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Article Contents

Conceptual framework, evolving definitions of adhd, what are the academic and educational characteristics of children with adhd, are academic and educational problems transient or persistent, what are the academic characteristics of children with symptoms of adhd but without formal diagnoses, how do treatments affect academic and educational outcomes, how should we design future research to determine which treatments improve academic and educational outcomes of children with adhd.

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Academic and Educational Outcomes of Children With ADHD

ADHD Special Issue, reprinted by permission from Ambulatory Pediatrics, Vol. 7, Number 2 (Supplement), Jan./Feb. 2007,

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Irene M. Loe, Heidi M. Feldman, Academic and Educational Outcomes of Children With ADHD, Journal of Pediatric Psychology , Volume 32, Issue 6, July 2007, Pages 643–654, https://doi.org/10.1093/jpepsy/jsl054

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Attention-deficit/hyperactivity disorder (ADHD) is associated with poor grades, poor reading and math standardized test scores, and increased grade retention. ADHD is also associated with increased use of school-based services, increased rates of detention and expulsion, and ultimately with relatively low rates of high school graduation and postsecondary education. Children in community samples who show symptoms of inattention, hyperactivity, and impulsivity with or without formal diagnoses of ADHD also show poor academic and educational outcomes. Pharmacologic treatment and behavior management are associated with reduction of the core symptoms of ADHD and increased academic productivity, but not with improved standardized test scores or ultimate educational attainment. Future research must use conceptually based outcome measures in prospective, longitudinal, and community-based studies to determine which pharmacologic, behavioral, and educational interventions can improve academic and educational outcomes of children with ADHD.

Problems in school are a key feature of attention-deficit/hyperactivity disorder (ADHD), often bringing the child with ADHD to clinical attention. It is important to establish the nature, severity, and persistence of these school difficulties in children with ADHD. It is also critical to learn how various treatments affect academic and educational outcomes. These findings inform clinical practice, public health, public education, and public policy. This review of academic and educational outcomes of ADHD is organized around 5 questions: (1) What are the academic and educational characteristics of children with ADHD? (2) Are academic and educational problems transient or persistent? (3) What are the academic characteristics of children with symptoms of ADHD but without formal diagnoses? (4) How do treatments affect academic and educational outcomes? (5) How should we design future research to determine which treatments improve academic and educational outcomes of children with ADHD?

We used the International Classification of Functioning, Disability, and Health (ICF) 1 as the conceptual framework for describing the functional problems associated with ADHD. The World Health Organization developed the ICF to provide a systematic and comprehensive framework and common language for describing and assessing functional implications of health conditions, regardless of the specific disease or disorder. Use of this model facilitates comparisons of health-related states across conditions, studies, interventions, populations, and countries.

In the underlying ICF conceptual framework, health conditions impact function at 3 mutually interacting levels of analysis ( Figure 1 ): body functions and structures, activities of daily living, and social participation. Problems of body functions and structures are called impairments , a more specific and narrow meaning for the term than that used in DSM-IV. 2 Problems of activities of daily living are called limitations . Problems of social participation are called restrictions. Environmental and personal factors can also affect functioning. Treatments may address the health condition directly, may be aimed at one or more domains within the levels of functioning, or may be designed to change the environment. Because of the bidirectional influences within and among these levels of analysis, treatments directed at one problem may indirectly improve problems at other levels.

Conceptual model of International Classification of Functioning, Disability, and Health.

Figure 2 applies the ICF model to school functioning in children with ADHD using the specific codes and terminology of the classification system. At the level of body functions, ADHD affects several global and specific mental functions: intellectual function; impulse control; sustaining and shifting attention; memory; control of psychomotor functions; emotion regulation; higher level cognition, including organization, time management, cognitive flexibility, insight, judgment, and problem solving; and sequencing complex movements. At the level of activities, ADHD may result in limitations in at least 2 domains relevant to this review (and other domains addressed by other chapters in this volume): (1) learning and applying knowledge, including reading, writing, and calculation; and (2) general tasks and demands, including completing single or multiple tasks, handling one's own behavior, and managing stress and frustration. Here, we will differentiate between academic underachievement , which will refer to problems in learning and applying knowledge, including earning poor grades and low standardized test scores, and academic performance , which includes completing classwork or homework. At the level of social participation, ADHD can compromise the major life area of education, including creating restrictions in moving in and across educational levels, succeeding in the educational program, and ultimately leaving school to work. Any one of these functional problems may have many contributors, including the health condition and functional problems at other levels of analysis. We will refer to the restrictions in participation as educational problems. Environmental factors relevant to outcomes in ADHD include general and special education services and policies.

Functional problems associated with attention-deficit/hyperactivity disorder using the International Classification of Functioning, Disability, and Health conceptual model.

The clinical criteria for ADHD have evolved over the last 25 years. Studies from the 1980s and 1990s often used different inclusion and exclusion criteria than were used in more recent studies. Some studies carefully differentiate between children with what we now label as ADHD-Combined subtype (ADHD-C) and attention deficit disorder or ADHD-predominantly Inattentive subtype (ADHD-I). We will address briefly the outcomes of the subtypes specifically. Many children with ADHD have comorbid conditions, including anxiety, depression, disruptive behavior disorders, tics, and learning problems. The contributions of these co-occurring problems to the functional outcomes of ADHD have not been well established. Therefore, in this review, we will consider the academic and educational outcomes of ADHD without subdividing the population on the basis of coexisting neurobehavioral problems in affected children.

Children with ADHD show significant academic underachievement, poor academic performance, and educational problems. 3–8 In terms of impairment of body functions, children with ADHD show significant decreases in estimated full-scale IQ compared with controls but score on average within the normal range. 9 In terms of activity limitations, children with ADHD score significantly lower on reading and arithmetic achievement tests than controls. 9 In terms of restrictions in social participation, children with ADHD show increases in repeated grades, use of remedial academic services, and placement in special education classes compared with controls. 9 Children with ADHD are more likely to be expelled, suspended, or repeat a grade compared with controls. 10

Children with ADHD are 4 to 5 times more likely to use special educational services than children without ADHD. 10, 11 Additionally, children with ADHD use more ancillary services, including tutoring, remedial pull-out classes, after-school programs, and special accommodations.

The literature reports conflicting data about whether the academic and educational characteristics of ADHD-I are substantially different from the characteristics of ADHD-C. 12, 13 Some studies have not found different outcomes in terms of academic attainment, use of special services, and rates of high school graduation. 14 However, a large survey of elementary school students found children with ADHD-I were more likely to be rated as below average or failing in school compared with the children with ADHD-C and ADHD–predominantly hyperactive-impulsive subtype. 15 A subset of children with ADHD-I are described as having a sluggish cognitive tempo, leading to the assumption that there is a higher prevalence of learning disorders in the ADHD-I than the ADHD-C populations. One study supporting this claim found more children with ADHD-I than children with ADHD-C in classrooms for children with learning disabilities. 16 Comparative long-term outcome studies of the subtypes in terms of academic and educational outcomes have not been conducted. 17

Longitudinal studies show that the academic underachievement and poor educational outcomes associated with ADHD are persistent. Academic difficulties for children with ADHD begin early in life. Symptoms are commonly reported in children aged 3 to 6 years, 18 and preschool children with ADHD or symptoms of ADHD are more likely to be behind in basic academic readiness skills. 19, 20

Several longitudinal studies follow school-age children with ADHD into adolescence and young adulthood. Initial symptoms of hyperactivity, distractibility, impulsivity, and aggression tend to decrease in severity over time but remain present and increased in comparison to controls. 21 In terms of activity limitations, subjects followed into adolescence fail more grades, achieve lower ratings on all school subjects on their report cards, have lower class rankings, and perform more poorly on standardized academic achievement tests than matched normal controls. 22–26 School histories indicate persistent problems in social participation, including more years to complete high school, lower rates of college attendance, and lower rates of college graduation for subjects than controls. 27–30

The subjects with ADHD in the longitudinal studies generally fall into 1 of 3 main groups as young adults: (1) approximately 25% eventually function comparably to matched normal controls; (2) the majority show continued functional impairment, limitations in learning and applying knowledge, and restricted social participation, particularly poor progress through school; and (3) less than 25% develop significant, severe problems, including psychiatric and/or antisocial disturbance. 31 It is unclear what factors determine the long-term outcomes. Persistent difficulties may be due to ADHD per se or may be due to a combination of ADHD and coexisting conditions, including learning, internalizing, and disruptive behavior disorders. The contribution of environmental factors to outcomes is also unclear.

Studies of outcome in children diagnosed with ADHD suffer from a potentially serious logical problem: circularity. 32 The clinical definition of ADHD in the DSM-IV requires the presence of functional impairment, typically defined in terms of behavior and performance at home and school. School problems are almost always present to make the diagnosis and therefore are more likely to be present at follow-up. Another problem in the use of clinic-referred samples is the selection bias in who gets referred to diagnostic clinics. One research strategy to complement the longitudinal studies of clinic-referred samples and avoid these problems is to evaluate children from community-based samples who demonstrate symptoms of ADHD but who have not necessarily been formally diagnosed with ADHD. In general, these studies find that children with symptoms of ADHD and without formal diagnoses also have adverse outcomes.

An early community-based study that charted the natural history of ADHD 33 followed subjects who were diagnosed and treated during childhood and children with symptoms and/or behavior indications who were never diagnosed or treated. Both groups were far more likely to attend special education schools and far less likely to graduate from high school or go to college than the asymptomatic controls. The magnitude of the difference was greater for the children with formal diagnosis than for those with pervasive symptoms.

Another community-based study on the relationship between symptoms of ADHD, scores on academic standardized tests, and grade retention found a linear relationship between the number of behavioral symptoms and academic achievement, even among children whose scores were generally below the clinical threshold for the diagnosis of ADHD. 34 Similar findings have been found in studies from Britain 35 and New Zealand. 36 Taken together, these findings suggest that the symptoms and associated features of ADHD are associated with adverse outcomes.

By using the ICF framework, treatments can be evaluated in terms of whether they improve body functions, including intelligence, sustained attention, memory, or executive functions; affect activities, including increasing learning and applying knowledge (such as raising standardized test scores or grades in reading, mathematics, or writing) and improving attending and completing tasks; or enhance participation, including moving across educational levels, succeeding in the educational program, and leaving school for work.

Medical Treatments

Psychopharmacological treatments, particularly with stimulant medications, reduce the core symptoms of ADHD 37 at the level of body functions. In addition, psychopharmacological treatments have been shown to improve children's abilities to handle general tasks and demands; for example, medication has been shown to improve academic productivity as indicated by improvements in the quality of note-taking, scores on quizzes and worksheets, the amount of written-language output, and homework completion. 38 However, stimulants are not associated with normalization of skills in the domain of learning and applying knowledge. 39 For example, stimulant medications have not generally been associated with improvements in reading abilities. 40, 41 In longitudinal studies, subjects demonstrated poor outcomes compared with controls whether or not they received medication. 24 , ,25 ,27 ,42–44 One caution in interpreting these findings is that it cannot be determined if outcomes would have been even worse without treatment because studies often lacked a true nontreatment group with ADHD. Another problem was attrition; subjects lost to follow-up may include those with worse outcomes. A third caution is that most children receive medication for only 2 to 3 years, 45 and it remains unclear whether steady treatment over many years would be associated with improved outcomes.

Behavior Management of ADHD

Behavioral interventions for ADHD, including behavioral parent training, behavioral classroom interventions, positive reinforcement and response cost contingencies, are effective in reducing core ADHD symptoms. 17 , ,30 ,46 However, in head-to-head comparisons behavior management techniques are less effective than psychostimulant medications 37 in reducing core symptoms. It has been shown that behavior management is equivalent or better than medication in improving aspects of functioning, such as parent-child interactions and reduction in oppositional-defiant behavior. However, the problem with this literature is that most behavior management intervention studies evaluate the impact on short-term behavior outcomes, not academic and educational outcomes. The impact of behavioral treatments on long-term academic and educational outcomes must be carefully studied.

Combined Management of ADHD

Given the chronic nature of ADHD and its impact on multiple domains of function, it is likely that multiple treatment approaches are needed. However, the impact of such combined treatments on long-term academic and educational outcomes has not been well studied. Combined treatment (medication and behavioral treatment) in the Multimodal Treatment Study of Children With ADHD was better than behavioral treatment and community care for reading achievement; however, the differences were small and of questionable clinical significance. 37 In addition, children with ADHD and co-occurring anxiety or environmental adversity derived benefit from the combination of medication and behavior management. 47, 48 We need studies to determine whether combined treatment has a larger impact on academic and educational outcomes in some subpopulations than others.

In terms of academic achievement and performance, a 2-year study comparing therapy with methylphenidate to therapy with methylphenidate plus multimodal psychosocial treatments found no advantage of combined treatment over medication alone on any academic measures. 49 The multimodal treatment included academic assistance, organizational skills training, individual psychotherapy, social skills training, and, if needed, reading remediation using phonics. In these studies, medication and/or behavior management, whether used alone or in combination, did not improve academic and educational outcomes of ADHD.

Educational Interventions and Services

The impact of remedial educational services on academic and educational outcomes is not known. Most available treatment outcome studies have not been conducted in general education classroom settings 50 and have focused on reducing problematic behavior rather than on improving scholastic status. 51 Even current rates of utilization are difficult to determine because ADHD itself is not an eligibility criterion for special education. 52 Although advocates pursued making ADHD a category of disability under the Individuals with Disabilities Education Act of 1990 (IDEA), this attempt was not successful. 53 Instead, the US Department of Education issued a policy memorandum 54 stating that students with ADHD were eligible for special education services under the Other Health Impairment category if problems of limited alertness negatively affected academic performance. Children with ADHD may qualify for special education services if they are eligible for another IDEA category, such as emotional disturbance or specific learning disability, but the children with ADHD are not disaggregated from students without ADHD in these categories. 55

Educational services are also provided to students with ADHD who do not meet IDEA eligibility requirements under Section 504 of the Vocational Rehabilitation Act of 1973 if the condition substantially limits a major life activity, such as learning. 53 Services include accommodations and related services in the general education setting, such as preferential seating, modified instructions, reduced classroom and homework assignments, and increased time or environmental modification for test taking. There is wide variability in the knowledge and application of Section 504 services among parents and educators. 53

For both special education and Section 504 services, the children most likely to obtain services are those with the most severe functional limitations. Therefore, it would be difficult to interpret associations among use of services and outcomes. There are no data regarding effectiveness of many commonly recommended accommodations, such as preferential seating, on outcomes.

The evidence that ADHD is associated with poor academic and education outcomes is overwhelming. However, studies thus far find that treatments are associated with relatively narrow improvements in core symptoms of inattention, hyperactivity, and impulsivity at the level of body functions and attending and completing tasks at the level of activities. We need prospective, controlled, and large-scale studies to investigate whether existing or new treatments will improve reading, writing, and mathematics skills; reduce grade retention; reduce expulsions and detentions; improve graduation rates; and increase completion of postsecondary education. In a literate, information-age society, these improved outcomes are vital to the economic and personal well-being of individuals with ADHD.

Because of the limitations of previous research, we recommend that future research incorporate several features. In terms of the subjects, the study must specify clear inclusion criteria, including diagnostic criteria for ADHD, subtypes, and coexisting conditions. Given the research history to date, we favor community- or school-based samples as opposed to clinic-referred samples to avoid selection bias. Studies should be conducted in general education as well as secondary school settings, given the lack of data from these settings. In terms of the outcome variables, we support use of standardized definitions of functional outcomes following the conceptualization of function provided by the ICF framework. We specifically favor repeated measures of academic achievement. Unfortunately, measures such as grades may vary across school systems. For this reason, the use of achievement tests may be preferable in large-scale studies. In addition, measures relevant to educational promotion, such as college entrance examinations, may provide more standardized information than graduation rates. In local or regional studies, other repeated measures may be possible, including analysis of portfolios. Another sensitive measure that could be collected on a continuous basis is curriculum-based measurement, 56 which involves probes of reading and math performance relative to the instructed curriculum and permits examination of relative trajectories over time as a measure of treatment outcome.

Designing convincing studies on the long-term impact of medication or behavior management on academic and educational outcomes is challenging because it is unethical to withhold standard treatments for long periods of time from an affected sample to create a control group. To circumvent this problem, we suggest large-scale studies that evaluate rates of change in the outcomes as a function of treatment strategy (or intensity) and that use statistical methods such as hierarchical linear modeling. 57 In this approach, individual students are nested in hierarchies that are defined by grade and diagnosis and also by treatment type and intensity. Repeated measures for outcomes, such as reading or math standard scores, are collected over time. The statistical methods estimate the effects of each factor—age and treatment intensity—on the rate of change. This method can demonstrate if the rate of change increases more rapidly in some groups than other groups and more rapidly than would have been predicted on the basis of status at study entry. The hierarchical linear modeling method is also helpful with differentiating rates of progress among children who adhere to treatment recommendations over long periods of time versus those who discontinue treatment after a few months or years.

We also recommend that the research strategy incorporate a 2-tiered approach. First, improvements in instruction/teaching methods, curriculum design, school physical designs, and environmental modifications should be offered to all students. We can call this phase improved universal design. Schools often try to change the child with ADHD to fit the school environment. Attempts to “normalize” behavior include pulling a child out of the classroom, perhaps applying a remedial strategy, and then putting the child back into the original setting, with the hope that the child will now be successful. 58 This strategy identifies the child as the problem, serves to isolate and potentially stigmatize the child, and precludes the exploration of environment-based solutions. 59 The advantage of universal design is that most children with ADHD are educated in general education settings. Improved universal design in the classroom could potentially benefit all children in the classroom, particularly those with ADHD. Such interventions may not decrease the differences between children with ADHD and their peers without ADHD on some measures, such as standardized test scores. However, more important is whether the children with ADHD reach a higher threshold of achievement, such as improved reading scores or higher rates of high school graduation.

The second tier for research is specific interventions for children with ADHD, layered on top of the basic reforms. These interventions can include teaching methods, new curricula, specific behavior management, and school-based intervention approaches. 60

We will focus on 6 different options that warrant further investigation in this 2-tiered research design: (1) small class size; (2) reducing distractions; (3) specific academic intervention strategies; (4) increased physical activity; (5) alternative methods of discipline; and (6) systems change.

Small Class Size

A study based in London schools of regular education students found that variations in average class size in the 25- to 35-student range are of little consequence in affecting student progress, probably because of a lack of opportunity for differences in classroom management techniques. 61 However, small classes of approximately 8 to 15 students have been beneficial for younger children and children with special needs. 62 Because children with ADHD are reported to do better with one-on-one instruction, smaller class size makes intuitive sense. Teachers perceive class size to be one of the major barriers to inclusion of ADHD students in regular education. 63 Empiric investigation on reduced class size is therefore warranted for all children, and also for children with ADHD. Small class sizes will probably result in use of innovative educational approaches that are precluded in the current system.

Reducing Distractions

Classrooms are often noisy and distracting environments. Children perform more poorly in noisy situations than do adults, and researchers have reported that the ability to listen in noise is not completely developed until adolescence or adulthood. 64–66 If an acoustic environment can be provided that allows +15 dB signal-to-noise ratio throughout the entire classroom, then all participants can hear well enough to receive the spoken message fully. 64 Accommodations in Section 504 plans often include repeating instructions and providing quiet test-taking areas that are free of distractions. Repetition of instructions alone is not likely to increase the attention of children with ADHD. Thus, methods for reducing noise and other distractions should be studied.

Specific Academic Intervention Strategies

As reviewed by Hoffman and DuPaul, 51 the so-called antecedent-oriented management strategies are good universal design features that hold promise for improving outcomes for children with ADHD. Antecedent interventions include choice making, peer tutoring, and computer-aided instruction, all reviewed below. Such strategies are proactive, support appropriate adaptive behavior, and prevent unwanted, challenging behaviors. These strategies make tasks more stimulating and provide students with opportunities to make choices related to academic work. 67 They may be particularly helpful for children with ADHD who demonstrate avoidance and escape behaviors.

Choice-making strategies allow students to select work from a teacher-developed menu. In a study of choice making with children with emotional and behavioral difficulties in a special education classroom, students demonstrated increased academic engagement and decreased behavior problems. 68 Another study demonstrated decreased disruptive behavior in a general education setting, 69 although more variable academic and behavioral performance occurred in a study of 4 students with ADHD in a general education setting. 51 A related concept is project-based learning, which capitalizes on student interests and provides a dynamic, interactive way to learn.

Studies of Class Wide Peer Tutoring, a widely used form of peer tutoring, have demonstrated enhanced task-related attention and academic accuracy in elementary school students with ADHD, 70, 71 as well as positive changes in behavior and academic performance in students without ADHD. 72 Teachers perceive time requirements of specialized interventions as a significant barrier to the inclusion of ADHD students. 63 Peer tutoring reduces the demands on teachers to provide one-on-one instruction. At the same time, it gives students with ADHD the opportunity to practice and refine academic skills, as well as to enhance peer social interactions, promoting self-esteem. Peer tutoring may be particularly effective when students are using disruptive behavior to gain peer attention. 51

Computer-aided instruction has intuitive appeal as a universal design feature and for children with ADHD because of its interactive format, use of multiple sensory modalities, and ability to provide specific instructional objectives and immediate feedback. Computer-aided instruction has not been well studied in children with ADHD. 51, 73 Studies with small numbers of subjects showed promising initial results 74, 75 but did not examine the effects on academic achievement. A small study of 3 children with ADHD that used a game-format math program found increases in academic achievement and increased task engagement. 76

Increased Physical Activity

Given that fidgeting and out-of-seat behavior are common in children with ADHD, increased use of recess and physical exercise might reduce overactivity. A study on the effects of a traditional recess on the subsequent classroom behavior of children with ADHD showed that levels of inappropriate behavior were consistently higher on days when participants did not have recess, compared with days when they did have recess. 77 A meta-analysis of studies on the effects of regular, noncontingent exercise showed reductions in disruptive behavior with greater effects in participants with hyperactivity. 78 Increased physical exercise would be beneficial for long-term health and for behavioral regulation in both children developing typically and children with ADHD.

Alternative Methods of Discipline

Many students receive suspensions or are sent to the principal's office for disruptive behavior. For those children who are avoiding work, these approaches are equivalent to positive reinforcement. Such avoidant or escape behavior could be countered with in-school as opposed to out-of-school suspensions. The use of interventions that teach children how to replace disruptive behaviors with appropriate behaviors is less punitive than suspensions and more effective in promoting academic productivity and success. 17

Systems Change

Classroom changes are unlikely to create adequate improvements without concomitant changes in the educational system. Three potential areas under the category of systems change are improved education of teachers and educational administrators; enhanced collaborations among family members, school professionals, and health care professionals; and improved tracking of child outcomes. Teacher surveys demonstrate that teachers perceive the need for more training about ADHD. 63 The optimal management of children with ADHD requires close collaboration of their parents, teachers, and health care providers. Currently there is no organized system to support this collaboration.

At the policy level, we need mechanisms to track the outcome of children with ADHD in relation to educational reform and utilization of special services. Federally supported surveys could focus on services and treatments for mental health conditions, including ADHD, and their impact on outcomes. Relevant data for the relationship of interventions and outcomes may also exist at the local and state level. Building on existing local and state databases to include health and mental health statistics could provide valuable information on this issue.

We remain ill informed about how to improve academic and educational outcomes of children with ADHD, despite decades of research on diagnosis, prevalence, and short-term treatment effects. We urge research on this important topic. It may be impossible to conduct long-term randomized, controlled trials with medication or behavior management used as treatment modalities for practical and ethical reasons. However, large-scale studies that use modern statistical methods, such as hierarchical linear modeling, hold promise for teasing apart the impact of various treatments on outcomes. Such methods can take into account the number and types of interventions, duration of treatment, intensity of treatment, and adherence to protocols. Educational interventions for children with ADHD must be studied. We recommend large-scale, prospective studies to evaluate the impact of educational interventions. These studies should be tiered, introducing universal design improvements and specific interventions for ADHD. They must include multiple outcomes, with emphasis on academic skills, high school graduation, and successful completion of postsecondary education. Such studies will be neither cheap nor easy. A broad-based coalition of parents, educators, and health care providers must work together to advocate for an ambitious research agenda and then design, implement, and interpret the resulting research. Changes in local, state, and federal policies might facilitate these efforts by creating meaningful databases and collaborations.

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ADHD and Graduate Writing

What this handout is about.

This handout outlines how ADHD can contribute to hitting the wall in graduate school. It describes common executive function challenges that grad students with ADHD might experience, along with tips, strategies, and resources for navigating the writing demands of grad school with ADHD.

Challenges for graduate students with ADHD

Many graduate students hit the wall (lose focus, productivity, and direction) when they reach the proposal, thesis, or dissertation phase—when they have a lot of unstructured time and when their external accountability system is gone. Previously successful strategies aren’t working for them anymore, and they aren’t making satisfactory progress on their research.

In many ways, hitting the wall is a normal part of the grad school experience, but ADHD, whether diagnosed or undiagnosed, can amplify the challenges of graduate school because success depends heavily on executive functioning. ADHD expert Russell Barkley explains that people with ADHD have difficulty with some dimensions of executive function, including working memory, motivation, planning, and problem solving. For grad students, those difficulties may emerge as these kinds of challenges:

• Being forgetful and having difficulty keeping things organized.
• Not remembering anything they’ve read in the last few hours or the last few minutes.
• Not remembering anything they’ve written or the argument they’ve been developing.
• Finding it hard to determine a research topic because all topics are appealing.
• Easily generating lots of new ideas but having difficulty organizing them.
• Being praised for creativity but struggling with coherence in writing, often not noticing logical leaps in their own writing.
• Having difficulty breaking larger projects into smaller chunks and/or accurately estimating the time required for each task.
• Difficulty imposing structure on large blocks of time and finishing anything without externally set deadlines.
• Spending an inordinate amount of time (like 5 hours) developing the perfect plan for accomplishing tasks (like 3 hours of reading).
• Having trouble switching tasks—working for hours on one thing (like refining one sentence), often with no awareness of time passing.
• Conversely, having trouble focusing on a single task–being easily distracted by external or internal competitors for their attention.
• Being extremely sensitive to or upset by criticism, even when it’s meant to be constructive.
• Struggling with advisor communications, especially when the advisors don’t have a strict structure, e.g., establishing priorities, setting clear timelines, enforcing deadlines, providing timely feedback, etc.

If you experience these challenges in a way that is persistent and problematic, check out our ADHD resources page and consider talking to our ADHD specialists at the Learning Center to talk through how you can regain or maintain focus and productivity.

Strategies for graduate students with ADHD

Writing a thesis or dissertation is a long, complex process. The list below contains a variety of strategies that have been helpful to grad students with ADHD. Experiment with the suggestions below to find what works best for you.

Reading and researching

Screen reading software allows you to see and hear the words simultaneously. You can control the pace of reading to match your focus. If it’s easier to focus while you’re physically active, try using a screen reader so you can listen to journal articles while you take a walk or a run or while you knit or doodle–or whatever movement helps you focus. Find more information about screen readers and everything they can do on the ARS Technology page .

Citation management systems can help you keep your sources organized. Most systems enable you to enter notes, add tags, save pdfs, and search. Some allow you to annotate pdfs, export to other platforms, or collaborate on projects. See the UNC Health Sciences Library comparison of citation managers to learn more about options and support.

Synthesis matrix is a fancy way of saying “spreadsheet,” but it’s a spreadsheet that helps you keep your notes organized. Set the spreadsheet up with a column for the full citations and additional columns for themes, like “research question,” “subjects,” “theoretical perspective,” or anything that you could productively document. The synthesis matrix allows you to look at all of the notes on a single theme across multiple publications, making it easier for you to analyze and synthesize. It saves you the trouble of shuffling through lots of highlighted articles or random pieces of paper with scribbled notes. See these example matrices on Autism , Culturally Responsive Pedagogy , and Translingualism .

Topic selection

Concept maps (also called mind maps) represent information visually through diagrams, flowcharts, timelines, etc. They can help you document ideas and see relationships you might be interested in pursuing. See examples on the Learning Center’s Concept Map handout . Search the internet for “concept-mapping software” or “mind-mapping software” to see your many choices.

Advisor meetings can help you reign in all of the interesting possibilities and focus on a viable, manageable project. Try to narrow the topics down to 3-5 and discuss them with your advisor. Be ready to explain why each interests you and how you would see the project developing. Work with your advisor to set goals and a check-in schedule to help you stay on track. They can also help you sort what needs to be considered now and what’s beyond the scope of the dissertation—tempting though it may be to include everything possible.

Eat the elephant one bite at a time. Break the dissertation project down into bite-sized pieces so you don’t get overwhelmed by the enormity of the whole project. The pieces can be parts of the text (e.g., the introduction) or the process (e.g., brainstorming or formatting tables). Enlist your advisor, other grad students, or anyone you think might help you figure out manageable chunks to work on, discuss reasonable times for completion, and help you set up accountability systems.

Tame perfectionism and separate the processes . Writers with ADHD will often try to perfect a single sentence before moving on to the next one, to the point that it’s debilitating. Start with drafting for ideas, knowing that you’re going to write a lot of sentences that will change later. Allow the ideas to flow, then set aside times to revise for ideas and to polish the prose.

List questions you could answer as a way of brainstorming and organizing information.

Make a slideshow of your key points for each section, chapter, or the entire dissertation. Hit the highlights without getting mired in the details as you draft the big picture.

Give a presentation to an imaginary (or real) audience to help you flesh out your ideas and try to articulate them coherently. The presentation can be planned or spontaneous as a brainstorming strategy. Give your presentation out loud and use dictation software to capture your thoughts.

Use dictation software to transcribe your speech into words on a screen. If your brain moves faster than your fingers can type, or if you constantly backspace over imperfectly written sentences, dictation software can capture the thoughts as they come to you and preserve all of your phrasings. You can review, organize, and revise later. Any device with a microphone (like your phone) will do the trick. See various speech to text tools on the ARS Technology page .

Turn off the monitor and force yourself to write for five, ten, twenty minutes, or however long it takes to dump your brain onto the screen. If you can’t see the words, you can’t scrutinize and delete them prematurely.

Use the Pomodoro technique . Set a timer for 25 minutes, write as much as you can during that time, take a five-minute break, and then do it again. After four 25-minute segments, take a longer break. The timer puts a helpful limit on the writing session that can motivate you to produce. It also keeps you aware of the passage of time, helping you stay focused and keeping your time more structured.

Sprints or marathons? Some people find it helpful to break down the writing process into smaller tasks and work on a number of tasks in smaller sprints. However, some people with ADHD find managing a number of tasks overwhelming, so for them, a “marathon write” may be a good idea. A marathon write doesn’t have to mean last-minute writing. Try to plan ahead, stock up on food for as many days as you plan to write, and think about how you’ll care for yourself during the long stretch of writing.

Minimize distractions . Turn off the internet, find a suitable place (quiet, ambient noise, etc.), minimize disruptions from other people (family, office mates, etc.), and use noise-canceling headphones or earplugs if they help. If you catch your thoughts wandering, write down whatever is distracting and you can attend to it later when you finish.

Seek feedback for clarity . Mind-wandering is a big asset for people with ADHD as it boosts creativity. Expansive, big-picture thinking is also an asset because it allows you to imagine complex systems. However, these things can also make graduate students with ADHD struggle with maintaining logical coherence. When you ask for feedback, specify logical coherence as a concern so your reader has a focus. If you’d like to look at your logic before you seek feedback, see our 2-minute video on reverse outlining .

Seek feedback for community . Talking to people about your ideas for writing will help you stay connected at a time when it’s easy to fade into a dark hole. Check out this handout on getting feedback .

Time management and accountability

Enlist your advisor . Graduate students with ADHD might worry about the perception that they’re “gaming the system” if they disclose their ADHD. Or they might struggle with an advisor with a more hands-off mentoring style. It will be helpful to be explicit about your neurodiversity and your potential need for a structure. Ask your advisor to clarify the expectations specifically (even quantify them), and work with them to come up with a clear timeline and a regular check-in schedule.

Enlist other mentors . Your advisor may be less understanding and/or may not be able to provide enough structure, or you may think it’s a good idea to have more than one person on your structure team. Look for other mentors on your faculty (inside or outside of your committee), and talk to senior grad students about their strategies.

Pay attention to your body rhythms . When do you feel most creative? Most focused? Most energetic? Or the least creative, focused, energetic? What activities could you engage in during those times? How can you do them consistently?

Think about task vs. time . It can be difficult to estimate how long a task is going to take, so think about setting a time limit for working on something. Set a timer, work for that amount of time, and change tasks when the time is over.

Tame hyperfocus . If you have trouble switching tasks, ask a friend or colleague to “interrupt” you, or figure out a system you can use to interrupt yourself. For example, when you find yourself trying to fix a sentence for 30 minutes, you can call a friend for a brief conversation about another topic. People with ADHD often find this helps them to look at the work from a more objective perspective when they return to it.

Set SMART goals . Check out the handout on setting SMART goals to help you set up a regular research and writing routine.

Set up a reward system . Tie your research or writing goal to an enjoyable reward. Note that it can also be pre-ward – something you do beforehand that will help you feel refreshed and motivated to work.

Find accountability buddies . These can be people you update on your progress or people you meet with to get work done together. Oftentimes, the simple presence of other people is able to motivate and keep us focused. This “body-doubling” strategy is particularly helpful for people with ADHD. Look for events like the Dissertation Boot Camp or IME Writing Wednesdays .

Find virtual accountability partners . There are a number of online platforms to connect you with virtual work partners. See this article on strategies and things to consider.

Use productivity and focus apps . Check out some recommendations among the Learning Center’s ADHD/LD Resources . To find the best options for you, try Googling “Apps for focus and productivity” to find reviews of timers and other focus apps.

Learn more about accountability . See the Learning Center’s Accountability Strategies page for great information and resources.

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

Barkley, R. (2022, July 11). What is executive function? 7 deficits tied to ADHD . ADDitude: Inside the ADHD Mind. https://www.additudemag.com/7-executive-function-deficits-linked-to-adhd/

Hallowell, E. and Ratey, J. (2021). ADHD 2.0: New science and essential strategies for thriving with distraction—from childhood through adulthood . Random House Books.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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Understanding and Supporting Attention Deficit Hyperactivity Disorder (ADHD) in the Primary School Classroom: Perspectives of Children with ADHD and their Teachers

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• Published: 01 July 2022
• Volume 53 , pages 3406–3421, ( 2023 )

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• Emily McDougal   ORCID: orcid.org/0000-0001-7684-7417 1 , 3 ,
• Claire Tai 1 ,
• Tracy M. Stewart   ORCID: orcid.org/0000-0002-8807-1174 2 ,
• Josephine N. Booth   ORCID: orcid.org/0000-0002-2867-9719 2 &
• Sinéad M. Rhodes   ORCID: orcid.org/0000-0002-8662-1742 1  

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Children with Attention Deficit Hyperactivity Disorder (ADHD) are more at risk for academic underachievement compared to their typically developing peers. Understanding their greatest strengths and challenges at school, and how these can be supported, is vital in order to develop focused classroom interventions. Ten primary school pupils with ADHD (aged 6–11 years) and their teachers (N = 6) took part in semi-structured interviews that focused on (1) ADHD knowledge, (2) the child’s strengths and challenges at school, and (3) strategies in place to support challenges. Thematic analysis was used to analyse the interview transcripts and three key themes were identified; classroom-general versus individual-specific strategies, heterogeneity of strategies, and the role of peers. Implications relating to educational practice and future research are discussed.

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Characterised by persistent inattention, hyperactivity and impulsivity (APA, 2013), ADHD is a neurodevelopmental disorder thought to affect around 5% of children (Russell et al., 2014 ) although prevalence estimates vary (Sayal et al., 2018 ). Although these core symptoms are central to the ADHD diagnosis, those with ADHD also tend to differ from typically developing children with regards to cognition and social functioning (Coghill et al., 2014 ; Rhodes et al., 2012 ), which can negatively impact a range of life outcomes such as educational attainment and employment (Classi et al., 2012 ; Kuriyan et al., 2013 ). Indeed, academic outcomes for children with ADHD are often poor, particularly when compared with their typically developing peers (Arnold et al., 2020 ) but also compared to children with other neurodevelopmental disorders, such as autism (Mayes et al., 2020 ). Furthermore, children with ADHD can be viewed negatively by their peers. For example, Law et al. ( 2007 ) asked 11–12-year-olds to read vignettes describing the behaviour of a child with ADHD symptoms, and then use an adjective checklist to endorse those adjectives that they felt best described the target child. The four most frequently ascribed adjectives were all negative (i.e. ‘careless’, ‘lonely’, ‘crazy’, and ‘stupid’). These negative perceptions can have a significant impact on the wellbeing of individuals with ADHD, including self-stigmatisation (Mueller et al., 2012 ). There is evidence that teachers with increased knowledge of ADHD report more positive attitudes towards children with ADHD compared to those with poor knowledge (Ohan et al., 2008 ) and thus research that identifies the characteristics of gaps in knowledge is likely to be important in addressing stigma.

Previous research of teachers' ADHD knowledge is mixed, with the findings of some studies indicating that teachers have good knowledge of ADHD (Mohr-Jensen et al., 2019 ; Ohan et al., 2008 ) and others suggesting that their knowledge is limited (Latouche & Gascoigne, 2019 ; Perold et al., 2010 ). Ohan et al. ( 2008 ) surveyed 140 primary school teachers in Australia who reported having experience of teaching at least one child with ADHD. Teachers completed the ADHD Knowledge Scale which consisted of 20 statements requiring a response of either true or false (e.g. “A girl/boy can be appropriately labelled as ADHD and not necessarily be over-active ”). They found that, on average, teachers answered 76.34% of items correctly, although depth of knowledge varied across the sample. Almost a third of the sample (29%) had low knowledge of ADHD (scoring less than 69%), with just under half of teachers (47%) scoring in the average range (scores of 70–80%). Only a quarter (23%) had “high knowledge” (scores above 80%) suggesting that knowledge varied considerably. Furthermore, Perold et al. ( 2010 ) asked 552 teachers in South Africa to complete the Knowledge of Attention Deficit Disorders Scale (KADDS) and found that on average, teachers answered only 42.6% questions about ADHD correctly. Responses of “don’t know” (35.4%) and incorrect responses (22%) were also recorded, indicating gaps in knowledge as well as a high proportion of misconceptions. Similar ADHD knowledge scores were reported in Latouche and Gascoigne’s ( 2019 ) study, who found that teachers enrolled into their ADHD training workshop in Australia had baseline KADDS scores of below 50% accuracy (increased to above 80% accuracy after training).

The differences in ADHD knowledge reported between Ohan et al. ( 2008 ) and the more recent studies could be due to the measures used. Importantly, when completing the KADDS, respondents can select a “don’t know” option (which receives a score of 0), whereas the ADHD Knowledge Scale requires participants to choose either true or false for each statement. The KADDS is longer, with a total of 39 items, compared to the 20-item ADHD Knowledge Scale, offering a more in-depth knowledge assessment. The heterogeneity of measures used within the described body of research is also highlighted within Mohr-Jensen et al. ( 2019 ) systematic review; the most frequently used measure (the KADDS) was only used by 4 out of the 33 reviewed studies, showing little consensus on the best way to measure ADHD knowledge. Despite these differences in measurement, the findings from most studies indicate that teacher ADHD knowledge is lacking.

Qualitative methods can provide rich data, facilitating a deeper understanding of phenomena that quantitative methods alone cannot reveal. Despite this, there are very few examples in the literature of qualitative methods being used to understand teacher knowledge of ADHD. In one example, Lawrence et al. ( 2017 ) interviewed fourteen teachers in the United States about their experiences of working with pupils with ADHD, beginning with their knowledge of ADHD. They found that teachers tended to focus on the external symptoms of ADHD, expressing knowledge of both inattentive and hyperactive symptoms. Although this provided key initial insights into the nature of teachers’ ADHD knowledge, only a small section of the interview schedule (one out of eight questions/topics) directly focused on ADHD knowledge. Furthermore, none of the questions asked directly about strengths, with answers focusing on difficulties. It is therefore difficult to determine from this study whether teachers are aware of strengths and difficulties outside of the triad of symptoms. A deeper investigation is necessary to fully understand what teachers know, and to identify areas for targeted psychoeducation.

Importantly, improved ADHD knowledge may impact positively on the implementation of appropriate support for children with ADHD in school. For example, Ohan et al. ( 2008 ) found that teachers with high or average ADHD knowledge were more likely to perceive a benefit of educational support services than those with low knowledge, and teachers with high ADHD knowledge were also more likely to endorse a need for, and seek out, those services compared to those with low knowledge. Furthermore, improving knowledge through psychoeducation may be important for improving fidelity to interventions in ADHD (Dahl et al., 2020 ; Nussey et al., 2013 ). Indeed, clinical guidelines recommend inclusion of psychoeducation in the treatment plan for children with ADHD and their families (NICE, 2018 ). Furthermore, Jones and Chronis-Tuscano ( 2008 ) found that educational ADHD training increased special education teachers’ use of behaviour management strategies in the classroom. Together, these findings suggest that understanding of ADHD may improve teachers’ selection and utilisation of appropriate strategies.

Child and teacher insight into strategy use in the classroom on a practical, day-to-day level may provide an opportunity to better understand how different strategies might benefit children, as well as the potential barriers or facilitators to implementing these in the classroom. Previous research with teachers has shown that aspects of the physical classroom can facilitate the implementation of effective strategies for autistic children, for example to support planning with the use of visual timetables (McDougal et al., 2020 ). Despite this, little research has considered the strategies that children with ADHD and their teachers are using in the classroom to support their difficulties and improve learning outcomes. Moore et al. ( 2017 ) conducted focus groups with UK-based educators (N = 39) at both primary and secondary education levels, to explore their experiences of responding to ADHD in the classroom, as well as the barriers and facilitators to supporting children. They found that educators mostly reflected on general inclusive strategies in the classroom that rarely targeted ADHD symptoms or difficulties specifically, despite the large number of strategies designed to support ADHD that are reported elsewhere in the literature (DuPaul et al., 2012 ; Richardson et al., 2015 ). Further to this, when interviewing teachers about their experiences of teaching pupils with ADHD, Lawrence et al. ( 2017 ) specifically asked about interventions or strategies used in the classroom with children with ADHD. The reported strategies were almost exclusively behaviourally based, for example, allowing children to fidget or move around the classroom, utilising rewards, using redirection techniques, or reducing distraction. This lack of focus on cognitive strategies is surprising, given the breadth of literature focusing on the cognitive difficulties in ADHD (e.g. Coghill, et al., 2014 ; Gathercole et al., 2018 ; Rhodes et al., 2012 ). Furthermore, to our knowledge research examining strategy use from the perspective of children with ADHD themselves, or strengths associated with ADHD, is yet to be conducted.

Knowledge and understanding of ADHD in children with ADHD has attracted less investigation than that of teachers. In a Canadian sample of 8- to 12-year-olds with ADHD (N = 29), Climie and Henley ( 2018 ) found that ADHD knowledge was highly varied between children; scores on the Children ADHD Knowledge and Opinions Scale ranged from 5 to 92% correct (M = 66.53%, SD = 18.96). The authors highlighted some possible knowledge gaps, such as hyperactivity not being a symptom for all people with ADHD, or the potential impact upon social relationships, however the authors did not measure participant’s ADHD symptoms, which could influence how children perceive ADHD. Indeed, Wiener et al ( 2012 ) has shown that children with ADHD may underestimate their symptoms. If this is the case, it would also be beneficial to investigate their understanding of their own strengths and difficulties, as well as of ADHD more broadly. Furthermore, if children do have a poor understanding of ADHD, they may benefit from psychoeducational interventions. Indeed, in their systematic review Dahl et al. ( 2020 ) found two studies in which the impact of psychoeducation upon children’s ADHD knowledge was examined, both of which reported an increase in knowledge as a consequence of the intervention. Understanding the strengths and difficulties of the child, from the perspective of the child and their teacher, will also allow the design of interventions that are individualised, an important feature for school-based programmes (Richardson et al., 2015 ). Given the above, understanding whether children have knowledge of their ADHD and are aware of strategies to support them would be invaluable.

Teacher and child knowledge of ADHD and strategies to support these children is important for positive developmental outcomes, however there is limited research evidence beyond quantitative data. Insights from children and teachers themselves is particularly lacking and the insights which are available do not always extend to understanding strengths which is an important consideration, particularly with regards to implications for pupil self-esteem and motivation. The current study therefore provides a vital examination of the perspectives of both strengths and weaknesses from a heterogeneous group of children with ADHD and their teachers. Our sample reflects the diversity encountered in typical mainstream classrooms in the UK and the matched pupil-teacher perspectives enriches current understandings in the literature. Specifically, we aimed to explore (1) child and teacher knowledge of ADHD, and (2) strategy use within the primary school classroom to support children with ADHD. This novel approach, from the dual perspective of children and teachers, will enable us to identify potential knowledge gaps, areas of strength, and insights on the use of strategies to support their difficulties.

Participants

Ten primary school children (3 female) aged 7 to 11 years (M = 8.7, SD = 1.34) referred to Child and Adolescent Mental Health Services (CAMHS) within the NHS for an ADHD diagnosis were recruited to the study. All participant characteristics are presented in Table 1 . All children were part of the Edinburgh Attainment and Cognition Cohort and had consented to be contacted for future research. Children who were under assessment for ADHD or who had received an ADHD diagnosis were eligible to take part. Contact was established with the parent of 13 potential participants. Two had undergone the ADHD assessment process with an outcome of no ADHD diagnosis and were therefore not eligible to take part, and one could not take part within the timeframe of the study. The study was approved by an NHS Research Ethics Committee and parents provided informed consent prior to their child taking part. Co-occurrences data for all participants was collected as part of a previous study and are reported here for added context. All of the children scored above the cut-off (T-score > 70) for ADHD on the Conners 3 rd Edition Parent diagnostic questionnaire (Conners, 2008 ). The maximum possible score for this measure is 90. At the point of interview, seven children had received a diagnosis of ADHD, two children were still under assessment, and one child had been referred for an ASD diagnosis (Table 1 ). The ADHD subtype of each participant was not recorded, however all children scored above the cut-off for both inattention (M = 87.3, SD = 5.03) and hyperactivity (M = 78.6, SD = 5.8) which is indicative of ADHD combined type. Use of stimulant medication was not recorded at the time of interview.

Following the child interview and receipt of parental consent, each child’s school was contacted to request their teacher’s participation in the study. Three teachers could not take part within the timeframe of the study, and one refused to take part. Six teachers (all female) were successfully contacted and gave informed consent to participate.

Due to the increased likelihood of co-occurring diagnoses in the target population, we also report Autism Spectrum Disorder (ASD) symptoms and Developmental Co-ordination Disorder (DCD) symptoms using the Autism Quotient 10-item questionnaire (AQ-10; Allison et al., 2012 ) and Movement ABC-2 Checklist (M-ABC2; Henderson et al., 2007 ) respectively, both completed by the child’s parent.

Scores of 6 and above on the AQ-10 indicates referral for diagnostic assessment for autism is advisable. All but one of the participants scored below the cut-off on this measure (M = 3.6, SD = 1.84).

The M-ABC2 checklist categorises children as scoring green, amber or red based on their scores. A green rating (up to the 85th percentile) indicates no movement difficulty, amber ratings (between 85 and 95th percentile) indicate risk of movement difficulty, and red ratings (95th percentile and above) indicate high likelihood of movement difficulty. Seven of the participants received a red rating, one an amber rating, and two green ratings.

Socioeconomic status (SES) is also known to impact educational outcomes, therefore the SES of each child was calculated using the Scottish Index of Multiple Deprivation (SIMD), which is an area-based measure of relative deprivation. The child’s home postcode was entered into the tool which provided a score of deprivation on a scale of 1 to 5. A score of 1 is given to the 20% most deprived data zones in Scotland, and a score of 5 indicates the area was within the 20% least deprived areas.

Semi-Structured Interview

The first author, who is a psychologist, conducted interviews with each participant individually, and then a separate interview with their teacher. This was guided by a semi-structured interview schedule (see Appendix A, Appendix B) developed in line with our research questions, existing literature, and using authors (T.S. and J.B.) expertise in educational practice. The questions were adapted to be relevant for the participant group. For example, children were asked “If a friend asked you to tell them what ADHD is, what would you tell them?” and teachers were asked, “What is your understanding of ADHD or can you describe a typical child with ADHD?”. The schedule comprised two key sections for both teachers and children. The first section focused on probing the participant’s understanding and knowledge of ADHD broadly. The second section focused on the participating child’s academic and cognitive strengths and weaknesses, and the strategies used to support them. Interviews with children took place in the child’s home and lasted between 19 and 51 min (M = 26.3, SD = 10.9). Interviews with teachers took place at their school and were between 28 and 50 min long (M = 36.5, SD = 7.61). Variation in interview length was mostly due to availability of the participant and/or age of the child (i.e. interviews with younger children tended to be shorter). All interviews were recorded on an encrypted voice recorder and transcribed by the first author prior to data analysis. Pseudonyms were randomly generated for each child to protect anonymity.

Reflexive thematic analysis was used to analyse the data (Braun & Clarke, 2019 ). This flexible approach allows the data to drive the analysis, putting the participant at the centre of the research and placing high value on the experiences and perspectives of individual participants (Braun & Clarke, 2006 ). The six phases of reflexive thematic analysis as outlined by Braun and Clarke were followed: (1) familiarisation, (2) generating codes, (3) constructing themes, (4) revising themes, (5) defining themes, (6) producing the report. Due to the exploratory nature of this study, bottom-up inductive coding was used. Two of the authors (E.M. and C.T.) worked collaboratively to construct and subsequently define the themes using the process described above. More specifically, one author (E.M.) generated codes, with support from another author (C.T.). Collated codes and data were then abstracted into potential themes, which were reviewed and refined using relevant literature, as well as within the wider context of the data. This process continued until all themes were agreed upon.

In the first part of the analysis, focus was placed on summarising the participants’ understanding of ADHD, as well as what they thought their biggest strengths and challenges were at school. Following this, an in-depth analysis of the strategies used in the classroom was conducted, taking into account the perspective of both teachers and children, aiming to generate themes from the data.

Knowledge of ADHD

Children and teachers were asked about their knowledge of ADHD. When asked if they had ever heard of ADHD, the majority of children said yes. Some of the children could not explain to the interviewer what ADHD was or responded in a way that suggested a lack of understanding ( “it helps you with skills” – Niall, 7 years; “ Well it’s when you can’t handle yourself and you’re always crazy and you can just like do things very fast”— Nathan, 8 years). Very few of the children were able to elaborate accurately on their understanding of ADHD, which exclusively focused on inattention. For example, Paige (8 years) said “ its’ kinda like this thing that makes it hard to concentrate ” and Finn (10 years) said “ they get distracted more just in different ways that other people would ”. This suggests that children with ADHD may lack or have a limited awareness or understanding of their diagnosis.

When asked about their knowledge of ADHD, teachers tended to focus on the core symptoms of ADHD. All teachers directly mentioned difficulties with attention, focus or concentration, and most directly or indirectly referred to hyperactivity (e.g. moving around, being in “ overdrive ”). Most teachers also referred to social difficulties as a feature of ADHD, including not following social rules, reacting inappropriately to other children and appearing to lack empathy, which they suggested could be linked to impulsivity. For example, “ reacting in social situations where perhaps other children might not react in a similar way” (Paige’s teacher) and “ They can react really really quickly to things and sometimes aggressively” (Eric’s teacher). Although no teachers directly mentioned cognitive difficulties, some referred to behaviours indicative of cognitive difficulties, for example, “ they can’t store a lot of information at one time” (Eric’s teacher) and, “ it’s not just the concentration it’s the amount they can take in at a time as well” (Nathan’s teacher), which may reflect processing or memory differences. Heterogeneity was mentioned, in that ADHD can mean different things for different children (e.g., “ I think ADHD differs from child to child and I think that’s really important” —Nathan’s teacher). Finally, academic difficulties as a feature of ADHD were also mentioned (e.g., “ a child… who finds some aspects of school life, some aspects of the curriculum challenging ”—Jay’s teacher).

After being asked to give a general description of ADHD, each child was asked about their own strengths at school and teachers were also asked to reflect on this topic for the child taking part.

When asked what they like most about school, children often mentioned art or P.E. as their preferred subjects. A small number of children said they enjoyed maths or reading, but this was not common and the majority described these subjects as a challenge or something they disliked. There was also clear link between the aspects of school children enjoyed, and what they perceived to be a strength for them. For example, when asked what he liked about school, Eric (10 years) said, “ Math, I’m pretty good at that”, or when later asked what they were good at, most children responded with the same answers they gave when asked what they liked about school. It is interesting to note that subjects such as art or P.E. generally have a different format to more traditionally academic subjects such as maths or literacy. Indeed, Felicity (11 years) said, “ I quite like art and drama because there’s not much reading…and not really too much writing in any of those” . Children also tended to mention the non-academic aspects of school, such as seeing their friends, or lunch and break times.

Teachers’ descriptions of the children’s strengths were much more variable compared to strengths mentioned by children. Like the children, teachers tended to consider P.E and artistic activities to be a strength for the child with ADHD. Multiple teachers referred to the child having a good imagination and creative skills. For example, “ she’s a very imaginative little girl, she has a great ability to tell stories and certainly with support write imaginative stories” (Paige’s teacher) . Teachers referred to other qualities or characteristics of the child as strengths, although these varied across teachers. These included openness, both socially but also in the context of willingness to learn or being open to new challenges, being a hard worker, or an enjoyable person to be around (e.g., “ he is the loveliest little boy, I’ve got a lot of time for [Nathan]. He makes me smile every day, you know, he just comes out with stuff he’s hilarious”— Nathan’s teacher). The most noticeable theme that emerged from this data was that when some teachers began describing one of the child’s strengths, it was suffixed with a negative. For example, Henry’s teacher said, “ He’s got a very good imagination, his writing- well not so much the writing of the stories, he finds writing quite a challenge, but his verbalising of ideas he’s very imaginative”. This may reflect that while these children have their own strengths, these can be limited by difficulties. Indeed, Paige’s teacher said, “ I think she’s a very able little girl without a doubt, but there is a definite barrier to her learning in terms of her organisation, in terms of her focus” , which reinforces this notion.

Children were asked directly about what they disliked about school, and what they found difficult. Children tended to focus more on specific subjects, with maths and aspects of literacy being the most frequently mentioned of these. Children referred to difficulties with or a dislike for reading, writing and/or spelling activities, for example, Rory (9 years) said “ Well I suppose spelling because … sometimes we have to do some boring tasks like we have to write it out three times then come up with the sentence for each one which takes forever and it’s hard for me to think of the sentences if I’m not ready” . Linking this with known cognitive difficulties in ADHD, it is interesting to note that both memory and planning are implicated in this quote from Rory about finding spelling challenging. In terms of writing, children referred to both the physical act of writing (e.g., “ probably writing cause sometimes I forget my finger spaces ”—Paige, 8 years; “ [writing the alphabet is] too hard… like the letters joined together … [and] I make mistakes” —Jay, 7 years) as well as the planning associated with writing a longer piece of work (e.g. “ when I run out of ideas for it, it’s really hard to think of some more so I don’t usually get that much writing done ”—Rory (9 years) .

Aside from academic subjects, several children referred to difficulties with focus or attention (e.g. “ when I find it hard to do something I normally kind of just zone out ”—Felicity, 11 years, “ probably concentrating sometimes ”—Rory, 9 years), but boredom was also a common and potentially related theme (e.g. “ Reading is a bit hard though … it just sometimes gets a bit boring” —Finn, 10 years, “ I absolutely hate maths … ‘cause it’s boring ”—Paige, 8 years). It could be that children with ADHD find it more difficult to concentrate during activities they find boring. Indeed, when Jay (7 years) was asked how it made him feel when he found something boring, he said “ it made me not do my work ”. Some children also alluded to the social difficulties faced at school, which included bullying and difficulties making friends (e.g. “ just making all kind of friends [is difficult] ‘cause the only friend that I’ve got is [name redacted] ”—Nathan, 8 years; “ sometimes finding a friend to play with at break time [is difficult] ” – Paige, 8 years; “ there’s a lot of people in my school that they bully me” —Eric, 10 years).

When asked what they thought were the child’s biggest challenges at school, teachers' responses were relatively variable, although some common themes were identified. As was the case for children, teachers reflected on difficulties with attention, which also included being able to sit at the table for long periods of time (e.g. “ I would say he struggles the most with sitting at his table and focusing on one piece of work ”—Henry’s teacher). Teachers did also mention difficulties with subjects such as maths and literacy, although this varied from child to child, and often they discussed these in the context of their ADHD symptom-related difficulties. For example, Eric’s teacher said, “ we’ve struggled to get a long piece of writing out of him because he just can’t really sit for very long ”. This quote also alludes to difficulties with evaluating the child’s academic abilities, due to their ADHD-related difficulties, which was supported by other teachers (e.g. “ He doesn’t particularly enjoy writing and he’s slow, very slow. And I don’t know if that’s down to attention or if that’s something he actually does find difficult to do ” —Henry’s teacher). Furthermore, some teachers reflected on the child’s confidence as opposed to a direct academic difficulty. For example, Luna’s teacher said, “ I think it’s she lacks the confidence in maths and reading like the most ” and later, elaborated with “ she’ll be like “I can’t do it” but she actually can. Sometimes she’s … even just anxious at doing a task where she thinks … she might not get it. But she does, she’s just not got that confidence”.

Teachers also commonly mentioned social difficulties, and referred to these difficulties as a barrier to collaborative learning activities (e.g. “ he doesn’t always work well with other people and other people can get frustrated” —Henry’s teacher; “ [during] collaborative group work [Paige] perhaps goes off task and does things she shouldn’t necessarily be doing and that can cause friction within the group” —Paige’s teacher). Teachers also mentioned emotion regulation, mostly in relation to the child’s social difficulties. For example, Eric’s teacher said “ I think as well he does still struggle with his emotions like getting angry very very quickly, and being very defensive when actually he’s taken the situation the wrong way” , which suggests that the child’s difficulty with regulating emotions may impact on their social relationships.

Strategy Use in the Classroom

Strategies to support learning fell into one of four categories: concrete or visual resources, information processing, seating and movement, and support from or influence of others. Examples of codes included in each of these strategy categories are presented in Table 2 .

Concrete or visual resources were the most commonly mentioned type of strategy by teachers and children, referring to the importance of having physical representations to support learning. Teachers spoke about the benefit of using visual aids (e.g. “ I think [Henry] is quite visual so making sure that there is visual prompts and clues and things like that to help him ”—Henry’s teacher), and teachers and children alluded to these resources supporting difficulties with holding information in mind. For example, when talking about the times table squares he uses, Rory said “ sometimes I forget which one I’m on…and it’s easier for me to have my finger next to it than just doing it in my head because sometimes I would need to start doing it all over again ”.

Seating and movement were also commonly mentioned, which seemed to be specific to children with ADHD in that it was linked to inattention and hyperactivity symptoms. For example, teachers referred to supporting attention or avoiding distraction by the positioning of a child’s location in the classroom (e.g. “ he’s so easily distracted, so he has an individual desk in the room and he’s away from everyone else because he wasn’t coping at a table [and] he’s been so much more settled since we got him an individual desk” —Eric’s teacher). Some teachers also mentioned the importance of allowing children to move around the room where feasible, as well as giving them errands to perform as a movement break (e.g. “ if I need something from the printer, [Nathan] is gonna go for it for me…because that’s down the stairs and then back up the stairs so if I think he’s getting a bit chatty or he’s not focused I’ll ask him to go and just give him that break as well” —Nathan’s teacher). Children also spoke about these strategies but didn’t necessarily describe why or how these strategies help them.

Information processing and cognitive strategies included methods that supported children to process learning content or instructions. For example, teachers frequently mentioned breaking down tasks or instructions into more manageable chunks (e.g. “ with my instructions to [Eric] I break them down … I’ll be like “we’re doing this and then we’re doing this” whereas the whole class wouldn’t need that ”—Eric’s teacher). Teachers and children also mentioned using memory strategies such as songs, rhymes or prompts. For example, Jay’s teacher said, “ if I was one of the other children I could see why it would be very distracting but he’s like he’s singing to himself little times table songs that we’ve been learning in class” , and Paige (8 years) referred to using mnemonics to help with words she struggles to spell, “ I keep forgetting [the word] because. But luckily we got the story big elephants can always understand little elephants [which helps because] the first letter of every word spells because” .

Both groups of participants mentioned support from and influence of others, and referred to working with peers, the teacher–child relationship, and one-to-one teaching. Peer support was a common theme across the data and is discussed in more detail in the thematic analysis findings, where teachers and children referred to the importance of the role of peers during learning activities. Understanding the child well and adapting to them was also seen as important, for example, Luna’s teacher said, “ with everything curricular [I] try and have an art element for her, just so I know it’ll engage her [because] if it’s like a boring old written worksheet she’s not gonna do it unless you’re sitting beside her and you’re basically telling her the answers” . As indicated in this quote, teachers also referred to the effectiveness of one-to-one or small group work with the child (e.g. “ when somebody sits beside her and explains it, and goes “come on [Paige] you know how to do this, let’s just work through a couple of examples”… her focus is generally better ” – Paige’s teacher), however this resource is not always available (e.g. “ I’d love for someone to be one-to-one with [Luna] but it’s just not available, she doesn’t meet that criteria apparently ” – Luna’s teacher). Children also referred to seeking direct support from their teacher (e.g. “if I can’t get an idea of what I’m doing then I ask the teacher for help” – Paige, 8 years), but were more likely to mention seeking support from their peers than the teacher.

Thematic Analysis

In addition to summarising the types of strategies that teachers and children reported using in the classroom, the data were also analysed using thematic analysis to generate themes. These are now presented. The theme names, definitions, and example quotes for each theme are presented in Table 3 .

Theme 1: Classroom-General Versus Individual-Specific Strategies

During the interviews, teachers spoke about strategies that they use as part of their teaching practice for the whole class but that are particularly helpful for the child/children with ADHD. These tended to be concrete or visual resources that are available in the classroom for anyone, for example, a visual timetable or routine checklist (e.g. “ there’s also a morning routine and listing down what’s to be done and where it’s to go … it’s very general for the class but again it’s located near her” —Paige’s teacher).

Teachers also mentioned using strategies that have been implemented specifically for that child, and these strategies tended to focus on supporting attention. For example, Nathan’s teacher spoke about the importance of using his name to attract his attention, “ maybe explaining to the class but then making sure that I’m saying “[Nathan], you’re doing this”, you know using his name quite a lot so that he knows it’s his task not just the everybody task ”, and this was a strategy that multiple teachers referred to using with the individual child and not necessarily for other children. Other strategies to support attention with a specific child also tended to be seating and movement related, such as having an individual desk or allowing them to fidget. For example, Luna’s teacher said, “ she’s a fidgeter so she’ll have stuff to fidget with … [and] even if she’s wandering around the classroom or she’s sitting on a table, I don’t let other kids do that, but as long as she’s listening, it’s fine [with me]” .

Similar to teachers, children spoke about strategies or resources that were in place for them specifically as well as about general things in the classroom that they find helpful. That said, it was less common for children to talk about why particular strategies were in place for them and how they helped them directly.

In addition to recognising strategies that teachers had put in place for them, children also referred to using their own strategies in the classroom. The most frequently mentioned strategy was fidgeting, and although some of the younger children spoke about having resources available in the classroom for fidgeting, some of the older children referred to using their own toy or an object that was readily available to them but not intended for fidgeting. For example, Finn (10 years) and Rory (9 years) both spoke about using items from their pencil case to fiddle with, and explained that this would help them to focus. (“ Sometimes I fidget with something I normally just have like a pencil holder under the table moving about … [and] it just keeps my mind clear and not from something else ”—Rory; “ Sometimes I fiddle with my fingers and that sometimes helps, but if not I get one of my coloured pencils and have a little gnaw on it because that actually takes my mind off some things and it’s easier for me to concentrate when I have something to do ”—Finn). Henry (9 years) spoke about being secretive with his fidgeting as it was not permitted in class, “ if you just bring [a fidget toy] in without permission [the teacher will] just take it off of you, so it has to be something that’s not too big. I bring in a little Lego ray which is just small enough that she won’t notice ”. Although some teachers did mention having fidget toys available, not all teachers seemed to recognise the importance of this for the child, and some children viewed fidgeting as a behaviour they should hide from the teacher.

Another strategy mentioned uniquely by children was seeing their peers as a resource for ideas or information. This is discussed in more detail in Theme 3—The role of peers , but reinforces the notion that children also develop their own strategies, independently from their teacher, rather than relying only on what is made available to them.

Theme 2: Heterogeneity of Strategies

Teachers spoke about the need for a variety of strategies in the classroom, for two reasons: (1) that different strategies work for different children (e.g. “ some [strategies] will work for the majority of the children and some just don’t seem to work for any of them ”—Jay’s teacher), and (2) what works for a child on one occasion may not work consistently for the same child (e.g. “ I think it’s a bit of a journey with him, and some things have worked and then stopped working, so I think we’re constantly adapting and changing what we’re doing ”—Eric’s teacher). One example of both of these challenges of strategy use came from Luna’s teacher, who spoke about using a reward chart with Luna and another child with ADHD, “ [Luna] and another boy in my class [with ADHD] both had [a reward chart]… but I think whereas the boy loved his and still loves his, she was getting a bit “oh I’m too cool for this” or that sort of age… so I stopped doing that for her and she’s not missing that at all” . These quotes demonstrate that strategies can work differently for different children, highlighting the need for a variety of strategies for teachers to access and trial with children.

Some children also referred to the variability of whether a strategy was helpful or not; for example, Henry (9 years) said that he finds it helpful to fidget with a toy but that sometimes it can distract him and prevent him from listening to the teacher. He said, “ Well, [the fidget toy] helps but it also gets me into trouble when the teacher spots me building it when I’m listening…but then sometimes I might not listen in maths and [use the fidget toy] which might make it worse”. This highlights that both children and teachers might benefit from support in understanding the contexts in which to use particular strategies, as well as why they are helpful from a psychological perspective.

For teachers, building a relationship with and understanding the child was also highly important in identifying strategies that would work. Luna’s teacher reflected upon the difference in Luna’s behaviour at the start of the academic year, compared to the second academic term, “ at the start of the year, we would just clash the whole time. I didn’t know her, she didn’t know me … and then when we got that bond she was absolutely fine so her behaviour has got way better ”. Eric’s teacher also reflected on how her relationship with Eric had changed, particularly after he received his diagnosis of ADHD, “ I think my approach to him has completely changed. I don’t raise my voice, I speak very calmly, I give him time to calm down before I even broach things with him. I think our relationship’s just got so much better ‘cause I kind of understand … where he’s coming from ”. She also said, “ it just takes a long time to get to know the child and get to know what works for them and trialling different things out ”, which demonstrates that building a relationship with and understanding the child can help to identify the successful strategies that work with different children.

Theme 3: The Role of Peers

Teachers and children spoke about the role of the child’s peers in their learning. Teachers talked about the benefit of partnering the child with good role models (e.g. “ I will put him with a couple of good role models and a couple of children who are patient and who will actually maybe get on with the task, and if [Jay] is not on task or not on board with what they’re doing at least he’s hearing and seeing good behaviour ”—Jay’s teacher), whereas children spoke more about their peers as a source of information, idea generation, or guidance on what to do next. For example, when asked what he does to help him with his writing, Henry (9 years) said, “ [I] listen to what my partner’s saying… my half of the table discuss what they’re going to do so I can literally hear everything they’re doing and steal some of their ideas ”. Henry wasn’t the only child to use their peers as a source of information, for example, Niall (7 years) said, “ I prefer working with the children because some things I might not know and the children might help me give ideas ”, and with a more specific example, Rory (9 years) said, “ somebody chose a very good character for their bit of writing, and I was like “I think I might choose that character”, and somebody else said “my setting was going to be the sea”, and I chose that and put that in a tiny bit of my story ”.

Some children also spoke about getting help from their peers in other ways, particularly when completing a difficult task. Paige (8 years) said, “ if the question isn’t clear I try and figure it out, and if I can’t figure it out then… don’t tell my teacher this but I sometimes get help from my classmates ”, which suggests some guilt associated with asking for help from her peers. This could be related to confidence and self-esteem, which teachers mentioned as a difficulty for some children with ADHD. In some instances, children felt it necessary to directly copy their peers’ work; for example, Nathan (8 years) spoke about needing a physical resource (i.e. “ fuzzies ”) to complete maths problems, but that when none were available he would “ just end up copying other people ”. This could also be related to a lack of confidence, as he may feel as though he may not be able to complete the task on his own. Indeed, Nathan’s teacher mentioned that when he is given the option to choose a task from different difficulty levels, Nathan would typically choose something easier, and that it was important to encourage him to choose something more difficult to build his confidence, “ I quite often say to him “come on I think you can challenge yourself” and [will] use that language”.

Peers clearly play an important role for the children with ADHD, and this is recognised both by the children themselves, and by their teachers. Teachers also mentioned that children with ADHD respond well to one-to-one learning with staff, indicating that it is important for these children to have opportunities to learn in different contexts: whole classroom learning, small group work and one-to-one.

In this study, a number of important topics surrounding ADHD in the primary school setting were explored, including ADHD knowledge, strengths and challenges, and strategy use in the classroom, each of which will now be discussed in turn before drawing together the findings and outlining the implications.

ADHD Knowledge

Knowledge of ADHD varied between children and their teachers. Whilst most of the children claimed to have heard of ADHD, very few could accurately describe the core symptoms. Previous research into this area is limited, however this finding supports Climie and Henley’s ( 2018 ) finding that children’s knowledge of ADHD can be limited. By comparison, all of the interviewed teachers had good knowledge about the core ADHD phenotype (i.e. in relation to diagnostic criteria) and some elaborated further by mentioning social difficulties or description of behaviours that could reflect cognitive difficulties. This supports and builds further upon existing research into teachers’ ADHD knowledge, demonstrating that although teachers understanding may be grounded in a focus upon inattention and hyperactivity, this is not necessarily representative of the range of their knowledge. By interviewing participants about their ADHD knowledge, as opposed to asking them to complete a questionnaire as previous studies have done (Climie & Henley, 2018 ; Latouche & Gascoigne, 2019 ; Ohan et al., 2008 ; Perold et al., 2010 ), the present study has demonstrated the specific areas of knowledge that should be targeted when designing psychoeducation interventions for children and teachers, such as broader aspects of cognitive difficulties in executive functions and memory. Improving knowledge of ADHD in this way could lead to increased positive attitudes and reduction of stigma towards individuals with ADHD (Mueller et al., 2012 ; Ohan et al., 2008 ), and in turn improving adherence to more specified interventions (Bai et al., 2015 ).

Strengths and Challenges

A range of strengths and challenges were discussed, some of which were mentioned by both children and teachers, whilst others were unique to a particular group. The main consensus in the current study was that art and P.E. tended to be the lessons in which children with ADHD thrive the most. Teachers elaborated on this notion, speaking about creative skills, such as a good imagination, and that these skills were sometimes applied in other subjects such as creative writing in literacy. Little to no research has so far focused on the strengths of children with ADHD, therefore these findings identify important areas for future investigation. For example, it is possible that these strengths could be harnessed in educational practice or intervention.

Although a strength for some, literacy was commonly mentioned as a challenge by both groups, specifically in relation to planning, spelling or the physical act of writing. Previous research has repeatedly demonstrated that literacy outcomes are poorer for children with ADHD compared to their typically developing peers (DuPaul et al., 2016; Mayes et al., 2020 ), however in these studies literacy tended to be measured using a composite achievement score, where the nuance of these difficulties can be lost. Furthermore, in line with a recent systematic review and meta-analysis (McDougal et al., 2022 ) the present study’s findings suggest that cognitive difficulties may contribute to poor literacy performance in ADHD. This issue was not unique to literacy, however, as teachers also spoke about academic challenges in the context of ADHD symptoms being a barrier to learning, such as finding it difficult to remain seated long enough to complete a piece of work. Children also raised this issue of engagement, who referred to the most challenging subjects being ‘boring’ for them. This link between attention difficulties and boredom in ADHD has been well documented (Golubchik et al., 2020 ). The findings here demonstrate the need for further research into the underlying cognitive difficulties leading to academic underachievement.

Both children and teachers also mentioned social and emotional difficulties. Research has shown that many different factors may contribute to social difficulties in ADHD (for a review see Gardner & Gerdes, 2015 ), making it a complex issue to disentangle. That said, in the current study teachers tended to attribute the children’s relationship difficulties to behaviour, such as reacting impulsively in social situations, or going off task during group work, both of which could be linked to ADHD symptoms. Despite these difficulties, peers were also considered a positive support. This finding adds to the complexity of understanding social difficulties for children with ADHD, demonstrating the necessity and value of further research into this key area.

The three key themes of classroom-general versus individual-specific strategies , heterogeneity of strategies and the role of peers were identified from the interview transcripts with children and their teachers. Within the first theme, classroom-general versus individual-specific strategies, it was clear that teachers utilise strategies that are specific to the child with ADHD, as well as strategies that are general to the classroom but that are also beneficial to the child with ADHD. Previously, Moore et al. ( 2017 ) found that teachers mostly reflected on using general inclusive strategies, rather than those targeted for ADHD specifically, however the methods differ from the current study in two key ways. Firstly, Moore et al.’s sample included secondary and primary school teachers, for whom the learning environment is very different. Secondly, focus groups were used as opposed to interviews where the voices of some participants can be lost. The merit of the current study is that children were also interviewed using the same questions as teachers; we found that children also referred to these differing types of strategies, and reported finding them useful, suggesting that the reports of teachers were accurate. Interestingly, children also mentioned their own strategies that teachers did not discuss and may not have been aware of. This finding highlights the importance of communication between the child and the teacher, particularly when the child is using a strategy considered to be forbidden or discouraged, for example copying a peer’s work or fidgeting with a toy. This communication would provide an understanding of what the child might find helpful, but more importantly identify areas of difficulty that may need more attention. Further to this, most strategies specific to the child mentioned by teachers aimed to support attention, and few strategies targeted other difficulties, particularly other aspects of cognition such as memory or executive function, which supports previous findings (Lawrence et al., 2017 ). The use of a wide range of individualised strategies would be beneficial to support children with ADHD.

Similarly, the second theme, heterogeneity of strategies , highlighted that some strategies work with some children and not others, and some strategies may not work for the same child consistently. Given the benefit of a wide range of strategy use, for both children with ADHD and their teachers, the development of an accessible tool-kit of strategies would be useful. Importantly, and as recognised in this second theme, knowing the individual child is key to identifying appropriate strategies, highlighting the essential role of the child’s teacher in supporting ADHD. Teachers mostly spoke about this in relation to the child’s interests and building rapport, however this could also be applied to the child’s cognitive profile. A tool-kit of available strategies and knowledge of which difficulties they support, as well as how to identify these difficulties, would facilitate teachers to continue their invaluable support for children and young people with ADHD. This links to the importance of psychoeducation; as previously discussed, the teachers in our study had a good knowledge of the core ADHD phenotype, but few spoke about the cognitive strengths and difficulties of ADHD. Children and their teachers could benefit from psychoeducation, that is, understanding ADHD in more depth (i.e., broader cognitive and behavioural profiles beyond diagnostic criteria), what ADHD and any co-occurrences might mean for the individual child, and why certain strategies are helpful. Improving knowledge using psychoeducation is known to improve fidelity to interventions (Dahl et al., 2020 ; Nussey et al., 2013 ), suggesting that this would facilitate children and their teachers to identify effective strategies and maintain these in the long-term.

The third theme, the role of peers , called attention to the importance of classmates for children with ADHD, and this was recognised by both children and their teachers. As peers play a role in the learning experience for children with ADHD, it is important to ensure that children have opportunities to learn in small group contexts with their peers. This finding is supported by Vygotsky’s ( 1978 ) Zone of Proximal Development; it is well established in the literature that children can benefit from completing learning activities with a partner, especially a more able peer (Vygotsky, 1978 ).

Relevance of Co-Occurrences

Co-occurring conditions are common in ADHD (Jensen & Steinhausen, 2015 ), and there are many instances within the data presented here that may reflect these co-occurrences, in particular, the overlap with DCD and ASD. For ADHD and DCD, the overlap is considered to be approximately 50% (Goulardins et al., 2015 ), whilst ADHD and autism also frequently co-occur with rates ranging from 40 to 70% (Antshel & Russo, 2019 ). It was not an aim of the current study to directly examine co-occurrences, however it is important to recognise their relevance when interpreting the findings. Indeed, in the current sample, scores for seven children (70%) indicated a high likelihood of movement difficulty. One child scored above the cut-off for autism diagnosis referral on the AQ-10, indicating heightened autism symptoms. Further to this, some of the discussions with children and teachers seemed to be related to DCD or autism, for example, the way that they can react in social situations, or difficulties with the physical act of handwriting. This finding feeds into the ongoing narrative surrounding heterogeneity within ADHD and individualisation of strategies to support learning. Recognising the potential role of co-occurrences should therefore be a vital part of any psychoeducation programme for children with ADHD and their teachers.

Limitations

Whilst a strong sample size was achieved for the current study allowing for rich data to be generated, it is important to acknowledge the issue of representativeness. The heterogeneity of ADHD is recognised throughout the current study, however the current study represents only a small cohort of children and young people with ADHD and their teachers which should be considered when interpreting the findings, particularly in relation to generalisation. Future research should investigate the issues raised using quantitative methods. Also on this point of heterogeneity, although we report some co-occurring symptoms for participants, the number of co-occurrences considered here were limited to autism and DCD. Learning disabilities and other disorders may play a role, however due to the qualitative nature of this study it was not feasible to collect data on every potential co-occurrence. Future quantitative work should aim to understand the complex interplay of diagnosed and undiagnosed co-occurrences.

Furthermore, only some of the teachers of participating children took part in the study; we were not able to recruit all 10. It may be, for example, that the six teachers who did take part were motivated to do so based on their existing knowledge or commitment to understanding ADHD, and the fact that not all child-teacher dyads are represented in the current study should be recognised. Another possibility is the impact of time pressures upon participation for teachers, particularly given the increasing number of children with complex needs within classes. Outcomes leading from the current study could support teachers in this respect.

It is also important to recognise the potential role of stimulant medication. Although it was not an aim of the current study to investigate knowledge or the role of stimulant medication in the classroom setting, it would have been beneficial to record whether the interviewed children were taking medication for their ADHD at school, particularly given the evidence to suggest that stimulant medication can improve cognitive and behavioural symptoms of ADHD (Rhodes et al., 2004 ). Examining strategy use in isolation (i.e. with children who are drug naïve or pausing medication) will be a vital aim of future intervention work.

Implications/Future Research

Taking the findings of the whole study together, one clear implication is that children and their teachers could benefit from psychoeducation, that is, understanding ADHD in more depth (i.e., broader cognitive and behavioural profiles beyond diagnostic criteria), what ADHD might mean for the individual child, and why certain strategies are helpful. Improving knowledge using psychoeducation is known to improve fidelity to interventions (Dahl et al., 2020 ; Nussey et al., 2013 ), suggesting that this would facilitate children and their teachers to identify effective strategies and maintain these in the long-term.

To improve knowledge and understanding of both strengths and difficulties in ADHD, future research should aim to develop interventions grounded in psychoeducation, in order to support children and their teachers to better understand why and in what contexts certain strategies are helpful in relation to ADHD. Furthermore, future research should focus on the development of a tool-kit of strategies to account for the heterogeneity in ADHD populations; we know from the current study’s findings that it is not appropriate to offer a one-size-fits-all approach to supporting children with ADHD given that not all strategies work all of the time, nor do they always work consistently. In terms of implications for educational practice, it is clear that understanding the individual child in the context of their ADHD and any co-occurrences is important for any teacher working with them. This will facilitate teachers to identify and apply appropriate strategies to support learning which may well result in different strategies depending on the scenario, and different strategies for different children. Furthermore, by understanding that ADHD is just one aspect of the child, strategies can be used flexibly rather than assigning strategies based on a child’s diagnosis.

This study has provided invaluable novel insight into understanding and supporting children with ADHD in the classroom. Importantly, these insights have come directly from children with ADHD and their teachers, demonstrating the importance of conducting qualitative research with these groups. The findings provide clear scope for future research, as well as guidelines for successful intervention design and educational practice, at the heart of which we must acknowledge and embrace the heterogeneity and associated strengths and challenges within ADHD.

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The funding was provided by Waterloo Foundation Grant Nos. (707-3732, 707-4340, 707-4614).

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Emily McDougal, Claire Tai & Sinéad M. Rhodes

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E.M. Conceptualization, Methodology, Investigation, Data Curation, Formal Analysis, Writing - original draft, C.T. Formal Analysis, Writing - review & editing, T.M.S., J.N.B. and S.M.R. Conceptualization, Methodology, Writing - review & editing.

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Interview Schedule—Teacher

Demographic/experience.

How many years have you been teaching?

Are you currently teaching pupils with ADHD and around how many?

If yes, do you feel competent/comfortable/equipped teaching pupils with ADHD?

If no, how competent/comfortable/equipped would you feel to teach pupils with ADHD?

Would you say your experience of teaching pupils with ADHD is small/moderate/significant?

Psychoeducation

What is your understanding of ADHD/Can you describe a typical child with ADHD?

Probe behaviour knowledge

Probe cognition knowledge

Probe impacts of behaviour/cognition difficulties

Probe knowledge that children with ADHD differ from each other

Probe knowledge that children with ADHD have co-occurring difficulties as the norm

(If they do have some knowledge) Where did you learn about ADHD?

e.g. specific training, professional experience, personal experience, personal interest/research

Cognitive skills and strategies

Can you tell me about the pupil’s strengths?

Can you tell me about the pupil’s biggest challenges/what they need most support with?

When you are supporting the pupil with their learning, are there any specific things you do to help them? (i.e. strategies)

Probe internal

Probe external

Probe whether they think those not mentioned might be useful/feasible/challenges

Probe if different for different subjects/times of the day

In your experience, which of these you have mentioned are the most useful for the pupil?

Probe for examples of how they apply it to their learning

Probe whether these strategies are pupil specific or broadly relevant

Probe if specific to particular subjects/times of the day

In your experience, which of these you have mentioned are the least useful for the pupil?

What would you like to be able to support the pupil with that you don’t already do?

Probe why they can’t access this currently e.g. lack of training, resources, knowledge, time

Is there anything you would like to understand better about ADHD?

Probe behaviour

Probe cognition

Interview Schedule—Child

Script: We’re going to have a chat about a few different things today, mostly about your time at school. This will include things like how you get on, how you think, things you’re good at and things you find more difficult. I’ve got some questions here to ask you but try to imagine that I’m just a friend that you’re talking to about these things. There are no right or wrong answers, I’m just interested in what you’ve got to say. Do you have any questions?

Script: First we’re going to talk about ADHD (Attention Deficit Hyperactivity Disorder).

Have you ever heard of/has anyone ever told you what ADHD is?

(If yes) If a friend asked you to tell them what ADHD is, what would you tell them?

Is there anything you would like to know more about ADHD?

Cognition/strategy use

Script: Now we’re going to talk about something a bit different. Everyone has things they are good at, and things they find more difficult. For example, I’m quite good at listening to what people have to say, but I’m not so good at remembering people’s names. I’d like you to think about when you’re in school, and things you’re good at and things you are not so good at. It doesn’t just have to be lessons, it can be anything.

Do you like school?

Probe why/why not?

Probe favourite lessons

What sort of things do you find you do well at in school?

Is there anything you think that you find more difficult in school?

Probe: If I asked your teacher/parent what you find difficult, what would they say?

Probe: Is there anything at school you need extra help with?

Probe: Is there anything you do to help yourself with that?

Script: Some people do things to try to help themselves do things well. For example, when someone tells me a number to remember, I repeat it in my head over and over again.

Can you try to describe to me what you do to help you do these things?

Solving a maths problem

Planning your writing

Doing spellings

Trying to remember something

Concentrating/ignoring distractions

Listening to the teacher

Remaining seated in class when doing work

Working with other children in the class

Probe: Do you use anything in lessons to help you with your work?

Probe: What kind of things do you think could help you with your work?

Probe: Is there anything you do at home, such as when you’re doing your homework, to help you finish what you are doing to do it well?

Probe: Does someone help you with your homework at home? If yes, what do they do that helps? If no, what do you think someone could do to help?

Script: In this last part we’re going to talk about your time at school.

How many teachers are in your class?

Is there anyone who helps you with your work?

Do you work mostly on your own or in groups?

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McDougal, E., Tai, C., Stewart, T.M. et al. Understanding and Supporting Attention Deficit Hyperactivity Disorder (ADHD) in the Primary School Classroom: Perspectives of Children with ADHD and their Teachers. J Autism Dev Disord 53 , 3406–3421 (2023). https://doi.org/10.1007/s10803-022-05639-3

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Overview of Attention Deficit Hyperactivity Disorder in Young Children

1 Department of Early Childhood and Elementary Education, College of Education and Human Services, Murray State University, Murray, KY, USA

Chia Jung Yeh

2 Human Development and Family Science, College of Health and Human Performance, East Carolina University, Greenville, NC, USA

Nidhi Verma

3 Department of Psychology, Kurukshetra University, Kurukshetra, India

Ajay Kumar Das

4 Department of Adolescent, Career and Special Education, Murray State University, Murray, KY, USA

Contributions: AS, NV contributed equally as first authors.

Attention deficit hyperactivity disorder (ADHD) is a complex disorder, which can be seen as a disorder of life time, developing in preschool years and manifesting symptoms (full and/or partial) throughout the adulthood; therefore, it is not surprising that there are no simple solutions. The aim of this paper is to provide a short and concise review which can be used to inform affected children and adults; family members of affected children and adults, and other medical, paramedical, non-medical, and educational professionals about the disorder. This paper has also tried to look into the process of how ADHD develops; what are the associated problems; and how many other children and adults are affected by such problems all over the world basically to understand ADHD more precisely in order to develop a better medical and or non-medical multimodal intervention plan. If preschool teachers and clinicians are aware of what the research tells us about ADHD, the varying theories of its cause, and which areas need further research, the knowledge will assist them in supporting the families of children with ADHD. By including information in this review about the connection between biological behavior, it is hoped that preschool teachers and clinicians at all levels will feel more confident about explaining to parents of ADHD children, and older ADHD children themselves about the probable causes of ADHD.

Overview of attention deficit hyperactivity disorder in young children

Literally thousands of studies have been conducted on attention deficit hyperactivity disorder (ADHD) and it’s various predecessors in diagnostic nomenclatures prior to DSM-V (The Diagnostic and Statistical Manual of Mental Disorders-V). Despite this long research history, ADHD is not necessarily well understood among the lay public, given the many controversies and public misconceptions concerning the disorder. 1 , 2 Longitudinal evidence suggests that childhood ADHD persists into young adulthood in 60-70% of the cases when defined relative to same-age peers and in 58% of the cases when DSM-V criteria and parental reports are used. 3-6 These early studies of childhood hyperactivity excluded many children that would currently meet the DSM criteria for ADHD, particularly the inactive sub-type. 7 The scientific status of ADHD is one of the most controversial issues in child health. 8-10 This paper examines the overview of ADHD in children in relation to its genetics, taxonomy, neurobiology, comorbidity, diet, treatment, and concludes with a discussion.

Précis of attention deficit hyperactivity disorder

ADHD is recognized as a common childhood psychiatric disorder and has a strong genetic, neuro-biologic, and neurochemical basis. 11 , 12 It is characterized by symptoms of inattention and/or impulsivity and hyperactivity which can significantly impact many aspects of behavior as well as performance, both at school and at home. 13 ADHD is characterized by pervasive and impairing symptoms of inattention, hyperactivity, and impulsivity according to DSM-V. 14-16 The World Health Organization (WHO) uses a different name hyperkinetic disorder (HD)-but lists similar operational criteria for the disorder. 17 Regardless of name used, ADHD is one of the most thoroughly researched disorders in medicine. 18 The DSM diagnostic criteria for ADHD were based on reviews of existing research and a field trial in which alternative diagnostic criteria were evaluated. 19

Classification of what constitutes ADHD has changed dramatically over the last 32 years, with each successive revision of the Diagnostic and Statistical Manual, the diagnostic criteria used to describe the disorder. Current classification for combined type ADHD requires a minimum of six out of nine symptoms of inattention of hyperactivity/impulsivity. 16 , 17 , 20 In addition there must be some impairment from symptoms in two or more settings ( e.g . home and school) and clear evidence of significant impairment in social, school or work functioning. The DSM also allows the classification of two sub-type disorders: i) predominantly inattentive where the child only meets criteria for inattention; and ii) predominantly hyperactive-impulsive where only the hyperactive-impulsive criteria are met.

Prevalence of attention deficit hyperactivity disorder

The relatively prevalence of the disorder is high, affecting approximately 4% of all children, although estimates vary widely from 3% to 11% or more. 21 , 22 The disorder usually begins in early childhood and is characterized by excessive activity, even when developmental level and limited behavioral control are taken into consideration. 23 , 24 reviewed the findings of six large epidemiological studies that identified cases of ADHD within these samples. The prevalences found in these studies ranged from a low of 2% to a high of 6.3%, with most falling within the range of 4.2% to 6.3%. Other studies have found similar prevalence rates in elementary school-age children (4-5.5%; in Breton et al ., 25 7.9% in Briggs-Gowan et al. , 26 5-6% in DuPaul, 27 and 2.5-4% in Pelham et al . 28 Lower rates result from using complete DSM criteria and parent reports (2-6% in Breton et al ., 25 and higher ones if just a cutoff on teacher ratings is used (up to 23% in DuPaul, 27 15.8% in Nolan et al ., 29 14.3% in Trites et al . 30 Sex and age differences in prevalence are routinely found in research. For instance, prevalence rates may be 4% in girls and 8% in boys in the preschool age group, 29 yet fall to 2-4% in girls and 6-9% in boys during the 6- to 12-year-old age period based on parent reports. 25 The prevalence decreases again to 0.9-2% in girls and 1-5.6% in boys by adolescence. 25 , 31-33 Overall ADHD affects 2% to 9% in school age children.

Etiological elucidation of attention deficit hyperactivity disorder

Underlying etiological explanations of ADHD can be simply divided into biological and environmental. In simple terms biological explanations include genetics, brain structure and their influence on neuropsychology, while predominant environmental explanations include problems during and after birth, exposure to environmental toxins, parenting and diet.

Heredity of attention deficit hyperactivity disorder

Heredity of ADHD has been an important issue. 34 For years, researchers have noted the higher prevalence of psychopathology in the parents and other relatives of children with ADHD. Between 10% and 35% of the immediate family members of children with ADHD are also likely to have the disorder, with the risk to siblings being approximately 32%. 35-37

Even more striking is the finding that if a parent has ADHD, the risk to the offspring is 57%. 12 Thus, ADHD clusters significantly among the biological relatives of children with the disorder, strongly implying a hereditary basis to this condition. 38 Subsequently, these elevated rates of disorders have been noted in African American samples with ADHD, 39 as well as in girls with ADHD compared to boys. 40

Genetic factor

The heredity basis for psychiatric disorders was already recognized at the turn of the nineteenth century by Enail Kraepelin. 41 There is now little doubt that ADHD is a condition in which genetic factors (genetic differences between children) make a substantial contribution to the risk of the disorder. 42 Genetic factors are accounted for 80% of the etiology of ADHD, while more recent studies have begun to examine which particular genes might be implicated in ADHD, 43 , 44 reported an association between ADHD and a null allele of the C4B complement locus in the MHC -gene region of chromosome 6, a locus also associated with reading disability. 45 Interest in a potential genetic mechanism underlying ADHD increased with reports of an association with a single dopamine transporter gene, 46 and with reports of variations within the D4 receptor gene. 47 Genetic studies have focused mainly on candidate genes involved in dopaminergic transmission. Several reasons exist for this particular focus, dopaminergic drugs (methylphenidate) are clinically efficacious in addressing the core problems associated with ADHD. A gene related to dopamine, the DRD4 (repeater gene), has been the most reliably found in samples of children with ADHD. 48 It is the seven-repeat form of this gene that has been found to be overrepresented in children with ADHD. 47 Such a finding is quite interesting, because this gene has previously been associated with the personality trait of high novelty-seeking behavior; because this variant of the gene affects pharmacological responsiveness; and because the gene’s impact on postsynaptic sensitivity is primarily found in frontal and prefrontal cortical regions believed to be associated with executive functions and attention. 49 The finding of an overrepresentation of the seven-repeat DRD4 gene has now been replicated in a number of other studies, not only of children with ADHD, but also of adolescents and adults with the disorder. 42 , 48

Monitoring the correspondence between the intended and actually executed action, a fundamental mechanism of behavioral regulation, is reflected by error-related negativity (ERN), an ERP component generated by the anterior cingulate cortex. Based on this process assumption, a study by LaHoste et al . 50 examined genetic influences on the ERN and other components related to action monitoring (correct negativity, CRN, and error positivity, P e ). A flanker task was administered to adolescent twins (age 12) including 99 monozygotic (MZ) and 175 dizygotic (DZ) pairs. Genetic analysis showed substantial heritability of all three ERP components (40-60%) and significant genetic correlations between them. This study provides the first evidence for heritable individual differences in the neural substrates of action monitoring and suggests that ERN, CRN, and P e can potentially serve as endophenotypes for genetic studies of personality traits and psychopathology associated with abnormal regulation of behavior. 50

Cognitive genetics

The sequencing of the human genome and the identification of a vast array of DNA polymorphisms has afforded cognitive scientists with the opportunity to interrogate the genetic basis of cognition with renewed vigor. Advances in the understanding of the neural substrates of sustained and spatial attention arising from the cognitive neurosciences can help guide putative linkages in cognitive genetics. 51 In line with catecholamine models of sustained attention, associations have been reported between sustained attention and allelic variation in the dopamine beta hydroxylase gene ( DBH ), the dopamine D2 and D4 receptor genes ( DRD2, DRD4 ) and the dopamine transporter gene ( DAT1 ). 51 Much evidence implicates the cholinergic system in spatial attention. Accordingly, individual differences in spatial attention have been associated with variation in an alpha-4 cholinergic receptor gene (CHRNA4). APOE-4 allele dosage has been shown to influence the speed of attentional reorienting in independent samples of nonaffected individuals. Preliminary evidence in both healthy children and children with ADHD suggests association with variants of the DAT1 gene and the control of spatial attention across the hemifields. 51

Fronto-striatal circuitry in attention deficit hyperactivity disorder

Imaging studies using positron emission tomography (PET), and magnetic resonance imaging (MRI) techniques have implicated the fronto-striatal circuitry in ADHD, an area rich in dopaminergic activity. However certain meta-analytic studies have questioned the robust association between dopaminergic genes and ADHD. 52 Other candidate genes have also been investigated including serotonin transporter genes. 53 Genetic investigations aim to examine whether different genes contribute to specific aspects of ADHD. For example, a meta-analysis by Bellgrove and Mattingley has shown that the dopamine transporter gene DAT1 is more closely associated with the ADHD combined sub-type than with the inattentive +sub-type. 54 Future molecular genetic studies aim to examine gene-environment interactions, the extent to which environmental factors moderate genetic risks for ADHD. As well as gene-gene interactions, the extent to which having a cocktail of different genetic influences might elevate risk for ADHD.

Brain structure

A wealth of literature has examined the anatomical structure of the brain in children with ADHD. Using brain scanning technology such as MRI these studies suggest that the brain circuits linking the prefrontal cortex, striatum and cerebellum are not functioning normally in children with ADHD. 55 Further evidence has examined the relationship between brain structure and behavioral measures of inhibition and attention. These results suggest that compromised brain morphology of selected regions is related to behavioral measures of inhibition and attention. 56 Another study suggests that abnormalities in circuits important for motor response selection contribute to deficits in response inhibition in children with ADHD. 57 This lends support to the growing awareness of ADHD-associated anomalies in medial frontal regions which are important for the control of voluntary actions. Studies using PET to assess cerebral glucose metabolism have found diminished metabolism in adults with ADHD, particularly in the frontal region. 58 , 59 Using a radioactive tracer that indicates dopamine activity, 60 found abnormal dopamine activity in the right midbrain region of children with ADHD, and discovered that severity of symptoms was correlated with the degree of this abnormality. Another study pointed that children with ADHD were found to have a smaller corpus callosum, particularly in the area of the genu and splenium and that region just anterior to the splenium. 61 Interestingly, the study by Zametkin et al. 62 also found smaller cerebellar volume in those with ADHD. This would be consistent with views that the cerebellum plays a major role in executive functioning and the motor presetting aspects of sensory perception that derive from planning and other executive actions. 63 MRI showed no differences between groups in the regions of the corpus callosum in either of the other studies. 62 , 64 Further investigations of anatomical structure may allow the development of pharmacological interventions for ADHD, 65 which are better targeted to specific sites of action in the brain.

Neurobiology of attention deficit hyperactivity disorder

Neurobiology of ADHD has been another valued topic of investigation. 66 Researchers describe at least 11 different neuroanatomical theories of ADHD. 67 These theories can be categorized into two domains. The bottom-up theories propose disturbances in subcortical regions, such as the thalamus, and hypothalamus and reticular activating systems are responsible for ADHD symptomology. The top-down theories attribute the dysfunction to frontal and prefrontal and sagittal cortices. Smaller frontal lobe or right prefrontal cortex was found for the ADHD groups in all studies that examined this measure. Five of six studies found a smaller anterior or posterior corpus callosum. Four of six found loss of the normal caudate asymmetry, and these four also found a smaller left or right globus pallidus. 68 Neuroimaging studies of children with ADHD have investigated and found evidence of abnormalities in the frontal cortex, basal ganglia, corpus callosum, and cerebellum. 69-72 The cerebellum is functionally linked with the pre-frontal cortex, and three anatomical measures, namely the right globus pallidus volume, caudate asymmetry, and left cerebellum volume, correlate highly with ADHD in children. 68 Preliminary evidence has not found differences in the thalamus in children with ADHD. 62 , 73

Role of the basal ganglia

The role of the basal ganglia in ADHD has been given serious importance in neuropsychological research. The basal ganglia are a collection of large subcortical structures that can be divided into two sets of core structures: i) the striatum consisting of the caudate, putamen, and ventral striatum and ii) the pallidum or globus pallidus consisting of the external segment, internal segment, and ventral pallidum. The striatum receives input from the entire cerebral cortex, thalamus, substantia nigra, and amygdala and sends projections to the pallidum and substantia nigra. The pallidum sends input to the thalamic nuclei and additional subcortical nuclei, where information will be sent back to the frontal or pre-frontal cortex. 74 The organization of the striatum is important in the execution of motor planning, sequencing, and coordination, as well as feedback and learning after motor execution, 75 suggest that the striatum serves as a crossroads , combining sensory-motor information with emotional processing from the amygdala and dopamine mediated reinforcement. The primary neurotransmitter involved in modulation of the basal ganglia is dopamine, and disruption of this system has been found in ADHD. Initial studies found higher levels of the dopamine metabolite, and homovanillic acid in cerebral spinal fluid were positively correlated with the amount of hyperactivity in boys. 62 A recent genetic study found that alleles of the gene encoding dopamine beta hydroxylase, an enzyme that breaks down dopamine, may be related to the expression of ADHD. 76 Further support for dopamine dysfunction in ADHD comes from a functional MRI study that found children with ADHD had reduced activity in the frontal-striatal regions and impaired performance on response inhibition tasks. 77 Additionally, methylphenidate, which acts on the dopamine transporter (DAT), increased both frontal-striatal activity and performance on response inhibition tasks. A study using single PET-CT found that adults with ADHD had increased levels of striatal DAT compared to normal controls, which may lead to decreased availability of striatal dopamine in ADHD. 78

Research on the role of the basal ganglia in ADHD has primarily focused on the caudate. 79 The caudate has been implicated in a complex loop , receiving information from the association cortices and indirectly sending it via the thalamus to the prefrontal cortex. 80 Studies have found neuroanatomical differences in the caudate of children with ADHD with mixed results. 56 , 62 ,69, 81-83 Found that boys with ADHD had a smaller right caudate; recently, this finding was not replicated in ADHD girls. 69 In boys with ADHD, smaller right caudate volumes were found to significantly correlate with poor accuracy on sensory selection tasks, and left and right caudate volumes were negatively correlated with mean reaction times. 81 Conflicting results found ADHD adolescents had larger right caudate than normal adolescents, and the right caudate volume was associated with poorer performance on attention tasks and higher ratings of hyperactivity and impulsivity. 83 Another study found that children with ADHD had smaller left caudate volumes. 73 , 82 More recently, Manor et al . 56 reported that boys with ADHD were found to have a decreased volume of the left head of the caudate. These children were also more likely to show a reversed caudate asymmetry when compared to healthy controls, with the left being smaller than right. Moreover, a significant relationship between the reduction in left caudate volume and performance on behavioral inhibition tasks was found. In addition, children displaying reversed caudate asymmetry (L<R) were more likely to perform poorly on tasks of behavioral inhibition and attention regardless of group membership. 56 , 81 It has been also previously found that reversed caudate asymmetry was related to deficits in response execution tasks in ADHD. This evidence suggests that asymmetry of the caudate regardless of volume has important implications in attention and behavioral control. Finally, functional imaging studies have found decreases in blood flow to the caudate in ADHD. 62 , 84

Role of the putamen

The role of the putamen has also been studied as an etiological factor for the ADHD. 85 The putamen is hypothesized to be part of the motor loop because it receives information from the sensory-motor cortex and then sends it indirectly back to the premotor regions of the frontal cortex. Based on the putamen’s anatomical connections and function, a role for the putamen in ADHD is possible although currently unclear because of equivocal evidence. 80 There are relatively few studies investigating the neuroanatomical role of the putamen in ADHD. 69 Another study have not found volumetric differences in the putamen between children with ADHD and healthy controls. 62 In addition, they found that the volume of the putamen did not correlate with performance on response inhibition tasks. However, two studies suggest that the putamen may actually be important in the expression of ADHD symptomology. Researchers found that the ADHD diagnosis was significantly associated with the titer of two ant streptococcal antibodies. 86

In addition, they found that higher antibodies titers were associated with larger volumes in the left putamen and right globus pallidus in children with ADHD. 86 Although this study found structural evidence for the role of the putamen in ADHD, the second study demonstrates functional differences in the putamen of children with ADHD. Recent advances in functional MRI technology have provided new methods to investigate blood flow to various regions of the brain. Functional MRI relaxometry allows researchers to investigate the resting or steady state conditions and medication-related changes and were able to indirectly assess blood volume to the striatum (caudate and putamen). 75 They found that blood flow to both sides of the putamen was decreased in ADHD children compared to normal children. In addition, they found that blood flow to the left was more decreased than blood flow to the right side. They found no differences in blood flow to the thalamus and caudate, although there was a non-significant trend in the right caudate. Methylphenidate administration significantly altered the blood flow to the right and left putamen, and changes were correlated to the child’s unmedicated state.

There were no significant differences in blood flow to the caudate off or on medication. Filipek et al . 75 found strong associations between measures of activity and inattention with T2-RT measures in the putamen. They propose that ADHD symptoms are closely related to functional abnormalities in the putamen, which is closely involved in the control of motor behavior. These hypotheses lay the foundation for our study of the neuroanatomy of the putamen in children with ADHD. Investigators in their study using magnetic resonance imaging scans of boys in residential treatment with symptoms of ADHDand psychopathic traits found no differences in the total, left and right putamen volumes across the ADHD or control group. A significant reversal of asymmetry across groups was found; children with ADHD more frequently had a smaller left putamen than right. In contrast, the control group more frequently has a smaller right than left putamen.

Several studies have examined cerebral blood flow using single-photon emission computed tomography (SPECT) in children with ADHD and normal children. 68 , 72 They have consistently shown decreased blood flow to the prefrontal regions (most recently in the right frontal area), and to pathways connecting these regions with the limbic system via the striatum and specifically its anterior region known as the caudate, and with the cerebellum. 87 , 88

Neuropsychology of attention deficit hyperactivity disorder

Studies examining the neuropsychology of ADHD provide an opportunity to understand the relationship between underlying biological processes and symptoms of ADHD. For many years it was accepted that symptoms of ADHD were the result of cognitive dysregulation. 89 The behavior of a child with ADHD resulted from insufficient forethought, planning and control. 90 Evidence to support this view point came from many studies using neuropsychological tests which demonstrated that children with ADHD performed less well on these tests than did matched controls to match familiar figures, children with ADHD demonstrated more impulsive responding and higher error rates than did matched controls. 91 , 92

Cognitive dysregulation

A summary of ADHD as a disorder of cognitive dysregulation suggested that the relationship between biology and behavior in children with ADHD was mediated by inhibitory dysfunction. 93 In contrast to the dominant view, researchers offered an alternative view of ADHD, not as a disorder of cognitive dysregulation, but as a motivational style. This viewed ADHD as a functional response by the child, aimed at avoiding delay. This alternative viewpoint of ADHD was based on other studies, 92 which showed that most of the neuropsychological evidence to support ADHD as a result of cognitive dysregulation was confounded by delay. To demonstrate this, researchers got children with ADHD and match control children to participate in the matching familiar figures test, and found the same results as previous studies. 92 Children with ADHD made more impulsive responses and more errors. However, researchers pointed out that all these studies involved trial constraints where as soon as one trial ended the next began and were confounded with delay. 92 In order words, children with ADHD made more impulsive responses because it allowed them to complete the task quicker and therefore escape delay. When researchers re-ran their study under time constraint (for a fixed period of time where early or impulsive responses had no influence on delay), children with ADHD performed no differently from controls. 92 Results of these studies lead to the development of the delay aversion hypothesis, 94 which characterized the influence of delay on behavior dependent upon whether the child has control over their environment or not. When the child is in control of their environment they can choose to minimize delay by acting impulsively, e.g. by skipping the queue at the end of the slide! When the child is not in control of their environment, or at least where they are expected to behave in certain ways or face sanctions, the child would choose to distract themselves from the passing of time. For example, in a classroom context during literacy lessons the child could achieve this either by daydreaming (inattention) or by fidgeting (hyperactivity). A summary of ADHD as a motivational style suggests that the relationship between biology and behavior in ADHD is mediated by delay aversion.

Traditionally these two different accounts of ADHD have both sought to independently explain the disorder. However, a study by Sonuga-Barke et al . 95 compared the measurement of both of these hypotheses in a head-to-head study. Results of this study showed that measures used to test each hypothesis were uncorrelated, demonstrating that they measured different constructs. Both sets of measures were correlated with ADHD, and when combined were highly diagnostic, correctly distinguishing 87.5 of cases from non-cases. These results suggested that both accounts appeared to help to explain ADHD, but that neither explanation was the single theory of ADHD which both theoretical camps had been searching for. Based on these findings, researchers proposed his dual pathway model of ADHD. 93 This model proposed two possible routes between biology and ADHD behavior. The first one is through cognitive dysregulation and another via motivational style. Clinically the dual pathway model suggests that there may be merit in targeting different sub-types with specific treatments, as well as allowing the development of novel interventions, perhaps aimed at desensitizing delay. Some have suggested ways in which the greater understanding about the influence of delay aversion on the development of ADHD could be used to develop alternative interventions. 93 , 96 These suggestions include the use of delay fading, a technique to systematically reorganize the child’s delay experience, as a means of increasing tolerance for delay, and reducing ADHD symptoms.

Some studies have not found a greater incidence of prenatal (pregnancy or birth complications) in children with ADHD compared to normal children whereas others have found a slightly higher prevalence of unusually short or long labor, fetal distress, low forceps delivery, and toxemia or eclampsia in children with ADHD. 97 Nevertheless, though children with ADHD may not experience greater pregnancy complications, prematurity, or lower birth-weight as a group, children born prematurely or who have markedly lower birth-weights are at high risk for later hyperactivity or ADHD.

Researchers found that smoking and maternal stress during the pregnancy is associated with onset of ADHD during early childhood. Similarly observed that parental smoking during pregnancy predicts non-responsiveness to intervention targeting ADHD symptoms in elementary school children. Hartsough et al . observed that behavioral symptoms of ADHD were predicted by a lower ponderal index (kg/m 3 ), 98 a smaller head circumference, and a smaller head-circumference-to-length ratio. Length of gestation, mother’s age, tobacco and alcohol during pregnancy and pre-pregnancy, body mass index or parity, the monthly gross income of family, child’s BMI at the age of five or six years or gender didn’t have any significant effect on the behavioral symptoms of ADHD at the age of five or six.

Exposure to environmental toxins

Exposure to environmental toxins specifically lead has also been reviewed as a causal factor for ADHD. An amazing variety of toxins extent in the modern environment have deleterious effects on the central nervous system that range from severe organic destruction to subtle brain dysfunction. 99 , 100 Toxic metals are ubiquitous in the modern environment, as are organohalide pesticides, herbicides, and fumigants, and a wide range of aromatic and aliphatic solvents. 101 All these categories of environmental pollutants have been linked to abnormalities in behavior, perception, cognition, and motor ability that can be subtle during early childhood but disabling over the long term. 102 Children exposed acutely or chronically to lead, arsenic, aluminum, mercury, or cadmium are often left with permanent neurological sequelae that include attentional deficits, emotional lability, and behavioral reactivity. 101 Elevated body lead burden has been shown to have a small but consistent and statistically significant relationship to the symptoms of ADHD. 103 , 104 However, even at relatively high levels of lead, fewer than 38% of children in one study were rated as having the behavior of hyperactivity on a teacher rating scale, 104 implying that most lead-poisoned children do not develop symptoms of ADHD. And most children with ADHD likewise, do not have significantly elevated lead burdens. 105

Environmental influences

Environmental influences on ADHD have also been reviewed extensively. Attention deficit hyperactivity disorder is best viewed as a gene × environment interaction. 106 Children who have a genetic predisposition will express the disorder when put in the correct environment, typically one characterized by chaotic parenting. 107 The best evidence for environmental influences on ADHD come from intervention studies which have demonstrated improvements in ADHD symptoms, when parents have been taught alternative parenting skills. 108 , 109 Results of these studies do not necessarily imply that parents of children with ADHD are bad parents. In fact, influence of parenting on ADHD is best viewed from an interactionist viewpoint. The relationship between ADHD and parenting may result from both negative aspects of the child influencing the parents’ behavior, and negative aspects of the parents influencing the child’s behavior. Studies examining mother-child interaction have found that children with ADHD are less often on task, less compliant, less responsive and more active than controls; researchers investigated both mother-son and father-son interactions and found that parents of boys with ADHD were more demanding, aversive and power assertive; 110-112 while the findings of Buhrmester et al. 113 have demonstrated that mothers of children with ADHD have been found to be more negative, controlling, intrusive and disapproving, and less rewarding and responsive than mothers of children without ADHD.

Research finds that ADHD affects the interactions of children with their parents, and hence the manner in which parents may respond to these children. 114 Those with ADHD are more talkative, negative and defiant; less compliant and cooperative; more demanding of assistance from others; and less able to play and work independently of their mothers. 115-118 Their mothers are less responsive to the questions of their children, more negative and directive, and less rewarding of their children’s behavior. 107 , 116 Mothers of children with ADHD have been shown to give both more commands and more rewards to sons with ADHD than to daughters with the disorder, 119 , 120 but also to be more emotional and acrimonious in their interactions with sons. 112 Children and teens with ADHD seem to be nearly as problematic for their fathers as their mothers. 112 , 118 , 121 Contrary to what may be seen in normal mother-child interactions, the conflicts between children and teens with ADHD (especially boys) and their mothers may actually increase when fathers join the interactions. 112 , 121 So while parents of children with ADHD may engage in less than optimal parenting, it is easy to see how such responses might have evolved.

In addition, genetic studies highlight the familial basis of ADHD. 122 , 123 Children with ADHD are more likely to have a parent with ADHD. ADHD symptoms in parents usually interfere with consistent and appropriate parenting. Researchers found that ADHD in parents prevented effective parental monitoring and consistent use of constructive parenting techniques. 124 Other researchers found that parental ADHD symptoms were associated with lax discipline, 125 while Harvey et al. 126 found that high ADHD symptoms in mothers were a barrier to successful psychosocial intervention for pre-school children with ADHD.

Most widely researched and commonly prescribed treatments for ADHD are the psychostimulants, including methylphenidate, amphetamine, and pemoline. 2 , 127 Several studies have demonstrated the short-term efficacy of stimulant compared to placebo conditions in improving both core ADHD symptoms and important ancillary features of the disorder. 128 Controlled studies of stimulants have shown their effect on reducing interrupting in class, reducing task-irrelevant activity in school, improving performance on spelling and arithmetic tasks, improving sustained attention during play, and improving parent-child interaction.

Meaningful effects have been documented across a wide array of outcome domains, cognitive attentional performance, school behavior, and learning, parent-child interactions, interaction with peers, and with a wide variety of assessment approaches, direct observations of behavior in natural and laboratory settings, and objective laboratory performance. 129

Diet is another environmental influence, often cited by parents as having an adverse influence on the ADHD symptoms of their child. 130 Specifically, food additives, refined sugars and fatty acid deficiencies have all been associated with ADHD symptoms. 131

However, the majority of this literature comes from older studies, with a variety of methodological problems, and small sample sizes. 131 In fact, a large recent randomized control trial examined the influence of food colorings and benzoate preservatives on pre-school hyperactivity. Results demonstrated a general adverse effect of food coloring and benzoate preservatives on hyperactive behavior of preschool children, based on parental reports, but not on simple clinic assessment. Children with high levels of hyperactivity were no more vulnerable to this effect than children with low levels of hyperactivity. 132 While improving children’s diet might impact on their general health and improve their overall behavior, the clinical importance of dietary change as a means of remediating ADHD remains doubtful. 133

Co-morbidity

ADHD appears to be associated with a wide variety of other psychiatry problems, which are often co-morbid with it. ADHD co-occurs with other childhood disorders far more often than it appears alone. 134 Notable associations exist with Oppositional Defiant Disorder (ODD), Conduct Disorder (CD), tic disorder, mood disorder, autism spectrum disorder, specific learning disorder such as dyslexia, 135 , 136 depression and anxiety. About 50-60% of children with ADHD meet criteria for ODD, even in the pre-school period. 137 Busch and colleagues (2002) reported that ADHD children in primary care settings were significantly more likely than non-ADHD clinic controls to demonstrate mood disorders (57%) such as depression, multiple anxiety disorders (31%), and substance use disorders (11.5%). However, in the recent British Child Mental Health Survey, 138 anxiety was not associated with ADHD when adjustment was made for the presence of a third disorder. It is widely accepted that ADHD is a co-morbid disorder. Copeland et al. 135 point out that co-morbidity can mean a common underlying etiology which leads to two or more different disorders, or that one disorder leads to another, or even that two unrelated disorders co-occur. The term co-morbid also implies that their entities are morbid conditions, i.e. diseases. High rates of comorbidity with either other neurodevelopmental disorders ( e.g ., mental retardation, and learning disabilities) or psychiatric disorders ( e.g ., anxiety) make delineation of the phenotype difficult. 139

Some studies found that 47% children with ADHD have co-morbid ODD, 140-142 27% have anxiety disorder and 7% have mood disorder. 38% of children with ADHD were found to have CD and 13% have depression. In fact, the vast majority of co-morbidities with ADHD represent functional impairments and symptoms, which are not rooted in specific diseases. 135 Studies of clinic-referred children with ADHD find that between 54% and 67% will meet criteria for a diagnosis of ODD by 7 years of age or later. ODD is a frequent precursor to CD, a more severe and often (though not always) later occurring stage of ODD. 143. The co-occurrence of CD with ADHD may be 20-50% in children and 44-50% in adolescence with ADHD. 144 By adulthood, up to 26% may continue to have CD, while 12–21% will qualify for a diagnosis of antisocial personality disorder (ASPD).

In addition to associations with other psychiatric disorders children with ADHD are also more likely than their non-ADHD counterparts to experience a substantial array of developmental, social and health risks. It therefore seems important to discuss associated problems along with co-morbidity.

Motor coordination

Children with ADHD often demonstrate poor motor co-ordination or motor performance and balance. 145-147 Substantial evidences have been observed for problems in motor development and motor execution children with ADHD. 148 Clinical and epidemiological studies report that 30% to 50% of children with ADHD suffer from motor coordination problems. 146 These percentage are dependent of the type of motor assessment, referral sources and the cut-off points used. 149-151 As noted by Needleman et al ., 105 children with ADHD display greater difficulties with the development of motor coordination, planning and execution of complex, lengthy tasks, and novel chains of goal directed responses.

Academic functioning

Children with ADHD have an impaired academic functioning and are usually at an educational disadvantage upon school entry. 152 , 153 ADHD children are more likely than their non-ADHD peers to demonstrate difficulties with basic mathematics and pre-reading skills during their first year at school. 147 , 154 , 155 Executive academic functions were found to be core deficits specific to ADHD. Girls with ADHD were found to be less impaired than boys with ADHD. 156 Even pre-school children with ADHD demonstrate educational disadvantage, DuPaul et al . 157 demonstrated that their sample of pre-school ADHD children demonstrated deficits in pre-academic skills even prior to formal school entry. The pre-school ADHD children in their sample scored on average one standard deviation lower on the Battelle Developmental Index, 158 than did their non-ADHD control group. Researchers emphasized the importance of look away behavior (inattention) as a major reason for poor academic achievement. 159

Clinic-referred children with ADHD often present with lower scores on intelligence tests than control groups, specifically verbal intelligence with differences ranging from 7 to 10 standard score points. 160 Studies with community samples of ADHD children have also demonstrated negative associations between ADHD and intelligence. 161 , 162

Children with ADHD demonstrate serious difficulties with psychosocial functioning. Social adjustment is often given little attention on assessment protocols, given its designation as an associated feature of ADHD. 15 However, the high levels of disruptive behavior demonstrated by ADHD children increases the likelihood of negative reactions from parent, teachers and also peers. 163 In addition, negative social interactions with peers ultimately lead to peer’s rejection, 164 because these social difficulties are often resistant to psychosocial and pharmacological treatment, 165 they are expected to continue into adolescence, and even adulthood when criteria for the disorder may no longer be met. 166 The patterns of disruptive, intrusive, excessive, negative, and emotional social interactions that have been found between children with ADHD and their parents, have also been found to occur in the children’s interactions with teachers and peers. 157 , 167 , 168 It should come as no surprise, then, that those with ADHD receive more correction, punishment, censure, and criticism than other children from their teachers, as well as more school suspensions and expulsions, particularly if they have ODD/CD. 168 , 169 In their social relationships, children with ADHD are less liked by other children, have fewer friends, and are overwhelmingly rejected as a consequence, 170 particularly if they have comorbid conduct problems. 107 , 125 , 171 , 172 Another research study demonstrated that the co-occurrence of conduct disorder and anxiety disorder with ADHD in childhood predicted a more severe course for ADHD in adolescence. 173

Unintentional physical injury

Children with ADHD appear to be at a greater risk for unintentional physical injury and accidental poisoning. 157 , 174 In one of the first studies of the issue, Stewart and colleagues found that four times as many hyperactive children as control children (43% vs . 11%) were described by parents as accidentprone. Later studies have also identified such risks; up to 57% of children with hyperactivity or ADHD are said to be accident-prone by parents, relative to 11% or fewer of control children. 175 , 176 Most studies find that children with ADHD experience more injuries of various sorts than control children. In one study, 16% of the hyperactive sample had at least four or more serious accidental injuries (broken bones, lacerations, head injuries, severe bruises, lost teeth, etc.), compared to just 5% of control children. 2 , 177 found that 68% of children with DSM-IV-TR ADD, compared to 39% of control children, had experienced physical trauma sufficient to warrant sutures, hospitalization, or extensive/painful procedures. Several other studies likewise found a greater frequency of accidental injuries than among control children. Researchers found that children with ADHD were at a greater risk for suffering fractures, 178 most likely as a result of hyperactive and impulsive behavior. Children with AD/HD are also more likely than their non-ADHD counterparts to be injured as pedestrians, to inflict injuries to themselves, to sustain injuries to multiple body regions and to experience head injury. 179 Knowledge about safety does not appear to be lower in these children; implying interventions aimed at increasing knowledge about safety may have little impact. 180

Sleep disturbances

Studies report an association between ADHD and sleep disturbances found that sleep problems occurred twice as often in ADHD as in control children. 181-184 The problems are mainly more behavioral and include settling difficulties, a longer time to fall asleep, and instability of sleep duration, tiredness at awakening or frequent night waking. The direction of effect, between ADHD and sleep problems is unclear. It is possible that sleep difficulties increase ADHD symptoms during the daytime, as the research on normal children implies. 105 Yet some research finds that the sleep problems of children with ADHD are not associated with the severity of their symptoms; this suggests that the disorder, not the impaired sleeping, is what contributes to impaired daytime alertness, inattention, and behavioral problems. 184 , 185

While knowledge about the associations between ADHD and other related variables is useful in terms of diagnostic profiles, less is known about the impact of related variables on the long-term outcome for the disorder. Even less is known about the specificity of these associated problems to ADHD. In the preschool years a wealth of evidence now exists comparing the symptoms of pre-school ADHD symptoms to its school-aged counterpart. Children with a pre-school variant of ADHD present with the same symptom structure, 186 , 187 similar associated impairment and developmental risk, 187 and similar patterns of neuropsychology. 188 Despite the similarities between pre-school ADHD and school-aged ADHD, little is known about what constitutes impairment during the pre-school years although school readiness should be what clinicians focus on. And even less is known about the relationship between early hyperactivity and later expression of the ADHD disorder. 189

While originally conceived of as a disorder of childhood and adolescence, evidence suggests scientific merit and clinical value in examining ADHD in adulthood, 40 , 189 as well as the pre-school period. 189 ADHD symptoms have been shown to persist into later life with up to 40% of childhood cases continuing to meet full criteria in the adult years. 190 , 191 Adult ADHD appears to share many characteristics of the childhood disorder. Similar to their childhood counterparts, adults with ADHD display impairment in the interpersonal, vocational and cognitive domains. 192-194 The adult and childhood disorders also appear to share a common neuropathology, 195 , 196 and demonstrate a similar response to treatment. 197

Conclusions

We have discussed two different possible causes of ADHD in neurological research. The top down theory says that ADHD begins with frontal and pre-frontal lobe dysfunction. The other theory says that the sub-cortical regions, the thalamus and the hypothalamus are responsible for ADHD. Neuro-imaging doesn’t show abnormality in the thalamus, but does show changes in the frontal and prefrontal area. Researchers agree that genetic factors are a strong contribution to the occurrence of ADHD.

DSM-IV has an aura of scientific legitimacy, many authors have written about its shortcomings in terms of reliability and validity. 198 , 199 The primary function and goal of the DSM, 200 is to lend credibility to the claim that certain (mis) behaviors are mental disorders and that such disorders are medical diseases. Although the DSM-IV is often used when discussing mental illnesses, be it in a research setting or a clinical practice setting. Researchers apply points out that such extensive use does not in itself guarantee either its validity or reliability. 201 The DSM-IV is purely descriptive and presents no new scientific insights about the causes of the many mental disorders it lists. Despite a wide level of acceptance, ADHD is not an uncontested condition. 202 For example, another researcher has argued that ….the working dogma that ADHD is a disease or neurobehavioral condition does not at this time hold up . 203 , 204 A more recent perspective presented by Lollar has also stated that there are no valid neurological markers for the diagnosis of ADHD. 205 Additionally, Shaw et al . 206 observe that there is currently no verifiable objective evidence to support the claims of ADHD advocates. Given the lack of validity as a medical condition, it is important to ask why the label of ADHD is applied, and under what conditions?

Another researcher found no association between DAT1 and ADHD. 207 Another gene for which there have been many studies is the dopamine receptor D4, DRD4, on chromosome 11. Another researchers found no evidence of an association between ADHD and DRD4. 208 Environmental effects could also include child-specific experiences of salient environmental influences such as maternal lifestyle or parenting. 209 Childhood ADHD symptoms do remit across time for some, 4 , 210 but not all children. 209

Some of the controversial treatments have involved dietary management, herbs and antioxidants. The removal of artificial food colorings and preservatives from the diet is an indispensable and practicable clinical intervention in ADHD, but rarely is sufficient to eliminate symptomatology. 102 Up to 88 percent of ADHD children react to these substances in sublingual challenge testing, but in blinded studies no child reacted to these alone. Allergies to the foods themselves must also be identified and eliminated. 211 Sugar intake makes a marked contribution to hyperactive, aggressive, and destructive behavior. 212 , 213-222 Overall body of evidence currently does not support dietary use as sole therapy for ADHD. There is a group of children with ADHD who do not respond well to treatment. More resources should be made available to help them, through clinical research and clinical-based treatment. 214

The actual degree to which genetic heritability may predispose to childhood onset of ADHD is still an open question. 102 Population studies indicate attentional problems, conduct problems, and emotional problems tend to cluster within families. 215 , 223 , 224 Genetics and environment are notoriously difficult to separate within the family unit, and researchers suggested the genetic predisposition to ADHD might fuel a negative family atmosphere that exacerbates latent ADHD in the child, 102 , 225 , 226

It is unknown whether the association of motor coordination problems with ADHD is comparable across ages. The limitation in daily life caused by poor motor performance varies with age. 146 Four to six years old children mainly have problems with dressing, use of scissors, drawing, trying shoelaces, and riding a bike. Children seven to ten years old encounter difficulties in writing, dressing, swimming, constructional play, ball skills and outdoor play, while eleven to nineteen year olds have problems of clumsiness in writing, drawing, ball skills, poor table manners and tool use. 218

Research on long term effects and safety of ADHD medications has been especially lacking. 36 , 219 According to researchers of a study of psychotropic drugs used with preschoolers, earlier ages of initiation and longer duration of treatment means that the possibility of adverse effects on the developing brain cannot be ruled out . Another research study of longer term ADHD treatments suggested the side effects such as depression, worrying, and irritability from ADHD medications. 227 , 228 In some of these children, drug therapy is insufficient because of persistent symptoms of coexisting conditions. 228 , 229 Future studies will be needed to define the subgroups clearly. There is much to learn about it.

ADHD Research Paper

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Get 10% off with 24start discount code, i. introduction.

II. Historical Context

III. Description and Diagnosis

A. The Core Symptoms

B. associated cognitive impairments, iv. theoretical framework.

V. Potential Etiologies

VI. Epidemiology of ADHD

Vii. developmental course and adult outcome, viii. diagnostic criteria, ix. conclusion.

X. Bibliography

It is not unusual for young children to be energetic and active, or to become bored quickly and move from one activity to another as they explore their environment. A young child’s desire for immediate gratification is to be expected, rather than the restraint or self-control that would be demanded of someone older. However, some children persistently display levels of activity that are far in excess of their age group. Some are unable to sustain their attention to activities, their interest in tasks assigned to them by others, or their persistence in achieving long-term goals as well as their peers.

When a child’s impulse control, sustained attention, and general self-regulation lag far behind expectations for their developmental level, they are likely to be diagnosed as having ADHD. Children with ADHD have a greater probability of experiencing a number of problems in their social, academic, and emotional development and daily adaptive functioning.

Attention Deficit/Hyperactivity Disorder (ADHD) has captured public commentary and scientific interest for more than 100 years. While the diagnostic labels for disorders of inattention, hyperactivity, and impulsiveness have changed numerous times, the actual nature of the disorder has changed little, if at all, from descriptions provided at the turn of the century. During the past century, and especially during the last 30 years, thousands of published scientific papers have focused on ADHD, making it one of the most wellstudied childhood psychiatric disorders.

II. Historical Context of ADHD

Serious clinical interest in children who have severe problems with inattention, hyperactivity, and poor impulse control is first found in three published lectures by the English physician, George Still, presented to the Royal Academy of Physicians in 1902. Still reported on a group of 20 children in his clinical practice whom he defined as having a deficit in “volitional inhibition” or a “defect in moral control” over their own behavior. Still’s observations described many of the associated features of ADHD that would be supported by research almost a century later, such as an overrepresentation of boys compared to girls, the greater incidence of alcoholism, criminal conduct, and depression among the biological relatives, and a familial predisposition to the disorder.

Initial interest in children with these characteristics arose in North America around the time of the great encephalitis epidemics of 1917 and 1918. Children surviving these brain infections were noted to have many behavioral problems similar to those comprising contemporary ADHD. These cases, as well as others known to have arisen from birth trauma, head injury, toxin exposure, and infections, gave rise to the concept of a “brain-injured child syndrome,” often associated with mental retardation. This term was eventually applied to children without a history of brain damage or evidence of retardation but who manifested behavioral problems such as hyperactivity or poor impulse control. This concept would later evolve into that of “minimal brain damage,” and eventually “minimal brain dysfunction” (MBD), as challenges were raised to the label given the lack of evidence of brain injury in many of these cases.

During the 1950s researchers became increasingly interested in hyperactivity. “Hyperkinetic impulse disorder” was attributed to cortical overstimulation resuiting from ineffective filtering of stimuli entering the brain. These studies gave rise to the notion of the “hyperactive child syndrome” typified by daily motor movement that was far in excess of that seen in normal children of the same age.

By the 1970s research findings emphasized the importance of problems with sustained attention and impulse control in addition to hyperactivity in understanding the nature of the disorder. In 1983 Virginia Douglas proposed that the disorder was comprised of major deficits in four areas: (1) the investment, organization, and maintenance of attention and effort; (2) the ability to inhibit impulsive behavior; (3) the ability to modulate arousal levels to meet situational demands; and (4) an unusually strong inclination to seek immediate reinforcement. Douglas’ work, along with numerous subsequent studies of attention, impulsiveness, and other cognitive factors, eventually led to renaming the disorder “Attention Deficit Disorder” (ADD) in 1980.

Just as significant as the renaming of the condition at that time was the distinction made between two types of ADD: those with hyperactivity and those without it. Little research existed at the time on the latter subtype. However, later research suggested that ADD without hyperactivity might be a separate and distinct disorder of a different component of attention (selective or focused) than was the type of inattention seen in those with ADD with hyperactivity (persistence and distractibility). Thus, rather than being related subtypes of a single disorder with a shared, common impairment in attention, future research may show these subtypes to constitute separate disorders of attention altogether.

Within a few years of the creation of the label ADD, concern was raised by Barkley in 1990 and Weiss and Hechtman in 1993 that problems with hyperactivity and impulse control were features critically important to differentiating the disorder from other conditions and to predicting later developmental risks. In 1987 the disorder was renamed Attention Deficit Hyperactivity Disorder. Diagnostic symptoms were identified from a single list of items incorporating all three constructs: hyperactivity, impulsivity, and inattention. The subtype of ADD without Hyperactivity was now renamed Undifferentiated ADD and relegated to minor diagnostic status until further research could clarify its nature and relationship to ADHD.

Around this same time (mid-1980s to 1990s) reports began to appear that challenged the notion that ADHD was primarily a disturbance in attention. Over the previous decade, researchers studying information-processing capacities in children with ADHD were having difficulty demonstrating that the problems these children had with attending to tasks were actually attentional in nature (i.e., related to the processing of incoming information). Problems in response inhibition and preparedness of the motor control system appeared to be more reliably demonstrated. Researchers, moreover, were finding that the problems with hyperactivity and impulsivity were not separate constructs but formed a single dimension of behavior. All of this led to the creation of two separate lists of symptoms for ADHD when the latest diagnostic manual for psychiatry, The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (also known as the DSM-IV) was published by the American Psychiatric Association in 1994. In the DSM-IV, one symptom list now existed for inattention and another for hyperactive-impulsive behavior. The inattention list once again permitted the diagnosis of a subtype of ADHD that consisted principally of problems with attention (ADHD Predominantly Inattentive Type). But two other subtypes were also identified (Predominantly Hyperactive-Impulsive and Combined Types). As of this writing, debate continues over the core deficit(s) involved in ADHD, with increasing emphasis being given to a central problem specifically with behavioral inhibition and more generally with self-regulation or executive functioning.

III. ADHD Description and Diagnosis

Problems with attention consist of the child’s inability to sustain attention or respond to tasks or play activities as long as others of the same age or to follow through on rules and instructions as well as others. The child appears more disorganized, distracted, and forgetful than others of the same age. Parents and teachers frequently complain that these children do not seem to listen as well as they should for their age, cannot concentrate, are easily distracted, fail to finish assignments, daydream, and change activities more often than others.

Research corroborates that, when compared to normal children, ADHD children are often more “off-task,” less likely to complete as much work as others, look away more from the activities they are requested to do (including television), persist less in correctly performing boring activities, and are slower and less likely to return to an activity once interrupted. Yet objective research does not find children with ADHD to be generally more distracted by most forms of extraneous events occurring during their task performance, although distractors within the task may prove more disruptive to them than to normal children. Research instead documents that ADHD children are more active than other children, are less mature in controlling motor movements, and have considerable difficulties with stopping an ongoing behavior. They frequently talk more than others and interrupt others’ conversations. They are less able to resist immediate temptations and delay gratification and respond too quickly and too often when they are required to wait and watch for events to happen.

Recent research shows that the problems with behavioral or motor inhibition arise first, at age 3 to 4 years, with those related to inattention emerging somewhat later in the developmental course of ADHD, at age 5 to 7 years. Whereas the symptoms of disinhibition seem to decline with age, those of inattention remain relatively stable during the elementary grades. Yet even the inattentiveness may decline by adolescence in some cases.

A number of factors have been noted to influence the ability of children with ADHD to sustain their attention to task performance, to control their impulses to act, to regulate their activity level, and to produce work consistently. They include: time of day or fatigue; increasing task complexity where organizational strategies are required; extent of restraint demanded for the context; level of stimulation within the setting; the schedule of immediate consequences associated with the task; and the absence of adult supervision during task performance.

It has been shown that children with ADHD are most problematic in their behavior when persistence in work-related tasks is required (i.e., chores, homework, etc.) or where behavioral restraint is necessary, especially in settings involving reduced parental monitoring (i.e., in church, in restaurants, when a parent is on the phone, etc.). Such children are least likely to pose behavioral management problems during free play, when little self-control is required. Fluctuations in the severity of ADHD symptoms have also been documented across a variety of school contexts. In this case, classroom activities involving self-organization and task-directed persistence are the most problematic, with significantly fewer problems posed by contexts involving fewer performance demands (i.e., at lunch, in hallways, at recess, etc.), and even fewer problems posed during highly entertaining special events (i.e., field trips, assemblies, etc.).

Although ADHD is defined by the presence of the two major symptom dimensions of inattention and disinhibition (hyperactivity-impulsivity), research indicates that these children often demonstrate deficiencies in many other abilities. These include: motor coordination and sequencing; working memory and mental computation; planning and anticipation or preparedness for action; verbal fluency and confrontational communication; effort allocation; applying organization strategies; the internalization of self-directed speech; adhering to restrictive instructions; the self-regulation of emotions; and self-motivation. Several studies have also demonstrated what both Still (1902) and Douglas (1983) noted anecdotally years ago–ADHD may be associated with less mature or diminished moral reasoning and the moral control of behavior.

The commonality among most or all of these seemingly disparate abilities is that all fall within the neuropsychological domain described as executive functions. The neurologist Joaquim Fuster wrote in 1989 that these executive abilities are probably mediated by the frontal cortex of the brain, and particularly the prefrontal lobes. Barkley has recently defined executive functions as being those neuropsychological processes that permit or assist with human self-regulation. Self-regulation is then defined as any self-directed form of behavior (both overt and covert) that serves to modify the probability of a subsequent behavior by the individual so as to alter the probability of a later consequence. Such behavior may even involve forgoing immediate rewards for the sake of maximizing delayed outcomes or even exposing oneself to immediate aversive circumstances for this same purpose. Self-regulatory behavior, therefore, includes thinking within this realm of private or covert self-directed behavior. By appreciating the role of the frontal lobes and the prefrontal cortex in these executive abilities, it is easy to see why researchers have repeatedly speculated that ADHD probably arises out of some disturbance or dysfunction of this brain region.

Many different hypotheses on the nature of ADHD have been proposed over the past century, such as Still’s (1902) notion of defective volitional inhibition and moral regulation of behavior, and Douglas’ (1983) theory of deficient attention, inhibition, arousal, and preference for immediate reward. Few of these have produced models of the disorder that were widely adopted by both scientists and clinicians or that served to drive further programmatic research initiatives. Some of these theories have suggested that ADHD is a deficit in sensitivity to reinforcement, a more general motivational disorder, or a deficit in rule-governed behavior (i.e., the control of behavior by language). Most recently, several theorists working in this area have proposed that ADHD represents a deficit behavioral inhibition; an assertion for which there is substantial evidence, at least for those subtypes that involve hyperactive-impulsive symptoms.

Consistent with these proposals, Barkley outlined a model of ADHD in 1994 that was based upon an earlier theory by Jacob Bronowski first set forth in 1966 on the evolution of the unique properties of human language and their relationship to response inhibition. Bronowski’s model was subsequently combined with that of Juaquim Fuster published in 1989, which specified that the overarching role of the prefrontal cortex is the cross-temporal organization of behavior. Barkley’s hybrid theoretical model of ADHD places behavioral inhibition at a central point and supportive point in relation to four other executive functions dependent upon it for their own effective execution. These functions are working memory, the self-regulation of emotion/motivation, the internalization of speech, and reconstitution (analysis and synthesis of behavioral structures in the service of goal-directed behavioral creativity). The four functions are believed to permit and subserve human self-regulation, bringing behavior progressively under the control of internally represented information, often about the future, and transferring it at least partially away from the control of behavior by more immediate consequences and external events. The executive control of behavior afforded by these functions is proposed to result in a greater capacity for predicting and controlling one’s self and one’s environment so as to maximize future consequences over immediate ones for the individual. And, more generally, the interaction of these executive functions permits far more organized and effective adaptive functioning.

Several assumptions are important in understanding this model as it is applied to ADHD. First, the capacity for behavioral inhibition begins to emerge first in the child’s development, prior to or corresponding with the emergence of the four executive functions. Second, inhibition does not directly cause the activation of these executive functions but sets the occasion for their occurrence and is necessary for their effective performance. Third, these functions probably emerge at different times in the child’s development and may have relatively independent developmental trajectories, although interactive. Fourth, the sweeping cognitive impairments that ADHD creates across these executive functions are secondary to the primary deficit in behavioral inhibition, implying that if inhibition were to be improved, these executive functions would likewise improve.

The deficit in behavioral inhibition is thought to arise principally from genetic and neurodevelopmental origins, rather than from purely social ones, although its expression is certainly influenced by a variety of social factors. The secondary deficits in the executive functions and self-regulation created by the primary deficit in inhibition feedback to contribute to further deficits in behavioral inhibition because self-regulation is required for self-restraint.

Behavioral inhibition is viewed in the model as comprising three related processes: (1) the capacity to inhibit “prepotent” responses prior to their initiation; (2) the capacity to cease ongoing response patterns once initiated such that both (1) and (2) create delays in responding to events; and (3) the protection of this delay and the self-directed (often private or cognitive) actions occurring within it from interference by competing events and their prepotent responses (interference control). Prepotent responses are defined as those for which immediate reinforcement (both positive and negative) is available for their performance or for which there is a strong history of reinforcement in this context. Through the postponement of the prepotent, automatic responses and the creation of this protected period of delay, the occasion is set for the four executive functions to act effectively in modifying the individual’s eventual initial responding to events or modifying their ongoing responses to those events (creating a sensitivity to feedback or errors). The executive system described here may exist so as to achieve a net maximization of both temporally distant and immediate consequences rather than immediate consequences alone. The chain of goal-directed, future-oriented behaviors set in motion by these acts of self-regulation is then also protected from interference during its performance by this same process of inhibition (interference control). Even if disrupted, the individual retains the capacity or intention (via working memory) to return to the goal-directed actions until the outcome is successfully achieved or judged to be no longer necessary.

Space permits here only a brief description of each of the four executive components of this new model of ADHD. The first of these involves working memory, or the capacity for prolonging and manipulating mental representations of events and using such information to control motor behavior. This particular type of memory can be thought of as remembering so as to do and serves to sustain otherwise fleeting information that will be useful in controlling subsequent responding, such as is seen in privately rehearsing a telephone number in mind so as to later dial it accurately. One component of working memory may be related to self-speech (verbal working memory), while a second component is related to perceptual imagery (visual-spatial) and probably involves self-directed sensing, as in visual imagery or covert audition. This retention of information related to past events (retrospection) gives rise to the conjecturing of future events (prospection), which sets in motion a preparedness to act in anticipation of the arrival of these future events (anticipatory set). Out of this continuous referencing or sensing of past and future probably arises the psychological sense of time. These activities taking place in working memory appear to be dependent upon behavioral inhibition. Such working memory processes have been shown to exist in rudimentary form even in young infants permitting them to successfully perform delayed response tasks to a limited degree. As the capacity for inhibition increases developmentally, it probably contributes to the further efficiency and effectiveness of working memory.

According to this model of ADHD, behavioral inhibition also sets the stage for the development of the second executive component of this model, that being the self-regulation of emotion in children. The inhibition of the initial prepotent response includes the inhibition of the initial emotional reaction that it may have elicited. It is not that the child does not experience emotion; rather, the behavioral reaction to or expression of that emotion is delayed along with any motor behavior associated with it. The delay in responding this creates allows the child time to engage in self-directed behaviors that will modify both the eventual response to the event as well as the emotional reaction that may accompany it. Because emotions are themselves forms of both motivational and arousal states, the model argues that deficits in the self-regulation of emotion should be associated with deficits in self-motivation and the self-control of arousal, particularly in the service of goal-directed behavior.

The internalization of self-directed speech, as originally described by Vygotsky, forms the third executive component of this model of ADHD. During the early preschool years, speech, once developed, is initially employed for communication with others. As behavioral inhibition progresses, language becomes turned on the self. It now is not just a means of influencing the behavior of others but provides a means of reflection as well as a means for controlling one’s own behavior (instruction).

The fourth component of this model involves the capacity to rapidly take apart and recombine units of behavior, including language. The delay in responding that behavioral inhibition permits allows time for information related to the event to be mentally prolonged and then dissassembled so as to extract more information about the event that will aid in preparing a response to it. In a related fashion, previously learned response patterns can also be broken down into smaller units of behavior. This internal decomposition of information and its associated response patterns permits the complementary process to occur, that being synthesis, or the invention of novel combinations of behavioral structures, including words and ideas, in the service of goal-directed action. This gives a highly creative or generative character as well as a hierarchically organized nature to human goal-directed behavior.

Finally, the internally represented information and motivation generated by these four executive functions is used to control a separate unit within the model, that being motor behavior itself. Such information serves to program, execute, and sustain behavior directed toward goals and the future, giving human behavior an intentional or purposive quality. Task-irrelevant movement is now more effectively suppressed, goal-directed behavior better sustained, and this pattern of behavior more efficiently reengaged should disruption of the behavioral pattern occur because of the control afforded by the internal information being generated from the four executive functions.

The impairment in behavioral inhibition occurring in ADHD is hypothesized to disrupt the efficient execution of these executive functions, thereby limiting the capacity of these individuals for self-regulation. The result is an impairment in the cross-temporal organization of behavior, in the prediction and control of one’s own behavior and environment, and inevitably in the maximization of long-term consequences for the individual.

How does this model account for the problems with attention believed to exist in ADHD? According to this model, it is critical to distinguish between two forms of sustained attention that are traditionally confused in the research literature on ADHD. The first is called contingency-shaped attention. This refers to continued responding in a situation or to a task as a function of the immediate available contingencies of reinforcement provided by the task or its context. Responding that is maintained under these conditions then is directly dependent on the immediate environmental contingencies. Many factors affect this form of sustained attention or responding: the novelty of the task, the intrinsic interest the activity may hold for the individual, the immediate reinforcement it provides for responding in the task, the state of fatigue of the individual, and the presence or absence of an adult supervisor (or other stimuli which signal other consequences for performance that are outside the task itself). The model predicts that this type of sustained attention relatively unaffected by ADHD as it is behavior under the control of external events.

As children mature, however, a second form of sustained attention emerges described in the model as goal-directed persistence. This form of sustained responding arises as a direct consequence of the development of self-regulation or the control of behavior by internally represented information. Such persistence derives from the development of a progressively greater capacity by the child to hold events, goals, and plans in mind (working memory), to adhere to rules governing behavior and to formulate and follow such rules, to self-induce a motivational state supportive of the plans and goals formulated by the individual so as to maintain goal-directed behavior, and even to create novel behaviors in the service of the goal’s attainment. The capacity to initiate and sustain chains of goal-directed behavior in spite of the absence of immediate environmental contingencies for their performance is predicted to be the form of sustained attention disrupted by ADHD.

Apart from this heuristically valuable distinction in forms of sustained attention, this theoretical model of ADHD makes numerous predictions about the cognitive and behavioral deficits likely to be found in those with the disorder (i.e., impaired working memory and sense of time, delayed internalization of speech, etc.), many of which have received little or no attention in research on ADHD. It also provides a framework by which to better organize and understand the numerous cognitive deficits identified in previous studies of children with ADHD than does the current view of ADHD as being chiefly an attention deficit.

V. Potential Etiologies of ADHD

The precise causes of ADHD are unknown at the present time. Numerous causes have been proposed, but evidence for many has been weak or lacking entirely. However, a number of factors have been shown to be associated with a significantly increased risk for ADHD in children.

The vast majority of the potentially causative factors associated with ADHD that are supported by empirical research seem to be biological in nature; that is, they are factors known to be related to or to have a direct effect on brain development and/or functioning. The precise causal pathways by which these factors lead to ADHD, however, are simply not known at this time.

Even so, far less evidence is available to support any purely psychosocial etiology of ADHD. In the vast majority of cases where such psychosocial risks have been found to be significantly associated with ADHD or hyperactivity, more careful analysis has shown these to be either the result of ADHD in the child or, far more often, to be related to aggression or conduct disorder rather than to ADHD. For instance, the child management methods used by parents, parenting stress, marital conflict, or parental psychopathology have now been shown to be far more strongly associated with aggressive and antisocial behavior than with ADHD. The strong hereditary influence in ADHD may also contribute to an apparent link between ADHD and poor child management by a parent — a link that may be attributable to the parent’s own ADHD. The environment in which the child is raised and schooled probably plays a larger role in determining the outcomes of children with the disorder and a much lesser role in primary causation.

Throughout the century, investigators have repeatedly noted the similarities between symptoms of ADHD and those produced by lesions or injuries to the frontal lobes of the brain, particularly the prefrontal cortex. Both children and adults suffering injuries to the certain regions of prefrontal cortex demonstrate deficits in sustained attention, inhibition, working memory, the regulation of emotion and motivation, and the capacity to organize behavior across time.

Numerous other lines of evidence have been suggestive of a neurological origin to the disorder. Several studies have examined cerebral blood flow in ADHD and normal children. They have consistently shown decreased blood flow to the prefrontal regions of the brain and the striatum with which these regions are richly interconnected, particularly in its anterior portion. More recently, studies using positron emission tomography (PET) to assess cerebral glucose metabolism have found diminished metabolism in adults and adolescent females with ADHD although not in adolescent males with ADHD. However, significant correlations have been noted between diminished metabolic activity in the left anterior frontal region of the brain and severity of ADHD symptoms in adolescent males with ADHD. This demonstration of an association between the metabolic activity of certain brain regions and symptoms of ADHD is critical in demonstrating a connection between the findings pertaining to brain activation and the behavior comprising ADHD.

More detailed analysis of brain structures using high resolution magnetic resonance imaging (MRI) devices has also suggested differences in some brain regions in those with ADHD. Initial studies that focused on reading-disabled children and used ADHD children as a contrast group examined the region of the left and right temporal lobes (the planum temporale). These regions are thought to be involved with auditory detection and analysis and, therefore, with certain subtypes of reading disabilities. For some time, researchers studying reading disorders have focused on these brain regions because of their connection to the rapid analysis of speech sounds. Children with ADHD and children with reading disabilities were found to have smaller right hemisphere plana temporale than the control group, while only the reading disabled children had a smaller left plana temporale. In another study, the corpus callosum was examined in subjects with ADHD. This structure assists with the interhemispheric transfer of information. Those with ADHD were found to have a smaller callosum, particularly in the area of the genu and splenium and that region just anterior to the splenium. An attempt to replicate this finding, however, failed to show any differences between ADHD and control children in the size or shape of the entire corpus callosum with the exception of the posterior portion of the splenium, which was significantly smaller in subjects with ADHD. Two additional studies examining the corpus callosum, however, documented smaller anterior (rostral) regions in children with ADHD; findings more consistent with prior studies of brain anatomy and functioning in children with ADHD. Most recently, two studies using larger samples of ADHD and normal children and MRI technology have both documented a smaller right prefrontal cortex and smaller right striatum and right basal ganglia (of which the striatum is a part) in ADHD children. Thus, despite some inconsistencies in findings across some of the earlier studies of brain morphology and functioning in ADHD, more recent studies are increasingly identifying the prefrontal regions of the brain and certain regions of the basal ganglia, such as the striatum, as probably being involved in the disorder.

None of these studies found evidence of frank brain damage in any of these structures in those with ADHD. This is consistent with past reviews of the literature conducted by Michael Rutter in 1983 suggesting that brain damage was related to less than 5% of those with hyperactivity. It is also consistent with more recent studies of twins suggesting that nonshared environmental factors, such as pre-, peri-, and postnatal neurological insults, among other factors, account for approximately 15 to 20% of the differences among individuals in the behavioral pattern associated with ADHD (inattention and hyperactive-impulsive behavior). Where differences in brain structures are found, they are probably the result of abnormalities that arise in brain development (embryology) within these particular regions, the causes of which are not known but may have to do with particular genes responsible for the construction of these brain regions.

No evidence exists to show that ADHD is the result of abnormal chromosomal structures (as in Down’s Syndrome), their fragility (as in Fragile X) or transmutation, or of extra chromosomal material (as in XXY syndrome). Children with such chromosomal abnormalities may show greater problems with attention, but such abnormalities are very uncommon in children with ADHD.

By far, the preponderance of research evidence suggests that ADHD is a trait that is highly hereditary in nature, making heredity one of the most well substantiated among the potential etiologies for ADHD. Multiple lines of research support such a conclusion. For years, researchers have noted the higher prevalence of psychopathology in the parents and other relatives of children with ADHD. In particular, higher rates of ADHD, conduct problems, substance abuse, and depression have been repeatedly observed in these studies. Research such as that by Joseph Biederman and colleagues at the Harvard Medical School (Massachusetts General Hospital) shows that between 10 and 35% of the immediate family members of children with ADHD are also likely to have the disorder, with the risk to siblings of the ADHD children being approximately 32%. More recent studies even suggest that if either parent has ADHD, the risk to offspring for the disorder may be as high as 50%.

Another line of evidence for genetic involvement in ADHD has emerged from studies of adopted children, which have found higher rates of hyperactivity in the biological parents of hyperactive children than in adoptive parents of hyperactive children. Biologically related and unrelated pairs of international adoptees also identified a strong genetic component to the behavioral dimension underlying ADHD.

Studies of twins conducted in the United States, Australia, and the United Kingdom provide a third avenue of evidence for a genetic contribution to ADHD. In general, these studies suggest that if one twin is diagnosed with ADHD, the concordance for the disorder in the second twin may be as high as 81 to 92% in monozygotic twins but only 29 to 35% in dizygotic twins.

Quantitative genetic analyses of a large sample of families studied in Boston by Joseph Biederman and his colleagues suggest that a single gene may account for the expression of the disorder. The focus of research recently has been on the dopamine type 2 gene, given findings of its increased association with alcoholism, Tourette’s Syndrome, and ADHD. However, difficulties have arisen in the replication of this finding. More recent studies have implicated the dopamine transporter gene as being involved in ADHD as might the D4D repeator gene, which has shown an association with novelty-seeking and risk-taking personality traits. Clearly, research into the genetic mechanisms involved in the transmission of ADHD across generations will prove an exciting and fruitful area of research endeavor over the next decade as the human genome is mapped and better understood and as more sophisticated genetic technologies arising from this project come to be applied to the study of the genetics of ADHD.

Pre-, peri-, and postnatal complications, and malnutrition, diseases, trauma, and other neurologically compromising events may occur during the development of the nervous system before and after birth. Among these various biologically compromising events, several have been repeatedly linked to risks for inattention and hyperactive behavior. Elevated body lead burden has been shown to have a small but consistent and statistically significant relationship to the symptoms comprising ADHD. However, even at relatively high levels of lead, less than 38% of these children are rated as hyperactive on teacher rating scales, implying that most lead-poisoned children do not develop symptoms of ADHD. Other types of environmental toxins found to have some relationship to inattention and hyperactivity are prenatal exposure to alcohol and tobacco smoke.

The prevalence of ADHD, as reviewed by Peter Szatmari in 1992, using large epidemiological studies ranges from a low of 2 % to a high of 6.3 %, with most falling within the range of 4.2 to 6.3 %. Most studies have found similar prevalence rates in elementary school-aged children. Differences in prevalence rates are due in part to different methods of selecting these populations, to the criteria used to define a case of ADHD, and to the age range of the samples. For instance, prevalence rates may be 2 to 3% in females but 6 to 9% in males during the 6 to 12-year-old age period, but fall to 1 to 2% in females and 3 to 4.5 % in males by adolescence.

While the declining prevalence of ADHD with age may reflect real recovery from the disorder, it may also involve, at least in part, an artifact of methodology. This artifact results from the use of items in the diagnostic symptom lists across the life span that are were developed upon and chiefly applicable to young children. These items may reflect the underlying constructs of ADHD very well at younger ages but may be increasingly less appropriate for older age groups. This could create a situation where individuals remain impaired by ADHD characteristics as they mature, but outgrow the diagnostic symptom list for the disorder, resulting in an illusory decline in prevalence over development. Until more age-appropriate symptoms are studied for adolescent and adult populations, this issue remains unresolved.

Gender appears to play a significant role in determining prevalence of ADHD within a population. On average, males are between 2 and 6 times more likely than females to be diagnosed with ADHD in epidemiological samples of children, with the average being roughly 3:1. Within clinic-referred samples, the sex ratio can rise to 6:1 to 9:1, suggesting that males with ADHD are far more likely to be referred to clinics than females, especially if they have an associated oppositional or conduct disorder. It is unclear at this time why males should be more likely to have ADHD than females. This could result partly from an artifact of the relationship between male gender and more aggressive and oppositional behavior; such behavior is known to increase the probability of referral to mental health centers. Because such behavior is often associated with ADHD, clinic-referred males are also more likely to have ADHD. The greater preponderance of males might also, in part, be an artifact of applying a set of diagnostic criteria developed primarily on males to females. Using a predominantly male population to set diagnostic criteria as was done for the DSM-IV (see below) could create a higher threshold for diagnosis for females relative to other females than for males relative to other males. Such a circumstance argues for the eventual examination of whether separate diagnostic criteria (symptom thresholds) ought to be considered for each gender.

ADHD occurs across all socioeconomic levels. Where differences in prevalence rates are found across levels of social class, they may be artifacts of the source used to define the disorder or of the association of ADHD with other disorders known to be related to social class, such as aggression and conduct disorder. No one, however, has made the argument that the nature or qualitative aspects of ADHD differ across social classes.

Hyperactivity or ADHD is present in all countries studied so far, such as New Zealand, Japan, Italy, Germany, India, and Australia. While it may not receive the same diagnostic label in each country, the behavior pattern comprising the disorder appears to be present internationally. ADHD arises also in all ethnic groups studied so far.

Major follow-up studies of clinically referred hyperactive children have been ongoing during the last 25 years at five sites: Montreal, New York City, Iowa City, Los Angeles, and Milwaukee. Follow-up studies of children identified as hyperactive during epidemiological screenings of general populations have also been conducted in the United States, Australia, New Zealand, and England.

The onset of ADHD symptoms has been found to be generally in the preschool years, typically by age 3 or 4, and usually by entry into formal schooling. First to arise in many cases is the pattern of hyperactive-impulsive behavior and, in some cases, oppositional and aggressive conduct. Preschool-aged children with significant degrees of inattentive and hyperactive behavior who are difficult to manage for their parents or teachers and whose pattern of such behavior is persistent for at least a year or more are highly likely to have ADHD and to retain their symptoms into the elementary school years.

By the time ADHD children move into the age range of 6 to 12 years, the problems with hyperactive-impulsive behavior are increasingly associated with difficulties with the form of sustained attention referred to above as goal-directed persistence and distractibility (poor interference control). These symptoms of inattention appear to arise by the age of 5 to 7 years and may emerge out of the increasing difficulties ADHD children are having with self-regulation. The inattentiveness evident in children having ADD without Hyperactivity (Predominantly Inattentive Type of ADHD) may be of a qualitatively different form (focused or selective attention) and may not emerge or be impairing of the child’s school performance until even later, such as mid-to-late childhood.

When ADHD is present in clinic-referred children, the likelihood is that 50 to 80% will continue to have their disorder into adolescence. Although severity levels of symptoms are declining over development, this does not mean hyperactive children are necessarily outgrowing their disorder relative to normal children; like mental retardation, the disorder of ADHD is defined by a developmentally relative deficiency, rather than an absolute one, that persists in many children over time.

The persistence of ADHD symptoms across childhood as well as into early adolescence appears to be associated with the initial degree of hyperactive/impulsive behavior in childhood, the co-existence of conduct problems or oppositional/hostile behavior, poor family relations and conflict in parent-child interactions, as well as maternal depression. These predictors have also been associated with the development and persistence of oppositional and conduct disorder into adolescence.

The Montreal follow-up study of Weiss and Hechtman reported in 1993 that at least half of their subjects were still impaired by some symptoms of the disorder in adulthood. The New York City longitudinal study by Salvatore Mannuzza and Rachel Klein suggested that 18 to 30% of hyperactive children continue to have significant symptoms of ADHD into adulthood. Most recently, the Milwaukee follow-up study by Barkley and Fischer suggests that the source of information about the symptoms may be a significant factor in establishing the persistence of the disorder into adulthood. Less than 25 % of ADHD children reported having significant symptom levels of the disorder in adulthood when asked about themselves as young adults while their parents indicated that more than 60% of these subjects continued to have clinically significant degrees of the disorder as young adults. Until more studies report adult outcomes for ADHD children using clinical diagnostic criteria appropriate for adults and collecting information not only from the adult but from a parent or an immediate family member who knows them well, the true persistence of the disorder into adulthood will remain a matter of some controversy. At the very least, current research suggests it may be 30 to 50%, although the percentage may be higher among clinic-referred children followed to adulthood.

The most recent diagnostic criteria for ADHD are defined in the DSM-IV (1994). They stipulate that individuals have had their symptoms of ADHD for at least 6 months, that these symptoms exist to a degree that is developmentally deviant, and that they have developed by 7 years of age. From the Inattention item list, six of nine items must be endorsed as developmentally inappropriate. Likewise, from the Hyperactive-Impulsive item list, six of nine items must be endorsed as deviant. Depending upon whether criteria are met for either or both symptom lists will determine the type of ADHD that is to be diagnosed: Predominantly Inattentive, Predominantly Hyperactive-Impulsive, or Combined Type.

These diagnostic criteria are empirically derived and are the most rigorous ever available in the history of clinical diagnosis for this disorder. They were developed by a committee of some of the leading experts in the field, a literature review of research on ADHD, an informal survey of rating scales assessing the behavioral dimensions related to ADHD by the committee, and from statistical analyses of the results of a field trial of the items using a large sample of children from 10 different sites in North America.

Controversy continues over whether ADHD-Predominantly Inattentive Type represents a true subtype of ADHD. It is unclear if these children share a common attentional disturbance with the Combined Type and are distinguished simply by the relative absence of significant hyperactivity-impulsivity or whether they have a qualitatively different impairment in attention from that seen in the Combined Type. Several recent reviews of the literature have suggested that this is not in fact a true subtype but actually a separate, distinct disorder having a different attentional disturbance than the one present in ADHD-Combined Type. However, evidence for this subtype’s existence was at least strong enough to place it within the DSM-IV while awaiting more research on its course and treatment responsiveness to help clarify its status. The very limited research available to date suggests that Predominantly Inattentive ADHD children have more problems in the focused or selective component of attention, appear sluggish in their speed of information processing, and may have memory retrieval problems; in contrast, those with ADHD-Combined Type have more problems with persistence and distractibility as well as with poor inhibition.

The research criteria from the International Classification of Diseases (ICD-10) for Hyperkinetic Disorders closely resemble the DSM-IV in stressing two lists of symptoms related to inattention and overactivity and in requiring that pervasiveness across settings be demonstrated. The specific item contents, manner of presenting these symptoms lists within the home and school setting, requirement for office observation of the symptoms, and the earlier age of onset (age 6 years) clearly differs from the DSM-IV, as does the specification of a lower bound of IQ below which the diagnosis should not be given.

Social critics have charged that professionals have been too quick to label energetic and exuberant children as having this mental disorder and that educators also may be using these labels simply as an excuse for poor educational environments. This would imply that children who are hyperactive or are diagnosed with ADHD are actually normal but are being labelled as mentally disordered because of parent and teacher intolerance. If this were actually true, then we should find no differences of any cognitive, behavioral, or social significance between ADHD children and normal children. We should also find ADHD is not associated with any significant later risks in development for maladjustment within any domains of adaptive functioning, social, or school performance. Furthermore, research on potential etiologies for the disorder should also come up empty-handed. This is hardly the case. It should become clear from the totality of information on ADHD presented here and elsewhere in reviews such as those by Barkley in 1990 and Hinshaw in 1994 that those with ADHD have significant deficits in behavioral inhibition and associated executive functions that are critical for effective self-regulation, that these deficits are significantly associated with various biological factors, and particularly genetic and neurodevelopmental ones, and that ADHD symptoms and other associated disorders pose substantial risks for these individuals over the life span.

Future research needs to address the nature of the attentional problems in ADHD given that current research seriously questions whether these problems are actually within the realm of attention at all. Most studies of ADHD point to impairment within the motor, output, or motivational systems of the brain being most closely affiliated with ADHD rather than deficiencies in the sensory processing systems where attention has been traditionally thought to reside. Even the problem with sustained attention may represent a deficiency in a more complex form of goal-directed persistence that arises out of poor self-regulation rather than representing a disturbance in the more primitive form of sustained responding that is contingency shaped. Our understanding of the very nature of the disorder of ADHD is at stake in how research comes to resolve these issues.

Key to understanding ADHD is the notion that it is actually a disorder of behavioral performance and not one of skill; of how and when one’s intelligence comes to be applied in everyday effective adaptive functioning and not in that knowledge itself; of doing what one knows how to do rather than of knowing what to do. The concepts of time, timing, and timeliness are likely to prove increasingly crucial in deepening our understanding of ADHD. In particular, psychological time, how it is sensed, and how it is used in the crosstemporal organizing of complex, goal-directed behavior and in self-regulation may come to be a critical element in models of ADHD. Undoubtedly, research on brain function and structure is likely to further our understanding of the unique role of the prefrontal cortex and the midbrain structures with which it is closely associated in ADHD. But advances in theoretical models must also occur in order to better understand the nature and organization of the executive functions subserved by these brain regions and even the relationship of genetics, which builds these brain regions in embryological development, to ADHD and the deficits it produces in behavioral performance. And the current body of twin studies further suggests that while such genetic influences are important, there exists a lesser but still important role for unique (nonshared) environmental influences on the differences among individuals in symptoms of ADHD and its underlying behavioral traits. Some of these influences are no doubt social in nature while others are likely to be nongenetic pre-, peri-, and postnatal factors affecting brain development. Such studies, not only on the basic psychological nature of ADHD but also on its basic neuroanatomic and neurogenetic origins and the influence of unique social factors upon them, forebode further significant and exciting advances to come in the understanding and treatment of this fascinating developmental disorder.

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• Rutter, M. (1983). Introduction: Concepts of brain dysfunction syndromes. In M. Rutter, (Ed.), Developmental neuropsychiatry (pp. 1-14). New York: Guilford.
• Szatmari, P. (1992). The epidemiology of ADHD. In G. Weiss (Ed.), Child and adolescent psychiatric clinics of North America (Vol. 1, pp. 361-372). Philadelphia: W. B. Saunders.
• Weiss, G. & Hechtman, L. (1993). Hyperactive children grown up. New York: Guilford.

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