Attention-deficit hyperactivity disorder (ADHD) is a highly comorbid disorder that can impact significantly on the individual and their family. ADHD is managed via pharmacological and nonpharmacological interventions. Parents also gain support from parent support groups, which may include chat rooms, as well as face-to-face meetings. With the growth of technology use over recent years, parents have access to more resources that ever before. A number of mobile apps have been developed to help parents manage ADHD in their children and young people. Unfortunately many of these apps are not evidence-based, and little is known of their suitability for the parents or whether they are helpful in ADHD management.The aim of this study was to explore the (1) parents’ views of the suitability of the top ten listed apps for parents of children and young people with ADHD and (2) the views of clinicians that work with them on the suitability and value of the apps.The top 10 listed apps specifically targeted toward the parents of children and young people with ADHD were identified via the Google Play (n=5) and iTunes store (n=5). Interviews were then undertaken with 7 parents of children or young people with ADHD and 6 clinicians who specialize in working with this population to explore their opinions of the 10 apps identified and what they believe the key components are for apps to be suitable and valuable for this population.Four themes emerged from clinician and parent interviews: (1) the importance of relating to the app, (2) apps that address ADHD-related difficulties, (3) how the apps can affect family relationships, and (4) apps as an educational tool. Two additional themes emerged from the clinician interviews alone: monitoring ADHD symptoms and that apps should be practical. Parents also identified an additional theme: the importance of the technology. Overall, the characteristics of the current top 10 listed apps did not appear to match well to the views of our sample.Findings suggest that these apps may not fully meet the complex needs of this parent population. Further research is required to explore the value of apps with this population and how they can be tailored to their very specific needs. Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder, characterized by three core symptoms: hyperactivity, impulsivity, and inattention, which has a profound impact on the individual and their family -3. ADHD Globally, ADHD treatments include pharmacological and nonpharmacological interventions -21. In lWhen young people diagnosed with ADHD reach their adolescent years, they are less likely to take their ADHD medication reliably and are more likely to disengage from services . This trParents are under tremendous strain when caring for a child or YP with ADHD . It is fEmphasis has been placed on the importance of the supportive role of the parent in ADHD ,33. YounThe increasing use and accessibility of the Internet, mobile phones, and mobile devices offers an additional way to support parents . TechnolThere have been a number of apps developed for parents for this purpose, but thus far, there is little evidence to underpin them. Some of these apps are designed for the parent and child to use jointly to enable the parent to monitor their child’s ADHD symptoms, monitor medication compliance, give parenting advice for managing a child with ADHD, and also to help with daily routines such as getting dressed and going to bed. Evidence includes app development papers such as the WHAAM app that involves monitoring ADHD behavior in children and data sharing between parents, teachers, and health care professionals . One stuFurthermore, app quality is not routinely monitored. Once the app has been bought, there is little feedback on usefulness. There is also minimal guidance available to demonstrate the reliability, validity , and suiThis study proposes to identify apps aimed at the parents of children and young people with ADHD and to interview the parents and specialist clinicians who work with them to explore what could make an app suitable in terms of appearance, content, and functionality for the parents of children and young people with ADHD. This will provide those developing apps for this population with some key components to consider.This research involved the identification of the top 10 listed apps aimed at the parents and guardians of children and young people diagnosed with ADHD. Subsequently, the parents tested the apps, and they were then interviewed to ascertain their views on the apps and to explore what they believed the key components are for apps to be helpful for them. Clinicians who work with children and young people with ADHD and their parents were also interviewed to explore their insights into how to make apps successful for this parent population.The research question was as follows: are the 10 top listed apps that are specifically designed and marketed for the parents of children and young people with ADHD suitable and what are the key components for apps to be suitable for this population?In July 2016, a search of mobile apps in the Apple iTunes store and the Android Google Play store was conducted. These databases were selected because they displayed systematically organized app rankings defined by algorithms unique to each app store, commonly known as app store optimization (ASO) . For AppThe search term used was “ADHD.” This is because other search terms such as “ADD,” “children,” “Young people,” and “parents” did not provide different results to the “ADHD” searches. The term “ADHD” was searched in both iTunes and Google Play.Preliminary screening was conducted based on app titles, full marketing description, and screenshots of the apps potentially relevant for inclusion. The first 5 listed apps that met the inclusion criteria from each app store were included, giving a total of 10 apps for study  and 2.Duplicate apps were removed . This waThe remaining 10 apps were downloaded onto an Apple iPad Mini (Model: A1489) or a Samsung device (Model: GT-P5220), and their content was summarized by the lead author . The appInclusion criteriaAn app that states it is aimed at a parent of a child or a young person with ADHD or attention deficit disorderMobile appApp is available in the English languageExclusion criteriaDoes not state app is aimed at parent of a child or young people with ADHDNot a mobile app Not available in the English languageDuplicate appConvenience sampling was adopted to recruit specialist clinicians who work with children and young people with ADHD and their families, as well as parents of children and young people with ADHD. Parents were recruited via a Family Action group  and an online ADHD community group. Clinicians were recruited via the NHS Child and Adolescent Mental Health Service in the South Yorkshire region. Participants were recruited until data saturation was achieved. Eligibility criteria for clinicians were that they had to be employed by a service that treats children and young people with ADHD.Eligibility criteria for the parents of the children and young people with ADHD were as follows: (1) must be a parent of a young person who has a confirmed ADHD diagnosis and (2) must be able to provide details of the medication the child is prescribed.Ten separate semistructured interviews took place in the Sheffield region. Three interviews with parents involved interviewing parents jointly. Interviews lasted up to 60 min with the clinicians, and up to 90 min with the parents. The study received ethical approval from the University of Sheffield’s School of Health and Related Research Ethics Committee , as well as NHS Health Research Authority and Research and Development approval.The researcher visited parents at the Family Action parent group and introduced the study. Parents then either contacted the researcher, or they requested that the researcher contacted them at a time convenient to them. Clinicians were approached via email. Interviews took place at a quiet convenient place with the clinicians and in the homes with the parents. Before the interviews, the clinicians and parents provided written informed consent.Information about the study was sent to all participants at least 1 week before the interviews took place. At the beginning of each interview, the study was explained to the participants and questions were answered.Clinicians and parents were presented with all 10 apps identified. Participants were given the opportunity to use the apps themselves during the interview. Interview discussions were guided by an interview schedule covering their views in four key areas:What makes a successful app?What makes an app less successful or unsuccessful?How could an app function benefit them as parents of young people with ADHD?How could apps for parents help manage ADHD or address difficulties in young people?The two groups provided two unique perspectives: a user perspective and a clinician perspective. Participants also completed a short questionnaire on their demographic characteristics. Parents additionally provided details of their child’s diagnosis and prescribed ADHD medication (where applicable).All interviews were audio-recorded and transcribed verbatim. Thematic analysis  was usedFive apps were identified from Google Play and five from iTunes in August 2016. A total of 13 participants were recruited from February to March 2017 (clinicians) and October to November 2016 (parents). Participants included 6 clinicians and 7 parents of young people diagnosed with ADHD. Participant characteristics are reported in Data was collected until data saturation was achieved. Transcripts were available for all 13 interviews. During analysis, agreement between the 2 primary coders was high. Seven themes were identified in total . Where sParents (n=7) and clinicians (n=4) believed it was important to relate to the app, especially when the app is aimed at both the parent and the child:...if you could choose who you were, [referring to avatar in app] she [child] could relate a bit better.P1...that’s an issue already [referring to gender and race of apps character], it’s not even a boy is it, is it a girl or a boy?P1Clinicians (n=5) and parents (n=7) believed that apps should be visually attractive and have an appealing audio component :I like quite visual things, I like visual things, I like stuff that takes 2 minutes, simple.P1Parents also believed that they should be able to alter apps to suit their own circumstances (n=7). Examples of this involve dressing a character in an order that is dictated by the parent; the parent could choose the items of clothing or the songs they play rather than the app dictating this. In terms of monitoring, they would like to choose the factors that they monitor rather than having these dictated by the app as well....having the option...at the beginning of being able to change the colors because he might go oh I can’t put that on because I don’t own a yellow t shirt...P2...like a [different] song every morning,...Michael Jackson, then Bob Marley, you know [tailoring the app to] what he [son] likes...if he woke up to something he likes it would put him in a better frame of mind [for the rest of the day]...P7Parents (n=7) and clinicians (n=6) also believed that the apps should target difficulties that specifically relate to ADHD, such as daily routines , behavior management (clinicians n=1), organizational skills (parents n=2), and to improve their communication with schools ....if you’ve done that preparatory work [using an app to learn how to get dressed in the morning] with the child then hopefully that would make things easier [for the parents] in the mornings.health care professional 2, HCP2...they’ve got no organizational skills what so ever so that’s [app targeting organizational skills] really good.P1Two parents acknowledged that apps have the potential to reduce their ADHD-related anxieties (parents n=2). One clinician (HCP1) stated how an app could do this and why it could be beneficial:...the parents’ reaction to the behavior...may be based on...day stress, my boss yelling at me so if I can do something to bring own my stress levels my response to the child with ADHD may be different.HCP1Almost all the participants  were able to highlight the benefits of using an app to monitor ADHD-related difficulties in ADHD:...might spot trends as to why their behavior became the way it was.P2...to help you see where your kids struggling I would say.P4...good idea because...school can give more information...because I don’t see my child with the medication so it would be useful if I could see what the teachers are saying...?P3One parent believed that an app shouldn’t try to slow down a young person with ADHD but harness their hyperactivity by having an app that is also fast paced:...having something that tries to slow em down just doesn’t work. You’re better off keeping them in one place by giving them something that will interact that’s fast.P5Parents and clinicians  noted that apps could be used to improve relationships between the parent and their child:...it’s like more bonding time, education for myself and my son.P6I like the idea of parent and child working alongside [using an app].HCP1...bit of fun between the parent and child cos mornings and mealtimes and bedtimes can be really stressful so [the app] takes away some stress and introduces a bit of relationship building as well.HCP4It was also noted that apps could help address an ADHD diagnosis and what it means with siblings so that they can learn about their brother or sister’s condition :...I think it would be useful to use with siblings [to explain ADHD to them] as well an’ they could interact with the game.HCP2Parents and clinicians liked the idea that apps could be used as an educational tool to learn about ADHD either via the app itself or via Web resources that are signposted within the apps . Parents also liked that some of the apps presented ADHD in a positive light (n=4):...you can’t keep going on courses for the rest of your life. And you can’t always get it from a book as you either have to buy the book or the library doesn’t have it.P5...being reminded of positive things I also good for you and the kids self-esteem...P3Clinicians acknowledged that apps should be culturally relevant (n=2). For example, one American app provided news stories that provided information that isn’t always relevant to the United Kingdom:...parents may be taking things on board that when you look into it there’s not much evidence for. Also, it’s promoting medications of therapies or whatever their whole healthcare systems structured differently to ours, which puts a bias on it...And also they have medication licenses that we don’t.HCP2One clinician stated that app developers should be mindful that parents also have varying abilities:...it’s hard for parents to understand exactly what ADHD means...if you have a parent with...learning difficulties then its explained in an easy simple to understand way...HCP2Many of the clinicians stated that parents of children and young people with ADHD lead busy and often hectic lives. Therefore, apps should be simple to use and easily integrated into their daily routines if they are to use them routinely (n=4). One clinician stated that if apps are visually appealing, then this would contribute to the ease of use of the product, which is important. They also believed that many parents may not want to pay for apps (n=3):I don’t think the parents have got time for apps...I’ve met very few parents that will have time...most of them will have a sibling with ADHD or...younger children...HCP3...if you are if you’re a parent…trying to catch up on something in a fairly fast way,...I want something that will be quick...HCP6I wouldn’t spend that [as a parent].HCP6Clinicians believed that apps could be a good tool to monitor the ADHD-related difficulties of a child, their symptoms relating to medication and also to provide reminders such as for appointments and taking ADHD medication (n=6):...if they are able to keep that record [ADHD monitoring on an app] it may be helpful for the clinician who is monitoring the young person’s care...HCP5...the best thing is...it will remind you say at 9 o’clock at night and you can record the day.HCP6; praising an app that reminds the parents to enter ADHD symptom information into the app on a daily basisParents stressed the importance of the technology itself. They believed that an app isn’t always necessary (n=5); they can be distracting, and accessing the technology can sometimes be problematic (n=5). They also discussed how some of the apps required the input of identifiable information. Parents raised concerns here regarding data security (n=3);...that’s all I do,...I type in ADHD in Twitter if I want to know about that I won’t download an app for it.P1Once again the only thing is it’s (the app) trapped in Apple world.P4...today your data might be safe, tomorrow your data maybe be going off on tour somewhere for a, for a price.P4This study identified 10 apps that stated they were aimed at the parents of children and or young people with ADHD. Seven parents of young people with ADHD and 6 clinicians working with this population were interviewed. Interviews involved sharing the 10 identified apps with participants and asking what they think would make an app suitable for parents of children and young people with ADHD. Parents stated that technology access can be a barrier, that apps could enhance family relationships, apps have the potential to explain what ADHD means to effected siblings, apps should be flexible, and they could be used as an ADHD educational tool. Additionally, clinicians felt that apps would be useful for parents to monitor their child’s ADHD symptoms and related difficulties and that apps should be practical, quick, and easy to use to account for the parents with often busy and chaotic lifestyles. The latter findings are consistent with the findings of Simons et al .As living with and managing the ADHD with a child or young person can be incredibly stressful for parents, the National Institute for Health and Care Excellence guidelines recommend that all the parents of children and young people diagnosed with ADHD should be invited to attend parent management and support groups . There aWe are living in a society where technology is routinely used and embedded into our lives. Many apps are advertised for parents of children and young people with ADHD, but there is little evidence to underpin them and little evidence to ascertain what makes such apps suitable for parents. The young people and clinicians whose views were sought in this study did not find that the apps reviewed fully met their expectations. The highest match was 5 out of 8; two apps scored 1 out of 8, and the mean score was 3.6. Parents wanted the apps to be visually pleasing and tailored to their own circumstances. Clinicians were keen to highlight the possibility of using apps to allow parents to monitor their child or young person's ADHD-related difficulties. Clinicians saw the opportunity to use this data clinically.Increasing knowledge about a disorder, for example, by using psychoeducation, is recognized as important in improving management and then outcomes in chronic disorders. The knowledge of parents or carers of children with ADHD and, in particular, of young people with ADHD themselves, has been shown to be poor . When yoThe perspectives of both the clinicians and the parents are needed to build up a full picture. Clinicians are keen to make use of apps to promote positive behaviors and target specific needs. The views of the parents give guidance as to whether they would actually use the app and whether they felt it was likely to be helpful.A Canadian study  considerIf technology is to be reliably helpful, some quality standards must be met. Apps are often developed rapidly with little evidence base. The pressure is often for financial success rather than proven benefit. This study gives us some insight into the quality of currently available apps and suggests that more research is needed to harness technology to benefit young people with ADHD and their families.This research suggests that currently the top 10 listed apps marketed for parents with young people with ADHD do not seem likely to meet their needs and crucially, do not have the key components of they believe will make an app helpful.According to our participants, key components of a successful app are likely to be; pleasing visuals, the facility to personalize, the ability to help with specific ADHD difficulties, design for joint use by a parent and young person, use as an ADHD educational tool, use in monitoring ADHD-related difficulties and symptoms, easy to use, possible use to improve daily routines.Future research is needed on the value of apps for parents of children and young people with ADHD and, in particular, any positive role for apps in the management of ADHD in this age group.Future research is needed to develop apps in coproduction with key stakeholders and explore the effectiveness of technology-based interventions.This could result in setting standards for apps for ADHD and other chronic conditions, which could guide users to the optimal apps for their needs.


It has been shown that an increasing number of adults deliberately feign attention deficit hyperactivity disorder (ADHD), which demonstrates the need for new tests designed to detect feigned ADHD.An Embedded Figures Test (EFT) was developed for the detection of feigned ADHD in adulthood. EFT performance of 51 adults with ADHD was compared to the performance of 52 matched healthy individuals, as well as to 268 undergraduate students who were randomly allocated in a simulation design to one of four experimental conditions, i.e. a control group, a naïve simulation group, a symptom-coached simulation group or a test-coached simulation group. Furthermore, an independent sample of 11 adults with ADHD as well as a sample of 17 clinicians experienced in the work with adults with ADHD were assessed for further validation of the EFT.The EFT was relatively easy to perform for both patients with ADHD and healthy comparisons as shown by low error rates and non-significant group differences. However, simulation groups differed from patients with ADHD by significant and large effects. An EFT index for the prediction of feigned ADHD was derived based on logistic regression coefficients. Receiver Operating Characteristics (ROC) demonstrated good classification accuracy of feigned ADHD relative to ADHD (AUC = 94.8%), i.e. high sensitivity (88%) and specificity (90%).This study supports the utility of the EFT for the detection of feigned adult ADHD. The diagnostic assessment of attention deficit hyperactivity disorder in adulthood (ADHD) comprises a complex clinical evaluation, including a variety of assessment tools  and multiple sources of information (self- as well as informant reports) –4. The cIn the light of the many negative consequences of false-positive diagnoses of adult ADHD, it is not surprising that a number of studies explored the usefulness of standard measures used in clinical practice to distinguish between feigned and genuine ADHD . StaConsequently, research considered the use of tests specifically designed for the detection of feigned cognitive dysfunctions; the stand-alone effort tests  ,18,22–25These findings underline the urgent need for the development of new stand-alone effort tests specifically designed for the detection of feigned ADHD. A suitable test for this purpose may follow the principles of an Embedded Figures Test (EFT) . In an EFurthermore, the development of an EFT that is sensitive in detecting feigned ADHD might benefit from also considering practice and transfer effects. Studies using EFTs in healthy individuals demonstrated that the repetition of a task with the same stimuli results in practice effects, whereas transfer effects are the consequence of the repetition of a task (applying same principles) with different stimuli . As the The present study describes the utility and sensitivity of an EFT which has been designed for the detection of feigned ADHD by making use of the rationale described above. Healthy individuals were allocated to either a control group requiring them to perform the EFT to the best of their abilities, or to one of three simulation groups asking them to perform the EFT as if they suffered from ADHD. The three simulation groups differed with regard to information they were provided prior to the assessment, as individuals attempting to feign ADHD in a clinical setting may prepare themselves before diagnostic evaluation, e.g. by familiarizing themselves with symptom criteria of ADHD and/or about instruments used at a typical diagnostic assessment. EFT performance of these groups was compared to the EFT performance of a group of patients with ADHD. Classification statistics were calculated in order to explore whether the EFT might be a suitable measure to distinguish between genuine and feigned ADHD. For clinical use, it was aimed to achieve overall accuracy as well specificity of at least 90% , 38.Fifty-one adults with ADHD participated in the study  = 4/7, IQ = 109.1±17.0, ASR = 25.1±9.1, WURS-K = 32.1±15.0). These patients were requested to perform the Embedded Figures Test EFT, see  section healthy comparison group (HCG) (n = 52) was recruited via public announcements, word-of-mouth and through contacts of the researchers involved. Healthy individuals were selected according to age, gender and intellectual functions, resulting in comparable characteristics to the first sample (n = 51) of patients with ADHD (2(1) = 1.65; p = .198) and intellectual functions (t(93) = 1.03; p = .306). However, as expected, patients with ADHD (first sample) scored significantly higher on self-report scales for both current ADHD symptoms (t(101) = 14.32; p < .001) and retrospective ADHD symptoms (t(100) = 12.78; p < .001).A ith ADHD . Particicontrol group (CG)  = 36/22, IQ = 98.0±9.4), the naïve simulation group (NSG)  = 54/16, IQ = 99.7±9.8), the symptom-coached simulation group (SSG)  = 51/19, IQ = 100.4±8.5), and the test-coached simulation group (TSG)  = 42/28, IQ = 101.7±10.1). Whereas the control group was instructed to perform all tests and measures to the best of their abilities, simulation groups were asked to perform the tests while pretending to be affected with ADHD (feigning ADHD). The simulation groups differed with regard to the additional information they received in preparation of their assessment  of the University of Groningen, the Netherlands, took part in the study in exchange of course credits. Participants had a mean age of 21.4 years (SD = 2.5 years) and a mean IQ of 100.1 (SD = 9.5). Prior to assessment, these participants were randomly assigned to one of four conditions, i.e. the ment see  sections2 = .018. First language of all participants was German. None of the healthy individuals reported a history of neurological or psychiatric diseases and none were taking any medication known to affect the central nervous system. Furthermore, none of the healthy participants endorsed clinically relevant scores of ADHD symptom severity as measured with two standardized self-report rating scales designed to quantify current and retrospective ADHD symptoms  [Descriptive variables did not differ significantly between groups, Wilk’s lambda = 0.946, F = 1.40, p = .185, ηficance) . The groexpert simulation group. All participants of this expert simulation group were clinically working psychologists or psychiatrists and were experienced in the diagnosis and treatment of adult ADHD. This expert group was requested to feign ADHD and to perform the EFT as if they suffered from ADHD, in order to bring the EFT into clinical context and to test its utility on a group that is considered to be highly trained and having expert status in the field. This group was included in order to check whether the sensitivity of the EFT is robust against the knowledge of clinicians experienced in the assessment and treatment of adult ADHD. By this, we attempted to prove whether the EFT has clinical utility above the clinicians’ experience. Because if clinicians are not able to feign ADHD convincingly when performing the EFT, or in other words are detected by the EFT as potential malingerers, the EFT may represent a valuable tool for clinicians when feigning is suspected.In addition, another group of 17 healthy individuals was recruited, the so-called Intellectual functions (IQ) were measured using the Multiple Choice Vocabulary Test (MWT-B) . This teChildhood ADHD symptoms were self-rated with the short version of the Wender Utah Rating Scale (WURS-K) including 25 items on a five-point scale . SeveritYes response button on the input device) or not (by pressing the No response button on the input device). Participants were explicitly instructed that this was a cognitively complex task requiring high demands on attention and concentration. Before the testing started, a test trial containing three example items was performed. The actual assessment was only initialized if correct answers were given to all example items. The test was self-paced as the subsequent item was presented as soon as a response was given to the current item. Between each block, participants were reminded that the test requires high attentional demands and were requested to maintain high cognitive effort. The mean response time and number of errors per block were registered.The EFT comprised 96 items, presented consecutively on a 15” notebook screen using the presentation software E-Prime 2.0. Each item showed simultaneously a complex figure on the left and a simple target figure on the right side of the. In half of the items, the target figure was embedded within the complex figure. The presentation of items was divided into four blocks of 24 items each. Items of each of the four blocks included the same 24 complex figures. Two different target figures were designed, one target figure for Blocks 1 and 3 and another target figure for Blocks 2 and 4. Consequently, Blocks 1 and 2  were identical to Blocks 3 and 4 , however, presentation order of test items was randomized within all four blocks. The target figure was embedded in twelve of the 24 complex figures per block, always presented at the same spatial location, in the same spatial orientation as well as the same size. This design was employed in order to create a task that may appear difficult to participants, but is actually rather easy to perform for most individuals. Participants were requested to indicate whether the target figure was hidden within the complex figure (by pressing the Focused attention was assessed with the test WAFF (Perception and Attention Functions: Focused Attention) [www.schuhfried.com/vienna-test-system-vts). In the WAFF test, a sequence of visual stimuli against a background of distracting stimuli was presented to participants on a computer screen. Participants were requested to respond to a predefined change in relevant stimuli but to ignore all other types of stimuli. The mean reaction time to stimuli (ms), the standard deviation of reaction times, as well as the number of omissions were registered as measures of focused attention. Internal consistency (Cronbach’s α) of the WAFF ranged between 0.93 and 0.97. Associations to other measures of cognition supported the construct validity  of the WAFF.tention)  of the Vtention) , a compuVigilance was measured with the computerized test VIGIL of the VTS [ the VTS . In thisResponse inhibition was measured with a Go/NoGo paradigm (INHIB) of the VTS [ the VTS . In Go/NInterference was assessed with the Stroop interference test (STROOP) of the VTS [ the VTS . The tesCognitive flexibility was assessed with the Trail Making Test (TMT) [st (TMT) . The Trast (TMT) .Figural fluency  was measured with the Five-Point Test (5PT) [st (5PT) ,54. The effort tests were used in the present study, i.e. the Test of Memory Malingering (TOMM) [Two established g (TOMM)  and the g (TOMM) . The TOMAll patients with ADHD (first and second sample) were tested individually and received no reward for participation. Written informed consent was sought from all participants prior to the assessment. It was pointed out to patients that all data collected in the research project will be analyzed anonymously and will not affect clinical assessment and treatment.The first sample (n = 51) of patients with ADHD was assessed with a comprehensive battery consisting of self-report questionnaires, interviews, the EFT, and routine measures of cognition . For the purpose of the present study, only a selection of measures will be considered. The total duration of the assessment of the first sample of patients with ADHD was about 2.5 hours. The assessment was split into two parts, divided by a break to recover from possible fatigue. The study was conducted in compliance with ethical standards of the Helsinki Declaration and was approved by the local institutional ethical committee .After completion of recruitment and assessment of patients with ADHD as described above, the independent sample of patients with ADHD  was assessed by requesting them to perform the EFT in addition to two established effort tests, i.e. the TOMM  and the expert simulation group who were assessed individually in a quiet office room at the hospital. At the beginning of the experiment, descriptive and anamnestic information was obtained including age, sex, intellectual functions and self-reported ADHD symptom severity. Furthermore, participants were asked for any history of psychiatric or neurological diseases as well as pharmacological treatment. Descriptive information was obtained from all participants at the beginning of the experiment, before simulation groups were instructed to feign ADHD. The subsequent assessment procedure differed between participants of the various groups . The expert simulation group was added after all assessments of the other groups  have already been completed.All healthy participants were tested individually in a quiet laboratory with the exception of the Participants in the HCG and CG were asked to perform all tests applied (including the EFT) to the best of their abilities. Participants received a notification by email on the day before the assessment in which the clinical significance of the study was introduced, but which did not contain information with regard to the aim of the study. The duration of the assessment of these groups was about 50 minutes.Participants in the simulation groups  were asked to perform the EFT while pretending to be affected with ADHD (feigning ADHD). For this purpose, participants in the simulation groups were presented with a vignette, describing a scenario in which someone would be motivated to feign ADHD. Several benefits were introduced in the vignette that may come with a diagnosis of ADHD, e.g. financial accommodations, more flexibility and freedom concerning working hours and deadlines, and the prescription of stimulant medication for improvement of work/academic performance or for recreational use. Information provided in the vignette was restricted to support participants to assume their role but did not contain information about the symptoms or nature of ADHD. Moreover, participants were explicitly instructed to make their feigning of ADHD seem realistic, i.e. by avoiding a very obvious exaggeration. In order to encourage participants to feign ADHD in a believable and realistic manner, participants were informed that the participant who feigned the condition best would be awarded with a top of the range tablet PC. This incentive was implemented because of methodological considerations in malingering research suggesting that an external incentive is an important element when using simulation designs [ designs ,56. Howe designs . ParticiParticipants of the expert simulation group were assessed after completion of the assessments of patients with ADHD and healthy individuals. At the beginning of the assessment, descriptive information was obtained and it was ensured that none of the participants was familiar with the EFT or its principles. Subsequently, participants were presented with the vignette and were requested to feign ADHD and to perform the EFT as if they suffered from ADHD (similar to instructions as presented to the NSG).2. The index η2 provides information about the proportion of variance which is accounted for by the factor group membership. As described by Cohen [2 is a function of the effect size index f. According to Cohen [2 = .0099, a medium effect size (f = .25) to an η2 = .0588 and a large effect size (f = .40) to an η2 = .1379. The effect size Cohen’s d was computed for pairwise comparisons between simulation groups and the first sample of patients with ADHD. According to Cohen [Neuropsychological test performance (routine measures of cognition) of the first sample (n = 51) of patients with ADHD was analyzed using descriptive statistics. A neuropsychological impairment was determined on the basis of a commonly accepted categorization of ability levels using test norms (percentile ≤ 10) . EFT perby Cohen , η2 is ato Cohen , a smallto Cohen . Rogers to Cohen , therefoexpert simulation group was also analyzed by means of descriptive statistics. EFT performance was interpreted based on the cutoff as derived from the present study.Test performance of the independent sample of patients with ADHD (n = 11) was analyzed using descriptive statistics. Test scores of the TOMM, DCT, and EFT were presented, together with cutoffs for noncredible performance as suggested in the test manuals and as derived from the present study. Test performance of the 2 = .093. However, MANOVA comparing patients with ADHD (first sample) with the CG and simulation groups  revealed a significant and large effect, Wilk’s lambda = 0.508, F = 7.13, p < .001, η2 = .156  = 7.06, p < .001, η2 = .083, Block 1, Errors, F = 32.87, p < .001, η2 = .295, Block 2, RT, F = 8.28, p < .001, η2 = .095, Block 2, Errors, F = 20.15, p < .001, η2 = .204, Block 3, RT, F = 5.50, p < .001, η2 = .065, Block 3, Errors, F = 32.48, p < .001, η2 = .293, Block 4, RT, F = 6.64, p < .001, η2 = .078, and Block 4, Errors, F = 22.07, p < .001, η2 = .219. Effect sizes ranged from medium to large size. Post-hoc pairwise comparisons (Tukey’s HSD) revealed that patients with ADHD had significantly slower response times than the CG in all four blocks. A comparison between patients with ADHD and simulation groups found that patients needed significantly more time to respond than the NSG (Block 1 and 2), SSG (Block 2), and TSG (Block 2). Furthermore, patients with ADHD made significantly fewer errors than each group of individuals instructed to feign ADHD in each block. Moreover, individuals in the CG made significantly fewer errors than individuals in each simulation group in each block, and responded significantly faster in Block 3 and 4 than the SSG and TSG (The comparison (MANOVA) of EFT performance between patients with ADHD  and the HCG indicated a non-significant medium difference between groups, Wilk’s lambda = 0.907, F = 1.21, p = .302, η2 = .156 . Univari and TSG . Effect 2  = 140.87, p < .001, explaining 41.7% of the variance (Cox & Snell R2). Logistic regression coefficients  in predicting feigned ADHD (criterion) relative to true ADHD. A significant model was found for the prediction of feigned ADHD  relative to ADHD , χficients  were useficients  denoted ficients . Fig 1 pFurthermore, an additional sample of 11 patients with ADHD was recruited and requested to perform the EFT in addition to two established effort tests, i.e. the TOMM and the DCT . This adexpert simulation group as presented in Finally, EFT performance of the The EFT developed for this study was relatively easy to perform for individuals with ADHD and healthy comparisons, as demonstrated by low error rates in both groups (about 6 errors out of 94 items) and a non-significant difference between groups. This is important to stress considering that a proportion of patients with ADHD were found to be impaired in attention and executive control, as indicated by poor performances in measures of cognition that are routinely applied in clinical neuropsychological evaluation. These cognitive impairments did obviously not affect the performance on the EFT. Furthermore, even though EFT performance of patients with ADHD did not differ significantly from healthy comparisons, an exploration of descriptive statistics revealed that patients tended to have longer response times but made fewer errors compared to the HCG. This might indicate a more pronounced trade-off speed for accuracy of patients with ADHD compared to healthy individuals. An inspection of EFT scores across blocks further revealed that both patients with ADHD and healthy comparisons clearly improved performance over time (Block 3 and 4 compared to Block 1 and 2), indicating the presence of practice effects by repetition of the task with the same stimuli . TransfeGroup comparisons of EFT performance between experimental conditions revealed that individuals instructed to feign ADHD performed significantly worse than control participants, as indicated by the accuracy of responses for all simulation groups as well as by the response time for the TSG. These differences demonstrate that healthy individuals assigned to simulation groups were compliant with instructions and altered their normal behavior. Further evidence for successful group manipulations is given as all participants were able to respond to questions regarding simulation instructions, and also indicated after completion of the study that they had followed instructions. A comparison between simulation groups and patients with ADHD showed significant effects in opposite directions on response time and committed errors, as it was found that all groups of instructed simulators committed consistently more errors compared to patients, but had faster response times in some comparisons . Applying Roger’s  categoriMore importantly with respect to the aim of the present study, it was examined whether the EFT was useful for the prediction of feigned ADHD. Support for the usefulness of the EFT was given by the logistic regression model demonstrating that the EFT could successfully predict feigned ADHD relative to patients with ADHD. The calculation of the EFT index comprised a summation of weighted EFT scores to find the best combination of variables for the prediction of feigned ADHD. This was done by using a collapsed group of all instructed simulators , as it would likely not be known in any assessment context if an individual had been coached, and as a mixed group of individuals with different levels of preparation is assumed to represent most realistically the situation at clinical practice. ROC analysis supported the utility of the EFT index for the identification of individuals feigning ADHD, by yielding high overall accuracy (AUC = 94.8%), as well as sensitivity to feigned ADHD of 88.1%, with a specificity to genuine ADHD of 90.2% (cutoff -0.25). The utility of the EFT index for the identification of feigned ADHD can also be concluded from a visual inspection of the ROC plot depicted in expert simulation group. All participants of the expert simulation group were clinically working psychologists or psychiatrists and experienced in the diagnosis and treatment of adult ADHD. The fact that none of these experts was able to produce a credible score on the EFT that one would expect from someone with genuine ADHD demonstrates the usefulness of the EFT for the clinical setting. On the basis of the present data, it can be concluded that the EFT might be robust to the level of preparation of individuals prior to the assessment, and that the EFT may provide valuable information in the identification of noncredible cognitive performance that might not be obviously visible to the clinician in a standard clinical assessment.Finally, the clinical utility of the EFT as a valid measure of noncredible cognitive performance of individuals during clinical evaluation of ADHD is supported by results from the The EFT index for the identification of feigned ADHD was derived from a sample of patients with ADHD and instructed simulators. Even though sensitivity to detect feigned ADHD was shown on a large sample of individuals that received different levels of coaching, specificity to ADHD was based on one sample of patients only and may therefore require independent replication. A validation of the specificity to genuine ADHD should take different characteristics of patients into account, e.g. comorbidity, medication status, or patients from a specific environment such as college students. A recent study by Williamson and colleagues  examinedknown-groups comparisons, should be used in order to validate the present findings. To assure realistic conditions for simulating ADHD, instructed simulators in the present study received information one day before the assessment, and were motivated by the incentive of a free tablet PC. Nevertheless, a replication of the present findings on individuals seeking clinical evaluation of ADHD, but who are believed to actually feign symptoms, would strengthen implications on the clinical utility of the EFT.As simulation designs are inherently prone to external validity problems, different research designs, such as Furthermore, the clinical assessment of patients with ADHD in the present study failed to include a validity measure indicating noncredible effort and symptom reporting. Thus, it cannot be excluded that a proportion of the sample of patients with ADHD may have exaggerated or feigned symptoms, which may have confounded the present analyses. In order to control for this limitation, all diagnoses were made on agreement between at least two experienced clinicians. Moreover, the diagnostic assessment included the identification of objective impairments supporting the diagnosis of ADHD and comprised multiple informants whenever possible. However, in case patients actually did exaggerate or feign symptoms in our sample, this would have resulted in a conservative estimation of the diagnostic accuracy of the EFT for feigned ADHD. Actual group differences between genuine patients with ADHD  and instructed simulators would have been even larger than observed, leading to higher classification rates than reported above. Additional evidence on the validity of the present data is given by inspecting test performance of the independent sample of patients with ADHD, in which credible effort was indicated in ten out of eleven cases based on the established effort measures TOMM and DCT. The EFT scores of this sample were comparable to the EFT scores obtained from the original sample of patients with ADHD as shown by a nonsignificant group difference. More importantly, the derived cutoff of the EFT index correctly identified credible performance in ten cases, as well noncredible performance in one case, and thus agrees with the classification of test performances into credible and suspect effort as determined by the established effort tests TOMM and DCT. It can therefore be assumed that even though a performance validity measure has not been included in the assessment of the original sample of patients with ADHD, test results of the original sample have been representative for genuine ADHD and presumably resulted in valid data analysis and conclusions. The inclusion of established effort tests in the assessment of instructed simulators, however, is more complicated as ‘failing’ an effort test cannot be clearly interpreted as low test taking effort in this group, considering that these individuals were instructed to simulate ADHD. Thus we would even expect that participants perform poorly on these tests which implies that low performance is not the consequence of low effort but of a successful simulation strategy. In this case, also, ‘passing’ an established effort test indicates either adequate effort, or otherwise low effort in assuming the role of a person with ADHD and in trying to simulate.Finally, a concern about many stand-alone effort tests is that they have high face validity as they often present with a distinct character in comparison to classic tests for the assessment of cognitive functions. These effort tests may therefore be easily detected by sophisticated malingerers at clinical evaluation, especially by malingerers who have reviewed adequate information about current effort tests used in clinical practice. The EFT as presented in this study, however, may appear like a classic test for the assessment of selective attention and/or response inhibition, and may therefore be less easily recognized as an effort test by individuals attempting to feign ADHD. Low face validity of the EFT may increase diagnostic sensitivity to feigned ADHD, and may thus support its usefulness for the assessment of adequate test-taking effort. However, face validity of the EFT cannot be explored with the present data, as participants were not asked to identify which tests in the assessment were designed to detect feigning. Furthermore, it is also relevant to explore reliability of the EFT, as it is currently unknown if effort tests such as the EFT are still successful in detecting feigned cognitive dysfunction when applied twice on the same individuals. These issues are to be addressed in future studies when applying the EFT among other tests in a comprehensive and repeated neuropsychological assessment.


Executive function deficits have been previously documented in individuals withAttention Deficit Hyperactivity Disorder (ADHD).The current study aimed to compare measures of executive functions among aclinical sample of adults with ADHD and normal control subjects, matched forage, gender and education.Twenty-three self-referred adults diagnosed with ADHD according to DSM-IVcriteria, and twenty-five control subjects were assessed using aneuropsychological battery which included the Wisconsin Card Sorting Test,Tower of Hanoi, Digit Span, Trail Making Test (A and B), Stroop Test andRaven’s Progressive Matrices.The ADHD group did not differ significantly from the control subjects on anyof the measures assessed.Measures of executive functions using this test battery were unable todiscriminate between adults with ADHD and control subjects in this clinicalsample. Recently,Biederman et al.6 showed thatself-reported questionnaires developed to evaluate EF deficits had better ecologicalvalidity than neuropsychological EF tests.A meta-analysis study comparing neuropsychological executive and non-executivefunctioning between adults with ADHD and normal controls found that neuropsychologicaldifficulties in the former group might be present in both executive and non-executivedomains.7Studies investigating neuropsychological aspects of ADHD in adults are scarce in Brazil,where most research has sought to evaluate neuropsychological aspects of ADHD inchildren and adolescents. However, some groups have been attempting to evaluate ADHDadults with new tasks adapted for use in Brazil.The purpose of our study was to compare measures of EFs among a clinical sample of adultswith ADHD versus normal control subjects, matched for age, gender and education. Basedon the literature review, we hypothesized that ADHD subjects would perform worse on theexecutive measures in comparison to controls.Eighty-nine self-referred adults aged 18 to 59 years enrolled for treatment at theAttention-Deficit Study Group (GEDA) at the Institute of Psychiatry of the FederalUniversity of Rio de Janeiro and underwent a comprehensive clinical assessment thatincluded:8A) a modified childhood module for ADHD from the Kiddie SADS-E adaptedfor adults, in Portuguese;B) a psychiatric evaluation by a board-certified adult psychiatrist,including medical history and9C) comorbid axis I disorders, assessed using the Mini InternationalNeuropsychiatric Interview (MINI).Past ADHD symptoms were investigated using the patients’ own recollections of achronic course of ADHD symptoms (according to DSM-IV criteria).The control group was recruited from a non-clinical population and comprisedindividuals who were invited to take part as volunteers. Some were undergraduatesand others were volunteers from the local community. Each participant was includedafter being screened for any alcohol and/or drug abuse/dependence or any obvioussymptoms of ADHD or depression.10 to evaluate visual-motor dexterityand conceptual flexibility; the Stroop Test11 as a control inhibition measure; Wisconsin Card SortingTest (WCST)12 to test hypothesesand conceptual flexibility; Tower of Hanoi13 to evaluate planning and solving capacity, and RavenProgressive Matrices14 as ameasure of fluid intelligence. ADHD individuals only started pharmacologicaltreatment after completing the tests. None of them were in use of psychostimulantsor other pharmacological treatment for ADHD at the time of the neuropsychologicalevaluation.All individuals were submitted to the following tests: Digit Span, both forward andbackward as a working memory (WM) measure; Trail Making Tests A and BThe study was approved by the institutional review board, and all subjects signed awritten informed consent term before inclusion in the study.Comparison between neuropsychological test scores for the ADHD group and controlgroup was performed using nonparametric analysis and the Mann-Whitney U test.Pearson’s Chi-Square test was employed for the gender variable, and theMann-Whitney U test was applied for age and number of years in formalschooling.Of 89 self-referred adults interviewed consecutively, 53 met the DSM-IV criteria forADHD. Out of these 53 positively diagnosed adults, those with comorbid majordepression and/or any drug or alcohol abuse or dependency, and/or who declared theywere regular users of psychoactive substances were excluded (30 patients).Forty-eight adults took part in the neuropsychological assessment. Twenty-threecomprised the ADHD group whereas 25 were normal controls. The ADHD group comprised 8male (34.8%) and 15 female subjects (65.2%). Their ages ranged from 18 to 59 years,with a mean age of 31.87 years and a standard deviation of 10.55 years. Formalschooling ranged from 5 to 21 years, with a mean of 14.13 years and a standarddeviation of 3.15 years. The control group comprised 9 men (36%) and 16 women (64%)aged between 22 and 48 years (mean: 33.24 years and standard deviation: 8.21 years).Formal schooling ranged between 7 and 21 years, with a mean of 13.36 years and astandard deviation of 3.64 years .p>0.05) for gender, age, or formal schooling. Results areshown in No statistically significant differences were found between the groups(p>0.05). We found no differences between ADHD and control groups in neuropsychological testsresults compared using nonparametric analysis (U-test). No statistically significantdifference was found for any of the neuropsychological variables the test battery employed was not sensitive in differentiatingpatients from controls orB) the magnitude of the difference between patients and controls wassmall and may only be demonstrated by a much larger sample orC) our sample was biased in toward a group of individuals withoutsignificative functional impairment.15 McGough and Barkley16 suggested that studies using neuropsychological tests ofEFs have not yet demonstrated sufficient positive or negative predictive power toallow their recommendation for clinical use in children or adults. Also, ameta-analysis study5 has shown thatEF deficits are not necessary nor sufficient to predict all cases of ADHD, whichmight suggest that negative results are to be expected in some situations. Recently,Biederman et al.17 demonstratedthat impaired performances on EFs tasks in ADHD individuals were more stronglylinked to lower IQ levels than to impairment in everyday activities that depend onEFs, which were shown to be better predicted by self-reported questionnaires devisedto assess EF deficits.Some authors have suggested that the lack of differences found in studies that haveused classic tests of EFs should be expected since such measures were not developedspecifically to evaluate persons with ADHD.6 have shown thatneuropsychological measures aimed to evaluate EFs were more prone to record deficitsassociated to low IQ, whereas self-report questionnaires that evaluate EF deficitswere better suited for functional impairments due to dysexecutive syndrome.It is likely that the participants of the present study represent a high-performanceADHD group in view of their length of schooling  together with the absence ofcomorbidity with depression and the use of substances. Also, Biederman etal.Interpretations of the present results must take into consideration the small samplesize and the consequent low statistical power. Also, a clinical self-referred sampledoes not necessarily mirror aspects that might be found in non-clinical samples. Thehigher prevalence of female patients must also be taken into account wheninterpreting the results. Moreover, we did not exclude some important axis-Icomorbid conditions that could have influenced test performance, such as GeneralizedAnxiety Disorder or Eating Disorders. Also, our test battery did not include sometests demonstrated to be more sensitive and/or ecological, such as Conners’Continuous Performance Test, the Iowa Gambling Test or even self-reportedquestionnaires for EFs. Future studies using ecological tests and self-reportedquestionnaires for EF deficits should be performed in order to broaden the currentinvestigation and bring new contributions to the theoretical knowledge and clinicalmanagement of executive dysfunctions in ADHD.18Our findings suggest that the neuropsychological battery employed was unable todiscriminate between adults with ADHD and controls. These results might be relatedto low sensitivity of the neuropsychological tests or a small magnitude ofdifference detectable only in much larger samples. An alternative explanation isthat our sample was comprised of ADHD persons with a high performance level, whichmay have minimized differences between groups. This explanation is supported byother studies that have previously suggested that ADHD subjects with above-averageIQs may not differ significantly from normal comparison subjects in terms ofEFs.


Several longitudinal studies have shown the partial symptomatic persistence of attention-deficit hyperactivity disorder (ADHD) in clinic-based samples. However, little is known about the patterns and trajectories of ADHD symptoms in community-based populations.To differentiate developmental trajectories of ADHD symptoms over 1 year, with a four-wave quarterly follow-up in children and adolescents in the community of Taiwan, we conducted this prospective study in 1281 students in grade 3, 5, and 8. All the students in the regular classes rather than special educational classes were eligible and recruited to the study. Inattention, hyperactivity–impulsivity, and opposition-defiance were rated by parent reports on the Chinese version of the Swanson, Nolan, and Pelham Version IV Scale (SNAP-IV). Group-based trajectory modeling and multivariable regression analyses were used to explore the individual, family and social factors associated with differential trajectories.Trajectories were classified as Low (29.9–40.6%), Intermediate (52.5–58.5%) and High (6.9–12.5%) based on the symptom severity of ADHD symptoms assessed by the SNAP-IV. The proportion of children in the high ADHD trajectory might approximately reflect the prevalence of ADHD in Taiwan. The following factors differentiated High from Low trajectories: male gender, more externalizing problems, fewer prosocial behaviors, school dysfunction, more home behavioral problems, and less perceived family support.Our findings that the concurrent conditions of emotional or externalizing problems, as well as impaired school and home function at baseline, might differentiate the high ADHD symptoms trajectory from others could help developing the specific measures for managing high ADHD symptoms over time in a school setting.The online version of this article (doi:10.1186/s13034-017-0165-4) contains supplementary material, which is available to authorized users. Attention-deficit/hyperactivity disorder (ADHD), characterized by developmentally inappropriate symptoms of inattention, hyperactivity, and impulsivity, is a common childhood-onset neurodevelopmental disorder, with a worldwide-pooled prevalence of 5.29%  and 7.5%Characterizing the persistence of ADHD symptoms is methodologically challenging, partly owing to the complexity in acquiring prospective longitudinal data, provided by a limited number of studies –10, seveInvestigating the trajectories of ADHD symptoms and their influencing factors may provide insight for the guidance and customization of optimal interventions across developmental stages. However, only a few studies have explored different trajectories of ADHD symptoms and identified associated factors in community samples of children and adolescents. The numbers and trends of trajectories found across studies were inconsistent. For example, Nagin and Tremblay found four levels of trajectory , in which less than 6% of 1037 boys aged 6–15 years in low socioeconomic areas of Canada were classified as being chronic high trajectory. Who started off scoring high continued to score high throughout the observation period in the hyperactive externalizing behavior section evaluated by the Social Behavior Questionnaire . In a biGiven that most ADHD studies focused on clinical rather than non-clinical samples, community-based studies using the trajectory analyses revealed inconsistent results about the patterns and predictors of trajectory. Also, very limited studies have examined the trajectory of OD symptoms. We did not know how these symptoms would change from time to time in a community sample nor did we know its associated factors. The objective of this study was thus to trace the distinct 1-year trajectories of IA, HI, and OD symptoms and to identify the associated factors for these trajectories in a large community sample of Taiwanese children and adolescents. Family function, parenting styles, social and school adjustment, and behavioral problems of participants were thoroughly assessed and tested for their associations with the trajectories of ADHD symptoms. Moreover, in light of previous studies demonstrating that the number of trajectories varied across studies using global ratings for ADHD, we expected to identify between two and four trajectories of ADHD symptoms as the majority literature found. We anticipated to identify at least one trajectory lied in high symptom severity for each symptom domain regardless of their pattern . We also hypothesized that those belong to the High trajectory would be associated with higher co-occurring externalizing problems, lower function at school and home, and lower perceived family function comparing to those belong the Low and Intermediate trajectories, for high symptom severity samples who get higher total scores on IA or HI domains might mimic clinical ADHD patients. The second objective was to compare cross-sectional differences in the severity of ADHD and OD symptoms across school grades, given that limited studies had investigated symptomatic differences across developmental periods. Declined IA, HI and OD severity with time was observed in a previous community study, especially in those showed high symptom severity . We inveThis prospective longitudinal questionnaire-based study was conducted using a school-based sample of 1281 students in grade 3, 5, and 8 from Northern Taiwan with a four-wave quarterly follow-up over 1 year of study completion (between February 2013 and January 2014). All the students in the regular classes rather than special educational classes were eligible and recruited to the study. We did not exclude any students with mental disorders in regular classes nor did we include students from special education classes . All the students who completed the informed consent were recruited. There were 638 boys and 615 girls at wave 1 (n = 1253); follow-up rates were 93.1% , 89.6% , and 84.1%  at the second, third, and fourth waves, respectively. The numbers of parents who participated in the first four waves were 1128, 1005 (follow-up rate 89.1%), 941 (83.4%), and 849 (75.3%), respectively. The numbers of parents who participated in the first, second, third and fourth waves were 1128, 1005 (follow-up rate 89.1%), 941 (83.4%), and 849 (75.3%), respectively. A portion of the data has been analyzed and published elsewhere . Third- SNAP-IV is a 26-item rating instrument which includes the core DSM-IV-derived ADHD subscales of IA, HI, and OD  . Each itThe SDQ, a 25-item behavioral screening questionnaire, is a brief behavioral screening questionnaire designed to assess the broader psychological problems experienced by children and adolescents. Each behavioral item is rated on a 3-point Likert scale  . It has The family APGAR, which consists of five parameters of family functioning: adaptability, partnership, growth, affection, and resolve, is used to assess perceived family support by examining his/her satisfaction with family relationships. Each parameter is assessed by reported satisfaction on a 3-point scale ranging from 0 (hardly ever) to 2 , with higher scores indicating a better satisfaction and a more highly functional family . The ChiThe SAICA, a 77-item semi-structured interview scale, provides an evaluation of children’s social adjustment functioning in school, in spare time activities, and with peers, siblings, and parents. It can be administered to school-aged children (aged 6–18) (self-report), or to their parents (who respond regarding their children). A higher mean score indicates either poorer social function or more severe social problems . The ChiThis study was approved by the Research Ethics Committee of the National Taiwan University Hospital (IRB number: 201212010RINC). Informed consent was obtained from all the participants and their parents after the researcher had explained the study purpose, procedures and assured the confidentiality of this study. The participants were collected in a convenience sample of primary and junior high students according to the positive response and cooperation of their school principals. The parents were invited to attend the speech delivered by the corresponding author (SSG) explaining the purpose and procedure of this study. The parents received the informed consent in paper format from their children. Parents who agreed to participate were asked to complete the questionnaire at home and return it in a sealed envelope within 1 week. The students then completed the questionnaires during class under the supervision of research assistants and their teachers. We collected data from participating students and their parents (75% from the mother) in four waves of surveys quarterly within 1 year. The student participants reported on the Chinese SDQ at the first wave. The parents reported on the Chinese versions of the family APGAR, and SAICA about the student participants at the first wave and the Chinese SNAP-IV about the student participants for all four waves of evaluations.Results are displayed as demographics (frequency and percentage), and as mean and standard deviation (SD) for continuous variables, including the SNAP-IV subscales, SDQ, SAICA, and family APGAR. To address missing data, we conducted the Expected-Maximization algorithm to impute missing variables based on gender, grade, and values from all other available waves.Group-based trajectory modeling analyses were conducted using Proc Traj, a SAS procedure for group-based modeling of longitudinal data . PossiblAfter the number of trajectories had been chosen, subgroup analyzes of group-based trajectory modeling analyses were conducted for each school grade. Multinomial logistic regression analyses carried out with trajectories as outcome and demographics, externalizing and internalizing behaviors, family support, and social and school adjustment as independent variables to identify correlates which could differentiate the trajectories. To further select the independent correlates, we used the stepwise model selection, which tests the addition and deletion of each variable, using p value less than 0.05 as the selection criterion. We used bidirectional elimination approach to conduct the stepwise selection including gender, grade, first wave scores from the SDQ, family APGAR, and family and home function in the SAICA in the initial model.Table Group-based trajectory modeling analyses according to four waves of the SNAP-IV subscales identified three trajectories in each symptom domain, classifying them as Low, Intermediate and High symptomatic severity groups based on their persistence of symptoms over time Fig. a–c. The Figure Subgroup analyzes for each grade showed separated three levels of trajectories  in each symptom domain  of three symptom domains  with various correlates of demographics, emotional and behavioral symptoms, family function, and school and social adjustment. Poor school function and less prosocial behaviors were the most consistent associated factors across the three symptom models that differentiated High to Low trajectories in different grades and could be used as a marker to identify patients at risk of ADHD in a community setting.The proportion of participants classified as a High trajectory in subgroups IA, HI, and OD were 12.5, 6.9, 8.5%, respectively. The majority of participants were in the Low and Intermediate symptom trajectories. The proportion of participants in High symptom severity trajectories (6.9–12.5%) is similar to our previous findings of ADHD prevalence (7.5%) by semi-structured psychiatric interview of randomly selected school samples in Taiwan . On the Students in High symptom trajectories were found to be associated with more severe externalizing behaviors and poorer school and home adjustment comparing to the Low or Intermediate symptom subgroups. This is consistent with a previous community-based study showing more severe externalizing and internalizing symptoms and a lower quality of life in high ADHD symptom trajectories . Having Poor perceived family support was associated with the High trajectory in the IA domain in the current study. Previous studies showed that poor family function increased aggression of ADHD children according to parental reports , and famRegarding the Intermediate and Low groups of the three symptom domains, our results showed globally flat trajectories of symptom severity. Generally suggesting a stable course and severity over time. However, not all High trajectories declined over time. Our results above contradict to the findings of previous studies of clinical patients with ADHD, which showed a persistent reduction in HI symptoms , 45 but Our study had several strengths. First, the large sample size decreased the possibility of type II errors. Second, the longitudinal study design made it possible to observe trends in different trajectories and compare baseline functions and problems at home and school in order to differentiate trajectories. Third, our behavioral measures were rated by both students and their parents. Multiple informants may have provided more diverse and ecologically valid evaluations of participants’ behaviors and functions.This study was not without limitations. First, the total follow-up duration was approximately 1 year, which prevents us from observing clearer trajectory patterns that were achieved in studies with longer follow-up durations. One year is a rather short time interval to understand trajectory patterns for illness. However, this did not preclude us from differentiating three trajectories across three symptom domains. Second, we used first-wave evaluation scores  to separate trajectories. Still, it is unclear whether scores were predictive of severity trajectories or whether impairment was caused by differing ADHD-symptom severity. Therefore, further investigation is needed to determine whether a causal relationship exists. Third, the measurements were made according to the student’s and parent’s reports of several questionnaires rather than teacher’s form. The absence of teacher’s rating may influence the evaluation of adjustment and symptom severity in a school setting. Fourth, considering that we collected data from urban samples in Northern Taiwan, results may not be generalizable to other areas in Taiwan. Lastly, a lack of formal clinical ADHD diagnosis and no records of psychostimulant use but assessment of ADHD symptoms and OD symptoms as evaluated by the SNAP-IV have impeded us from the direct comparisons with earlier studies that examined clinical samples. However, our previous clinical studies have clearly demonstrated that ADHD diagnosis is associated with, more emotional/behavioral problems, less family support and more functional impairment in school and at home –49. HencThree different trajectories  for the IA, HI, and OD symptom domains were identified in a community-based sample. Two trajectory patterns, a quadratic or linear decreasing model, and an intercept-only model were noted and High trajectory in the three domains showed all linear decreasing patterns in grade 8. About 6.9–12.5% children were classified in the High trajectories of ADHD symptoms, which might be the approximate prevalence of ADHD in Taiwan. The High trajectory can be differentiated from others by the following factors: male gender, more externalizing problems, less prosocial behaviors, more severe school dysfunctions, more severe home behavioral problems, and less perceived family support. Among these predictors, poor school function and less prosocial behavior had the most robust influence on different levels of ADHD symptomatology. Our findings could help to develop the specific measures for managing high ADHD symptoms over time in a school setting. These findings extend the literature on ADHD trajectories and may inform future research.


Bartonella. Our objective was to describe three cases of Bartonella quintana endocarditis identified within one year at a large hospital in Washington, DC, USA.Prior studies (predominantly from Europe) have demonstrated blood culture-negative endocarditis due to Bartonella quintana serum immunoglobulin G (IgG) with negative immunoglobulin M (IgM). PCR on DNA extracted from cardiac valves was positive for Bartonella, and DNA sequencing of PCR amplicons identified Bartonella quintana. Patients received treatment with doxycycline/rifampin or doxycycline/gentamicin. We constructed a descriptive case series from a retrospective review of medical records from April to December 2013 at an 800-bed urban hospital. All three patients  were undomiciled/homeless men with a history of alcoholism. Although they had negative blood cultures, echocardiography demonstrated aortic/mitral valve perforation and regurgitation in one patient, aortic/mitral valve vegetation with mitral regurgitation in the second patient, and aortic valve vegetation with regurgitation in the third patient. The patients had positive Bartonella endocarditis as a differential diagnosis in patients who fit elements of the Duke Criteria, as well as having a history of homelessness and alcoholism. Clinicians should consider  Bartonella quintana is a small, fastidious Gram-negative rod that caused trench fever during World War I. The organism can lead to chronic bacteraemia and endocarditis among the homeless and in patients who chronically abuse alcohol (Pediculus humanus) is a known vector for Bartonella  organisms more commonly cause blood culture-negative endocarditis, and they are easily isolated when the bacteria are incubated for at least five days. Hence, ‘true’ blood culture-negative endocarditis is due to other fastidious organisms, notably Coxiella burnetii and Bartonella spp. Six species of Bartonella can cause infective endocarditis in humans: Bartonella quintana, B. henselae, B. elizabethae, B. vinsonii, B. koehlerae and B. alsatica  and enzyme-linked immunosorbent assay (ELISA). Titres of 1 : 1600 (via a microimmunofluorescence test) have a positive predictive value of 0.88 , RNA polymerase beta-subunit-encoding gene (rpoB) and citrate synthase gene (gltA). The 16S rRNA gene has been the focus for most PCR methods because it is one of the most conserved genes  in homeless persons without human immunodeficiency virus (HIV) infection had been reported in the USA, specifically in Seattle, WA  titre of >1 : 128 suggested a current or previous infection. PCR testing was performed on DNA extracted from cardiac valve tissue. A portion of the citrate gltA of B. henselae served as a target sequence, and a base substitution in the donor probe sequence was used to achieve greater separation in the melting-curve analysis between B. henselae and B. quintana.  for species identification  approval. Patients were evaluated by the infectious diseases consultation service, and laboratory testing for uintana. . This asB. quintana were identified between April and December 2013 .Due to cardiac valve destruction or incompetence, valve replacement was required for all patients. DNA extracted from cardiac valve tissue was identified by PCR as part of the genus Bartonella are fastidious Gram-negative bacteria that require specific laboratory conditions for laboratory growth and identification. In our case series, we observed a cross-reaction between Bartonella and Chlamydophilia in one patient. Identification of Bartonella species with serology was unreliable in our patients, as B. henselae IgG titres were higher than B. quintana titres in two patients, and equivalent in one patient. All of our patients had detectable Bartonella DNA from cardiac valve tissue, and even though PCR of valve tissue reportedly has 100 % specificity, the sensitivity of this test can be compromised with prior antibiotic use . Papers by both Fournier et al and Beitkopt et al  have developed an algorithm that suggests a diagnostic strategy for evaluating blood culture-negative endocarditis and recommends serological testing for BartonellaBartonella endocarditis may be an under-recognized cause of blood culture-negative endocarditis in the USA. Our improved knowledge of the spectrum of pathogens involved in blood culture-negative endocarditis should also advance our empiric antibiotic therapy selections.In summary, although much of the existing literature regarding


N = 86), ADHD + ODD versus controls (N = 86), and ADHD + ODD versus ADHD-only (N = 90). Adverse life events and parental ADHD were risk factors for both ADHD + ODD and ADHD-only, and more adverse life events were an even stronger risk factor for comorbid ODD compared with ADHD-only. For ADHD + ODD, but not ADHD-only, parental criticism, deviant peer affiliation, and parental SES acted as risk factors. Maternal smoking during pregnancy acted as minor risk factor for ADHD-only, while higher birth weight acted as minor risk factor for ADHD + ODD. No effects of age were present. Findings emphasise the importance of these factors in the development of comorbid ODD. The identified risk factors may prove to be essential in preventive interventions for comorbid ODD in ADHD, highlighting the need for parent-focused interventions to take these factors into account.Oppositional defiant disorder (ODD) is highly prevalent in attention-deficit/hyperactivity disorder (ADHD). Individuals with both ADHD and ODD (ADHD + ODD) show a considerably worse prognosis compared with individuals with either ADHD or ODD. Therefore, identification of risk factors for ADHD + ODD is essential and may contribute to the development of (early) preventive interventions. Participants were matched for age, gender, and ADHD-subtype (diagnostic groups), and did not differ in IQ. Predictors included pre- and perinatal risk factors , transgenerational factors , and postnatal risk factors . Three models were assessed, investigating risk factors for ADHD-only versus controls (The online version of this article (doi:10.1007/s00787-017-0972-4) contains supplementary material, which is available to authorized users. Attention-deficit/hyperactivity disorder (ADHD) is a common childhood psychiatric disorder that is defined by developmentally inappropriate levels of inattention, and/or hyperactivity and impulsivity . PreviouA condition which is frequently comorbid with ADHD is oppositional defiant disorder (ODD), occurring in up to 60% of individuals with ADHD , 21. ODDCompared with ADHD, relatively few studies have investigated risk factors for comorbid ODD in ADHD. Reported risk factors for ODD, which are arguably also implicated in the development of comorbid ODD, include both risk factors overlapping with those reported for ADHD and risk factors specific for ODD. Overlapping risk factors for ODD and ADHD encompass maternal smoking during pregnancy, a family history of ADHD or ODD, and higher levels of family conflict , 36, 39.The aim of the current study was to investigate potential risk factors for the development of comorbid ODD in individuals with ADHD (ADHD + ODD), and to identify whether risk factors differed for individuals with ADHD-only and individuals with ADHD + ODD. To this end, we assessed pre- and perinatal risk factors , transgenerational influences , and postnatal risk factors  in three groups: ADHD + ODD, ADHD-only, and typically developing controls. All groups were matched for age and gender, and the diagnostic groups were additionally matched for IQ and ADHD-subtype. We hypothesised that for both ADHD + ODD and ADHD-only (compared with controls), pre- and perinatal adversities and negative transgenerational influences would be risk factors , 33. In N = 246) were equally divided over three groups: (1) participants with ADHD + ODD (n = 82), (2) participants with ADHD-only (n = 82), and (3) typically developing controls (n = 82). Groups were carefully matched on age (≤1 year) and gender, and the diagnostic groups were additionally matched on IQ  and ADHD-subtype. Mean age of the participants was 16 years (SD 3.1), and each group consisted of 55 boys and 27 girls. See Table Participants  and Conners ADHD questionnaires from multiple informants. For each individual the K-SADS interview was completed by the parent(s), and for individuals aged 12 and older the K-SADS interview was also completed by the participant. Furthermore, each individual was assessed with a teacher-rating  on either one of the Conners questionnaires [T ≥ 63 on the DSM Oppositional behaviour scale of the CTRS-R:L.For ADHD, a diagnostic algorithm was applied to combine symptom counts on the K-SADS and CTRS-R:L (for participants <18 years) or CAARS-S:L (for participants ≥18), both providing operational definitions of ADHD defined by the DSM-IV . Particionnaires . LikewisPre- and perinatal risk factors were assessed using a parent-reported questionnaire and included pregnancy duration (weeks) and birth weight (grams). Furthermore, maternal smoking during pregnancy was assessed per trimester and dosage. In the control group, 10 mothers smoked during pregnancy: 2 mothers smoked 11–15 cigarettes per day, 2 mothers smoked 6–10 cigarettes per day, 6 mothers smoked 1–5 cigarettes per day. In the ADHD-only group, 14 mothers smoked during pregnancy: 6 mothers smoked 6–10 cigarettes per day, 8 mothers smoked 1–5 cigarettes per day. Finally, in the ADHD + ODD group, 9 mothers smoked during pregnancy: 2 mothers smoked 11–15 cigarettes per day, 2 mothers smoked 6–10 cigarettes per day, 5 mothers smoked 1–5 cigarettes per day. Given that the number of smoking mothers and the range in dosage was very low together with our findings that our regression models substantially improved when using a dichotomous (yes/no) measure of smoking, rather than a trimester or dosage-related measure, we decided to include the dichotomous measure. Hence, maternal smoking during pregnancy was scored as a ‘yes’ when the mother smoked during at least one trimester.Parents were assessed for ADHD, using a similar combination of a semi-structured interview (K-SADS) and an Observer-Rated Symptom questionnaire (Conners) to the one used for the participants. Parental ADHD was scored present if one or both of the parents had a childhood or current diagnosis of ADHD, otherwise it was scored absent.Parents completed the Long-Term Difficulties questionnaire [developed by TRAILS: Socioeconomic status (SES) was assessed using the highest successfully completed educational level of the parents as reported on a Self-Report questionnaire (averaged over both parents). Because in the Netherlands many different trajectories can lead to higher education, it is possible that individuals with a similar amount of educational years differ in their level of education  . TherefoDeviant peer affiliation was measured using the Friends Inventory, in which participants were asked about the characteristics of their peers  . This quExpressed emotions (EE) was assessed during the diagnostic interview (PACS) of the IMAGE-study, which was performed 6 years previous to the current study , using tThe current study was part of a comprehensive assessment protocol encompassing phenotypic, neurocognitive, and magnetic resonance imaging assessments . Data onN = 86 participants for the analyses for controls versus ADHD-only and for the analyses for controls versus ADHD + ODD, while for ADHD-only versus ADHD + ODD the final sample size was N = 90.All dependent variables were normally distributed and did not contain outliers (defined as a score of >3 SD from the mean score). Groups were compared on demographic and ADHD-related variables using analysis of variance (ANOVA) or Chi-square tests. For pre- and perinatal risk factors, data were available for 57–81% of the subjects. For other risk factors, there were some missing data , which were mainly due to not assessed questionnaires, logistic problems or incompletely filled out questionnaire, and were randomly distributed over the groups. The assessed analysis  does not allow missing data on the predictors; therefore, cases with missing values were omitted from the analysis. Since LASSO can be applied even in models with the number of predictors exceeding the number of participants, the smaller sample size poses no problem in the current study where the number of participants still substantially exceeds the number of predictors. Final sample size was Due to the amount of missing data, we investigated whether the resulting subsamples differed from the initial matched samples. Results of these comparisons showed that the subsamples were still matched for age, gender, IQ, and ADHD-type (for diagnostic groups), and showed similar group comparison results in terms of ADHD symptom and ODD symptom levels, as shown in Table glmnet-package [2 were investigated. Finally, to control for the possible impact of family relations, due to the inclusion of siblings, we performed sensitivity analysis excluding the siblings .For the predictive value analysis of the complete set of risk factors, least absolute shrinkage and selection operator (LASSO) penalised logistic regression in R was used, using the -package . The LAS-package , 52. Tha-package . Post hoThe analyses comprised three models to identify the risk factors for comorbid ODD in ADHD. First, two separate models were assessed to investigate risk factors for ADHD-only compared with controls (model 1) and risk factors for ADHD + ODD compared with controls (model 2). Subsequently, the model for the ADHD + ODD group versus the ADHD-only group (model 3) was assessed. Significance of a risk factor was assumed if the LASSO model included that factor. Finally, for each of the three models, the sensitivity (percentage correctly identified cases) and specificity (percentage correctly identified non-cases) were calculated.As shown in Table 2 or age3 (p > .105), indicating that the effects of the predictors on diagnostic status were independent of the age of the participants.Results for all three models are shown in Table r = .42. After LASSO selection, the model showed a total explained deviance of 55.2% , while for the comorbid ODD model the explained deviance increased slightly (to 17.6%). All models included the same predictors with the same direction of associations.The aim of the current study was to investigate risk factors for the development of comorbid ODD along with ADHD. Therefore, we assessed pre- and perinatal factors, transgenerational influences and postnatal factors. We hypothesised that pre- and perinatal adversities and negative transgenerational influences would act as risk factors for both ADHD and ADHD + ODD, and postnatal adversities to act primarily as risk factors for ADHD + ODD compared with ADHD-only , 23, 33.higher (not lower) birth weight acted as a relatively minor risk factor for ADHD + ODD, relative to controls. This supports the notion that there may be an optimum birth weight in terms of the development of behavioural problems such as ADHD, as previously suggested in other studies [Our first hypothesis that negative transgenerational influences and pre- and perinatal adversities would act as risk factors for the diagnostic groups was supported by our findings, since we found that parental ADHD acted as a relatively major risk factor within our models, showing the highest explained deviance for both diagnostic groups relative to the control group. This is in line with the many studies showing significant heritability rates for ADHD , 22, and studies , 25, 54. studies , which mWe also found support for our second hypothesis of postnatal adversities acting as risk factors for ADHD + ODD rather than for ADHD-only. For both ADHD-only and ADHD + ODD, adverse life events, which included parental divorce and family conflicts, acted as a risk factor. However, adverse life events acted as a stronger risk factor for ADHD + ODD than for ADHD-only, as stressed by its differentiating ability between the ADHD + ODD and ADHD-only groups. The mechanism by which adverse life events may affect ODD is still unclear, and may vary between types of event; potential explanations include (a) negative effects on maturation of cerebral brain structures in the child due to stress, (b) teaching individuals to use antisocial strategies to cope with stressful situations, and (c) causing an overactive sympathetic nervous system , 29. AllOur third hypothesis, that transgenerational influences in addition to the postnatal factors would differentiate between ADHD + ODD and ADHD-only, was largely supported by our results. Parental criticism acted as a relatively strong risk factor for ADHD + ODD compared with ADHD-only, within our model. This is in line with previous studies and is presumably due to its negative influence on the child’s socialisation process , 23, 37.Even though our study has some important strengths, there are some limitations too. First, we assessed pregnancy duration, birth weight and maternal smoking during pregnancy using a retrospective parent questionnaire. Especially for maternal smoking during pregnancy, the self-report nature of our assessment may have confounded our data, due to socially acceptable answering . HoweverOverall, our study showed that postnatal risk factors (adverse life events) and transgenerational influences  are important risk factors for the development of ADHD + ODD and ADHD-only. The development of comorbid ODD in individuals with ADHD was predicted by both postnatal adversities  and negative transgenerational influences . These risk factors were significant for all ages. Our findings are in line with theories stating that environmental factors play an important role in the development of comorbidities such as ODD in individuals with ADHD , 23, 50.Supplementary material 1 (DOCX 16 kb)Below is the link to the electronic supplementary material.