADDS (misconceptions):■70 (88.6%) – When an ADHD child’s treatment is terminated, it is rare for the symptoms to return (Q 12).■63 (79.7%) – Most ADHD children will ‘outgrow’ their symptoms by the onset of puberty and function normally in adulthood (Q 19).■73 (92.4%) – Reducing sugar or food additives effectively decreases ADHD symptoms (Q 23).■60 (75.9%) – Children with ADHD generally experience more problems in novel situations than in familiar situations (Q 27).■62 (78.5%) – Treatment that focusses mainly on punishment is the most effective for reducing ADHD symptoms (Q 36).■53 (67.1%) – Prolonged use of stimulant medications leads to increased addiction  in adulthood (Q 37).■70 (88.6%) – If a child responds to stimulant medications , they probably have ADHD (Q 38).Association between KADDS sub-scale scores with parent characteristics:The small sample size must be noted as a limiting factor.In addition, the analysis of the parent’s socio-demographic factors and KADDS sub-scale scores is summarised in The aim of this study was to determine the knowledge and misconceptions of ADHD among parents of children receiving treatment for ADHD at an urban public sector psychiatric unit in KwaZulu-Natal, and to establish any associations with their socio-demographic characteristics. The key findings of this study were that parents of children with ADHD all had knowledge of the diagnosis of ADHD, and despite majority believing that they had received information on diagnosis and treatment from the clinic, there was gaps in knowledge on symptoms, treatment and associated features as evidenced by the mean scores for the three sub-scales on KADDS. Misconceptions about punishment as a treatment modality for ADHD, sugar intake associated with symptoms, stimulants causing addiction and ‘outgrowing’ ADHD were most common. In addition, almost a third of parents consulted a traditional healer with support clinical staff being the main source of knowledge on ADHD.22 In South Africa, there is a glaring lack of child mental health services, with faith healers playing an important role in trying to bridge that gap, as they are generally accessible. Providing mental health education for faith healers may facilitate appropriate and timeous referral faith healers maybe the first point of contact for parents when seeking an understanding of unusual behaviour.23 In this study, 32.9% of parents seeking medical care at an urban facility consulted a traditional healer, further emphasising the critical role they play in the local socio-cultural context and the need to integrate them in a holistic health service. No studies on the extent of traditional health-seeking behaviour for children with ADHD were found.As per the World Health Organization, only 10% of people with neuropsychiatric conditions are estimated to have access to mental health services.24 as being common sources, which suggests that access to suitably trained medical staff may vary between countries. The most common source of information in other studies is the media (radio and television),24 which is in contrast to the findings of this study where all parents claimed to have received information related to ADHD from the treating medical staff of the clinic. Media is the third most common cause of information in this study. This may represent a form of subjective bias reporting from parents or suggests that parents in this context have less access to media for health education. This suggests that health care services need to ensure that appropriate psychoeducation and support around ADHD is provided as they appear to be the main source of information. This is critical in primary health care settings where parents may have even greater challenges accessing reliable knowledge sources.All parents (100%) in this study claimed to have received information from the medical staff of the clinic, the other most common sources being schoolteachers (89.8%), the media (88.6%) and Internet (56.9%). Other studies reported the media (radio and television)Although all parents were aware of the ADHD diagnosis, the mean scores for the three sub-scales of 6.1 (symptom or diagnosis), 6.4 (treatment) and 6.9 (associated features)  suggest that there were still gaps in their knowledge.16 The current study found no association between educational level with improved knowledge on any KADDS sub-scales. This is contrary to the literature that higher education is a positive factor in health-seeking behaviour.25 Traditionally studies suggest that while the parents recognised that there could be a behavioural problem with their children, their own educational levels may affect their health-seeking behaviour with relevant health authorities. Parents of lower educational and income levels appear to be less knowledgeable about appropriate treatment behaviour for their children in other international studies;27 however, possibly, access to a specialist service with more individualised care may have modified this finding. The lack of positive association between education and better knowledge of symptom and treatment sub-scales suggests the need to in addition further explore this and other parental variables in a larger study that is possibly better placed at community-level services as access to care may also be measured in those contexts.These scores are consistent with the literature, which demonstrated that parents have knowledge but still harbour misconceptions relating to ADHD.16 The misconceptions regarding the sugar intake-associated symptoms of ADHD (most common misconception in this study), use of stimulant leading to addiction, reliance on punishment to bring behavioural change and outgrowing ADHD were common in this and other studies.33 An earlier American study suggested that black Americans strongly accepted the ADHD ‘sugar’ aetiology.30 In the study the authors proposed that this may be because of factors such as different cultural thresholds and perception of bad behaviour, beliefs that ADHD is not a medical condition, discrimination, lack of trust of health professionals and economic constraints based on socio-cultural differences.32 Perold and colleagues reported similar findings relating to ADHD and the sugar myth amongst teachers in South Africa, who believed that sugar was the cause and the children would outgrow the symptoms.18 This suggests that as health care workers, we need to provide more information on the role of diet, particularly sugar and ADHD symptoms. There is also a need for more and better qualitative studies to understand the influences that drive these misconceptions.In line with other studies, this study showed some common parental misconceptions that are present in research from developed and developing countries.34 This is an important misconception that should be more actively focussed in psychoeducation as it has treatment and prognostic implications. Parents need to be aware that untreated ADHD is a risk factor for substance use.35 This study did not further explore the associations with regard to misconceptions and parental factors as the study sample size limits credibility of findings.Another common misconception was related to the addiction potential of stimulants, as this may be associated with poorer medication adherence if the parents have concerns about the treatment options. In this study, 67% of parents believed that a prolonged use of stimulant medications leads to increased risk of substance addiction  in adulthood, and these findings being consistent with the literature.3 The psycho-education content on ADHD therefore needs to be reviewed to address common myths held by parents. We also need to consider if the gaps are because of insufficient staff training in communication skills and ADHD knowledge. We also need to provide information – including tailored information, avoiding use of jargon and inviting questions for clarification and providing psycho-education in the first language such as isiZulu for parents so that it bridges their gaps in knowledge.The findings of this study have important implications in planning various interventions about ADHD education, as parents are the most significant role players who influence child health outcomes. By providing accurate knowledge, relating to misconceptions, myths and misperceptions will fade and potentially alter the health-seeking behaviour of parents with children of ADHD. Ideally, paediatric mental health care should be integrated and available at community-based services to improve access and allow early referral of children requiring more complex care to specialist services and hence better utilising scarce mental health resources. This will enable parents to have better problem recognition, selection and utilisation of health resources.The study had several limitations such as the small sample size, which limit generalisability, and the study setting being in an urban area and at a specialist hospital, which may prevent the results being generalisable to other settings. The inclusion of English-speaking parents only may have biased the sample, as many people attending public sector facilities speak isiZulu as their first language, their knowledge and misconceptions were not captured and they may have been more vulnerable to poorer psycho-education as some information may be lost in translation. The convenience sampling and the participants’ profile are not representative of the national South African demography that may further limit the generalisation of the findings. Although the KADDS has been used in the South African setting, the lack of a validated multilingual tool to assess ADHD knowledge and misconceptions in this setting is another limitation. However, the study does provide insight into parent’s knowledge and perceptions of ADHD in an African mental health care setting.There is a need for more focussed psychosocial interventions to address the gaps in knowledge and misconceptions held by parents of children with ADHD. A community-based participatory research study would be useful to determine needs and more appropriate, sustainable interventions.The study findings reveal substantial knowledge gaps among parents of children with ADHD regarding treatments and associated features of ADHD and the need to consider more appropriate interventions to address these better in clinical settings including involving appropriate staff and intervention planning.


Analyses showed a differential link between FMS and lexical processing as a function of age. Whereas response latencies indicated that children’s FMS were associated with “hand” words, adults’ FMS linked to the broader concept of BOI. Findings have implications for shared activation theories positing that FMS support lexical processing.Children’s fine motor skills (FMS) link to cognitive development, however, research on their involvement in language processing, also with adults, is scarce. Lexical items are processed differently depending on the degree of sensorimotor information inherent in the words’ meanings, such as whether these imply a body-object interaction (BOI) or a body-part association . Accordingly, three studies examined whether lexical processing was affected by FMS, BOIness, and body-part associations in children (study 1,  Language development is perhaps the most anticipated event in the early years, providing the key to communication, cognitive development, and academic success . SomewhaFMS can be described as the use of small muscles in movements involving the  extremities when, for example, manipulating objects . FMS oftA second account  proposes, that FMS contribute actively to the development of vocabulary, in the sense that children with better motor skills have greater interactions with the environment, which introduces possibilities to explore and expand their lexicons .Thirdly, the shared activation hypothesis suggests that FMS and vocabulary utilize similar underlying brain structures and processes, such as the Broca-area, the cerebellum, or the pre-frontal cortex e.g., . PresumaTo date a significant amount of evidence has linked FMS and vocabulary development (word comprehension). In a large-scale study investigating children’s academic achievement and FMS, robust links between FMS and receptive vocabulary from kindergarten to second grade were found . CameronHowever, studies also show contradicting results. In summary, these mixed findings generally point to a role of FMS in vocabulary development, although findings are somewhat inconclusive and limited to children and little is little known about underlying mechanisms. As discussed next, research on lexical processing has identified sensorimotor word features that are associated with faster response latencies, which may provide an avenue to better understand links between FMS and vocabulary.Research suggests that lexical items are not stored exclusively in amodal information structures, but instead in complex networks involving the sensorimotor system . Neuropschair or couch, and the opposite applies to low-BOI words . In a series of experimental studies, One index for the degree of sensorimotor information relates to the degree of body-object interaction (BOI), referring to the “extent to which a human body can physically interact with a word’s referent” , p. 12. Although studies with adult participants have shown robust processing advantages for high-BOI vocabulary, those with younger populations yield mixed results. A study by Given lexical processing advantages for words with a high-BOI rating, a question arises as to whether such lexical items especially relate to FMS at a behavioural level, that is, beyond evidence indicating shared neurological activation. According to the shared-activation and nimble-hands, nimble minds hypotheses, FMS might share neurobehavioral processes with lexical processing, particularly for words that are high-BOI  or relatper se is manipulable, but instead which body-part it is typically manipulated with. This assumption is partly supported by a study from Alternatively, it may not be essential that the object feather, picking) showed a greater link to FMS than BOI words. Thus, evidence is mixed as to whether a body-part localized action, or BOI per se, or both, mediate links between FMS and vocabulary.Relating body-part association to the BOI effect, To date, research has found mixed evidence of links between FMS and general vocabulary e.g., . AccordiTherefore, in three experiments, we measured FMS as well as BOI and body-part association ratings of select lexical items, alongside a host of lexical and cognitive control variables. Extending previous work , we examIn experiment 1, we investigated the role of body-part associations in children’s lexical performance (response latencies in a word-picture recognition task), in comparison to BOI while controlling for a host of lexical and cognitive variables. In study 2, we explored whether the results extended to an adult population. Study 3 sought to replicate the findings of study 2, using a different measure of FMS with a higher ceiling to that employed in study 2.To date, only three studies have assessed the relationship between children’s FMS and vocabulary while taking BOI into consideration . Two of First, we expected children to show shorter response latencies to high BOI words, compared to low BOI words, thereby replicating the results by Participants. A total of 77 children attending pre-school aged three to six years  took part in this study, of which 52% were female. A post-hoc power analysis revealed that with four predictors  and the current sample size, assuming a conservative total variance estimate , an adequate power of.83 would be obtained. The two pre-schools were located in and around a small city in southern Germany with a population of approximately 160,000 people. Overall, 78% of children were right-handed, 17% left-handed and 5% ambidextrous. On average, 23% of children spoke an additional language to German at home. Regarding educational background, 36% of mothers and 51% of fathers had acquired a university degree. Therefore, this sample was better educated than the average German norm of 28% , were tested individually in their pre-schools. To minimize potential concentration issues, the experiment was divided into two sessions of approximately 30 min. Session one contained the Matrices test, the BOI vocabulary task and the FMS tasks. To establish the dominant hand for the FMS tasks, a handedness test was administered at the beginning of session one by asking children to show how they brushed their teeth and held a pen or pencil. Invariably, children used the same hand to imitate brushing their teeth and writing, which was then recorded as their dominant hand. This was followed by the matrices test. Subsequently, to maintain children’s interest as well as avoid order of sequence effects, the BOI-vocabulary task and the FMS tasks were executed in alteration. Session two included the PPVT, conducted in two blocks separated by the general knowledge task. Half of the children started with Session one, the other half with session two. Sessions were held approximately one week apart. For each finished task the children received a sticker as a reward. The experiment was run by the first-author and trained undergraduate education students.Measures. Measures included demographics, FMS, general vocabulary and reasoning. Demographic information, such as age, gender, spoken languages at home, number of siblings and highest educational qualification of both parents was obtained via a parent questionnaire.Fine Motor Skills. FMS was assessed with the Movement Assessment Battery for Children  as to “…the ease with which a human body can physically interact with a word’s referent”  based on the question “To what extent do you associate these words with following body-parts?”. Twenty-one different undergraduate university students, who worked in the department as research assistants or were completing undergraduate research projects, rated each word’s association with the hand, arm, foot and mouth. Here again, an excellent interrater reliability was attained, Cronbach’s alpha = 0.96, ICC = 0.96.1 for length, syllables, and frequency. Means and standard deviations for the words ratings (BOI and body-part) and different word variables, can be found in To ensure that any effects found in this study could either be attributed to the degree of BOI or to the body-part association, we additionally incorporated different linguistic variables including: age of acquisition, semantic neighbourhood, semantic diversity, length, number of syllables and frequency of the words. We collected the ratings using databases from various studies, such as Pictures representing BOI-vocabulary words were chosen from the International Picture Naming Project IPNP, , if avaiFor the actual test, children were positioned in front of a computer screen, on which two pictures were shown, the target picture and a distractor. The distractor item was randomly drawn from the other 122 items. Each item was therefore presented twice, once as the target word and once as a distractor in a randomized fashion . Children were instructed to look at the pictures while simultaneously hearing a pre-recorded word. The orally presented word matched the target picture on the screen. The children were required to identify the corresponding picture by pressing the equivalent buzzer as quickly as possible. Children were asked to return their hands to a resting position next to the buzzer after each trial. To make sure the participants understood the task, three practice trials were held. Here the words were not presented via headphones, instead the experimenter spoke the words to make it possible to intervene immediately should the task be executed falsely, by providing constructive corrective feedback . To ensure a standardized and exact procedure, the experiment was conducted and reaction times were recorded using the software E-Prime 3.0.General Vocabulary. The Peabody Picture Vocabulary Test (PPVT 4), German Adaptation , Matrices and General Knowledge, were administered  and approved by the Ethics Committee of the University. Written informed parental consent was obtained and children gave their verbal assent prior to test administration, in accordance with the Declaration of Helsinki.As a result of illness, four children completed one session only, and three participants’ data were excluded because experimental instructions appeared to have been misunderstood, leaving 70 of the original 77 participants. To ensure that only correct responses were included in the analyses, reaction times following an incorrect response were omitted. Additionally, four words  were dropped from subsequent analyses, as error rates for these words were 20% or higher. On an individual level, reaction times were corrected for outliers that lay three standard deviations outside of the individual response means of high, low and medium BOI words. In total 10.03% of responses were omitted.To create a general estimate of FMS, a factor analysis was conducted, showing, that all FMS tasks  loaded onto a single factor . Therefore, the scores were combined to be represented by a single z-factor  = 5.01, p < 0.001, showing that responses to high BOI words were significantly faster than to low BOI words. Following, gender differences were assessed. Female participants showed overall better scores in the maze tracing task, t(71) = 2.08, p = 0.04. No further differences were found .Descriptive statistics of age, IQ estimate, general vocabulary, FMS, and BOI reaction latencies as well as accuracy rates are presented in Links between lexical ratings. To examine the relationship between the word ratings (BOI and body-part), the picture ratings (complexity and fit) and the different word variables , correlation analyses were conducted and are presented in r = 0.69, p < 0.001, as well as arm ratings, r = 0.47, p < 0.001, emerged.FMS and response latencies. To investigate the role of FMS and body-part association in the processing advantage of high BOI words, analyses using mixed-effects models for experimental research designs (codes were extracted from lme4 (R Studio (rom lme4  in R StuR Studio .2(4) = 21.94, p < 0.001. BOI ratings, body-part association ratings , picture ratings (fit and complexity) and word variables , syllables, and frequency class) were then entered as Level 2 covariates (see 2(14) = 397.55, p < 0.001. Lastly, we tested for interactions between FMS and the different word rating measures for BOI and body-part association ratings , which again improved the model significantly, χ2(5) = 27.88, p < 0.001.As a first step, the unconditional model was calculated to assess the relation of within-subjects to between-subjects variance. An intraclass correlations coefficient (ICC) of.46 was obtained revealing a significant inter-subject variance, therefore supporting the decision to use a mixed-effects model. In a second step, we modelled individual intercepts using random effects but modelled slopes as fixed effects due to model convergence problems. To predict children’s response latencies, FMS, intelligence, age, and general vocabulary were entered as Level-1 covariates, which significantly improved the model, χThe model in We attempted to replicate, clarify, and extend previous work examining links between BOI , FMS, anr = 0.69, see Interestingly, a study by Previous studies on the role of BOI for the link between FMS and vocabulary development , 2017 haParticipants. A total of 80 adults aged 19–30  of which 66.25% were female took part in this study. 95% of the participants were right-handed, 2.50% left-handed and 2.50% ambidextrous. All were native speakers of German. The participants gave written informed consent and received 10 € as compensation. The study was approved by the University Ethics Committee.Measures and procedure. Students’ demographic information concerning age, marital status, highest school qualification, job training and current job was gathered via a questionnaire.As in Experiment 1 the M-ABC 2 was used to assess FMS. However, the tasks vary depending on the age group. Hand dominance was determined simply by asking the adults as to whether they were left or right handed (or ambidextrous). For the adult population until age 16, the FMS tasks included turning pegs with the dominant and the non-dominant hand, building a triangle with nuts and bolts and maze tracing. Although the Movement-ABC is only normed for individuals up to age 16, we reasoned that FMS development is thought to plateau around this age and hence, to also preserve task continuity with study 1, we opted for this test battery. Again, two trials were possible for each task, depending on whether the first trial was completed within a certain time frame (pegs and triangle) or completed without a mistake (tracing).The same BOI-vocabulary test and general vocabulary test (PPVT-4) were used as in Experiment 1. To obtain an intelligence estimate, two subtests of the Wechsler Adult Intelligence Scale, German Adaptation (WAIS-GA), Matrices and General Knowledge, were used, equivalent to the WPSSI in study one . Both scOne participant performed the peg task incorrectly and was eliminated from the analyses, leaving 79 out of 80 participants. In accordance with experiment 1, only correct responses were admitted to the analysis, while incorrect responses were omitted. No words were dropped from the subsequent analyses, as error rates were all below 10%. On an individual level, reaction times were corrected for outliers that lay 3 standard deviations outside of the individual response means of high, low and medium BOI words. In total, 3.52% of responses were omitted.As the norms of the M-ABC 2 only extend to the age of sixteen, adults’ M-ABC 2 scores were not converted into standard scores. Instead, the raw scores were used in the analyses. To facilitate interpretation, adult motor scores were converted by multiplying -1, such that greater FMS scores indicate more pronounced FMS levels. Having determined that students’ FMS  loaded onto the same factor , the FMS data were combined to be represented by a single factor z-score.t(79) = −11.68, SE = 4.11, p < 0.001. Responses to high BOI words were significantly faster than to low BOI words. Gender differences were subsequently analysed. Male participants were overall older, t(78) = 2.70, p = 0.01, female participants were better at turning pegs with their dominant hand, t(77) = 1.00, p = 0.004. No further differences were found .Descriptive statistics of age, IQ estimate, general vocabulary, FMS, reaction latencies and response accuracies were calculated see . They sh2(4) = 3.44, p = 0.49. The linguistic variables , syllables, and frequency class), picture ratings (complexity and fit), and word ratings (BOI and body-part) represented Level-2 covariates. Using this model, significantly more variance was explained than in the previous model, χ2(14) = 1225.5, p < 0.001. As a third step, interactions between FMS and word ratings were entered into the model, further improving the model, χ2(5) = 14.01, p = 0.02.As in Experiment 1, mixed-effects models for experimental research designs were used to assess the role of FMS and body-part association in the processing advantage of high BOI words. Firstly, to measure the relation of within-subjects to between-subjects variance, the unconditional model was computed, revealing an intraclass correlation coefficient of 0.25. Secondly, we modelled individual intercepts using random effects. The between-subjects variables FMS, IQ estimates, age, and general vocabulary represented the Level-1 covariates. Entering the level 1 variables did not improve the model significantly, χThe results of the mixed-effects model can be seen in Our goal in Experiment 2 was to expand the understanding of how FMS relate to lexical processing, with a particular focus on the role of BOI and body-part associations in an adult population. The most important finding is the significant interaction between BOI rating and FMS, as well as the lack of interaction between any body-part association and FMS. Participants with greater FMS reacted more rapidly to words with a high BOI, whereas body-part association played no significant role. This is contrary to the results found in experiment 1, where a unique role for the hand was found. It appears as though the link between FMS and vocabulary in children may be specific to words containing a high association to the body-part hand, whereas in adults, this link seems to incorporate words that have a high BOI rating, thus extending previous work , 2017.Additionally, the results of the study show a significant facilitatory effect for high BOI words over low BOI words. This is consistent with findings from other studies assessing the BOI effect with adult populations e.g., ,b. FurthIn study 2, participants performed a FMS task that was developed as a screening for children and adolescents, giving rise to the possibility that it did not have a sufficiently high ceiling to capture adults’ true performance. Accordingly, we replicated study 2, but replaced the Movement ABC FMS tasks with a classic pegboard task commonly used to assess FMS in adults e.g., . AlthougSD = 3.50) and 88.7% indicated that they were right-handers. The participants gave written informed consent and received no compensation. Participants were tested individually in a single session by trained education students as part of their research theses. The methods in study 3 followed those of study 2 with the following exceptions. First, given that vocabulary and the intelligence tasks did not uniquely predict response latencies in study 2, these were dropped.Participants were 71 adults, 62% female, aged 23.85 years  5mm holes spaced 1cm apart and in two parallel rows of 12 holes, with the one row being 4cm from the other. The pegs were located in a small container fastened to the end of the pegboard which they held onto with their non-operative hand while they inserted the pegs into the first row, one at a time, as quickly as possible. In the second trial, the participants shifted the pegs from the one row to the next. Both trials were firstly conducted with the right hand, then the left hand. Scores represent the time (s) taken to insert all pegs across all four trials. Internal consistency across the four trials was acceptable, αSD = 13.17) seconds for the pegboard tasks and complete the BOI task with a 92% accuracy and a mean response latency of 872.41 (SD = 137.28) milliseconds. An identical analysis to that presented in Across the four trials, participants required 133.97  and picture fit (p < 0.001) were also significant predictors. As with studies 1 and 2, pegboard scores were multiplied by −1, such that greater scores indicate greater performance. Participant age (p = 0.08) was not significant but FMS were, β = 3.13 ms, p < 0.05, as was the interaction between FMS and BOI rating, β = −0.57, p = 0.001.The resulting model was similar to that in study 2, with a host of significant level 2  predictors, ICC = 0.11, marginal Thus, consistent with study 1 and 2, FMS played a significant role in predicting response latencies, as did BOI and body-part association ratings. Beginning with FMS, in study 3 this was a significant predictor of response latencies, whereby adults with greater FMS performed more slowly on the lexical decision task. Words with a higher BOI rating were processed more quickly and there was a positive significant interaction between FMS and BOI ratings, such that greater FMS resulted in more rapid processing of higher BOI words. Accordingly, the data support the hypothesis that FMS create processing advantages for high-BOI words. The finding that foot and mouth were significant and hand and arm were not, probably indicates that body-part is a construct that is closely related to BOI. Perhaps mouth and foot captured aspects of embodiment that were not captured entirely by the BOI ratings, whereas arm and hand words were made redundant by BOI rating and the FMS measures. The current study extends study 2, confirming a link between BOI and FMS using a task that can be expected to capture variance in FMS in adults.performance relates to lexical processing. Such a line of work would appear to have a number of benefits, providing an additional line of enquiry into the nature of embodiment that is less dependent on imaging studies, which can only infer motor involvement via motor cortex activation. Perhaps most importantly, examining the performance of the fine motor system in relation to lexical processing asks the unique question of whether skill, or nimbleness, in two seemingly unrelated domains is actually interdependent. In this spirit, we conducted the three experiments reported here.In three experiments, we examined whether lexical items contain a unique link to the body, with a particular focus on the sensorimotor, or more specifically, fine motor system. A vast literature finds that concepts , includiSpecifically, although there is some literature on the link between BOI and FMS in children , it is, Our results emphasize the importance of considering BOI as well as body-part associations when assessing the relationship between FMS and vocabulary. Considering the mixed and inconclusive results on the link between FMS and vocabulary e.g., , our resFurther, the above findings offer helpful insights into the theoretical mechanisms. As found in previous studies e.g., , 2017, aGiven the persistence of links into adulthood, explaining the current findings from a purely functionalistic viewpoint therefore, seems to be insufficient. Although children primarily show strong links to words associated with the body-part hand, BOI should not be taken out of the picture entirely. Our findings of links between FMS and embodied lexical items (either BOI or body-part association) lead to the assumption that more advanced FMS may result in better lexical processing skills for all embodied lexical items, not just words associated with the body part hand. The results of the adult population further point in this direction, with response latencies for high-BOI words benefitting from greater FMS, over and above the control variables, as postulated by the nimble-hands, nimble-minds hypothesis , 2017. TIn terms of purely lexical processing without considering the role of FMS, the pattern of findings, from a specific concept  in childhood to less defined concepts  in adulthood, correspond to results obtained by Nevertheless, due to methodological and conceptual reasons, we interpret these findings with caution. Firstly, we assessed reaction times using a manual design  while simultaneously evaluating hand associations. One might argue that pressing a buzzer using the hands enhances the semantic processing of words associated with the hand. A study by Secondly, we did not assess environmental motor influences such as children’s actual physical interactions with the objects used as stimuli in the study. Therefore, it is not possible to draw any firm conclusions about the extent to which functionalism may or may not play a role in the link between FMS and lexical processing. We furthermore did not conduct an imaging study enabling us to assess neurological structures underlying cognitive representations. This makes it difficult to directly investigate the neurological basis of the shared-activation account.Thirdly, all ratings on BOI and body-part associations were acquired from adults. Generalizing these ratings to an early childhood population may prove difficult. Words that adults deem as having a low BOI may be categorized differently by children. Perhaps future work could gather these from children or from parents of young children. For instance the word “star” may be seen as a celestial body by adults , whereas children may associate the word “star” with a star-shaped toy . Furthermore, BOI measures the actual experience one has had interacting with the words’ referent. This experience may differ substantially between adults and children .Finally, we included various linguistic variables  that have been shown to influence semantic processing e.g., . NeverthThe current findings have both clinical and educational implications. From a clinical viewpoint, it is interesting to view our findings in light of object exploration. A number of researchers have found compelling evidence linking object exploration and communicative and language development in typically developing children , autistiConcerning the educational implications, our findings highlight the notion that language development does not occur independently from motor development. From antiquity to the 20th century, psychologist, philosophers and educationalists, such as Jean Piaget and Maria Montessori, have attributed an important role to the sensorimotor system in semantic processing and mental development e.g., . FurtherThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Ethikkommission der Universität Regensburg. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.RW, HS, and SS conceived and planned the experiments. RW carried out the experiments 1 and 2, wrote the first draft of the manuscript. SS conducted experiment 3, wrote the section on study 3 of the manuscript. RW and SS performed the statistical analysis. All authors provided critical feedback and helped shape the research, analysis and 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.


Previous studies have reported associations between attention-deficit/hyperactivity disorder (ADHD) and lower socioeconomic status and intelligence. We aimed to evaluate the causal directions and strengths for these associations by use of a bi-directional two-sample Mendelian randomization (MR) design.We used summary-level data from the largest available genome-wide association studies (GWAS) to identify genetic instruments for ADHD, intelligence, and markers of socioeconomic status including the Townsend deprivation index, household income, and educational attainment. Effect estimates from individual genetic variants were combined using inverse-variance weighted regression.p<0.001). A genetically predicted one SD higher education level conferred an OR of 0.30 (95% CI 0.25–0.37) (p<0.001), and a genetically predicted one SD higher family income provided an OR of 0.35 . The associations remained after adjustment for intelligence whereas the lower odds of an ADHD diagnosis with higher intelligence did not persist after adjustment for liability to greater educational attainment . The MR analysis of the effect of ADHD on socioeconomic markers found that genetic liability to ADHD was statistically associated with each of them (p<0.001) but not intelligence. However, the average change in the socioeconomic markers per doubling of the prevalence of ADHD corresponded only to 0.05–0.06 SD changes.A genetically predicted one standard deviation (SD) increment in the Townsend deprivation index conferred an odds ratio (OR) of 5.29  1.89–14.76) for an ADHD diagnosis (Our results indicate that an ADHD diagnosis may be a direct and strong intelligence-independent consequence of socioeconomic related factors, whereas ADHD appears to lead only to modestly lowered socioeconomic status. Low intelligence seems not to be a major independent cause or consequence of ADHD.The online version contains supplementary material available at 10.1186/s12916-022-02314-3. The diagnosis of attention-deficit/hyperactivity disorder (ADHD) has become highly prevalent during the last two decades , but theGenetics clearly contribute to ADHD. Family studies indicate a five-fold higher risk in first-degree relatives of cases, and genetic liability to an ADHD diagnosis in children and adolescents is estimated to be 70–80% , 6, but Due to a complex web of interrelated associations, the independence and direction of the associations between a diagnosis of ADHD with specific markers of socioeconomic status and intelligence is unclear . The obsThe Mendelian randomization (MR) design can overcome such biases, thereby strengthening causal inference regarding an exposure-outcome association by leveraging genetic variants as instrumental variables for an exposure . In thisOur aim was therefore to use a bi-directional two-sample MR design to assess the associations between markers of SES or intelligence and an ADHD diagnosis.We used a two-sample MR design in which the genetic instruments for the exposure, and the outcome are extracted from independent GWAS data sources. Our analyses were bidirectional, first assessing the causal effect of the socio-economic variables on ADHD and then investigating the reverse relationship. Each analysis used multiple genetic variants obtained from publicly available GWAS summary data . None ofData regarding the Townsend index of deprivation (TID) , househon=462,464; https://gwas.mrcieu.ac.uk/datasets/ukb-b-10011/) using a z score with a mean of −1.29 and a standard deviation (SD) of 3.10. A greater TID corresponds to a lower socioeconomic status. The UK Biobank was also used for a GWAS of self-reported household income , calculated as the average total household income in 2006–2010 before tax reduction.Genetic instruments for the TID  was retrieved from the UK Biobank , based on longitudinal assessment of cohort participants measured at an age of at least 30 [We obtained genetic instrument data for education level from the Social Science Genetic Association Consortium  [We used Savage et al.’s GWAS meta-analysis of intelligence  . Include269,867) .Finally, we included genetic data from the international Psychiatric Genomics Consortium, which involved 20,183 individuals diagnosed with ADHD and 35,191 controls . In the p<5×10-8, were selected from the corresponding genome-wide association studies. Linkage disequilibrium  between SNPs was assessed based on the 1000 Genomes European reference panel . For SNPs in linkage disequilibrium, those with the strongest association with the exposure were retained. Remaining independent SNPs who had met a GWAS-wide significance threshold were used as genetic instruments. SNPs that were unavailable in an outcome dataset were replaced by suitable proxies (minimum linkage disequilibrium R2=0.8) where available. We removed SNPs without an imputed substitute as well as all palindromic SNPs. Our genetic instruments included 17 SNPs for the TID, 42 SNPs for household income, 219 SNPs for educational attainment, and 132 SNPs for intelligence. These explained 0.13%, 0.53%, 2.8%, and 3.2% of the variance in the TID, household income, educational attainment, and intelligence, respectively. For the analysis with ADHD as the exposure, we used nine (out of 12) [Genetic instruments, identified at a genome-wide significance threshold of Since our different phenotypes are linked to each other, we first illustrate these relationships by the genetic correlations of ADHD with attained education, family income, TID, and intelligence using LD score regression .In our main analysis, we assessed the direction and strengths of the associations of ADHD with socioeconomic markers and intelligence in a bi-directional design. We first estimated the impact of our SES variables and intelligence on the odds of ADHD, estimating both the total effect of each variable and the direct effect independent of intelligence and SES, respectively, by use of multivariable Mendelian randomization . SecondlThe principal analyses Fig. A were coe 2) times the causal estimate on the untransformed scale [p-value <0.006 (with Bonferroni correction for 8 main outcomes) were considered to show strong evidence of association. P-values <0.05, but higher than 0.006, were regarded as showing suggestive evidence of associations, requiring confirmation.We report odds ratios (ORs) of ADHD per one SD increase of genetically predicted socioeconomic marker or intelligence. For ADHD as the exposure, effect sizes are expressed as SD changes in the socioeconomic markers or intelligence per unit increase in genetically predicted log odds ratio of ADHD. A log odds ratio of one thus corresponds to an OR of 2.7, and the average change in socioeconomic markers per doubling of the prevalence of an ADHD diagnosis equals 0.693  the weighted median method, which provides a causal estimate if at least 50% of the weight in the analysis comes from valid instrumental variables ; (2) MR-With traditional MR methods there remains a concern that valid instrument selection are often violated, leading to false positive findings through correlated horizontal pleiotropy. To avoid this bias, we adopted a new MR method as the eighth (8) sensitivity analysis, using summary effect estimates (MR-CAUSE), to differentiate correlated pleiotropy from causal effects . MR-CAUSThe TwoSampleMR , Mendelir=0.73; 95% CI 0.68 to 0.78)), and education was also correlated with household income ) and with TID . Intelligence was correlated with both household income  and TID .Genetic variants with a positive effect on ADHD tended to have a negative association with intelligence and educational attainment: the genetic correlations were −0.37 (95% CI −0.44 to −0.30) and −0.51 (−0.57 to −0.45), respectively. Education and intelligence were genetically related, as expected (p<0.001), and one SD higher genetically predicted family income gave an OR of 0.35 . A one SD increment in genetically predicated TID conferred an OR of 5.29  (p<0.001) for ADHD. The direct effects, after adjustment for intelligence, were similar  per SD higher predicted intelligence. This lower odds of genetic liability of an ADHD diagnosis with genetically predicted higher intelligence did not remain after adjustment for educational attainment . The estimate was also attenuated by the adjustment for household income .We also observed Fig.  that intp = 0.038). The MRMix analysis indicated independent causal effects of education, intelligence, and income (but not TID) on ADHD, while all four exposures remained statistically significant causes of ADHD when data were analyzed by GSMR. We found also similar patterns with MR-Mode although with lower precision of the estimates. Sensitivity analysis by MR-CAUSE . Expressed in another way, the average change in adverse socioeconomic markers per genetically predicted doubling in the prevalence of the ADHD diagnosis corresponded to only 0.05–0.06 SD units lower SES measures. The modest impact of ADHD on SES and intelligence can theoretically be a consequence of weak instrument bias given that we only included 9 ADHD SNPs in our analyses. However, the F-statistics with values between 181 and 514 do not indicate such bias.IVW-random effect analysis in the reverse direction indicated that genetic predisposition to ADHD was statistically significantly associated with SES variables but not with intelligence Fig. . Howeverp-values from 0.11 to 0.78) as also indicated by analyses using MR-Mode, MRMix (Table n=9) precluded an analysis by use of GSMR.The results were similar in sensitivity analyses based on the weighted median, MR-PRESSO methods, and contamination mixture approach Table . There wix Table , and MR-ix Table . The numPreviously, the independence and direction of the associations between a diagnosis of ADHD with different markers of socioeconomic and intelligence have been unclear. Our results based on a bidirectional two-sample MR-analysis design show that a genetic predisposition to socioeconomic position including attained educational level, household income, and TID has a direct and strong intelligence-independent association with ADHD. Genetically predicated intelligence per se was not independently associated with ADHD. Genetic liability to ADHD was only modestly inversely associated with SES measures and not clearly with lower intelligence.Using the bidirectional MR design, our study provides a deeper understanding of previous observational findings –18, 29 bOne possible explanation for the fact that we see that SES-related factors are strongly linked to the receipt of an ADHD diagnosis may be that social vulnerability, lack of cultural, and economic capital or immaturity can be a basis for difficulty concentrating and sitting still, e.g., in a school environment. Lack of cultural capital, in the form of the parents’ level of education, can be manifested as shortcomings in language competence, for example. Parental SES is related to language development in multiple domains throughout both childhood and adulthood . ChildreThe resourceful family may also have greater opportunity to protect, stimulate, and train their children to become physically and mentally competent and thus avoid an ADHD diagnosis . In addiBy some measures, children of lower socioeconomic status score more than 2 years behind their more well-off peers on standardized language development tests by the time they enter school . As a reIndirect support for the view that immaturity can affect the likelihood to being diagnosed with ADHD, is the fact that children in Norway born in October through December are at 50% higher risk of being diagnosed and treated for ADHD compared with children born the same year but in January through March . ChildreCollectively, our findings of a strong 3–5 fold change in the odds of ADHD diagnosis per SD change in genetically predicated various dimensions of SES raise questions about whether the current criteria for diagnosis are sufficiently accurate and culturally generalizable tools to correctly identify ADHD, a descriptive diagnosis for which there is not yet any clinically valid biological marker. We definitely acknowledge that ADHD is regarded as a highly debilitating and costly disease , but ourIn the Psychiatric Genomics Consortium GWAS, genetic markers for ADHD were identified either by an ADHD diagnosis or by having been prescribed ADHD medications, though without heterogeneity . TherefoUsing genetic data from large-scale GWASs and genetic consortia, the present study is the first to comprehensively and jointly investigate the causal effects of different aspects of SES and intelligence on the diagnosis of ADHD and vice versa. In addition, we disentangled the independent effect of socioeconomic factors from intelligence using a multivariable MR approach. The analyses were based on data from individuals of the European ancestry thereby limiting the potential for population stratification bias. However, this restriction limits the transferability of the present findings to populations of the non-European ancestries.Our genetic instruments for social class were not strong, as measured by the explained variance. However, this potential limitation can be regarded of less importance given our two-sample design, a large number of SNPs in the SES instrument variables, and large sample sizes , 60. In Another conceivable serious limitation of the present study is the possibility of unbalanced horizontal pleiotropy from genetic variants acting through several different biological pathways. Thus, an alternative underlying causal explanations for the SES impact of on the risk of ADHD diagnosis might be factors linked to low SES such as parental mental health, substance abuse, and maternal smoking during pregnancy . CarefulNon-genetic familial influences could not directly be assessed in the present MR study and for obvious reasons, some SES genetic liability markers in our study  pertain to the parent’s circumstances when a child receives an ADHD diagnosis. The genetic liability of low or high SES still pertains to the child. Nonetheless, our design precludes the evaluation of timing of exposure effects and induction periods on the occurrence of the outcomes. The strength of the associations from the analyses in different directions are not directly comparable, but the interpretation of the overall pattern was straightforward. Since identification of socioeconomic patterns with specific ADHD subtypes was not in the scope of our study, we suggest refined evaluation of different disease development pathways between SES and ADHD.We conclude that there is a strong direct impact of genetically predicted household income, educational attainment, and social deprivation index on the risk of an ADHD diagnosis. Lower intelligence seemed not to be a strong independent cause or a consequence of ADHD. The associated effect of genetic liability of ADHD on genetically predicted socioeconomic markers were modest.Additional file 1: Table S1. Data sources for the genetic instruments.


The permanent human settlement of the Tibetan Plateau (TP) has been suggested to have been facilitated by the introduction of barley agriculture ∼3.6 kilo-years ago (ka). However, how barley agriculture spread onto the TP remains unknown. Given that the lower altitudes in the northeastern TP were occupied by millet cultivators from 5.2 ka, who also adopted barley farming ∼4 ka, it is highly possible that it was millet farmers who brought barley agriculture onto the TP ∼3.6 ka. To test this hypothesis, we analyzed mitochondrial DNA (mtDNA) from 8277 Tibetans and 58 514 individuals from surrounding populations, including 682 newly sequenced whole mitogenomes. Multiple lines of evidence, together with radiocarbon dating of cereal remains at different elevations, supports the scenario that two haplogroups (M9a1a1c1b1a and A11a1a), which are common in contemporary Tibetans (20.9%) and were probably even more common (40–50%) in early Tibetans prior to historical immigrations to the TP, represent the genetic legacy of the Neolithic millet farmers. Both haplogroups originated in northern China between 10.0–6.0 ka and differentiated in the ancestors of modern Tibetans ∼5.2–4.0 ka, matching the dispersal history of millet farming. By showing that substantial genetic components in contemporary Tibetans can trace their ancestry back to the Neolithic millet farmers, our study reveals that millet farmers adopted and brought barley agriculture to the TP ∼3.6–3.3 ka, and made an important contribution to the Tibetan gene pool. With an extreme and harsh environment that is generally considered inhospitable to humans, the Tibetan Plateau (TP) has been inhabited since the late upper Pleistocene . In contAs revealed by archaeological evidence, modern humans settled extensively in the northeastern TP (below 2500 m above sea level (masl)) with millet cultivation around ∼5.2 ka, and further expanded to high-altitude plateau areas (above 2500 masl) ∼3.6 ka with barley and sheep from west Asia . These oIn this study, by exploring mitogenomes in Tibetans and surrounding populations  Fig. , as wellde novo differentiation in contemporary Tibetans  were <6 ka in age  between 5.2 and 3.6 ka Fig. . Of notePhylogeographic analyses, very useful in identifying the origins and migrations of haplogroups , were peOf note, both haplogroups showed the highest frequencies (M9a1a1c1b1a: 16.5% and A11a1a: 4.3%) in Tibetans, accounting for 20.9% of the Tibetan gene pool . As thisBoth M9a1a1c1b1a and A11a1a are distributed ubiquitously in contemporary Tibetans, with total frequencies ranging from 12.0%  to 37.5% (Ngari) across all regional Tibetan populations studied Fig. . This suin situ differentiation in Tibetans 5.2–4.0 ka, likely represent the genetic legacy of Neolithic millet farmers in contemporary Tibetans. Interestingly, ancient samples excavated from different Neolithic sites in northern China, in which millet was the most important crop and thus most likely represent the remains of the Neolithic millet farmers, show close genetic affinity to our identified genetic legacy of millet farmers in the Tibetans. For example, haplogroup M9a1a1c (defined by HVS-I variants 16223–16291-16234–16316-16362), an ancestor type to M9a1a1c1b1a, has been observed at the Miaozigou (5.5–5.0 ka) [In this study, we combined archaeological and genetic data to investigate the mode of spread of barley agriculture to the TP. Specifically, we identified that haplogroups A11a1a and M9a1a1c1b1a, which can trace their ancestry back to northern China ∼10 ka and underwent –5.0 ka) ,22 and Z–5.0 ka) . The aboThe maternal genetic components of millet farmers, which accounted for 20.9% of current Tibetans and may have been more frequent prior to historical immigrations (40–50%), demonstrated substantial genetic contributions of Neolithic millet farmers from northern China into Tibetans. Moreover, this contribution, represented at least by the two haplogroups (A11a1a and M9a1a1c1b1a) identified in the present study, existed in Tibetans at relatively high frequencies for >3 ka, and even contributed to the genetic differentiation observed between the Tibetans and other ethnic groups. Therefore, by showing that the ancestry of the Tibetans on the TP can largely be traced back to millet farmers from northern China, our study indicates substantial migration of millet farmers onto the TP, which probably occurred during the Neolithic period. Although it was barley agriculture that finally promoted the permanent settlement of humans at high altitudes after 3.6 ka , the genOf note, our observation based on mtDNA is somewhat similar to the Neolithic migration of males from northern China, in which a westward expansion of males initiated in the middle Yellow River Basin during 10.0–5.0 ka ,25. HoweIn summary, by combining archaeological and high-resolution genetic data, we have identified a substantial genetic contribution of Neolithic millet farmers, represented by haplogroups A11a1a and M9a1a1c1b1a, to contemporary Tibetans, which has even played an important role in shaping the Tibetan matrilineal landscape. Therefore, our study provides the first piece of evidence demonstrating that it was Neolithic millet farmers originating from northern China, rather than immigrants from the west, who brought barley agriculture to the TP ∼3.6 ka and contributed to the permanent human occupation of the TP.Blood samples from 671 Tibetans from 11 Tibetan populations were collected, covering all seven districts of Tibet Fig. . Blood sAdditionally, 201 whole mitogenomes  and 7405n = 120, n = 131, 13C) values  [Quality control was performed according to previous research . Potentiee.org/) .Phylogenetic trees of lineages of interest were reconstructed manually based on the complete sequences and confirmed by mtphyl software . Rho (ρ)Nef) through time were reconstructed based on 13 protein coding regions using BEAST v1.7.5. [Nef change, a strict molecular clock with a fixed rate of 1.691e−8 substitutions per site per year [http://tree.bio.ed.ac.uk/software/tracer/). Population growth rate and time of population growth were calculated based on skyline plots, as per our previous study [Nef values of the haplogroups and all Tibetans in the BSP analyses.Bayesian skyline plots (BSP) for effective population size ( v1.7.5. , as desc v1.7.5. ,39. In tper year  was chosus study . To avoius study , for BSPnwz080_Supplemental_FileClick here for additional data file.


There were no significant linear trends indicative of a poorer outcome with the presence of A-ADHD after adjustment for demographic, clinical and pharmacological factors. Conclusions: ADHD symptomatology does not seem to exert any influence on the retention in AOT of HUD patients.The role of opioids and opioid medications in ADHD symptoms is still largely understudied. We tested the hypothesis that, in Heroin Use Disorder (HUD), when patients are treated with Agonist Opioid medications (AOT), treatment outcome is associated with the presence of Adult Attention-Deficit/Hyperactive Disorder (A-ADHD) symptomatology. A retrospective cohort study of 130 HUD patients in Castelfranco Veneto, Italy, covering 30 years, was divided into two groups according to the Adult ADHD Self-Report Scale (ASRS) score and compared them using demographic, clinical and pharmacological factors. Survival in treatment was studied by utilizing the available data for leaving treatment and relapsing into addictive behavior and for mortality during treatment as poor primary outcomes. Thirty-five HUD subjects (26.9%) were unlikely to have A-ADHD symptomatology, and 95 (73.1%) were likely to have it. Only current age and co-substance use at treatment entry differed significantly between groups. Censored patients were 29 (82.9%) for HUD patients and 70 (73.9%) for A-ADHD/HUD patients (Mantel-Cox test = 0.66  Attention Deficit Hyperactivity Disorder (ADHD) is a pervasive neurodevelopmental disorder affecting both children and adults. It is clinically distinguished by improper levels of inattention, impulsivity and/or hyperactivity, especially in children and adolescents. In adults, the disorder is almost invariably accompanied by various internalizing and externalizing psychiatric manifestations ,2,3,4, cOn the whole, A-ADHD patients show a four to nine times greater prevalence of co-existent mental illnesses  and are Presently, methylphenidate and amphetamines are among the most effective medications for A-ADHD patients . ConsistLastly, the role of opioids in ADHD symptoms continues to be largely understudied and calls for further studies. In two residential treatment programs, 17% of drug users experienced hyperactivity in childhood. Although patients reported being polysubstance users, opioids were usually the drug of choice in people with a history of hyperactivity . LimitedOur research group has already demonstrated that the correct treatment with stimulants of dual disorder A-ADHD patients dramatically reduced the use of street stimulants. Still, our results were obtained in subjects who were not heroin users or who had only used heroin in the past .As the whole question of the influence of substance use in the treatment of dual disorder A-ADHD patients is still controversial, the present study aimed to apply testing techniques to determine whether the co-occurrence of A-ADHD symptomatology in HUD patients can influence clinical and long-term therapeutic aspects in an out-patient Agonist Opioid Treatment (AOT) setting. On this topic, we aimed to figure out the clinical impact of opioid medications on ADHD psychopathology.We identified people resident in the Northeast part of Italy  registered at the local drug addiction unit and treated with AOT medications (methadone or buprenorphine) for their heroin addiction for 30 years. This study population represents all individuals attending the local public . We collected demographic details, clinical aspects of Heroin Use Disorder (HUD) and its psychiatric comorbidity, therapeutic medications used and treatment outcomes.In the Castelfranco Veneto AOT, the Dole and Nyswander (D&N) methodology of treatment ,26 has bThe CGI consists of three items. Severity of Illness varies from (0) normal to (7) among the most extremely ill, on a seven-point scale. Global Improvement varies on a similar seven-point scale, from (1) very much improved to (7) very much worse. The Efficacy Index considers the ratio Therapeutic Effect/Side Effect. Therapeutic effect is ranging from (1) Unchanged or Worse to (4) Marked; side effect is ranging from (1) None to (4) Outweighs.The frequency of self-reported adult ADHD symptoms, derived from the DSM-IV criteria, was assessed by the ASRS, a Likert scale, ranging from 0 (“never”) to 4 (“very often”). Participants who have a score below 16 are unlikely to have A-ADHD; those in the 16-24 range are likely to have A-ADHD, and those over 24 are highly likely to have an A-ADHD diagnosis.No formal psychiatric diagnosis was required to be admitted to the program. Independently of recruitment criteria, the clinical records collected dichotomous information from these patients to document: The lifetime presence of any psychiatric diagnosis, previous hospitalization referable to psychiatric reasons; suicide attempts; and mental disability benefits. Additional psychiatric information was extracted from follow-up clinical records, which were compiled during the stay in treatment of the patients, so allowing the collection of data regarding the use of psychiatric medications during the program. We classified patients as having experienced lifetime psychiatric difficulties if they showed one or more of these psychiatry-related conditions; alternatively, if they did not show any such psychiatric proxies, they were classified as patients whose lives had remained free of any other lifetime psychiatric problems.We presented data as the number (percentage) of individuals for categorical variables. We divided patients into two groups based on A-ADHD symptoms co-occurrence. Univariate differences were tested through nonparametric tests (comparing medians across groups using the Wilcoxon–Mann–Whitney Z test) for metric variables and Chi-squared analysis (comparing column proportions) for categorial ones, using Fischer’s Exact Test when necessary.Comparison of retention in treatment was performed using the Kaplan–Meier survival analysis and the Log Rank (Mantel–Cox) test for comparison between groups. For the analysis, positive outcome (‘censored observations’) refers to patients still in treatment or leaving treatment for reasons not related to the treatment itself . When a patient dropped out of the treatment by not presenting at the scheduled follow-up, we considered it a ‘terminal’ event (negative outcome). For positive outcome, the following characteristics have been added: “if symptoms are present, they are transient, acceptable reactions to psychosocial stressors : no more than modest damage in social, occupational, or school functioning. In cases that had a ‘negative’ outcome, these criteria were not met.We assessed survival rates for the patients according to the presence of a comorbid A-ADHD symptomatology. The association between A-ADHD and retention in treatment was abridged using Cox regression (Omnibus Tests of Model Coefficients). Sociodemographic, clinical and symptomatological variables that may act as confounding factors influencing a negative outcome were included in our model .p < 0.05.In consideration of the exploratory nature of the study, we referred to levels of significance of Data were obtained on all 130 individuals who entered treatment at any time between 14 October 1987, and 19 October 2020; to avoid discrepancies, they were, without exception, evaluated by the same doctor on duty (PR). Most of our cohort were regularly observed for about ten years (within the range the maximum was 33 years). When treatment began, patients were markedly ill. In contrast, at the endpoint, the severity of illness had been reduced so that patients appeared mildly ill, with partial remission of symptoms and no side effects.According to our assessment, 99 (76.2%) patients showed a good and 31 (23.8%) a poor outcome. More specifically, seven (5.4%) patients successfully completed their program. Twenty-one (16.2%) were transferred to other services as stabilized patients. As many as 71 participants (54.6%) had stayed in treatment. Five (3.8%) patients had died, while 26 (20.0%) patients had dropped out of the program.According to the ASRS test, our cohort could be divided into two groups. Thirty-five subjects (26.9%) were unlikely to have A-ADHD, whereas 95 (73.1%) were likely to have A-ADHD (A-ADHD/HUD).We found no statistically significant differences between HUD patients with and without A-ADHD symptomatology, the only exceptions being their age at the time of the study and co-substance use . The HUDp < 0.001) only regarding patients’ age  and CGI endpoint efficacy index .As many as 73.1% of our HUD patients presented A-ADHD symptomatology—a much higher percentage than those reported in the literature ,21. ThisConsequently, patients use drugs to reduce ADHD symptoms. Stimulants, including cocaine, can, paradoxically, act to calm and counteract emotional lability, hyperactivity, and inattention in ADHD patients . In one Similarly, executive dysfunction and poor judgment may lead individuals with ADHD to try heroin and cocaine, increasing the vulnerability to developing addiction disorders compared to their peers without ADHD. Like HUD patients, ADHD individuals have often reported difficulties in delaying or modulating the reward response, with a strong tendency to develop multiple addictive behaviors . FinallyIn summary, at the time of the study, HUD patients likely to have ADHD were younger and, at treatment entry, made more frequent use of alcohol and stimulants than their peers. The retention rate of A-ADHD/HUD failed to reveal any statistically significant differences. Older patients were more frequently retained in treatment than younger ones, and the negative outcome was correlated with the absence of improvement at the most recent clinical evaluation.HUD patients—considering both those with and without A-ADHD—did not show differences when their investigated demographic data were compared regarding the severity of illness at treatment entry or during the study. They also showed the same retention in treatment and outcomes in dropping out of treatment, successful termination, and treatment continuation. The number of deceased patients or those transferred as stabilized patients revealed no statistical differences. Long-term retention in treatment was no different, and demographic, clinical and therapeutic variables were not correlated with a negative outcome.In our sample, we found only two variables related to negative outcome. Older patients were more frequently retained in treatment than younger ones, and a negative outcome was correlated with the poor efficacy of treatment at the last clinical evaluation. These two results appear to be tautological when analyzing a long-term treatment.The first consideration to be made, at this point, is about the use of sedatives (major and minor); in our cohort, the frequency was around 30%, without negative effects on the outcome. Treating A-ADHD with opioids, which can themselves be considered sedative medications, does not seem to have, in our cohort, the same clinical impact as the use of other sedatives, such as benzodiazepines (BDZs). As GABA-agonist drugs, the non-medical use of BDZs and Z-drugs has shown a significant correlation with ADHD. In a way, like alcohol use, from the SMH perspective, BDZ may offer short-term relief for restlessness and hyperactivity in ADHD subjects. Regrettably, long-term and high doses of BDZ have been shown to induce the significant clinical impairment of patients’ neurocognitive and executive functions and quality of life, regardless of whether they have ADHD or not ,35. BDZ-In general, persistent ADHD symptoms can adversely affect many dimensions of an individual’s life, including physical, social, occupational, and behavioral functioning, and can lower the overall quality of life ,42, but The second consideration is that the only difference found between groups is that A-ADHD/HUD patients at treatment entry took more stimulants and alcohol than those with HUD but without A-ADHD. In a recent study, by applying a factorial analysis we, clustered our dual disorder A-ADHD patients in two different typologies of substance use and then correlated these typologies with clinical A-ADHD aspects. Two patterns of substance use were identified: The first (type 1) was distinguished by stimulants/alcohol, and the second (type 2) using cannabinoids (THC). Type 1 users were significantly younger and had more legal problems, but the two patterns were similar in terms of ADHD-specific symptomatology and severity at treatment entry ,32. DualWe have already observed a dramatic reduction of cocaine use in dual disorder patients with concomitant ADHD treated with stimulant and non-stimulant A-ADHD medications . We haveInteractions between opioid and dopaminergic systems have been documented. Both stimulants and opioids can increase dopamine release in the brain. The former directly enhances the effect of dopamine, and the latter indirectly promotes dopamine levels by activating opioid receptors . From a Lastly, it should be noted that 4-hydroxyatomoxetine, the human metabolite of atomoxetine, is a partial KOR agonist . SubsequA-ADHD/HUD patients use more cocaine than those with HUD alone, confirming the craving for relief by taking cocaine in these patients too. However, a stimulant such as methylphenidate has been shown to activate the μ opioid receptor (MOPR) in the brain, particularly when taken at sufficiently high doses ,68,69, sLimitations: The obvious limitations of this study are because this is a retrospective analysis carried out on a relatively small cohort of patients rather than a study specifically designed to elucidate this issue. Assessments of the same patient in various clinical presentations of the natural history of this illness would have provided more widespread evidence. A better level of information would be derived from a specific protocol. In addition, the ARS is not sufficient to make a retrospective ADHD diagnosis or to make any consideration on ADHD as a diagnostic category. Since ADHD in adults is a chronic condition that begins in childhood, it is necessary to estimate the symptoms, development and relative level of functional impairment during childhood, using a retrospective interview aimed at investigating the behaviors relating to that period of life. The information collected from the patient should be supplemented by significant people who knew the subject when he was a child .This study, however, covers a very long-time span and enables us to study the effect of opioid medications on ADHD symptomatology in the absence of the concomitant use of stimulants for A-ADHD. In Italy, stimulants for A-ADHD can only be prescribed in selected psychiatric centers that cannot prescribe opioid medications. Addiction Units only can prescribe opioid medications; however, these units cannot use stimulant drugs for A-ADHD/HUD patients. This situation was typical of the Castelfranco Veneto Addiction Unit.In HUD patients with or without A-ADHD symptomatology, an enhanced AOT designed according to the D&N methodology is beneficial in both cases, as significant changes in the outcome of these patients cannot be highlighted.