The cross-sectional study assessed the knowledge, attitudes, and practices regarding the recommended vaccinations and factors affecting such outcomes among a sample of healthcare workers (HCWs) in public hospitals in Italy. Only 14.1% knew all the recommended vaccinations for HCWs. Physicians and those who had received information about vaccinations from scientific journals, educational activities, or professional associations were more likely to have this knowledge, while those aged 36–45 were more likely to have less knowledge than those in the age group below 36 years. Only 57.3% agreed that the information received about vaccinations was reliable. Respondents who had children, who worked in pediatric/neonatal wards, who were more knowledgeable, or who did not need further information about vaccinations considered the available information to be reliable. Only 17.7% of respondents always recommended vaccinations to their patients. This behavior was more likely to occur in physicians, in HCWs, in pediatric/neonatal wards, in those who considered the information received about vaccinations reliable, and in those who considered themselves to be at high risk of transmitting an infectious disease to their patients. Health promotion programs and efforts are needed to improve the level of knowledge about vaccinations and immunization coverage among HCWs. Healthcare workers (HCWs) have an important role in informing, advising, and promoting vaccinations in accordance with the most up-to-date scientific evidence as a preventive measure for self-protection from the risks of contracting the vaccine-preventable diseases and, consequently, of their transmission to other members of staff and their patients, particularly the vulnerable groups ,2.In view of this, in Italy, vaccinations against hepatitis B, measles–mumps–rubella, varicella, pertussis, and influenza are currently highly recommended for HCWs , and theReports worldwide have been carried out to examine the knowledge, attitudes, and practices of HCWs in relation to vaccinations ,8,9. DesThe cross-sectional study lasted from May to July of 2019 and took place in six randomly selected public general hospitals distributed in Naples, Italy. The study population of HCWs was randomly sampled from the selected hospitals. The sample size of the study was calculated using a single population proportion formula with the assumption of 15% of HCWs who knew all the vaccinations recommended for them, a confidence level of 95%, a margin of error at 5%, and a response rate of 50%. The final sample size of the study was 392 HCWs.Before commencing the survey, hospital directors were contacted with an introductory letter requesting their collaboration explaining the objectives of the study and the methodology, after which they were asked to provide a list of HCWs. After the approval was received, the random sample of HCWs received an envelope containing the questionnaire. This questionnaire was accompanied by an information sheet that outlined the rationale for the study and explained that participation was voluntary, that they could leave the assessment at any time, and that full confidentiality and anonymity would be maintained. Included were a written informed consent form and an envelope to return the completed questionnaire and the consent form. The completed surveys were anonymous. Participants were given two weeks to complete the survey, and a follow-up visit was made weekly to each hospital to ensure maximum participation of the sampled HCWs. All participants gave written informed consent before participating in the survey. There were no incentives offered to those who participated in the survey.A pilot test among 50 HCWs was undertaken in order to evaluate the feasibility of the study design, readability of the items, and reliability of the questionnaire. Data from the pilot were included in the final analysis. The study protocol, questionnaire, and informed consent were reviewed and approved by the Ethics Committee of the Teaching Hospital of the University of Campania ‘‘Luigi Vanvitelli” (number 411). The research team developed a self-administrated structured questionnaire containing five fields of inquiry. In the first part of the survey, there were eight questions, which asked age, gender, marital status, number of children, professional status, length of practice, type of ward, and previous practice in other unit areas. The second part of the survey consisted of 14 predefined questions that asked HCWs about their knowledge regarding the vaccinations recommended for them. The questions could be answered as “yes”, “no”, or “do not know”. The third section consisted of questions about the sources and needs of information regarding vaccines recommended for HCWs. The fourth section contained questions that measured attitudes towards vaccinations for HCWs and their patients. It contained questions surrounding the perception of the risk of contracting a vaccine-preventable infectious disease and of transmitting one to patients, beliefs about the usefulness of the recommended vaccines for HCWs and patients, and reliability of the information received about vaccinations. All questions pertaining to attitudes were measured on a 5-point Likert scale with options from “strongly disagree” to “strongly agree”. The fifth section asked about practices regarding vaccinations. The questions in this section asked whether HCWs recommended vaccinations to their patients, whether they convince their patients to vaccinate, and whether they discussed vaccinations with colleagues. The practice was measured on five-response options from “never” to “always”. Finally, coverage for all recommended vaccines for HCWs was also investigated, and the response options included ‘‘yes”, ‘‘no”, “do not remember”, or “naturally immunized”.p-value less than or equal to 0.25 [Stata software version 15   was used to 0.25  in the up-values <0.2 and >0.4 were included and excluded in the model, respectively. Odds ratios (ORs) and their 95% confidence intervals (CIs) were presented to express the results of the logistic regression analysis and standardized regression coefficients for the linear regression model. For all analyses, the tests for significance were two-sided, and p-values of less than 0.05 were considered significant.The following independent variables were included in all models: gender ; age, in years ; marital status ; length of practice, in years (continuous); having a child ; working in pediatric/neonatal wards ; and use of scientific journals, educational activities, or professional associations as sources of information about the vaccines recommended for the HCWs . In Models 2 and 3, the variable “knowledge of the vaccines recommended for HCWs” (continuous) was also included. In Model 3, the variables “considering themselves at high-risk of contracting an infectious disease during their practice” , “considering themselves at high-risk of transmitting an infectious disease to their patients” , “believing that the information received about vaccinations was reliable” , “considering the vaccinations beneficial for their own health” , “being favorable to vaccinations” , and “considering the vaccinations beneficial for their patients”  were also included. A stepwise backward variable selection was applied to test for factors predicting outcomes of interest, and factors with Among the total of 715 questionnaires distributed, 412 HCWs agreed to participate and returned the survey for an overall response rate of 57.6%.The main socio-demographic and professional characteristics of the study participants are displayed in Overall, only 14.1% of the respondents were aware of all recommended vaccinations for HCWs. Out of a maximum knowledge score of 9, the mean score achieved by the participants was 4.8 ± 2.8 (SD), and 1.9% did not answer any question correctly. The majority of HCWs correctly identified that the vaccines against hepatitis B (94.7%) and influenza (68%) were recommended for them. In contrast, lower values have been observed for measles (54.6%), tetanus (49.8%), rubella (48.5%), varicella (45.4%), mumps (43.5%), pertussis (42%), and diphtheria (37.6%). On the importance of vaccinations for HCWs, the vast majority (88%) were favorable and considered the immunizations recommended useful to protect their own health (87.1%) and their patients (86.6%). Only 50.9% and 36.5% of the HCWs considered themselves at high risk of contracting and of transmitting an infectious disease during their activity. Only 57.3% agreed or strongly agreed that the information received about vaccinations was reliable. The multivariate logistic regression model showed that HCWs having a child, those who worked in pediatric/neonatal wards, those more knowledgeable, and those who did not need further information about vaccinations, considered the information received about vaccinations reliable (Model 2 in The self-reported coverage for the vaccines recommended for HCWs by the study participants is reported in The vast majority of the HCWs stated that they had obtained information about vaccinations (81.5%). The preferred method for acquiring information was the internet (38.6%), followed by educational activities (36.9%), scientific journals (31.3%), colleagues (27.4%), and professional associations (24.7%). Moreover, 58% of HCWs reported the need for additional information about vaccinations.This study provides novel insights into vaccination knowledge, attitudes, and coverage among a large sample of Italian HCWs.The results of the present survey showed that the HCWs had a poor level of knowledge, since only 14.1% were aware and knowledgeable about all vaccines recommended for them. It is well known that HCWs have a crucial role in vaccinations, and they should have adequate knowledge in order to correctly inform the population and the most fragile and susceptible patients. Indeed, several recent investigations among different groups of individuals conducted in the same geographic area have underlined that HCWs are the most important and trusted source of information on vaccine-preventable infectious diseases ,16,17,18A disturbing result was that only 57.3% agreed or strongly agreed that the information received about vaccinations was reliable. This issue could be addressed through targeted education and awareness campaigns to combat misconceptions and concerns regarding vaccine safety and efficacy and to increase confidence in vaccines.An objective of this investigation was to evaluate the HCWs’ self-reported vaccine coverage; except for hepatitis B, all rates were very low, including those for influenza 21.6%), tetanus (17%), and measles 12.1%). Overall, the low coverage among this risk group is alarming. Indeed, since it is well established that HCWs play a role in nosocomial transmission of infectious diseases, the low-level coverage of those susceptible did not contribute to limit the spread of infections and might not provide indirect protection for the patients. The findings of previous investigations showed a higher coverage for several vaccinations in different groups of HCWs compared to the results of this survey, with values of 41.7% .6%, teta for infl.1%. OverAnother point of interest was that the frequency of the sampled HCWs who recommended the vaccinations to the patients was very low, as less than one in five declared to make the recommendation. Previous studies conducted in the United States highlighted that 98% of primary care providers recommended influenza vaccine to those ≥ 65 years, 90% to adults 50–64 years, and 75% to 19–49 years ; 54.4% aAs with all similar research, it is important to reflect on some potential limitations of this survey. Firstly, the cross-sectional nature limits inferences on the directional causality of the associations observed in this study. Secondly, the sample was selected only from one geographic area; therefore, the collected responses might not be generalizable to other parts of the country. Thirdly, the information about vaccination status was self-reported and not based on the vaccination records of staff. This might be prone to recall, declaration, or desirability biases; therefore, an over- or underestimation of coverage could occur. However, the fact that the survey maintained full confidentiality and anonymity may suggest that the responses were likely to be authentic, with minimal social desirability bias.In conclusion, these findings are valuable for the design and planning of training to ensure that HCWs improve their level of knowledge about vaccinations and develop skills with the resultant positive impact on their responsibility to patients and on their immunization coverage in a geographic area with disturbingly low vaccination implementation.


N = 642, USA: N = 579) that the tool resulted in considerable overestimation of ADHD, indicating probable ADHD in 26.0% and 17.3% of participants, as compared to expected prevalence of 2.5%. The estimated positive predictive value was only ~11.5%. Both samples had normal levels of trait impulsivity as assessed using the Barratt Impulsiveness Scale. The data indicate that using the ASRS in general population samples will result in 7–10 times over-identification of ADHD. We use these results to highlight how such tools should most appropriately be used. When being used to determine possible cases  they should be complemented by clinical assessment – we give examples of how non-specialists might determine this. When measuring ADHD symptoms dimensionally, researchers should be mindful that the ASRS captures impulsive symptoms other than those due to ADHD. Lastly, we note the need to screen for impulse control disorders  when using such tools to measure ADHD, be it for onward referral, or for dimensional research studies.Adult Attention-Deficit/Hyperactivity Disorder (ADHD) is prevalent but often overlooked and undertreated. Left untreated, it is linked to increased risk of untoward outcomes including unemployment, relationship breakups, substance use, driving accidents and other mental health conditions. Several brief screening tools have been developed for adult ADHD. The most frequently used is the World Health Organization's Adult ADHD Self-Report Scale (ASRS V1.1). Here, we show in two independent population samples (UK:  •ADHD commonly persists into adulthood.•We deployed the most widely used screening tool for adult ADHD in two normative samples•The screening tool considerably over-identified probable ADHD, with low positive predictive value.•Key advice is provided about the appropriate use of such tools, to maximise benefits and minimise harms. A meta-For clinical purposes, ADHD should be diagnosed by a mental health specialist, using structured clinical instruments, taking into account self-report as well as confirmatory collateral reports of childhood and adult symptoms. As well as ensuring interventions are targeted to those most in need, this also reduces the risks of inappropriate prescribing and diversion of stimulants for non-medical uses. However, given that the prevalence of adult ADHD is 2.5% [The World Health Organization (WHO) Adult ADHD Self-Report Scale v1.1 (ASRS v1.1) Part A is the most widely used screening tool for ADHD cases in adults . The tooN = 642), and one in the USA (n = 579). This was one of several self-report scales included for studies exploring latent phenotypes of impulsivity and compulsivity. For both cohorts, those receiving treatments for any mental health conditions were excluded at entry. Using the standard threshold, the rates of probable ADHD in these two cohorts based on the ASRS v1.1 Part A were 26.0% (UK) and 17.3% (USA) respectively. Given that the expected rate of ADHD was 2.5%, this indicates that 86–90% of people identified as having probable ADHD in these two normative cohorts were unlikely to have ADHD. The estimated positive predictive value  was only ~11.5%.We included ASRS v1.1 Part A in two non-treatment seeking normative cohorts of young adults: one in the UK . As such, and given that the UK dataset was follow-up from an epidemiologically representative cohort recruited using stratified sampling, it seems unlikely that actual levels of ADHD in the two datasets would deviate meaningfully from population expectations. However, a limitation is that we did not conduct gold-standard clinical interviews for ADHD.These findings suggest that a positive screen will often not reflect ADHD, and the tool did not show high specificity. This is extremely important for all users of the screener to be aware of. If this tool was used as the sole means of identifying people who should have a specialist ADHD assessment, healthcare resources would be overstretched and many individuals would be subjected to referral, waiting times, and in-depth interviews when it is unlikely they have the diagnosis. Therefore, we recommend that the tool only be used as a screener for categorical ADHD, in people for whom there is high clinical suspicion of ADHD. Examples of ensuring high clinical suspicion that could be used by non-ADHD experts would include, for example checking:1) that there is collateral support for symptoms , 2) symptoms were evident in childhood, 3) symptoms occur in two or more functional domains , and 4) for other obvious types of disorder that could better account for the problems reported.Why might people screen positive on ADHD rating tools when they do not have ADHD? First, of course all rating tools have limitations  relative to clinical interview by a specialist. Even gold-standard diagnoses are not always accurate, since there is an element of subjectivity, and mental health disorders are likely not ‘one thing’ but reflect different biological processes. Second, we suspect many cases of apparent positive self-reported ADHD are due to other conditions such as impulse control disorders and obsessive-compulsive disorders. These are very rarely screened for, but validated convenient screening tools do exist. As such, an accurate differential diagnosis is pivotal. Third, ADHD exists along a continuum and it can be challenging to know where to draw the line: for a diagnosis there must be impairment in at least two distinct life domains  but screening tools do not typically capture that.Overall, we would suggest that the ASRS v1.1 Part A remains a good choice of the available brief screening tools for ADHD suitable for general population use, but users need to be aware a positive screening outcome will often  not reflect ADHD. We highlight the cardinal importance of considering other diagnoses, and for rigorously screening for the same if an ADHD diagnosis is being considered. The ASRS v1.1 Part A is also useful to generate a ‘total score’ to provide a dimensional measure of ADHD symptoms to explore associations with such symptoms, rather than as a binary thresholding tool. However, again it is important for researchers to be mindful it likely reflects not only ADHD, but also a multitude of other impulse symptoms for other disorders. Overall, from a research point of view, in view of the very high apparent rates of ADHD detected in our two normative cohorts using such tools, we would caution against assuming self-reported ADHD symptoms reflect ADHD, without measuring other types of disorder especially disorders of impulsivity (e.g. gambling disorder), and controlling for them.10.13039/100001455American Foundation for Suicide Prevention, Takeda, Neurocrine, Biohaven, and 10.13039/100014934Avanir Pharmaceuticals. He receives yearly compensation for acting as editor-in-chief of the Journal of Gambling Studies and has received royalties from Oxford University Press, American Psychiatric Publishing, Inc., Norton Press, and McGraw Hill. Dr. Grant has received a research grant from the TLC Foundation for Body-Focused Repetitive Behaviors. Dr. Chamberlain consults for Promentis; and receives a stipend from Elsevier for editorial work. Dr. Chamberlain's research was funded by a 10.13039/100010269Wellcome Trust Clinical Fellowship (110049/Z/15/Z & 110049/Z/15/A).Dr. Cortese declares honoraria and reimbursement for travel and accommodation expenses for lectures from the following non-profit associations: Association for Child and Adolescent Central Health (ACAMH), Canadian ADHD Alliance Resource (CADDRA), British Association of Pharmacology (BAP), and from Healthcare Convention for educational activity on ADHD. Dr. Grant has received research grants from the TLC Foundation for Body-Focused Repetitive Behaviors, the


Attention-deficit/hyperactivity disorder (ADHD) is associated with a higher risk of burn injury than in the normal population. Nevertheless, the influence of methylphenidate (MPH) on the risk of burn injury remains unclear. This retrospective cohort study analysed the effect of MPH on the risk of burn injury in children with ADHD.n = 90 634) in Taiwan's NHIRD between January 1996 and December 2013. We examined the cumulative effect of MPH on burn injury risk using Cox proportional hazards models. We conducted a sensitivity analysis for immortal time bias using a time-dependent Cox model and within-patient comparisons using the self-controlled case series model.Data were from Taiwan's National Health Insurance Research Database (NHIRD). The sample comprised individuals younger than 18 years with a diagnosis of ADHD  0.64–0.77) and 0.43 in children taking MPH for ≥90 days (95% CI 0.40–0.47), with a 50.8% preventable fraction. The negative association of MPH was replicated in age-stratified analysis using time-dependent Cox regression and self-controlled case series models.This study showed that MPH treatment was associated with a lower risk of burn injury in a cumulative duration of treatment dose-related effect manner. Taiwan launched a single-payer National Health Insurance programme on 1 March 1995, covering the delivery of all health care services to 99.5% of the national population Ng, . The NHIThe ADHD cohort was selected from NHIRD. It included individuals younger than 18 years by 31 December 2013. For ensuring the diagnosis of ADHD, we only recruited participants with ADHD who received at least one inpatient diagnosis of ADHD  or more than two outpatient diagnoses within 1 year between 1 January 1996 and 31 December 2011.et al., The main outcome of this study was burn injury (ICD-9-CM codes: 940–949). Patients with a diagnosis of burn injury . Psychiatric comorbidity included intellectual disability (ICD-9 codes: 317–319), autism (ICD-9 code: 299), conduct disorder (ICD-9 code: 312), opposition defiant disorder (ICD-9-CM code: 313.81), anxiety (ICD-9 code: 300) and depression . Baseline medication use was identified based on a prescription of any benzodiazepine , benzodiazepine-related drugs (ATC code: N05CF), antipsychotic (ATC code: N05A) or antidepressant (ATC code: N06A) 12 months prior to the burn injury diagnosis.et al., MPH (ATC code: N06BA04) has been the only stimulant approved for treating ADHD in Taiwan and is regarded as the first-line treatment for ADHD according to Taiwan's National Insurance. In 2017, atomoxetine (ATX), a non-stimulant, was also approved for ADHD treatment in Taiwan. However, compared with MPH, ATX has a much lower prescription rate   with 95% confidence intervals (CIs). We calculated the duration of medication use for each patient with ADHD and tested the cumulative effect on the burn incidence according to stratification into three groups, 0, <90, ≥90 days, by adjusting for covariates in competing risk-adjusted Cox regression models  and R 4.0.0 . To describe the distribution of the study population, a et al., et al., et al., For within-patient comparisons, we used the self-controlled case series (SCCS) model, in which time was divided into periods similar to the stratified Cox regression model, with each patient as a separate stratum (i.e. the patient served as his or her own control). The risk estimated from the SCCS model indicates the risk of burn injury when individuals took MPH compared to the period when they did not take MPH. The SCCS model automatically adjusts for all time-invariant factors (e.g. sex) for the same patient before and during the follow-up. The effect period for MPH was set at 1–3 months based on previous studies (Chen p < 0.0001). The preventable fraction of MPH medication was 0.508, indicating that 50.8% (11 352 patients) incidence of burn injury could be prevented if they took MPH medication.p < 0.01). In addition, age-stratified analyses revealed a similar pattern in different age groups and the adjusted HR ranged from 0.55 to 0.87 for those taking MPH for <90 days and 0.32 to 0.55 for those taking MPH for ≥90 days, respectively. p = 0.002), but not in autistic spectrum disorder (p > 0.05). The protective effect (RR) was decreased from 0.49 in participants with ADHD to 0.61 in participants with ADHD and intellectual disability.To our knowledge, this is the first nationwide population-based cohort study to investigate the effect of medication usage on the risk of burn injury in ADHD patients. Our study looked into the risk of burn injury specifically and added to the existing evidence that MPH treatment was associated with a lower risk of burn injury among ADHD children. We found a lower incidence of burn injury in patients with ADHD prescribed MPH in the whole sample and different age subgroups. In total, 50.8% incidence of burn injury among patients with ADHD not taking MPH could be prevented if they took MPH medication. The effect was more prominent with increased duration of MPH use: a 30% reduction in the risk of burn injury with <90 days of MPH use was observed, and a 57% reduction in the risk of burn injury with ≥90 days of MPH use was noted. Similar reductions were replicated in age-stratified analysis and the time-dependent and SCCS design. These results suggest the robust effect of MPH use on burn injury in ADHD.et al., et al., et al., et al., Research has indicated that ADHD patients have a higher risk for burn injury than non-ADHD controls  on the risk of burn injury in patients with ADHD and found that the burn injury risk reduction was linked to an increased MPH usage duration. Studies have identified attenuation in the risk of fracture, suicide and traumatic brain injury to be associated with the dosage effect of MPH treatment  reported experiencing burn injury  to examine the effect of MPH on unintentional injuries (Ruiz-Goikoetxea This study had several limitations. First, the accuracy of disease diagnoses for ADHD or burn injury has not been documented. Second, information on drug adherence was lacking. Third, we did not evaluate the therapeutic effect of non-pharmacological treatment because behavioural therapy and psychoeducation were not fully registered in the NHIRD. Finally, the lack of MPH use in some patients may be due to a worsening of symptoms, and we did not have information on the severity of ADHD.In conclusion, MPH treatment was linked to a lower risk of burn injury in children with ADHD, and the effect was stronger with longer MPH use.


Optimal transition from child to adult services involves continuity, joint care, planning meetings and information transfer; commissioners and service providers therefore need data on how many people require that service. Although attention-deficit hyperactivity disorder (ADHD) frequently persists into adulthood, evidence is limited on these transitions.To estimate the national incidence of young people taking medication for ADHD that require and complete transition, and to describe the proportion that experienced optimal transition.Surveillance over 12 months using the British Paediatric Surveillance Unit and Child and Adolescent Psychiatry Surveillance System, including baseline notification and follow-up questionnaires.Questionnaire response was 79% at baseline and 82% at follow-up. For those aged 17–19, incident rate (range adjusted for non-response) of transition need was 202–511 per 100 000 people aged 17–19 per year, with successful transition of 38–96 per 100 000 people aged 17–19 per year. Eligible young people with ADHD were mostly male (77%) with a comorbid condition (62%). Half were referred to specialist adult ADHD and 25% to general adult mental health services; 64% had referral accepted but only 22% attended a first appointment. Only 6% met optimal transition criteria.As inclusion criteria required participants to be on medication, these estimates represent the lower limit of the transition need. Two critical points were apparent: referral acceptance and first appointment attendance. The low rate of successful transition and limited guideline adherence indicates significant need for commissioners and service providers to improve service transition experiences. There are few empirical data on the number of young people with ADHD who wish to access ongoing care in adulthood, or the number that successfully do so. Some studies have attempted to quantify national estimates for transition, but they have either focused on all neurodevelopmental conditions rather than just ADHD or were limited geographically.4To plan services, commissioners and service providers need accurate and timely data on how many people may require that service. There are currently limited national and international data on the number of young people with attention-deficit hyperactivity disorder (ADHD) who need transition to adult services when they become too old for child services. ADHD affects approximately 5% of the childhood population, 15% of which still meet the full, formal diagnostic criteria at age 25 and up to 65% still have impairing symptoms at age 25 but may not meet the full formal criteria.5 These definitions are in line with recommendations in the current National Institute for Health and Care Excellence (NICE) guidelines for ADHD.6The current study aimed to estimate the incidence of young people with ADHD who need transition from child and adolescent services to adult services across the UK and Republic of Ireland . For the purposes of this study, transition refers to the transfer of care from child and adolescent mental health services (CAMHS) or paediatric services to an adult service for continued treatment for ADHD once the young person reaches the service transition boundary. The main objectives of the study were to describe the group of young people diagnosed with ADHD who require medication beyond the end of children's services in terms of range and mean age for transition, to estimate the incidence rate of young people with ADHD who require ongoing medication for ADHD after they pass the age boundary for the child service, to estimate the proportion of young people with ADHD judged in need of transition to adult mental health services due to ongoing need for medication that successfully transferred to a specialist health service, and to describe the proportion of young people who experience optimal transition. Successful transition was defined as a referral to an adult service made, accepted and the first appointment attended; and optimal transition as joint care, planning meetings, information transfer and continuity of care.7 used the British Paediatric Surveillance Unit (BPSU) and the Child and Adolescent Psychiatry Surveillance System (CAPSS) to collect prospective data on the number of young people with ADHD who undergo transition from children's services to adult mental health services. These surveillance units provide a method that allows the collection of reliable national estimates of service level incidence about rare health conditions or events in paediatrics and child mental health services to improve their identification and clinical management. The surveillance methodology is described in more detail elsewhere but is briefly summarised below.10This study, which was part of a research programme that explored transition in ADHD (CATCh-uS) funded by the National Institute for Health Research (HS&DR 14/21/52),https://doi.org/10.1192/bjp.2019.131. A follow-up questionnaire regarding those individuals confirmed as eligible at baseline was sent to paediatricians and psychiatrists 9 months later. Duplicate reporting of cases was checked by matching minimal identifiers.Young people taking medication for a clinical diagnosis of ADHD who were requiring transition to an adult service for continued treatment were notified prospectively using the BPSU and CAPSS methodology over 13 months from 1 November 2015 to 30 November 2016. The first (pilot) month was discarded as per BPSU and CAPSS protocol. Consultant paediatricians and consultant child and adolescent psychiatrists in the British Isles were systematically prompted by a monthly email or postal reporting card which asked them to indicate the number of eligible young people with ADHD they had seen in the previous month or ‘nothing to report’. Details regarding each reported case were subsequently gathered by study investigators using a notification questionnaire sent to the reporting clinician. Information on the outcome of the transition of eligible young people was collected using a follow-up questionnaire 9 months after notification. Baseline notification and follow-up questionnaires were developed using the BPSU and CAPSS templates, which comprised structured questions (30 at baseline and 19 at follow-up) with two open text responses. A copy of the questionnaires used can be found as Supplementary Material available at The study was approved by both BPSU and CAPSS Executive Committees. Health Research Authority and Confidentiality Advisory Group (CAG) approvals permitted access to case note information without patient/parent consent .6 It was designed in close collaboration with both BPSU and CAPSS to ensure that both paediatricians and child and adolescent psychiatrists would identify young people in a similar manner. The surveillance asked for young people seen in the previous month to be reported if they were judged to meet the following criteria by the reporting clinician.(a)Clinical diagnosis of ADHD, under the care of CAMHS or paediatrics, reviewed within 6 months of the service's upper age (transition) boundary.(b)Considered to require and willing to take continued medical treatment for symptoms of ADHD after crossing the transition boundary of the child service.(c)only if it was the ADHD that required ongoing medical treatment in adulthood.Comorbid diagnoses, including intellectual/developmental disabilities, were included The case definition criteria were developed to be itemised and precise and to specify the need for the young person to have ongoing support for medical treatment from specialist adult mental health services, as outlined in the NICE guidelines.11 The incidence rate of transition was calculated by dividing the number of confirmed young people with ADHD who need transition identified over the course of the study's 12 month surveillance period by the population at risk. The population at risk was derived by applying the estimated prevalence of ADHD (approximately 5% in the child and adolescent population)1 to the total number of children aged 17–19 years in the British Isles as reported in 2016 (n = 2 333 035).12 The quotient was then multiplied by 100 000 to provide the incidence rate of transition per 100 000 population of people aged 17–19 per year. Two incidence rates were calculated: the incidence of young people who required transition as defined by the case definition criteria and the incidence rate of successful transition in the obtained sample, defined as those whose referrals were accepted and attended their first appointment in the adult service. The observed incidence rate was adjusted to take into account the age of the young person, the current NICE guidance about the age of transition (18 years) and missing data (failures to notify or return questionnaires) as suggested in a previous study .n = 86). However, information from partially completed questionnaires was included in the analysis. The 315 eligible individuals were reported by 148 different clinicians.No individuals were reported through both BPSU and CAPSS. A total of 13 duplicate reports were identified from clinicians who reported the same individual more than once during the surveillance period. A total of 17 questionnaires could not be completed at follow-up as the clinician no longer had access to the patient's records or was no longer in post. Some questionnaires at baseline and follow-up were returned blank or not fully completed  and White British (91%). Individuals were reported from across the British Isles but most (over 85%) were seen in England. The modal age boundary between child and adult services was 18 years old, but ranged from 14 to 19 years. Two individuals who did not originate from the British Isles were international students seen in private practice in England. The reported age range of reported individuals extended from 14 to 20 years, although 85% were aged 17 to 19 years at the point of referral for transition, and age was not reported for 6% of individuals.A large proportion of individuals  were reported to have a comorbid condition; for 25% the comorbidity was an autism spectrum disorder. Polypharmacy was common: 23% of patients from paediatricians and 41% from psychiatrists were prescribed more than one medication.Figures in bold in Half of all the reported individuals  were referred to a specialist adult ADHD service, just over a quarter to general adult mental health services and 10% were referred back to primary care. Referral destinations were similar regardless of whether the young person was reported by a paediatrician or a psychiatrist.n = 158) of the 247 individuals who were referred to adult mental health services were accepted , but only 22% (n = 55) were reported to have attended a first appointment  (n = 3), the referral did not meet adult service criteria (n = 1), there was no funding available (n = 1) or the adult service was closed to new referrals due to lack of resources or long waiting lists (n = 4). No reason for a failed transition was given for the remaining individuals (n = 46).In total, 64% (% CAPSS) . Reportev. 39%) and use of (66% v. 36%) a transition protocol in their organisation.Nearly all (93%) clinicians reported that the young person had been involved in the planning of the transition process, and over 80% reported that the parent or carer was also involved. More child and adolescent psychiatrists than paediatricians reported access to (81% v. 68.8% at follow-up), young person involvement (81.4% v. 69.6%) and joint working (25.5% v. 10.5%).At baseline notification only 6% of paediatricians and 10% of psychiatrists indicated that all five optimal criteria pre-transition see  were appThis surveillance study generated the first national data to estimate the number of young people with ADHD taking medication who require and complete a transition to an adult service in the British Isles. Our findings suggest that the annual scale of the need for young adults with ADHD who require transition to adult services for ongoing medication in the British Isles lies between 202.9 and 511.2 per 100,000 17–19 year olds per year. Given the study's inclusion criterion that the eligible young person had to need and want to continue with medication for ADHD after reaching the age boundary of the children's service, which does not take into account the demand for psychological support, these figures are likely to be a considerable underestimate of the actual need for service provision. Further, a comparison of the surveillance data collected in the current study with the Clinical Records Interactive Search (CRIS) at the South London and Maudsley National Health Service (NHS) Trust (SLaM) highlighted that surveillance with CAPSS only identified 25% of potential ADHD transition cases in the London area. Details regarding this study are available from the author on request. Sadly, there were no comparable data to triangulate with BPSU reports, but the CRIS data emphasise that although our estimates should therefore be treated as extremely conservative, they remain the best empirically based British Isles data available for service commissioners and providers. The use of population data restricted to age 17–19 is a limitation of the study and may have therefore excluded relevant cases, however it reflects 85% of eligible reported cases and the NICE guidance that transition should occur by age 18. The requirement that reported individuals needed ongoing medication aimed to increase reliability by having an unequivocal reference for the reporting clinician.3 A study from the Republic of Ireland used the same methodology and found 20 ADHD cases from 4 CAMHS teams annually requiring transition, with only 3 individuals successfully transitioning to an adult service.4 Similarly there are a lack of comparative international data on transition in ADHD; an ongoing European study on transition focuses on mental health transition generally but is not specific to ADHD.14 Given the rise in prescriptions for ADHD over the past decades,15 estimates may quickly become out of date as later cohorts are likely to contain a higher proportion of young adults who may have benefitted from medication and therefore wish to continue to take it. A recent report reviewing children and young people's mental healthcare highlighted a lack of data availability and monitoring of transition16 and reviews such as this only consider young people up to the age of 18, so knowledge of the needs of young adults in their later teens or early twenties is poor.Previous studies have only been able to estimate the number of transition cases in smaller localities that are difficult to compare directly with our findings. A London-based study suggested an average of 12 neurodevelopmental individuals annually per CAMHS team that require a transition to an adult service, with 8 of the 12 making the transition successfully.17 Others have demonstrated above predicted levels of medication cessation between the ages of 15 to 18, before transition, which may be influenced by the lack of availability of services.18 Data from UK primary care suggested that only 18% were still taking medication for ADHD at age 18.15 These findings suggest a worrying discontinuity of service between child and adult services, given that patient registry studies of young adults who discontinue their medication show poorer outcomes compared with those who continue to take it.19 Given the number of young people reported in this surveillance study that did not attend the first appointment in the adult service, it is possible that the transition referral for ongoing treatment might reflect a clinician decision regarding the need for treatment, rather than a decision made by the young person.The estimated annual incidence of successful transitions lies between 38.5 and 96.9 per 100 000 young people aged 17–19 years per year, which suggests that only a fifth of those requiring transition for ongoing medication successfully made the transfer. A small proportion of failed transitions related to the young person disengaging from services or their medication, which would render them ineligible by our definition, but it may also relate to the lack of suitable services for onward referral. A study of a locality in North West England reported that only 15% of patients eligible for transition actually successfully transferred to the adult service.6 The guidelines do not specify what type of adult service a young person should be transitioned to, they only state adult mental health services, and encouragingly over 75% of individuals in this study were referred to either a specialist ADHD or adult mental health service. In contrast, we found that a joint planning meeting, a care plan and a joint handover period were conducted in fewer than 30% of cases. Other studies have also highlighted the lack of planning for transition of young people with ADHD.21 Although the reported high level of involvement of the young person and carer in the process is commendable, paediatricians in particular reported poor continuity and consistency of care. This may reflect weaker links between paediatricians and adult mental health services when compared with CAMHS. A lack of planning is likely to undermine the potential for successful transition, and the need to adhere to recommendations to ensure effective transition has been highlighted.22 Further, it is recommended that policies and guidelines are reviewed regularly so they can be operationalised and effectively translated into clinical practice.23 A systematic review of guidelines has suggested that this does not occur; guidelines are often not incorporated into protocols locally and do not always reflect the clinical reality.24Our findings suggest poor adherence to the recommendations for transition from the NICE guidelines for ADHD. NICE recommend that a good transition between child and adult services should be complete by age 18, involve a detailed care plan, include a formal joint meeting between the child and adult service, use the care-programme approach and involve the young person and the parent or carer.25 who would not ordinarily be reached by either surveillance system. There is also a relative underrepresentation of clinicians reporting to the surveillance units in the private sector despite its increasingly important role in healthcare provision,26 which may particularly be an issue for young adults with ADHD for whom there are few NHS services.7 Indeed, our findings highlighted referral back to primary care in 10% of cases. Incomplete data also presented a limitation: some contact details provided by both surveillance organisations were not up to date and some questionnaires were returned blank or with missing data.The use of the BPSU and CAPSS systems provided national-level, prospectively collected data but also presented a number of methodological challenges. Registration to receive the monthly reporting cards is voluntary and mostly consists of those in the consultant grade. Therefore not all relevant clinicians may receive them . This is likely to be the main explanation for the discrepancy between CAPSS and the CRIS case note review. Details of this study are available from the author on request. Other research has demonstrated that patients may be reviewed in settings other than paediatrics and CAMHS, such as primary care or forensic services,27 the average return rate was much lower in CAPSS. CAPSS was set up more recently (2009), so is perhaps less ingrained in clinical practice for child and adolescent psychiatrists than BPSU is for paediatricians. The lower return rate may reflect a lack of awareness of the system and not necessarily a reflection of clinicians actively being non-compliant. Potential difficulties with the case definition could also have led to a lack of reported cases. Previous surveillance studies have also cited difficulties with reporting, case definitions and low return rates.31 Research is enshrined in the NHS constitution as a core activity,32 however clinicians reported that current workloads made it difficult to respond to questionnaires and some service providers did not support their clinicians to participate. We provided certificates for questionnaire completion that indicated involvement in research for appraisals, but it is clear that busy clinicians need more support and encouragement to engage with research.Although the return rate of reporting cards by paediatricians via BPSU was excellent, perhaps due to longevity of the system,Surveillance methodology has stringent governance and requires considerable researcher time for data collection and analysis, but has offered a more complete national picture of the need and success of transition to adult service among young people with ADHD than previous studies have achieved. Surveillance allows researchers to ask a wider and more tailored set of questions than case note review alone. The findings emphasise a relative lack of adherence to recommended guidelines for transition and the low proportion of eligible patients that experience successful transition and a continuity of care.14 and the societal impact of ADHD if not managed.19 Our findings are significant for commissioners and service providers, internationally as well as in the British Isles, to address the drop in attendance from child to adult services. It is imperative that mental health services develop policy and strategy to better support this group of young people in the future.Attempts have been made to correct for incomplete ascertainment and to provide a series of transparent estimates for policy, commissioning and service provision. Despite some limitations, to our knowledge these data are the best currently available. European studies have similarly highlighted a lack of transition policy


Inattention/Hyperactivity subscale of the Strength and Difficulties Questionnaire. ADHD diagnosis was determined by a physician or psychologist. Serum thyroid stimulating hormone (TSH), free triiodothyronine (fT3), and free thyroxine (fT4) concentrations were determined enzymatically. Adjusted regression models were used to relate serum TSH, fT3, and fT4 with risk for ADHD diagnosis or symptoms. In children, a 1 mIU/l higher TSH was related to a 10% lower risk  of ADHD diagnosis. We found a significant positive association between fT3 and continuously assessed ADHD symptoms in children . Our results suggest that physical maturity may influence the association between thyroid function biomarkers and risk for ADHD.The relation between thyroid function biomarkers and attention deficit hyperactivity disorder (ADHD) in children and adolescents is currently unclear. Cross-sectional data from the German Health Interview and Examination Survey for Children and Adolescents (KiGGS Baseline) was analyzed to assess the association between thyroid function biomarkers and ADHD in a population-based, nationally representative sample. The study cohort included 11,588 children and adolescents with 572 and 559 having an ADHD diagnosis or symptoms, respectively. ADHD symptoms were assessed through the  Symptoms are characterized by difficulties with concentration and attention, with controlling behavior, and hyperactivity2. ADHD affects approximately 7.1% of children and adolescents worldwide3 exceeding previous estimates of 5.3%4, and persists into adulthood in 65% of cases5.Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders in children and is showing an increasing prevalence6. However, their effect sizes are rather small. Interestingly, twin and adoption studies9 found a high mean heritability of 0.77. Endocrine disorders also influence ADHD susceptibility. Specifically, environmental toxins in-utero or early childhood such as exposure to lead, organophosphate pesticides, and polychlorinated biphenyls are risk factors for ADHD10. ADHD susceptibility is not influenced by nutritional deficiencies, nutritional surpluses , and low or high Immunoglobulin G (IgG) foods11. Further evidence suggests that there is no causal association between maternal smoking during pregnancy and offspring ADHD12. While a recent meta-analysis provided evidence for an association between maternal smoking and offspring ADHD 13, the authors also reported significant heterogeneity between studies .ADHD shows considerable clinical heterogeneity in terms of symptom severity, admixture of symptoms, developmental course, and comorbidities. These parameters are influenced by inherited and non-inherited factors. Genetic variants (i.e. single nucleotide polymorphisms) are likely to be involved in the pathophysiology of ADHD15, high thyroid stimulating hormone (TSH) concentration during pregnancy16, and maternal autoimmune thyroiditis17 in early pregnancy increase the offspring’s risk for ADHD. Though there is an association between maternal thyroid dysfunction and offspring ADHD18, the knowledge on the association between iodine intake in pregnancy and offspring’s risk of diagnosed ADHD is sparse. A large Norwegian cohort study did not find a significant association with maternal iodine intake and child ADHD diagnosis but with symptoms19. This is supported by a large Danish cohort study. Inadequate maternal iodine intake and increased risk of ADHD symptoms in children is suggested by previous research14.Maternal thyroid dysfunction may adversely affect fetal brain development. Maternal (overt) hyperthyroidism20, thyroid function becomes important for the cognitive development in children and adolescents21. As individuals with hyperthyroidism may have ADHD-like symptoms 22, several studies investigated the association between thyroid dysfunction and ADHD in children. Zader et al. concluded that children with hyperthyroidism have an ADHD prevalence ratio of 1.7 compared to children without hyperthyroidism. Even more notably, in 40% of cases, the mental health diagnosis antedated the hyperthyroidism by 90 days, with ADHD being diagnosed before hyperthyroidism in 68.3% of cases23. Even within the normal range, TSH concentrations in the upper quartile were positively associated with ADHD symptoms in healthy children24. In adolescents, on the other hand, thyroid disorders were not related with ADHD25. Early studies with clinically referred ADHD children and adolescents were inconclusive with regards to thyroid dysfunction. Some supported a link between thyroid function abnormalities and the cognitive-behavioral manifestations of ADHD26, while others did not27. Hence, previous investigations showed large heterogeneity, which may be partly due to the relatively small sample sizes between 15027 and 35026 evaluated ADHD cases.As synthesis and secretion of thyroid hormones are regulated by a negative feedback system that involves the hypothalamus, pituitary and thyroid gland (the HPT axis)28. In line with this finding, recent research suggested that changes in the symptom profile of ADHD, with hyperactivity emerging in childhood for males but having later onset at the time of adolescence for females, may contribute to this pattern29. We also included body mass index (BMI) because previous meta-analyses found a positive association between ADHD and overweight or, in extreme cases, obesity31. ADHD has also been found to be associated significantly with low birth weight and prematurity in several cohort studies and meta-analyses33. Since maternal smoking is a risk factor for lower birth weight and preterm birth35, this covariate was also used along with weight at birth in our regression analysis. In summary, for our regression analysis we included offspring’s sex and birth weight, age, BMI and maternal smoking as covariates.We associated TSH and circulating thyroid hormones with the risk of ADHD using cross-sectional data from the large-scale population-based German Health Interview and Examination Survey for Children and Adolescents (KiGGS Baseline). Specifically, we investigated first how serum TSH, free triiodothyronine (fT3), and free thyroxine (fT4) were related to ADHD symptoms as well as ADHD diagnosis. We adjusted our regression models with several covariates previously identified in the literature to be associated with thyroid function and ADHD. We included sex since male children are three times more likely to have ADHD compared to female children. In adulthood men and women are equally likely to have ADHDTables 36.TSH and ft4 concentrations were significantly lower in children with compared to children without ADHD diagnosis Table . AdolescChildren in both groups, ADHD diagnosis and ADHD symptoms, were born during an earlier gestational week, weighted less at birth and had a lower socioeconomic status compared to controls. Children with an ADHD diagnosis had a higher BMI while children with ADHD symptoms had a lower BMI compared to controls. In adolescents no differences for BMI, gestational week of birth, birth weight and socioeconomic status were found.The association of serum TSH, fT3 and fT4 for both groups, ADHD diagnosis and ADHD symptoms as categorical variable, is presented in Table 36 In this subgroup, we observed no significant associations of TSH, fT3 or fT4 with ADHD diagnosis or symptoms. In another sensitivity analysis, we excluded all obese children and adolescents. Here we found a strong trend for the association between TSH with ADHD diagnosis in children (p = 0.064). However, the effect size was similar to the one of the main analyses. Likewise, when excluding children with a birthweight below the gestational week specific 10th percentile the effect size for TSH on ADHD diagnosis did not change compared to the main analysis, but the p-value was 0.055. When excluding children born preterm, the effect size for the association between TSH and ADHD cases was markedly lower than in the main analysis . We have also tested interactions of TSH, fT3 and fT4 with sex on ADHD diagnosis and symptoms; however, we did not find any significant interactions (e.g. interactions for TSH-sex on ADH diagnosis was 0.759 in children and 0.595 in adolescents).For sensitivity analyses, we excluded all children and adolescents with an already diagnosed thyroid disorder as well as those with TSH, fT3 or fT4 values outside the reference range as defined by Kratzsch et al.37.The present study investigated whether thyroid function biomarkers of children and adolescents are associated with ADHD diagnosis or symptoms. We demonstrated that higher serum TSH levels were associated with a lower risk for ADHD diagnosis in children but not adolescents. When analyzing ADHD symptoms as a continuous variable, fT3 was positively associated with ADHD symptoms in children. No relationship was found for fT4 with an ADHD diagnosis or ADHD symptoms in children or adolescents. Overall, our results support the notion that lower serum TSH may be related to a higher risk for ADHD in children but not adolescents. These findings agree with recent work by Villanger et al. who reported that ADHD risk appeared to be elevated among newborns with low TSH levels after analyzing TSH concentrations below 10 mIU/L in 405 ADHD cases and 1092 controls24. Therefore, serum TSH measurements might offer a better sensitivity for detecting thyroid dysfunction in comparison to fT3 and fT4 testing. This is especially important in light of our results regarding the positive association between TSH and ADHD diagnosis in children.Thyroid function can be determined either directly, by measuring thyroid hormones or indirectly, by assessing TSH concentrations, which inversely reflects the thyroid hormone concentration sensed by the pituitary41. As this holds true for all stages of brain development, maternal thyroid function is important for early brain development while childhood thyroid function is important for subsequent stages of the maturing brain43. Our analysis showed that although the prevalence of ADHD diagnosis remains approximately the same between children and adolescents, thyroid hormones are different. In children with an ADHD diagnosis, serum TSH and fT4 were lower. In adolescents with either an ADHD diagnosis or ADHD symptoms, fT3 was higher. Hence, serum TSH and fT3 may influence the risk for ADHD.Solid evidence points to thyroid function being pivotal for brain developmentInattention/Hyperactivity scale.In our cohort, a 1 mIU/L higher TSH was related to a 10% lower risk for ADHD in children previously diagnosed with ADHD. These data may support the importance of TSH during early brain development, since these associations disappeared in adolescents. In addition, since we found no significant relations between TSH and fT4 with ADHD symptoms, our results suggest that these parameters may not be suitable for ADHD diagnosis in adolescents. In addition, it should be noted that the positive association of fT3 with ADHD symptoms might simply be measures of behavior at the high-end normal variation for the While earlier investigations explored the association between severe thyroid dysfunction and ADHD in children and adolescents, these cases, 224 in total, were excluded from our analysis. Thyroid function and ADHD symptoms may have changed significantly since the medication was initiated; therefore, it is difficult to assess the influence of present thyroid function when participants are on thyroid medication.44. Unfortunately, collecting additional information from teachers and/or relatives was unfeasible in this cohort study with more than 10,000 participants. Second, the use of stimulant medication (e.g. methylphenidate) in participants with an ADHD diagnosis was not assessed in the questionnaire. However, methylphenidate treatment had no sustained effects on thyroid function in pre-pubertal children with ADHD45. Third, although both hypo- and hyperthyroidism in mothers during pregnancy have been associated with a greater risk of ADHD in children, the cohort did not include information on thyroid status of the mother during pregnancy. Fourth, our significant findings may be driven by our large sample size  influencing our p-values. Fifth, a meta-analysis of studies with longitudinal follow-up of children with ADHD suggests that 35% of children recover whereas 50% meet criteria for ADHD in partial remission and 15% continue to meet full diagnostic criteria for ADHD46. Lastly, our cross-sectional study design cannot provide causal relationships between thyroid function biomarkers and ADHD diagnosis, therefore a longitudinal analysis should assess when and how thyroid dysfunction may contribute to the pathophysiology of ADHD.This investigation has several limitations. First, ADHD diagnosis was parent-reported after a previous diagnosis by a physician or psychologist and the age of the children/adolescents at time of diagnosis is unknown. We do acknowledge that when assessing ADHD symptoms, multi-informant rating scales are highly recommended and widely used to assist in decision-makingNonetheless, this analysis also has several strengths. Our study population consisted of a very large cohort of children and adolescents  representative of the German youth. Specifically, the information on numerous potential confounders was available. For the assessment of ADHD symptoms of participants aged 3 to 11 years, a behavioral assessment was conducted during medical examination in addition to the Strengths and Difficulties Questionnaire (SDQ) score of the parents’ questionnaire. Moreover, a central laboratory was used to measure age-specific TSH, fT3, fT4 thereby reducing variability.47. The association between TSH and ADHD diagnosis in children within the KiGGS Baseline study further highlights the significance to promote investigations to explore this interaction. Also, the lack of an association between TSH and ADHD diagnosis in adolescents points to important timing considerations for treatment options.The various short- and long-term medical, social and health economic consequences of ADHD illustrate the high level of public health relevance of this disorder. Yet, possibilities of primary prevention are limited due to the high proportion of genetic factors in the etiology of ADHD. The association of thyroid dysfunction with neurodevelopmental disorders has always been of special interest because the brain is a target organ for thyroid hormones, and even small differences in neurobehavioral outcomes can have major public health consequences48. The sampling procedure followed a two-stage protocol developed in cooperation with the Centre for Survey Research and Methodology (ZUMA), Mannheim, Germany. First, to consider proportionately the population size according to degree of urbanization and geographic distribution in Germany, 167 communities were selected as primary sample units (PSUs), with a disproportionate number of PSUs in Berlin and East as well as West Germany, to represent these regions separately. At the second stage, an equal number of addresses (n = 24) per birth cohort was randomly selected (simple random sample) from local population registries within selected PSUs, eight weeks before the start of examinations. A final simple random sample was drawn at the Robert Koch Institute , including a total of eight, nine, or ten children and adolescents per birth cohort, depending on community size. The total KiGGS Baseline sample included 28,299 children and adolescents. The ethics committee of the Charité/University Medicine Berlin approved the study.KiGGS Baseline is based on a cross-sectional, nationally representative sample of children and adolescents 0–17 years of age with their main residence in GermanyParents of eligible children and adolescents were contacted by letter and invited to participate in the survey. Following a random route plan, 167 PSUs were covered by four study teams within three years . Personal contact was sought to those who had not responded to the invitation letter. A total of 17,641 children and adolescents participated in the study (response 66.6%). The parents of all participants gave informed written consent.For the purpose of our study of the 17,641 KiGGS Baseline participants, children younger than three years were excluded (n = 2805) because of inadequate blood sample volume to measure thyroid function biomarkers. Further, we excluded 224 participants taking thyroid medication and 2871 participants with missing data for serum TSH levels or other co-variables leaving 11,588 participants for the analysis of thyroid function biomarkers and ADHD diagnosis. For the second regression analysis, assessing the relation between thyroid function biomarkers and ADHD symptoms, missing data was present for 36 participants. Further, the 572 ADHD diagnosed individuals were excluded in this analysis resulting in a final sample size of 10,980 children and adolescents.49, were determined using computer-assisted parental interviews conducted by a study physician. This multidimensional aggregated SES index comprises the dimensions of parents’ education , income , and occupational status. In addition, a broad range of health information was collected from a self-administered questionnaire. These questionnaires were child age group-specific and administered to parents of all participants aged 0–17 years and in addition directly to participants aged 11–17 years. The parental questionnaire included a question on whether their child had been diagnosed with ADHD according to the established symptom profile  through a multi-informant assessment2. From the already frequently tested and validated Strengths and Difficulties Questionnaire (SDQ)51 the subscale Inattention /Hyperactivity was included in the parental questionnaire. To determine ADHD symptoms the cutoff value of the English standard random sample was used52, which is identical with the cut-off value of the German standardization53. The internal consistency of Subscale Inattention/Hyperactivity is α = 0.59 and varies from 0.52  to 0.63 54. Although a multi-informant assessment was not feasible to be ascertained in the KiGGS study setting, an additional behavioral assessment was carried out independently from the parental Inattention/Hyperactivity assessment by the study team during the physical examination  for the age group of 3- to 11-year-olds. The criteria for the behavioral assessment conducted by the study team were oriented on the three main symptoms of ADHD: inattention, restlessness, impulsivity. Resulting from the parental questionnaires, participants were categorized as ADHD diagnosis cases, if a doctor or psychologists had diagnosed ADHD previously. ADHD symptoms were determined as followed: participants age 3- to 11-years-old, who scored a sum value of ≥ 7 in the Inattention/Hyperactivity scale of the SDQ and in addition received a positive behavioral assessment from the study team, yet had no previous ADHD diagnosis, were assigned in this group. For participants older than 11 years, the SDQ subscale result determined the ADHD symptoms. Participants were assigned to the control group for our first round of analyses, if no previous ADHD diagnosis was attested. In our second round of analyses, the control group consisted of participants with no previous ADHD diagnosis and whose behavioral assessment and the SDQ subscale result pointed towards no ADHD symptoms.The examination and interview component, which was tailored to age range, was carried out in a Standard Operating Procedure (SOP)-compliant, standardized manner. Each team involved in the study, which consisted of a physician and two examiners, attended a comprehensive training program explaining the guidelines set out in the SOP manuals before starting fieldwork. Follow-up training was regularly carried out during the data collection phase as required. Children’s age, sex, birth weight, gestational week at birth as well as maternal smoking during gestation  and family’s socioeconomic status (SES), which was defined as “low”, “medium”, or “high” based on an established and validated index by Winkler and Stolzenberg55. The Tanner stages one through five were assigned based on the participants’ external primary and secondary sex characteristics, such as breast size and development of pubic hair. Afterwards all participants were classified into two groups according to their Tanner status: children (stages one through three) and adolescents (stages four and five). The differentiation by physical development was chosen as there are substantial changes in TSH and thyroid hormone levels during childhood, in particular for fT3, which appear to relate to pubertal readiness56.Participant BMI was calculated by dividing body weight in kg by height in cm to the square, which was measured during the physical examination. The Tanner Scale was observed by the study examiner and used to describe physical development57. TSH, fT3, and fT4 were determined using electrochemiluminescence . The inter-serial coefficients of variation (CVs) were 3.9% for TSH, 5.9% for fT3, and 5.3% for fT4. The difference in the median serum TSH level was marginal regardless of the timing of the sample  and unlikely to influence the results. As all measurements were conducted in the same laboratory, higher or lower thyroid hormone levels were defined using age- and sex-specific reference ranges36.A non-fasting blood sample was drawn during the appointment for the health interview and examination and processed within 45 minutes2 test , respectively. Associations of TSH, fT3 and fT4 with ADHD diagnosis as well as categorical ADHD symptoms were calculated using logistic regression models adjusted for sex, age, weight at birth, mother’s smoking habit during pregnancy and current BMI z-score of the child/adolescent. Linear regression models adjusted for the same confounders were used to analyze the association between TSH, fT3 and fT4 with continuous ADHD symptoms. To account for potential non-linear relationships we modeled the exposure variable continuously and tested potential non-linear transformations of the exposure variable by sophisticated statistical methods such as fractional polynomials or restricted cubic splines to account for potential non-linear relationships of TSH/fT3/fT4 with ADHD diagnosis and symptoms. In our analyses, we found no evidence for non-linear associations. A p < 0.05 was considered statistically significant. All statistical analyses were performed in Stata 14 .The total study population was stratified by Tanner status (children and adolescents) and the presence of an ADHD diagnosis or ADHD symptoms, which resulted in four different groups. Continuous data were expressed as median and 25th/75th percentiles . Nominal data are provided as total numbers and percentages. Differences between groups were calculated using Kruskal–Wallis (continuous variables) and ΧThe parents/legal guardians of all participants gave informed written consent. The Ethics Committee of the Charité/University Medicine Berlin approved the study. Hence, all methods were carried out in accordance with relevant guidelines and regulations.Supplementary Information.


Research found that adults with attention deficit hyperactivity disorder (ADHD) have more problems with financial decision-making than healthy controls. The present study investigates the impact of symptoms of ADHD on impulsive buying and the use of financial decision styles. Furthermore, the influence of personality, symptoms of depression and demographics on the association between ADHD and these aspects of financial decision-making is evaluated. A community sample of 1292 participants  completed questionnaires related to ADHD, impulsive buying, financial decision styles, personal financial situation, depression and personality. Four groups were formed based on self-reported ADHD symptoms: an ‘ADHD’ group (n = 45), an ‘Adult-only ADHD’ group (n = 57), a ‘Subthreshold ADHD’ group (n = 162) and a ‘No ADHD’ group (n = 265). Groups were compared using ANOVA and chi-square tests. Furthermore, multiple regression analyses in the complete sample were employed to examine the association between ADHD and financial decision-making. The ADHD and Adult-only ADHD groups reported significantly more impulsive buying, used more often an avoidant or spontaneous decision style and less often saved money compared to the No ADHD group. Regression analyses revealed that impulsive buying and financial decision styles were not significantly associated with ADHD symptoms when controlling for personality, symptoms of depression and demographics. The present study confirms previous research on adults with ADHD by indicating more impulsive buying and a more frequent use of disadvantageous financial decision styles  in individuals with an elevated number of current symptoms of ADHD compared to individuals without symptoms of ADHD. Personality and demographic variables were found to be related to both impulsive buying and the use of specific financial decision styles and might be of influence on the association between impulsive buying, the use of financial decision styles and ADHD. Attention Deficit Hyperactivity Disorder (ADHD), characterized by symptoms of inattention, hyperactivity and impulsivity , is histAlthough financial decision-making has hardly been investigated in adults with ADHD, there are indications that adults with ADHD also have problems with this important capability in everyday life. Financial decision-making describes several components related to the ability to manage or direct to manage financial affairs. It involves practical skills and abilities, e.g., counting coins, but also financial knowledge and judgment to perform financial actions . The limIn the dual pathway model of decision-making, affective processing of information is described as one of two systems involved in decision-making –18. TogeInadequate financial decision-making can have major negative consequences for individuals, such as debts and poverty, and further investigation of this topic in adults with ADHD is, therefore, important. According to the framework of Appelbaum et al. , financiThe aims of the present study are, therefore, (1) to investigate the impact of current symptoms of ADHD on two types of financial performance, i.e., impulsive buying and the use of financial decision styles, (2) to partly replicate a recent study on financial decision-making in adults with ADHD  and (3) Based on previous research , a positA community sample of 1292 participants  with an age range of 18 to 93 years  participated in the present study. Demographical characteristics of the participants are described in ADHD’ (n = 46), met the self-reported symptom criteria for both adulthood and childhood ADHD as defined in the DSM-5 , met the DSM-5 classification for adulthood ADHD, but not for childhood ADHD. Group 3, named ‘Subthreshold ADHD’ (n = 162), did not meet the DSM-5 criteria for adulthood ADHD, but reported 3 or 4 current symptoms of inattention and/or 3 or 4 current symptoms of hyperactivity and impulsivity. Retrospective symptoms of ADHD  were not part of the inclusion criteria for this group. However, 20.4% of participants in the Subthreshold ADHD group met the DSM-5 self-reported symptom criteria of childhood ADHD . Based on their scores on the ARS, four groups were formed to use for group comparison analysis . Group 1, named ‘ood ADHD . Since tn = 265; . Partici‘rarely or never’, 1 = ‘sometimes’, 2 = ‘often’ and 3 = ‘very often’), participants had to indicate for each item which answer alternative described their behavior best in the past six months  or during childhood when being 0–12 years old . Using the scoring system of Kooij et al. ) and the Subthreshold ADHD group . Furthermore, the Adult-only ADHD group obtained significantly higher scores compared to the No ADHD group on the IBQ total score  and on both subscales . No significant differences were found regarding the other group comparisons and groups also did not differ in the situational subscale of the IBQ . The scores on the FDS avoidant subscale of the Adult-only ADHD group were also significantly higher compared to the Subthreshold ADHD group . No significant differences were found on the FDS avoidant subscale between the other groups. With regard to the FDS spontaneous subscale, the ADHD group obtained significantly higher scores compared to the Subthreshold ADHD group  and the No ADHD group , while no significant differences were found between the other groups. Furthermore, groups did not differ with regard to the rational, intuitive and dependent subscales of the FDS.Significant group differences were found on the FDS avoidant subscale and the FDS spontaneous subscale . For theX2(1) = 8.0; p = .005; d = 0.32, 95% CI ) and the Subthreshold ADHD group  = 4.9; p = .026; d = 0.31, 95% CI ). Comparable results were found for the Adult-only ADHD group: 22.8% of the Adult-only ADHD group saved for their retirement, which were significantly less individuals compared to the No ADHD group (X2(1) = 7.0; p = .008; d = 0.30, 95% CI ) and the Subthreshold ADHD group (X2(1) = 3.8; p = .050; d = 0.27, 95% CI ). Furthermore, compared to the No ADHD group, the Adult-only ADHD group significantly less often saved money actively  = 10.3; p < .001; d = 0.38, 95% CI ). Other group comparisons of these and other personal financial situation variables were not significant  = 43.33; p < .001; F = 4.0; p = .045; ΔR2 = .002). Instead, a significant positive relation was found with extraversion and neuroticism. Conscientiousness and agreeableness were significantly negatively related to the IBQ total score. Furthermore, being female and a lower age were also related to a stronger tendency to buy on impulse  = 36.7; p < .001); 24.2%  = 38.4; p < .001) and 3.6%  = 5.4; p < .001) of variance could be explained in the third regression model, respectively  = 2.2; p = .137; affective: ΔR2 = .003; F = 4.6; p = .032; and situational: ΔR2 = .001; F = 1.7; p = .192). For the IBQ cognitive component, the significant predictors were similar to the contributors of the IBQ total score: while extraversion and neuroticism were significantly positively related, conscientiousness and agreeableness were significantly negatively related to the cognitive component. Also, being female and a lower age were significantly related to higher scores on the cognitive component of impulsive buying. For the IBQ affective component, extraversion and neuroticism were found to be significantly positively related, while other Big Five personality traits and symptoms of depression did not significantly contribute to this model. However, being female and a lower age were significantly related to the affective component of impulsive buying as well. Regarding the situational component of the IBQ, only conscientiousness was found to be a significant negative predictor  = 0.3; p = .580; intuitive: ΔR2 = .000; ΔF = 0.1; p = .827; dependent: ΔR2 = .006; ΔF = 8.7; p = .003; avoidant: ΔR2 = .005; ΔF = 7.6; p = .006 and spontaneous: ΔR2 = .001; ΔF = 1.2; p = .278). Decision styles could, however, be explained by other variables included in the regression model  = 32.2; p < .001). The use of a rational decision style was significantly positively related to conscientiousness and openness and significantly negatively related to extraversion. In addition, level of education was also a significant positive predictor of the rational decision style  = 13.7; p < .001). The use of an intuitive decision style was significantly negatively related to level of education and significantly positively related to extraversion and symptoms of depression  = 16.3; p < .001) and the use of a dependent decision style was significantly positively related to neuroticism, extraversion and being female  = 37.2; p < .001). The use of an avoidant decision style was significantly positively related to age, neuroticism and extraversion and significantly negatively related to conscientiousness and agreeableness  = 37.9; p < .001). The use of a spontaneous decision style was significantly positively related to extraversion and neuroticism and significantly negatively related to conscientiousness and agreeableness  compared to individuals without symptoms of ADHD. Furthermore, individuals who met the self-reported symptom criteria for ADHD  showed higher scores on the cognitive component of impulsive buying compared to individuals without symptoms of ADHD and individuals with current subthreshold symptoms of ADHD. A similar result was found for individuals in the Adult-only ADHD group compared to individuals without symptoms of ADHD . Previous research reported a significant relation between current symptoms of ADHD and compulsive buying, a pathological form of impulsive buying ,47, partThe results with regard to the use of specific financial decision styles showed a similar pattern as found for impulse buying. In accordance with previous research , signifiWhen interpreting the results regarding impulsive buying and the use of financial decision styles, it is important to keep in mind that associations were found between symptoms of ADHD and personality traits  Tables. With regard to the personal financial situation, the ADHD group less often saved for their retirement compared to the No ADHD group. On all other aspects  the financial situation of the ADHD group was comparable to individuals without symptoms of ADHD. Compared to the No ADHD group, the Adult-only ADHD group also made less often financial decisions for the future . Previous research comparing a clinical ADHD group with healthy controls, however, revealed that adults with ADHD have various problems related to their personal financial situation . TheBesides a group meeting the self-reported DSM-5 symptom criteria of adult ADHD , two other ADHD groups were created based on the number of reported symptoms of ADHD: an Adult-only ADHD group meeting the self-reported symptom criteria of adult ADHD but not for childhood ADHD and a Subthreshold ADHD group reporting a subthreshold number of current symptoms of ADHD . Based on the results, no evidence has been found that individuals with a subthreshold number of ADHD symptoms have difficulties with financial decision-making, since no differences were found between the Subthreshold ADHD group and the No ADHD group with regard to impulsive buying and the use of financial decision styles. However, the Adult-only ADHD group showed inadequate financial performances on both the cognitive and affective domain of impulsive buying. Furthermore, the avoidant style was more often used by this ADHD group compared to individuals without symptoms of ADHD. This indicates that individuals with current symptoms of ADHD without the presence of retrospective symptoms of ADHD might have difficulties with financial decision-making, similar to individuals meeting the self-reported symptom criteria of adult ADHD. Previous research already found similar neuropsychological performances and personality profiles in individuals who met all DSM-IV criteria for childhood-onset ADHD and individuals having so-called late-onset ADHD ,49. ThesAn important limitation that needs to be taken into account when interpreting the results of the present study is the lack of clinical information about the participants . Consequently, results may not be generalized to a clinical ADHD population. Current findings with regard to impulsive buying and the use of financial decision styles are, however, comparable with and seem to confirm previous research using a clinical group of adults with ADHD . FurtherF = .33; p = .808). A third limitation is that the use of different recruitment and compensation modalities might have resulted in differences in clinical or demographical characteristics and motivation between participants recruited via an online research panel (n = 474) and participants recruited via other modalities (n = 818). Additional analyses comparing participants recruited via these two modalities, however, indicated no significant differences between groups with regard to retrospective and current symptoms of ADHD. Furthermore, no marked differences in the main findings were found between these modalities (data not published).Another limitation is that the total administration time of the questionnaires was longer than initially expected. On average, participants needed 56 minutes to complete all questionnaires. The sequence of questionnaires was, however, equal for all participants see . NeverthAnother limitation is that no direct causal conclusions can be drawn about the observed associations between the dependent and independent variables in current study. This is a common problem in cross-sectional studies and especially when studying personality and psychopathology ,52. In tDespite the described limitations, the results of the present study appear to confirm previous research in adults with ADHD and indicate more impulsive buying and more frequent use of disadvantageous financial decisions styles  in individuals fulfilling self-reported current ADHD criteria  compared to individuals without symptoms of ADHD. Contextual factors, i.e., personality and demographic variables, were also found to be related to both impulsive buying and the use of specific financial decision styles. Personality and demographic variables might (at least partly) be of influence on the association between impulsive buying, the use of financial decision styles and ADHD since no significant association between symptoms of ADHD and these types of financial performance could be found when controlling for personality characteristics, symptoms of depression and demographics. However, no direct causal conclusions can be drawn and prospective longitudinal research is suggested to further investigate causality between these variables. The evaluation of financial decision-making in adults with ADHD remains nevertheless a topic of major interest in both research and clinical practice, since problems with managing financial matters may have far-reaching consequences for both patients and their social environment, and more attention for this topic is therefore recommended.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.