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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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• Published: 08 June 2024

Improving the efficacy and effectiveness of evidence-based psychosocial interventions for attention-deficit/hyperactivity disorder (ADHD) in children and adolescents

• Anil Chacko   ORCID: orcid.org/0000-0002-3275-4726 1 ,
• Brittany M. Merrill 2 ,
• Michael J. Kofler   ORCID: orcid.org/0000-0002-8604-3647 3 &
• Gregory A. Fabiano 2  

Translational Psychiatry volume  14 , Article number:  244 ( 2024 ) Cite this article

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Attention-deficit/hyperactivity disorder (ADHD) is a prevalent, chronic, and impairing mental health disorder of childhood. Decades of empirical research has established a strong evidence-based intervention armamentarium for ADHD; however, limitations exist in regards to efficacy and effectiveness of these interventions. We provide an overview of select evidence-based interventions for children and adolescents, highlighting potential approaches to further improving the efficacy and effectiveness of these interventions. We conclude with broader recommendations for interventions, including considerations to moderators and under-explored intervention target areas as well as avenues to improve access and availability of evidence-based interventions through leveraging underutilized workforces and leveraging technology.

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Evidence-based treatments for adhd - an overview.

Multiple groups, committees, and professional organizations have provided the field with recommendations for evidence-based treatment approaches for ADHD. There is clear consensus across these recommendations that pharmacological treatments, notably stimulant medication, psychosocial treatments, and a combination of these two approaches have the strongest evidence base. Table 1 provides a brief overview of the major conclusions of each guideline for the treatment of ADHD in children. It is clearly recommended that families should receive psychoeducation regarding ADHD, and that the evidence-based psychosocial treatments are behavioral parent training (BPT), behavioral interventions in classroom and peer settings, and organizational skills training [ 1 , 2 , 3 , 4 , 5 ].

There are inconsistencies among the guidelines that make broad statements of consensus difficult. For instance, there are differences in precision in recommendations for psychosocial treatments, with some very broad in scope [ 6 ] compared to others with more precise recommendations regarding particular treatment types (e.g., BPT [ 2 ]) and particular populations (e.g., children under six; [ 5 ]). Broad suggestions of seeking “psychological” or “educational” treatment is unhelpful in some guidelines and practice parameters, as there are many approaches that fall under this category and some are clearly efficacious whereas other approaches commonly deployed do not have evidence of efficacy for ADHD [ 1 , 2 , 3 , 4 ]. There are also differences in the strength of recommendations, with more contemporary guidelines emphasizing multimodal treatments more so than older guidelines. However, perhaps most notably, there is not clear consensus among the recommendations on the best sequence or combination of treatments for ADHD, even though this is a key question for most families pursuing treatment for ADHD. It is also important to note that most guidelines focus on proximal ADHD treatment – as ADHD is now conceptualized as a life-course persistent disorder [ 7 ], treatment efforts will need to be protracted across time and appropriate for evolving developmental levels.

Efforts at improving efficacy and effectiveness of psychosocial intervention for ADHD: what do we know and where do we go?

Given the prominent role of psychosocial, primarily behavioral interventions, for ADHD, we highlight the evidence for several of these key interventions, integrating the literature on improving efficacy and effectiveness of these interventions. We also discuss digital therapeutics given the explosion in its availability and purported efficacy for children with ADHD. Following this, we close with potential broad future directions for psychosocial treatments for children with ADHD.

Behavioral parent training

Behavioral parent training (BPT) is likely the most well-studied psychosocial intervention for children’s mental health disorders, including for ADHD [ 8 ]. It serves as the first line intervention approach for younger children with ADHD and is an integral part of comprehensive intervention approaches for school-age children with ADHD. Importantly, BPT is less studied in adolescents with ADHD. Although parenting is not etiological to ADHD, there are clear reasons to focus on parenting when supporting a child with ADHD. Of primary importance is that raising a child with ADHD is stressful, and not surprisingly, elicits ineffectual parenting practices (e.g., inconsistent, harsh, lax, overreactive, less responsive). As a result, parents often have lower parenting efficacy/competence, higher levels of coercive management practices, utilize maladaptive coping strategies (e.g., increased use of alcohol), and have more negative attributions/perceptions of their child [ 8 ]. These parent-level challenges can be addressed, in part, by supporting parents to utilize more proactive and effective parenting practices which can help improve functioning for themselves and ultimately their children. Importantly, the most common comorbidities with ADHD, Oppositional Defiant Disorder [ODD] and Conduct Disorder (CD) are best treated with BPT—making BPT an essential treatment for the most common disruptive behavior disorders in childhood [ 8 ].

BPT is based on operant-conditioning and social learning theories, with techniques that focus on antecedents (e.g., effective instructions, rules) and consequences (e.g., active ignoring, time-out from positive reinforcement) of behaviors. This core content is delivered in a flexible manner with varying formats (e.g., group, individual) durations (brief vs longer), with or without child involvement, delivery (e.g., with or without video-based learning). Moreover, over the past two decades, there have been efforts at tailoring BPT to meet the needs of specific populations (e.g., single mothers, fathers; Latine; [ 9 , 10 , 11 , 12 ]). These BPT programs, often referred to as “homegrown” BPT as compared to commercialized BPT programs (those that have been more extensively developed, manualized and are commercially available; e.g., Defiant Children [ 13 ]) retain the core content of traditional BPT but have modifications to format or additional content that are based on the needs of the targeted populations. Overall, commercialized BPT and homegrown BPT have been found to be effective in improving the functioning of children with ADHD and their parents [ 14 , 15 , 16 ]. A recent meta-analysis also suggests sustained benefits of BPT over the course of a year on child ADHD symptoms, parenting behavior, parenting sense of competence and parental mental health [ 17 ]. The significance of BPT should be, however, put into a broader context to appreciate the clinical benefits of this intervention. While multiple randomized controlled trials have established the statistical significance of BPT for ADHD, the effect size for BPT ranges from small to medium effects, depending upon the outcome [ 18 ]. This means that for many outcomes, the effect sizes would be “visible to the naked eye of a careful observer” [ 19 ]. While there is limited data, only a significant minority of children are “normalized” following BPT [ 15 ]. Collectively, a more nuanced perspective on BPT for ADHD suggests that it is an evidence-based intervention that can result in visible improvements on key outcomes. There is room, however, to improve the potency of BPT. The implications of the findings reported above suggest several broad areas for further investigation. First is to increase access to BPT given the benefits of the intervention. Wolraich et al. [ 20 ] note that there is a lack of an adequate pool of behavioral and mental health specialists who are available to provide evidence-based psychosocial treatments for ADHD, including BPT. National data suggest that the majority of youth with ADHD are receiving no treatment, even when identified, and the lack of BPT treatment is most pronounced in young children with ADHD [ 21 ]. Efforts at utilizing technology to increase the workforce offers novel and promising approaches to address this issue [ 22 ].

A second area is to increase the potency of BPT. We believe there are multiple ways to achieve this goal, with the most apparent being improving the extent to which parents fully engage in BPT, given the relation between increased engagement and improved potency of outcomes [ 23 ]. It is common for families of children with ADHD, even those who have enrolled in BPT, to not initiate treatment or drop out of BPT prior to completion [ 9 , 23 ]. Given this, there have been notable efforts at improving engagement to BPT through addressing perceptual (e.g., expectations about BPT), practical (e.g., transportation) and cultural barriers to treatment prior to BPT [ 10 , 24 ] as well as during BPT [ 25 ]. Given that engagement challenges often involve practical barriers (e.g., transportation, child care, fixed appointment times), there has been efforts at increasing access through reducing these barriers such as providing BPT through mobile applications [ 26 ], web-based platforms [ 27 ] and telehealth delivery [ 28 , 29 ]. These efforts have led to improved engagement and associated outcomes for families, beyond traditional BPT [ 30 ]. Engagement with BPT remains an important area of research, particularly the extent to which these enhancements to BPT can be readily applied in routine settings [ 25 , 31 , 32 ], an understudied empirical question.

A second and meaningful line of research to improve the potency of BPT has been focused on improving specificity of BPT content by translating contemporary theories of ADHD into refinements to BPT. Van der Oord and Tripp [ 33 ]), utilizing contemporary motivational reinforcement-based theories of ADHD, suggest that given altered reinforcement sensitivity in ADHD, rewards and punishment should be judiciously provided. As an example, they note evidence that while mild negative punishment (e.g., response-cost, time-out from positive reinforcement) improves on-task behavior in children with ADHD, mild punishment can also lead to more errors on tasks, increased emotionality in children with ADHD, missed learning opportunities, and lack of task persistence [ 34 , 35 ]. These authors note caution in the use of punishment, especially positive punishment (e.g., verbal reprimands), with children with ADHD. Rather, there should be a focus on rewarding alternative adaptive behaviors to reduce the need to use punishment. These theory-driven considerations to adapting BPT are important, yet empirically understudied. As such, the extent to which these ADHD-theory-adapted BPT results in improved outcomes relative to standard BPT is not known. Importantly, however, some efforts in this area have resulted in little difference for ADHD-adapted BPT relative to standard BPT. As an example, in an RCT, the New Forest Parenting Program (NFPP), which was developed to address underlying mechanisms of ADHD (self-regulatory and cognitive problems [ 36 ] was found to be no better than a standard BPT program and in some areas less effective (e.g., parental stress, parenting behavior, parent reports of ADHD symptoms at follow-up) for preschool children with ADHD [ 37 ]. These data suggest the importance of rigorously evaluating novel approaches that are considered improvements to BPT to well-established traditional BPT for ADHD.

Overall, the efficacy of BPT suggests that this should be first-line intervention approach for children with ADHD, with significant and noticeable effects of BPT on both parent- and child-level outcomes with maintenance of gains over the course of a year. This statement comes with the caveat that there is room for improvement in the potency of BPT. As we will discuss in the future directions section below, greater attention must be given to dissemination of BPT (and all psychosocial interventions for ADHD) within routine systems of care and evaluation of the effectiveness of these interventions alone and in combination when delivered within these systems.

Behavioral classroom management

ADHD is largely defined by challenges in settings such as schools where behavioral expectations are often demanding of attention capacity and self-control, and so it is not surprising that many of the efficacious treatments for ADHD have focused on improving academic functioning and classroom behaviors. Children with ADHD are effectively treated with classroom contingency management strategies [ 38 ]. Systematic reviews [ 1 , 2 , 4 , 5 , 39 ] as well as meta-analyses [ 40 , 41 , 42 ] clearly illustrate that behavioral classroom management is an efficacious treatment for ADHD.

As noted above, behavioral classroom management is an efficacious treatment for ADHD. Before discussing evidence for efficacy and effectiveness of behavior classroom management, it is worth noting approaches that do not strongly support positive outcomes. In the United States, children with ADHD are eligible for behavioral classroom management support through Section 504 Accommodation plans administered through the Americans with Disabilities Act or through an Individualized Education Program if the committee on special education determines it is needed. These policies have provided school-based behavioral supports for students with ADHD for over 30 years. However, given that follow-up studies indicate that the long-term educational outcomes for students with ADHD are modest, at best [ 43 , 44 , 45 , 46 ], it is important to emphasize that these accommodation plans or individualized education programs are only useful if they include effective interventions and supports for the child or adolescent with ADHD.

Practically speaking, behavioral classroom management approaches that are effective will include setting clear goals and rules, ensure that the child receives clear feedback on progress toward meeting goals, and that consequences, typically rewards and privileges contingent on meeting behavioral goals and following rules, are provided liberally. It is important to note that positive behavior support strategies are interwoven into the fabric of elementary school classrooms - teachers provide rules and structure for activities, there is praise issued for appropriate behavior, and schools have standard discipline procedures including office referrals or detentions for rule violations. Feedback is provided on a regular, if infrequent basis (i.e., on quarterly report cards). For most children with ADHD this provides a reasonable baseline of behavioral classroom management, but additional strategies and supports are typically needed to make the overall approach to supporting a child with ADHD more efficacious.

Children with ADHD typically need much more frequent behavioral feedback and positive consequences for appropriate behavior in schools. For that reason, a daily report card is among the most efficacious positive behavior supports within a classroom [ 47 , 48 ]. The daily report card has long been used effectively to treat ADHD, monitor outcomes, and open a daily line of communication between teachers and the child’s parent [ 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 ], and it is a procedure aligned with a long tradition of using contingency management with children with disruptive behavior in general educational settings [ 58 ] and in special education settings [ 57 , 59 , 60 ]. In addition to being among the most efficacious classroom interventions, it is also one of the most cost effective [ 61 ].

Recent changes in the ways schools address social, emotional, and behavioral challenges may promote greater effectiveness of the implementation of classroom behavior management strategies. Multi-tiered systems of support (MTSS [ 62 ] in schools conceptualize the behavior of children as being within a continuum, and through regular screening and progress monitoring, provide more intensive intervention, when indicated and for as long as is needed. Currently MTSS efforts in schools are focused on academic achievement targets, and there is less emphasis on MTSS for behavior [ 63 ]. However, the MTSS model of screening and intervention is similar to the single case design approach to intervention that has been long-used within the ADHD treatment literature [ 4 , 5 , 47 ]. In this approach, following the collection of baseline data, behavior classroom management interventions are systematically introduced to evaluate their effectiveness. Educators also benefit from ongoing coaching, support, and monitoring of progress to promote consistent and protracted use of these behavioral interventions [ 64 ].

Supporting this approach to school-based intervention is a recent study that evaluated the effectiveness of different sequences of ADHD treatment [ 65 ]. In this study, using a sequential, multiple assignment randomized trial (SMART [ 66 ]), children were randomly assigned to begin the school year with one of the two evidence-based treatments for ADHD - a low dose of stimulant medication or an initial course of behavior therapy (eight parent training sessions and a daily report card intervention at school). Teachers provided feedback on how the child was functioning in the classroom, and if there was evidence of impaired functioning, the child was then randomly assigned to more treatment – either a greater dose of the treatment at the start of the school year, or a other modality. Thus, children could have a treatment sequence of: (1) medication followed by an increased dose of medication; (2) medication with behavior therapy added; (3) behavior therapy followed by an increased dose of behavior therapy; or (4) behavior therapy followed by medication. Results were interesting as they illustrated the best sequence of treatment for reducing discipline referrals and disruptive behaviors observed in the classroom were those that started with behavior therapy first. Further, the behavior therapy first approaches also cost less to implement across the school year than the treatment sequences that included medication [ 61 ]. Importantly, this study of the effectiveness of treatment sequencing spanned an entire school year, improving upon the research base of efficacy treatments where many studies focused on shorter time periods. While the Pelham study provides a foundation for considering combined and sequenced approaches, far less has been done on the effectiveness of behavioral classroom approaches when conducted within and supported entirely by school-staff over the course of multiple school years.

Overall, there is strong support for behavioral classroom interventions, including the Daily Report Card [ 48 , 50 , 67 ], and it is strongly recommended that this intervention be initiated for children with ADHD experiencing classroom-based impairment. For older children (e.g., middle school, high school), a behavioral contract may be used to initiated contingency management across the multiple classrooms characteristic of this grade level. Educators and parents should ensure that school-based interventions are implemented consistency and continuously, as school-based behavioral challenges are likely to extend across school years and grade levels.

Organization skills training

Related to their difficulties staying on task and following the rules in the classroom setting, children with ADHD have impaired organization, time management, and planning skills that undermine their academic abilities and potential. Homework management and organizational skills have been shown to predict concurrent GPA and later academic outcomes [ 68 , 69 ]. Organizational skills training (OST) interventions utilize behavioral methods to teach skills directly to students with ADHD. The training programs often include behavioral management procedures administered by a counselor, parent, or teacher to reinforce skill use and progress in treatment. Organizational interventions have largely targeted middle school to early high school students with ADHD (ages 10–14 [ 70 ]), with sessions focusing on materials organization, understanding time and time management, and planning larger assignments. Session frequency and length vary widely from about 10, 60-minute family sessions in a clinic [ 71 ] to 40, 2.5-hour student sessions in an after-school setting [ 72 ]. Multicomponent OST packages lead to improvements in organizational skills, planner use, and adolescent impairment [ 73 ].

Embedding OST in schools is key to enhancing the reach of these interventions. Though availability of school personnel to implement OST varies across districts, current work aims to train school counselors to implement OST with students with ADHD [ 74 ]. Langberg and colleagues [ 74 ] found that OST delivered by school staff led to improvements in organization, time management, and planning skills as performance and behavior during homework based on parent-report. Importantly, these results were found despite the school counselors receiving only 2 h of training in the intervention with no ongoing supervision. Purposefully limiting training and post-training investment allows for the examination of treatment effects in the context in which they would likely be provided—i.e., in schools, by school mental health providers with little funding for training and ongoing supervision. Toward the same goal of increasing the sustainability of OST within schools, investigators are developing online tools to assist school staff with OST implementation at low to no cost [ 75 ].

Psychosocial treatments for children with ADHD have primarily been researched in elementary-age youth, and early work in developing organizational skills interventions addressed this gap by upwardly extending treatments to middle school age youth. As the evidence accumulated that such interventions were efficacious among children with ADHD in middle school [ 1 , 2 ], further developmental extension was clearly justified [ 76 ]. adapted their OST program developed for middle schoolers to pilot with high school students with ADHD. Pilot data demonstrated feasibility and indicated that high schoolers may need about 50 sessions to benefit from the OST program. In the full-scale randomized clinical trial [ 77 ], high schoolers attended an average of 40 brief OST sessions while their caregivers attended an average of 4 behavioral parent training sessions. Compared to the control group, beneficial effects of treatment were found on parent-reported academic functioning and organizational skills, and no significant effects on grades, teacher-reported, or self-reported outcomes were found. Results are promising, and much more work is needed to support the academic functioning of older adolescents with ADHD.

Digital therapeutics

Of all the available non-medication treatments, this category is the only one that features protocols patented by the US Patent and Trademark Office (USPTO) and cleared by the U.S. Food and Drug Administration (FDA) for the treatment of ADHD. It is also the most controversial, with competing consensus statements concluding that these types of interventions have proven effective vs. proven ineffective [ 78 ], millions of dollars in fines for false advertising [ 78 ], and a perceived disconnect between benchmarks for effectiveness between the FDA and professional organizations that evaluate psychosocial treatments for children [ 79 ]. Overall, there appears to be evidence for small benefits of cognitive training on reducing inattentive symptoms, and potentially overall ADHD symptoms [ 80 ]. However, we contend that omnibus meta-analytic effect sizes are fundamentally uninterpretable in the context of cognitive training/digital therapeutics because the treatments that fall under this general umbrella feature wide variations in neurocognitive/neurological training targets, conceptual models of neurocognition that define these intended training targets, success/failure to meaningfully engage and improve the intended training target(s), and technologies employed to ‘hit’ the intended target(s). Therefore, what these treatments share are more peripheral features, rather than core mechanistic features necessary to meet meta-analytic assumptions. Even interventions given the same, more specific label (e.g., “working memory training”) vary widely in their approach, conceptual basis, and success/failure at engaging their mechanistic target as shown previously [ 81 ]. It will be important for the field to evaluate each intervention on its own merits because these protocols generally share very little with each other except for the use of a serious games approach [ 82 ] to engaging children in treatment.

Several neurocognitive training protocols have been developed and tested for children with ADHD; we briefly review three of the most prominent: EndeavorRX, CogMed, and Central Executive Training (Cenextra; an intervention developed by one of the co-authors). All three of these approaches are computerized digital therapeutics that include gaming elements and adaptive changes in difficulty. EndeavorRX trains cognitive attention abilities [ 83 ], Cenextra trains the ‘working’ components of working memory [ 84 ] and CogMed is intended to improve attention and working memory abilities [ 85 ], though clinical trial and meta-analytic evidence indicates that CogMed successfully engages short-term memory but not working memory abilities [ 81 , 86 , 87 ].

In terms of efficacy, EndeavorRX showed early promise in pilot/uncontrolled studies given generally favorable feasibility, acceptability, and engagement data [ 83 ]. In addition, EndeavorRX showed potential for reductions in parent-reported ADHD symptoms in proof-of-concept and open-label trials with children with ADHD [ 88 , 89 ]. However, the only controlled trial to date [ 83 ] demonstrated that these potential reductions were likely attributable to placebo effects – that is, Endeavor RX failed to show superior improvements in ADHD behavioral symptoms relative to a control condition (a spelling game). Evans et al. [ 79 ] concluded that “there is no evidence that using this game will result in any benefit in terms of their functioning and presenting problems.” (p. 125).

Cenextra also showed early promise in a head-to-head comparison with behavioral parent training (BPT) indicating favorable feasibility, acceptability, and engagement data. Cenextra was superior to BPT for improving working memory ( d  = 1.06) and reducing objectively-assessed hyperactivity ( d  = 0.74), and equivalent to BPT for reducing parent-reported ADHD symptoms at post-treatment [ 90 ]. These benefits were largely confirmed in an RCT comparing Cenextra with an active, credible digital therapeutic control called Inhibitory Control Training (ICT; [ 84 ]). Evidence suggesting improved functional outcomes is also emerging, and includes superior improvements relative to both BPT and ICT on masked teacher perceptions of organizational skills, academic success, impulse control, and academic productivity 1–2 months after treatment ended [ 91 , 92 ].

Similar to EndeavorRX and Cenextra, Cogmed showed considerable promise in early trials, and is arguably the most extensively studied neurocognitive training program. Results from meta-analytic reviews and RCTs, however, suggest that CogMed does not improve working memory, but rather improves select components of short-term memory (meta-analytic d  = 0.63; [ 81 , 86 , 93 , 94 ]. This is an important limitation for at least two reasons: First, most children with ADHD do not have deficits in short term memory (20–38% impairment rates) despite the majority having impairments in working memory (75–81%; [ 95 , 96 , 97 ]). Second, short-term memory abilities are not significantly associated with ADHD symptoms in most studies [ 81 , 95 ], which suggests limited potential for downstream improvements in ADHD behavioral symptoms. Indeed, conclusions from multiple meta-analytic reviews suggest that benefits on ADHD behavioral symptoms from CogMed are generally limited to unblinded parent ratings [ 81 , 93 ]. Notably, however, a more recent meta-analysis published by the developer of CogMed suggests significant, small benefits for reducing inattention ( d  = 0.37; [ 98 ]), though the extent to which this was driven by unblinded parent ratings was unclear.

A key benefit of digital therapeutics – and ‘software as medicine’ in general – is that they have the potential to continually adapt and improve based on real-time patient data. Thus, it is possible that interventions that are not showing the behavioral/functional benefits we had hoped for now could begin to do so in the future. Thus, we highlight some key areas for improvement based on conceptual models and the limited available literature on moderators of cognitive training efficacy for children with ADHD. First, there is a need to maximize dosage . In the context of digital therapeutics, ‘dosage’ refers to the quantity and quality of time spent actively engaging with the training exercises. Most existing protocols have been studied over a relatively limited time frame of 4–10 weeks of training, with a total training time of about 10–12 h across intervention protocols [ 83 , 84 , 99 ]. It is possible that this level of training is insufficient for producing large enough neurocognitive improvements to translate into meaningful – and statistically detectable – gains in downstream behavioral/functional outcomes, suggesting the need for more intensive/longer duration training.

An option closely related to maximizing dosage is increasing the specificity of the neurocognitive training target(s). Although training a variety of neurocognitive functions is appealing at face value, meta-analytic evidence indicates that such protocols produce smaller near-transfer effects than protocols that focus on a single neurocognitive training target [ 81 ]. It is presumed that the reason for this finding is that the more different cognitive ‘muscles’ that we are trying to train, the less time we can spend on any one of those ‘muscles’. Thus, it appears likely that maximizing efficacy will require separate protocols for each neurocognitive function that is impaired in ADHD, combined with a ‘personalized medicine’ approach in which each child’s neurocognitive profile is estimated at pre-treatment, and then a treatment plan is developed to target each of their identified weaknesses. We must leverage basic science to link training targets with behavioral/functional outcomes . Related to dosage and specificity issues is the idea of matching neurocognitive training targets with the specific outcome(s) of interest. Stated bluntly, neurocognitive training is not likely to be helpful if we are training neurocognitive abilities that are not robustly linked with the reason(s) a child presents for treatment. On the other hand, neurocognitive training protocols have great potential if they are able to produce robust improvements in their training target, and if that training target is robustly associated with the observable behaviors/functional outcomes we are trying to improve. A final area that shows promise for improving the efficacy of digital therapeutic interventions is augmentation: Combining them with existing treatments to (potentially) produce synergistic and/or augmentative benefits. This area of inquiry is in its infancy, and currently shows more conceptual promise than actual benefits [ 100 ].

Future directions in improving efficacy and effectiveness

This brief review of psychosocial treatments for ADHD illustrates the robust evidence in support of these interventions. Importantly, there is no panacea or magic bullet for ADHD; the interventions reviewed herein have notable limitations and response to interventions vary. As such, there continues to be efforts at refining existing approaches and developing novel approaches to treating the complex presentation of ADHD. We highlight here what we believe are key future directions, broadly speaking, in improving the effectiveness and efficacy of treatment for ADHD. These fall under two broad areas: future directions in treatments and future directions in service delivery of these treatments.

Future directions in treatment for ADHD

Moderators of treatment effects.

Much of the intervention literature has focused on static factors or social addresses (terms that describe rather than explain; e.g., marital status, child age;) as factors, largely because these are measures of convenience. Efforts toward using dynamic factors have shed light on what works for whom and can further refine an intervention to increase potency. As an example, in BPT, parent-level variables (e.g., parenting stress [ 101 ]) have been shown to moderate BPT engagement and outcomes, suggesting that future refinements to BPT that more directly address parental stress may increase the potency of BPT. Such efforts should be employed across all psychosocial interventions for ADHD. Importantly, as we have discussed elsewhere [ 8 , 102 ], efforts should go beyond variable-centered approaches (e.g., child age, parent stress) toward holistic, person- and/or family-centered approaches (the clustering of variables that more fully represent a child/parent/family). As an example, Dale et al. [ 103 ] employed a person-centered approach to create subgroups of families based on the intersection of multiple parent, child, and family factors to understand response to BPT for families of preschool children with ADHD. Three distinct family profiles emerged, with data suggesting differential response for families with high stress, elevated parental anxiety, and elevated parental depression. These typological approaches better reflect reality- people are more accurately reflected as a complex intersection of variables rather than just any one variable- and taking this approach may better result in a nuanced understanding of response to treatment and further inform treatment for types of people and families.

ADHD is complex and presentations vary. It is not uncommon for children and adolescents with ADHD to also have significant difficulties outside of core symptoms of ADHD (e.g., emotion dysregulation, sleep disturbances) that may moderate treatment response. As an example, ADHD is frequently associated with emotional regulation challenges, with studies suggesting that the vast majority of children with ADHD (i.e., 75%) have some symptoms of emotion dysregulation, with 25% having severe emotion dysregulation [ 104 ]. In fact, children with ADHD and severe emotion dysregulation are more likely to have complex presentations, cross-situational impairments and severe psychopathology [ 105 ]. Interestingly, there are few rigorous randomized controlled trials evaluating the effects of psychosocial interventions for emotion dysregulation in children with ADHD [ 106 ]. These and other moderators may best be evaluated through novel approaches such as individual participant data meta-analysis [ 107 ]. Addressing the needs of youth with ADHD and their families will require going beyond addressing core symptoms of ADHD. In fact, we have long argued that these types of functional impairments (e.g., academic, social functioning) should be the targets for ADHD treatment rather than ADHD symptoms [ 8 ].

Novel intervention targets

The presentation of ADHD at key developmental periods/tasks may pose significant challenges for affected youth and their families- necessitating novel targets of intervention. An example of this is the transition to learning to drive. Adolescents are the riskiest drivers on the roadway, overall; if an adolescent has ADHD they are significantly more at risk for negative driving outcomes including accidents, accidents that cause injury, and fatalities [ 108 , 109 ]. The period of time when individuals with ADHD are learning to drive may therefore be a critical, and also opportune time to initiate intervention. A recent RCT with adolescents with ADHD [ 110 ], evaluated a specially designed computerized simulated-driving program with feedback and found reduced problematic driving as compared with a control program. During real-world driving in the year after training, the rate of collisions and near-collisions was lower in the intervention group. These efforts highlight the potential of psychosocial interventions for addressing impairments inherent with developmental transitions for youth with ADHD. Related work suggests that intervening with adolescents at the transition to middle school and high school with intensive summer “bridge” programs may be a useful approach with high levels of engagement [ 111 ]. Future work should focus on embedding treatment efforts into other developmental tasks/transitions/tasks (e.g., start of preschool or initiation of employment).

Future directions in service delivery

ADHD is now very clearly understood to persist throughout development and into adulthood and there has rightfully been a shift toward a chronic care model [ 7 ]. Given this, attention must be given to developing integrated, consistently available and longitudinal approaches embedded in routine service systems such that children, adolescents (and even adults) with ADHD and their families can receive appropriate care. Unfortunately, availability and access to evidence-based interventions are limited. Recent studies suggest that only 31% of families of children with ADHD receive BPT [ 21 ] and just 32% receive behavioral classroom management [ 112 ]. Given this, we highlight herein issues related to increasing availability and access to evidence-based psychosocial treatment for ADHD- important goals to help close the science-to-service-gap in ADHD. More specifically, we briefly highlight efforts on (1) leveraging the existing workforce, and (2) using technology to deliver evidence-based psychosocial treatments.

Leveraging existing workforces

In light of mental health workforce shortages ( https://data.hrsa.gov/topics/health-workforce/workforce-projections ) new models of care will need to utilize and expand existing, but underdeveloped, non-professional and paraprofessional workforces [ 31 , 32 ]. One example of a sustainable, scalable model of care is the Family Peer Advocate (FPA) ADHD Model [ 25 ]. FPAs are part of a national family support model of current and former parent/caregivers of children with identified mental health needs who provide a range of services, including parenting skills training, emotional support, education about mental health services, and direct advocacy [ 30 ]. FPA-services are flexibly delivered in a variety of parent-identified settings (e.g., parent’s homes, community settings) and often connect and engage parents with key service settings/providers (e.g., schools, primary care, mental health clinics), reducing the systemic barriers associated with traditional service delivery models. Moreover, FPAs have many shared experiences with the families they serve including personal experience with providing care and navigating the service system for children with mental health challenges, often within the same community as those they serve. As a result, FPA care is associated with high acceptability ratings and increased engagement [ 113 ]. This FPA Model appears to be especially effective in reaching ethnically diverse families from socioeconomically disadvantaged backgrounds [ 30 , 113 ]. Emerging data suggest that FPAs can reliably and effectively deliver BPT for youth with ADHD [ 25 ], suggesting that this and other workforce (e.g., ADHD Coaches) should be leveraged in order to increase availability and access to evidence-based psychosocial interventions for ADHD.

The idea of leveraging the existing workforce also applies to school settings. The MTSS intervention framework, which embeds intervention in schools into universal, targeted, and indicated approaches is an example of a potential means of re-allocating professional time and expertise. Rather than waiting for school psychologists and special educators to get involved only when the child is considered for special education, a MTSS approach might utilize the expertise of these professionals to consult with the general education teacher on how to implement positive behavior supports for a child with ADHD. In this way, intervention is implemented quicker, in the setting where the initial impairment is identified, by existing school professionals [ 56 , 114 ].

Use of technology

Technology-based approaches to delivering evidence-based interventions have the potential to revolutionize mental health service access and delivery across multiple mental health disorders [ 115 ]. Online self-directed BPT approaches are potentially more feasible, affordable, and acceptable, can have significant reach to include traditionally underserved populations, and are readily scalable and sustainable [ 116 , 117 ]. Over 13 studies have recently been conducted demonstrating that online BPT can improve child behavioral outcomes. Importantly, a recently published trial compared Triple P Online (TPO; an evidence-based, commercially available, self-directed online BPT) to a face-to-face (F2F) therapist-delivered Triple P for preschool children with disruptive behavior problems [ 118 ]. This large randomized controlled trial found that TPO was non-inferior to F2F Triple P on observed and parent-reported child behavior, with clinically meaningful effect sizes. This study, combined with several other studies [ 27 , 119 , 120 ] demonstrate the effectiveness of online BPT in general and specifically for ADHD. Technology is increasingly being utilized in practice settings (e.g., ADHD Care Assistant in primary care [ 121 ]; Online Daily Report Card in schools [ 122 ]) to increase access to evidence-based psychosocial interventions. Concerted efforts and rigorous empirical investigation will be necessary to further determine the effectiveness of these approaches. Importantly, while there is high potential for such technology-delivered approaches, engagement to these formats will remain important to address [ 123 ].

Conclusions

ADHD is a prevalent, pervasive, chronic and impairing disorder that necessitates early, integrated, continuous interventions over a child’s development. Fortunately, several psychosocial interventions are available that address key functional impairments in children and adolescents with ADHD. Given the complex presentation of ADHD, novel approaches to address both underlying pathophysiological mechanisms associated with ADHD (e.g., working memory) as well as domains closely impacted in those with ADHD (e.g., emotion regulation) and key developmental tasks (e.g., driving) are emerging areas in ADHD intervention science. Efforts to improve the efficacy of psychosocial interventions remain important as the acute benefits of these interventions do not result in normalized functioning for many youth and there remains an under-appreciation for whom these interventions are most impactful. Likely most pressing is the translation of the intervention science to improve outcomes for the millions of youth affected by ADHD, the science-to-service gap is prominent; many children who can benefit from evidence-based psychosocial interventions do not receive them. Improving access and availability of evidence-based psychosocial interventions remains critical to ensure that the significant efforts made over decades in developing and evaluating interventions for ADHD result in population-level benefits for youth with ADHD.

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Chacko, A., Merrill, B.M., Kofler, M.J. et al. Improving the efficacy and effectiveness of evidence-based psychosocial interventions for attention-deficit/hyperactivity disorder (ADHD) in children and adolescents. Transl Psychiatry 14 , 244 (2024). https://doi.org/10.1038/s41398-024-02890-3

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DOI : https://doi.org/10.1038/s41398-024-02890-3

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Prevalence estimates were weighted and are among children and adolescents aged 4 to 17 years. The weighted prevalence of ADHD was 10.00% (95% CI, 9.11%-10.90%) in 2017, 10.41% (95% CI, 9.42%-11.39%) in 2018, 9.34% (95% CI, 8.51%-10.16%) in 2019, 10.83% (95% CI, 9.61%-12.04%) in 2020, 10.14% (95% CI, 9.33%-10.96%) in 2021, and 10.80% (95% CI, 9.83%-11.76%) in 2022. P for trend was calculated using a weighted logistic regression model, which included survey year as a continuous variable and was adjusted for age (4-17 years: P  = .31; 6-11 years: P  = .79; 12-17 years: P  = .07), sex (female: P  = .04; male: P  = .95), race and ethnicity (Hispanic: P  = .52; non-Hispanic Black: P  = .08; non-Hispanic White: P  = .55; other: P  = .46), family income-to-poverty ratio (<1.00: P  = .61; 1.00-1.99: P  = .30; 2.00-3.99: P  = .35; ≥4.00: P  = .11), and highest educational level of family members (<high school: P  = .74; high school: P  = .50; ≥college: P  = .33). Other races and ethnicities included non-Hispanic American Indian or Alaska Native (individual only), non-Hispanic American Indian or Alaska Native and any other group, non-Hispanic Asian (individual only), and other single and multiple races or declined to respond, no response, or unknown. The family income-to-poverty ratio is the total family income divided by the poverty threshold.

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Li Y , Yan X , Li Q, et al. Prevalence and Trends in Diagnosed ADHD Among US Children and Adolescents, 2017-2022. JAMA Netw Open. 2023;6(10):e2336872. doi:10.1001/jamanetworkopen.2023.36872

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Prevalence and Trends in Diagnosed ADHD Among US Children and Adolescents, 2017-2022

• 1 Department of Child and Adolescent Health, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, Guangdong Province, China
• 2 Department of Pediatrics, The First Affiliated Hospital, University of Science and Technology of China, Hefei, Anhui Province, China
• 3 Division of Birth Cohort Study, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, Guangdong Province, China

Attention-deficit hyperactivity disorder (ADHD) is the most common childhood-onset neurodevelopmental disorder, characterized by persistent and impairing inattention, hyperactivity, and impulsivity, with a high prevalence among US children and considerable implications for individuals and families. 1 , 2 Studies have found that prevalence of ADHD increased from 1997 to 2016 in US children. An analysis of the National Health Interview Survey (NHIS) 2 reported that the prevalence of ADHD among children increased from 6.1% in 1997 to 1998 to 10.2% in 2015 to 2016. Similarly, the National Survey of Children’s Health showed a 42.0% increase from 2003 to 2011. 3 However, the latest prevalence has not been updated in the past 6 years. The aim of this study was to estimate the prevalence and trends of ADHD among children and adolescents in the US in 2017 to 2022.

Data for this cross-sectional study were obtained from the NHIS, 2017 to 2022, a nationally representative cross-sectional survey using multistage, stratified sampling. 4 Information about ADHD diagnosed by a physician or other health professional was reported by a parent or guardian. The final sample child and adolescent response rate was 45.8% to 60.6% from 2017 to 2022. The Guangdong Pharmaceutical University academic review board deemed the study exempt from review because of the use of deidentified data. The NHIS has been approved by the National Center for Health Statistics ethics review board, and all respondents provided verbal informed consent before participation. The study followed the STROBE reporting guideline.

The weighted prevalence of ADHD among individuals in the US aged 4 to 17 years from 2017 to 2022 was calculated based on the complex sampling design following NHIS statistical guidelines. 5  P values for overall differences across strata were calculated using χ 2 tests. Trends in prevalence over time were tested using a weighted logistic regression model, which adjusted for age, sex, race and ethnicity, family educational level, and family income-to-poverty ratio. Race and ethnicity were self-reported in the survey and were assessed to gather demographic information for health care research and investigate health disparities. Statistical analyses were conducted using survey procedures in SAS statistical software version 9.4 (SAS Institute). A 2-sided P  < .05 was considered statistically significant.

A total of 37 609 individuals aged 4 to 17 years (18 185 female [48.35%] and 19 424 male [51.65%]; 9030 Hispanic [24.01%], 4119 non-Hispanic Black [10.95%], 19 816 non-Hispanic White [52.69%], and 4644 non-Hispanic other race [12.35%]) were included. Among them, 4098 children and adolescents (10.90%) were reported to have ever been diagnosed with ADHD. The weighted prevalence of ADHD was 10.20% (95% CI, 9.54%-10.87%) in 2017 to 2018, 10.08% (95% CI, 9.33%-10.83%) in 2019 to 2020, and 10.47% (95% CI, 9.81%-11.13%) in 2021 to 2022. There were significant differences in prevalence by age, sex, race and ethnicity, and family income-to-poverty ratio ( Table ).

Prevalence had no significant change annually (10.00% [95% CI, 9.11%-10.90%] in 2017; 10.80% [95% CI, 9.83%-11.76%] in 2022; P for trend = .31). All subgroups evaluated also showed no significant change in prevalence from 2017 to 2022 ( Figure ).

Based on US national representative data, the estimated ADHD prevalence was 10.08% to 10.47% among children and adolescents aged 4 to 17 years from 2017 to 2022, which was similar to the prevalence from the NHIS in 2015 to 2016 (10.20%). 2 No significant annual change in the prevalence of ADHD was found from 2017 to 2022. Notably, the estimated prevalence of ADHD among individuals in the US in this study was higher than worldwide estimates (5.3%) in earlier years (1978-2005). 6 The prevalence of ADHD differed significantly by age, sex, race and ethnicity, and family income-to-poverty ratio, consistent with previous study findings. 2 , 3

This study has some limitations. First, information on ADHD provided by parents may lead to misreporting and recall bias. Second, the NHIS underwent a major redesign in 2019, which may affect comparability with prior years, and the COVID-19 pandemic affected data collection in 2020, which may also affect survey estimates. Given that the estimated ADHD prevalence was still high, further investigation is warranted to assess potentially modifiable risk factors and provide adequate resources for treatment of individuals with ADHD in the future.

Accepted for Publication: August 28, 2023.

Published: October 4, 2023. doi:10.1001/jamanetworkopen.2023.36872

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2023 Li Y et al. JAMA Network Open .

Corresponding Author: Wenhan Yang, MD, PhD, Department of Child and Adolescent Health, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, Guangdong Province 510006, China ( [email protected] ); Jinhua Lu, MM, Division of Birth Cohort Study, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, Guangdong Province 510623, China ( [email protected] ).

Author Contributions: Drs Lu and Yang had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Mss Y. Li, Yan, and Qishan Li contributed equally to this work.

Concept and design: Lu, Yang.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Y. Li, Qishan Li.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Y. Li, Yan, Qishan Li, Qian Li, Xu, Yang.

Supervision: Lu, Yang.

Conflict of Interest Disclosures: None reported.

Disclaimer: The data used in this study were obtained from the National Health Interview Survey (NHIS), a public database provided by the US Centers for Disease Control and Prevention (CDC). The authors acknowledge the contributions of the CDC in providing access to the NHIS. Any errors or omissions are the responsibility of the authors.

Data Sharing Statement: See the Supplement .

Additional Contributions: The authors would like to acknowledge the support from all the team members and all staff of the National Center for Health Statistics. These individuals participated voluntarily and without compensation.

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• Published: 22 April 2022

University students with attention deficit hyperactivity disorder (ADHD): a consensus statement from the UK Adult ADHD Network (UKAAN)

• Jane A. Sedgwick-Müller 1 ,
• Ulrich Müller-Sedgwick 2 ,
• Marios Adamou 3 ,
• Marco Catani 4 ,
• Rebecca Champ 3 ,
• Gísli Gudjónsson 5 ,
• Dietmar Hank 6 ,
• Mark Pitts 7 ,
• Susan Young 8 &
• Philip Asherson 9  

BMC Psychiatry volume  22 , Article number:  292 ( 2022 ) Cite this article

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Attention deficit hyperactivity disorder (ADHD) is associated with poor educational outcomes that can have long-term negative effects on the mental health, wellbeing, and socio-economic outcomes of university students. Mental health provision for university students with ADHD is often inadequate due to long waiting times for access to diagnosis and treatment in specialist National Health Service (NHS) clinics. ADHD is a hidden and marginalised disability, and within higher education in the UK, the categorisation of ADHD as a specific learning difference (or difficulty) may be contributing to this.

This consensus aims to provide an informed understanding of the impact of ADHD on the educational (or academic) outcomes of university students and highlight an urgent need for timely access to treatment and management.

The UK Adult ADHD Network (UKAAN) convened a meeting of practitioners and experts from England, Wales, and Scotland, to discuss issues that university students with ADHD can experience or present with during their programme of studies and how best to address them. A report on the collective analysis, evaluation, and opinions of the expert panel and published literature about the impact of ADHD on the educational outcomes of university students is presented.

A consensus was reached that offers expert advice, practical guidance, and recommendations to support the medical, education, and disability practitioners working with university students with ADHD.

Conclusions

Practical advice, guidance, and recommendations based on expert consensus can inform the identification of ADHD in university students, personalised interventions, and educational support, as well as contribute to existing research in this topic area. There is a need to move away from prevailing notions within higher education about ADHD being a specific learning difference (or difficulty) and attend to the urgent need for university students with ADHD to have timely access to treatment and support. A multimodal approach can be adapted to support university students with ADHD. This approach would view timely access to treatment, including reasonable adjustments and educational support, as having a positive impact on the academic performance and achievement of university students with ADHD.

Peer Review reports

Going to university can be an exciting experience, but it is also a daunting and stressful experience for new and returning students. The pressure to do well academically and cope with an array of lifestyle changes, can impact on the mental health and wellbeing of university students, especially students with ADHD who are transitioning from adolescence into adulthood [ 1 ]. This transitional phase defines a critical developmental stage in life termed “emerging adulthood” [ 2 ]. Institutions of higher education (HEIs or universities) are arguably designed for the kind of identity exploration that defines emerging adulthood. This includes leaving home to go to university, and perhaps for the first time, being independent and responsible for managing one’s own finances and dietary needs, whilst at the same time being exposed to a multitude of different worldviews and new opportunities for friendships, romances, partying and work [ 3 ]. Emerging adulthood is also recognised as a peak period for experimentation with substance use or high-risk sexual and other behaviours, and for the onset or exacerbation of mental health problems including self-harm and suicide [ 4 ]. The mental health and wellbeing of university students is a cause for concern [ 1 , 5 ], and the experience of the expert group is that emerging adults with ADHD may be particularly vulnerable during and after transitioning to university.

ADHD is a neurodevelopmental disorder that begins in childhood and frequently persists into adulthood. ADHD is clinically defined by persisting symptoms of inattention, hyperactivity and impulsivity that can cause functional impairments in multiple domains of daily life. In the Diagnostic and Statistical Manual version 5 (DSM-5) [ 6 ], and the International Classification of Diseases version 11 (ICD-11) [ 7 ], diagnostic requirements for ADHD are broadly similar. For this reason, and since the ICD-11 officially comes into effect in January 2022, in this report, reference is made to DSM-5 diagnostic requirements for ADHD in adults. Table 1 lists some typical characteristics and behaviours seen in adults with ADHD, including university students. It is also not uncommon for university students with ADHD to present with co-occurring specific learning differences (or difficulties) (SpLDs), developmental co-ordination disorder (DCD) or dyspraxia as the former term, autism spectrum disorder (ASD), anxiety, depression, personality, eating, and substance use disorders [ 8 , 9 , 10 , 11 , 12 , 13 , 14 ]. A significant majority of university students with ADHD will experience academic difficulties to varying degrees of severity [ 15 , 16 ]. Previous studies refer to “educational or academic outcomes” in terms of academic achievement ( attainment of information and skills learnt, grades obtained on continuous assessments such as standardised examinations or coursework ) and academic performance ( completed years of schooling, enrolment into university, final grades awarded, retention, and progression ) [ 17 ]. Evidence suggests ADHD will impact on these different academic domains in a negative way [ 18 ].

Historical context

The historical context matters a lot for understanding the ways in which ADHD exists in society, including how it is perceived, experienced, and managed. Within UK HEIs, ADHD is perceived and/or conceptualised as a SpLD [ 22 ]. In the special educational needs and disability (SEND) code of practice (0 to 25 years), ADHD is conceptualised as a social, emotional, and mental health difficulty [ 23 ], and in the DSM-5 and ICD-11, ADHD is defined as “ the most common mental health disorder in childhood that often persists in adulthood ” [ 6 , 7 ]. These conceptual differences reflect how the nomenclature, understanding of functional impairments, and clinical characteristics of ADHD within different professional contexts have evolved over time. However for some authors, it was the inception of compulsory education in the late nineteenth century, rather than advances in the medical sciences, that transformed ADHD into a salient societal concern [ 24 ]. In the UK, when compulsory education was first instituted, government funding to schools including salaries for teachers, was based on the numbers of students that attended school for at least 100 days per academic year and passed standardised examinations in the 3Rs (reading, writing, arithmetic) [ 25 ]. This system, known at the time as “payment by results” [ 26 ], is said to have also motivated teachers to raise concerns about students who struggled to pass the 3Rs examinations, and eventually these students were deemed uneducable in mainstream schools [ 27 , 28 ]. Some of these students were described as “… hyperactive, distractible, unruly and unmanageable in school … frequently disturbing the whole class … quarrelsome and impulsive … often leaving the school building during class time without permission ” [ 29 ], p.15).

The Egerton Royal Commission [ 30 ], was first to examine the problem of uneducable students in mainstream schools. In its final report the umbrella term “feeble-minded”, although pejorative today, was introduced to categorise students assessed and certified as needing special education. Arguably, feeble-mindedness is the antecedent for a variety of social, emotional, mental and physical health difficulties that can cause learning problems for a sub-set of students. The early use of the term in education also marked the medicalisation of poor scholastic performance and failure [ 31 ]. Although Still’s observation of a “ moral defect without intellectual impairment ” in school children [ 32 ], was heralded as an early descriptor of the contemporary medical concept of ADHD [ 33 ], the term feeble-minded categorised all “ children who could not be properly taught in ordinary elementary schools by ordinary methods, ” and this included the children who Still had described [ 34 ]. In the early twentieth century, new research on the heritability of intelligence roused a relentless eugenic enterprise to eradicate feeble-mindedness by preventing its procreation [ 35 ]. These events coincided with the development of psychometric tests of intelligence [ 36 , 37 , 38 ], and their use within education became the means by which students were differentiated as either feeble-minded or “simply dull/backward”. The former group of students were sent to newly established residential colonies for care and management under the Mental Deficiency Act 1913, whilst the dull/backward students continued to be educated within mainstream schools [ 39 ].

In 1913, Cyril Burt (1883–1971), the father of educational psychology in the UK, was the first psychologist to be appointed by the London County Council (LCC) to assess students referred under the Mental Deficiency Act. Burt administered psychometric tests with these students, conducted extensive ground-breaking research into educational backwardness, developed standardised tests for use in schools and provided teachers with psychological advice on how best to manage emotional and behavioural disorders in students [ 40 ]. Through his work, Burt argued that intellectual ability was on a continuum, intelligence between boys and girls was the same, academic performance and achievement was variable, and that learning differences (or difficulties) observed in students considered dull, backward, feeble-minded or maladjusted, constituted a single problem [ 41 , 42 , 43 , 44 ]. Burt’s seminal work on educational backwardness was insightful, in the sense that it not only associated causes of backwardness in students with low scores on a psychometric test or other environmental factors, but also with disorders of temperament and conduct. One category within these disorders was the “excitable and unrepressed child” [ 44 ], and descriptors of this disorder are clearly akin to the characteristics of ADHD known today. Interestingly, Burt published his work on the “backward child” in 1937, the same year that Charles Bradley in the USA reported on the positive effects of psychostimulant medication in students who exhibited various behaviour disorders [ 45 ].

The influence of Burt’s work on educational policy and provisions for students with special educational needs was profound [ 46 ]. It was reflected in the landmark Warnock Report on special education [ 47 ]. The recommendations of Warnock Report compelled legislators to enshrine the policy of inclusion within the Education Act 1981, and to introduce the broad concept of “special educational needs” (SEN) to categorise students with a range of learning difficulties and/or disabilities. Descriptors of SEN have since transformed into those listed in the current SEND code of practice (0 to 25 years) [ 23 ]. But despite all this early work, ADHD has continued to be a contentious and controversial medical diagnosis in UK, with one study reporting that only “ 73 hyperactive children were seen at the Maudsley and Bethlem Royal Hospital in London between 1968 and 1980 ” [ 48 ], p.16–17). Following the publication of a protocol for the treatment of ADHD based on DSM-IV criteria [ 49 ], diagnostic rates of ADHD increased in the UK and continued to do so with subsequent publications of clinical guidance for the diagnosis and management of ADHD in children, young people, and adults [ 50 ]. There are still many challenges with regards to timely access to diagnosis and treatment for university students with ADHD, and support for practitioners and educators who have reported ADHD as one of the most challenging disorders to deal with in university students [ 51 ]. These views echoed in the Institute for Employment Studies (IES) report on support for disabled students in higher education in England for the Office for Students (OfS) [ 52 ]. This IES report noted that “… providers [university disability services] were facing a number of, often shared, challenges ...” (p.132), which included dealing with a rising numbers of university students with ADHD and complex mental health needs. One provider quoted by the IES said that:

“… the support provisions for disabled students is understandably being affected by external factors. How to manage that impact is a focus for the disability and dyslexia team… this includes… the number of students with ADHD which has grown dramatically in recent years. This group of students are very challenging to support for both the service and for academic staff. The disability and dyslexia service need training and development to enable them to both support these students and the academic staff working with them ... ” [ 52 ] p.134).

Effects of ADHD within higher education

In the UK, across Europe and worldwide, there is a paucity of research about university students with ADHD. Previous studies mostly seem to originate from North America, where research activity in this topic area has been ongoing since the 1990s, and the impact of ADHD on the educational outcomes of college (or university) students is more widely understood. A comprehensive review of these studies was conducted by Sedgwick [ 21 ], and a summary of the main findings are presented in Table 2 .

ADHD and intellectual giftedness

The relevance of intellectual giftedness to university students with ADHD was considered by the expert group. Intellectual giftedness is another contested concept variously defined as exceptional intellectual ability, academic talent, or high-potential learners, with concurrent traits of creativity, curiosity, effort, and self-motivation [ 53 , 54 , 55 , 56 ]. Intellectual giftedness is referenced in the Canadian ADHD Practice Guidelines [ 57 ], but not in the DSM-5 or ICD-11 [ 6 , 7 ], or other clinical guidelines [ 50 ]. Research suggests that intellectual giftedness can either over-shadow or compensate for attention difficulties, or the behaviours associated with ADHD can over-shadow traits of intellectual giftedness, and that students with both ADHD and intellectual giftedness can be difficult to identify or assess using standardised measures and observational checklists [ 58 , 59 , 60 , 61 , 62 ]. The co-existence of ADHD in intellectually gifted individuals, including university students, is controversial. The theories of positive disintegration [ 63 ], and asynchronous development [ 64 ], have both been used to understand various aspects of intellectual giftedness in students with ADHD. Important areas of current research include the potential misdiagnosis of intellectual giftedness as ADHD, and the occurrence of ADHD and intellectual giftedness as a dual diagnosis [ 65 ].

Intellectual giftedness in students with ADHD is thought to be under-identified by parents, educators, psychologists, and physicians. Brown et al., for instance, reported that “ adults with IQ scores in and above superior range have often sought evaluation and treatment for chronic difficulties with organizing their work, excessive procrastination, inconsistent effort, excessive forgetfulness, and lack of adequate focus for school and/or employment. They question whether they might have an attention deficit disorder, but often they have been told by educators and clinicians that their superior intelligence precludes having ADHD ” [ 66 ], p.161).

Intellectual giftedness does not preclude having ADHD, and in some university students with ADHD it could mitigate some deficits in executive function and allow them to flourish academically or to go on and have successful careers [ 67 , 68 , 69 ]. Some authors proposed that a degree of autism (or savantism) could foster a special talent in gifted individuals [ 70 ], including individuals with ADHD [ 71 , 72 ]. Other authors warn that intellectual giftedness may only be a protective factor for students with ADHD during their pre-18 school years [ 59 , 73 ]. This may change when they transition into higher education where self-directed learning becomes an essential academic skill and when challenges such as living away from a structured home environment, or needing to be more organised, can precipitate a worsening of ADHD symptoms and significant levels of impairment start to emerge [ 74 , 75 ]. These issues may become more apparent in post-graduate students, who are selected based on their undergraduate academic achievements [ 56 , 76 , 77 ]. Empirical studies between 2000 and 2014 about the identification, misdiagnosis and dual diagnosis of intellectual giftedness and ADHD were reviewed by Mullet and Rinn, [ 65 ]. From this review, traits of intellectual giftedness versus ADHD have been compiled for the purposes of clarity. These are listed in Table 3 below.

In sum, this report presents a selective review of previously published literature on ADHD in university students and consensus based on expert opinions. It aims to critically examine and discuss the impact of ADHD on educational outcomes of university students and provide evidence-based, practical advice and guidance on how best to support these students during their programme of studies. Expert consensual advice and guidance in relation to screening and diagnostic assessments for ADHD in adults, specific interventions for university students with ADHD, a potential model for service provision, staff training and development, will contribute to existing research in this topic area.

The purpose of the expert consensus meeting was to formulate practical advice, guidance, and recommendations for supporting medical, mental health, educational and disability practitioners who work with university students with ADHD. This report is based on previously published literature that was identified, selected, collated, and critically reviewed using a framework for scoping studies [ 78 ], as well as the professional experience of the expert group. The consensus meeting was convened by the UK Adult ADHD Network ( www.UKAAN.org ) in July 2017. UKAAN is an organisation founded in 2009 by a group of mental health specialists, responding to NICE guidelines [ 50 ], and recommendations from the British Association for Psychopharmacology (BAP) [ 79 , 80 ], for the purpose of providing support, research, education, and training to professionals working with adults with ADHD. The aims of the consensus meeting were to address the following questions:

Is ADHD a hidden disability within higher education institutions (HEIs)?

Is ADHD a specific learning (difficulty) or difference?

What are the similarities and differences between ADHD, specific learning (difficulties) or differences & other mental health conditions?

What is the impact of stigma?

What constitutes best practice for supporting university students with ADHD?

Service provision

Screening & diagnostic testing

Pharmacological & non-pharmacological interventions

Staff training and development

Meeting attendees included the authors and 48 other mental health, neurodiversity, and disability practitioners, learning assessors and 2 university students with ADHD from England, Wales, and Scotland. The authors who attended the meeting represented a multidisciplinary group of prescribing and non-prescribing clinicians, practitioners, and academics, with extensive experience and expertise in working with adults with ADHD, including university students. Attendees engaged in conversations throughout the day with the aim of achieving consensus. The meeting was structured around presentations on relevant topics that are listed below, and the personal accounts from the 2 university students with ADHD, followed by questions, and answers (Q&As).

The first author facilitated discussions among the attendees to elicit verbal accounts of experience and to reach a consensus position on the topic being discussed. At the end of the meeting, the first author presented a summary of the main points previously agreed (which are listed in Table 4 ), and then asked the attendees to raise a hand to indicate whether they agreed with each point being raised. This is line with the phenomenological methodological framework that was used to gain an emic or “insiders” perspective of the attendee’s experiences, knowledge, and expertise of working with university students with ADHD [ 81 , 82 ]. The consensus meeting started with an overview of the neurobiology of ADHD to set the scene, then invited speakers presented on the following topics:

The effectiveness of stimulant medication in treating ADHD.

Academic coaching for university students with ADHD.

The SpLD Assessment Standards Committee (SASC) guidelines for the assessment of ADHD in university students.

Tele-psychiatry: Internet based treatment services for university student with ADHD.

The student experience: What is it like to be a university student with ADHD?

The attendees and speakers consented to the presentations and discussions being audio recorded. After the meeting, the recording was transcribed verbatim with care taken to remove all identifiable information. Authorship of the manuscript was based on involvement during the meeting, a willingness to work on the manuscript after the meeting, clinical and professional expertise in the assessment and treatment of ADHD in university students. The first author (JSM) consolidated the presentations, data from the transcripts and notes relevant to the main points agreed in the meeting, into a manuscript that was circulated amongst the authors for review, revision, final agreement, and approval. This manuscript reflects the clinical experience and expertise of the authors and is supported by published literature.

Results and consensus outcome

The series of questions and summary of main points addressed during the meeting were collated and are discussed below. A summary of the main recommendations is listed in Table 10 .

Only one study was found that reported on the prevalence of ADHD in UK university students. In this study Pope et al. [ 83 ] used the Conners’ Adult ADHD Self-Rating Scale to assess for symptoms of ADHD in 1185 undergraduate psychology students from four UK universities. The findings revealed that about 7% of these students self-reported above-threshold symptoms of ADHD. In a study from the USA, DuPaul et al. [ 84 ] reported that at least 25% of college students with disabilities were diagnosed with ADHD. Among university students in China ( n  = 343), and in the USA ( n  = 283), ADHD was reported to be around 5% in the USA cohort and 8% in the Chinese cohort [ 85 ]. These data clearly depict variability, with some reported rates suggesting a higher prevalence of ADHD among university students, when compared to the reported worldwide prevalence estimate of 2–3% for ADHD in adults [ 10 ]. However the studies that reported higher prevalence estimates (e.g., Norvilitis et al. [ 85 ] did seem to have determined the presence of ADHD based on a count of symptoms alone, and did not assess functional impairments to meet full diagnostic requirements for ADHD. Perhaps if functional impairments had also been considered, prevalence rates of ADHD in university students may have been similar to the prevalence rates reported for adults [ 86 ].

University students with ADHD are part of a much bigger group of disabled students that are represented within the widening participation (WP) strategy that forms a major component of higher education policy in the UK [ 87 ]. The WP strategy requires HEIs in the UK to collect, analyse, and respond to data on disabled students. To do so, HEIs utilise UCAS (Universities and Colleges Admissions Service), codes and categories of disability listed in Table 5 . As shown, ADHD is listed “ G – Specific Learning Difference e.g., dyslexia, dyspraxia, or ADHD .” The Higher Education Statistical Agency (HESA, https://www.hesa.ac.uk ) also collect, process, and publish data about disabled students within higher education in the UK. Figure 1 depicts percentages of the HESA Data for “ UK domiciled students’ enrolments by disability and sex” based on a total number of 307,975 for the academic years 2014/15–2018/19 [ 22 ]. From this data it is also not possible to ascertain a prevalence estimate for ADHD among university students or even to identify if ADHD exists within higher education.

Disabled university students in the UK. Source: Table 15: UK-domiciled student enrolments by disability and sex , for the academic year 2018-19, (total number of disabled students 316,380) [ 22 ]. NB: There are high rates of overlap between ADHD and both SpLDs and mental health conditions, but the prevalence of ADHD is unknown, because there is no separate category for it

Figure 2 depicts in percentages published data from 25 HEIs in Ireland, based on a total number of 12,630 university students who declared a disability for the academic year 2016/17 [ 88 ]. There are clear similarities between this data and the HESA data depicted in Fig. 1 . But there are also differences in the numbers of university students who declared a mental health condition (27% in the UK vs. 13.9% in Ireland), a specific learning difference (UK 36% vs. Ireland 41.4%) and autism spectrum disorder/ASD (UK 4% vs. Ireland 5.4%). In Ireland, data is also collected on university students who declare a developmental co-ordination disorder (DCD, or dyspraxia, 6.1%) and ADHD (5.2%), but similar data is not collected in the UK. During the consensus meeting there was unanimous agreement that ADHD should no longer be subsumed under the category of a SpLD. The obvious consequence of continuing to do so is that a prevalence estimate for ADHD in UK university students will always be hard to ascertain.

Disabled university students in Ireland. Source: Fig. 3 Breakdown of students by Category of Disability 2016/17 (total number of disabled students 12,630) [ 88 ]

Recommendation 1. The categorisation of ADHD

The expert group recommends that ADHD should no longer be subsumed under the category of a SpLD in HESA data return categories or by university services and should be coded or categorised separately. If ADHD continues to be coded or categorised as an SpLD then no specific data about the numbers of university students who declare ADHD as a disability within UK HEIs will be collected. ADHD is a mental health condition and not a SpLD. ADHD has specific diagnostic criteria within the DSM-5 [ 6 ], and ICD-11 [ 7 ], as well as efficacious treatments (medication and psychosocial interventions) [ 89 , 90 ]. A separate code to categorise ADHD within UK HEIs could result in greater recognition of the disorder and increase understanding about how it impacts on academic performance and achievement.

What are the differences between ADHD and SpLDs?

Dyslexia, dyscalculia, dysgraphia, and dyspraxia (or DCD) and ADHD are all categorised as SpLDs within UK HEIs. However, in the DSM-5, dyslexia, dyscalculia, and dysgraphia are grouped together under a single diagnostic category of “specific learning disorder” (SLD, or learning disorder), whilst DCD is classified separately as a motor disorder and ADHD as a neurodevelopmental disorder [ 6 ]. SpLDs are not synonymous with SLD, but a university student who has been diagnosed with a SLD can also expect to meet criteria for a SpLD, be registered as disabled and qualify for reasonable adjustments under the Equality Act 2010. Specifiers and characteristics of SLD and typical SpLD terms used in higher education are listed in Table 6 . Unlike ADHD, there are no known medical treatments for SLD (or SpLDs), therefore reasonable adjustments (or accommodations) are required to limit their impact within educational settings. Reading disorder (RD, e.g., dyslexia) is the most prevalent SpLD reported to account for up to 80% of all SpLDs [ 91 ]. Bidirectional comorbidity between RD and ADHD which is estimated at 25–40%, is likely due to shared genetic risk factors [ 92 ]. This may also explain why deficits in executive function are seen in both ADHD and RD [ 93 , 94 ]. Executive functions (EF) are described as a set of top-down mental skills essential for academic performance. In Table 7 , EFs are conceptualised in terms of their organisational and regulatory functions. The three commonly described EFs are inhibitory control, working memory and cognitive flexibility [ 95 , 96 ]. Although research suggests that deficits in EF can adversely impact academic functioning due to the problems they can cause with sustaining attention, forgetfulness, procrastination, organisation skills, prioritising, regulating alertness, emotional and behavioural self-control, psychometric tests of EF are still not sensitive enough to assess for the core deficits of ADHD [ 97 , 98 , 99 , 100 , 101 , 102 , 103 ].

The Baddeley and Hitch [ 107 ] conceptual model of working memory (WM) in Fig. 3 , proposes that WM is a core EF for storing and manipulating information, and with a central role in attention, allocating data to its slave systems (phonological loop and visuo-spatial sketchpad), performing task switching, mental arithmetic, problem solving and interfacing with long-term memory through the episodic buffer. The episodic buffer acts as a temporary store for the phonological loop, which processes spoken and written information, whilst the visuo-spatial sketchpad processes visual imagery. Although this model can be used to understand the importance of WM in academic tasks such as reading, comprehension, verbal reasoning (phonological loop), navigation (visuo-spatial processing) and problem-solving (central executive) [ 107 , 108 , 109 , 110 , 111 ], the model can also be used to understand how deficits in WM might occur in both ADHD and reading disorder [ 93 ]. Reading disorder (e.g., dyslexia) is defined by deficits in decoding the speech sounds of words and structure of language (phonological weakness), fluency (an inability to ready quickly with appropriate expression) and processing speed [ 11 , 91 , 93 , 102 ].

Model of Working Memory (Adapted from Baddeley [ 111 ]

Processing speed (PS) is not an EF per se, rather it is said to be a cognitive ability that describes the amount of time it takes to identify, understand, react, or respond to information received, whether it be visual (letters and numbers), auditory (language) or movement [ 112 ]. Since PS is surmised to impact on WM, phonological loop and visuo-spatial sketchpad processes, and the fine motor co-ordination associated with DCD, it’s impact on academic performance is also said to be direct [ 113 ]. PS is an index score on the WAIS (Wechsler Adult Intelligence Scale), measured by rapid automatized naming of pictured objects, letters, numbers, and colours [ 112 ]. Slow PS or PS deficits, often identified by a low PS score on the WAIS, has been associated with reading disorder [ 102 ], ASD and ADHD [ 114 ]. This also means when a student is identified with PS deficits on the WAIS for instance, certain academic tasks, such as an examination which requires “ an ability to quickly come up with an answer and retrieve information from memory ”, may take longer to complete, hence these students tend to be awarded extra writing time for examinations as a reasonable adjustment [ 115 ], p4). PS deficits are also implicated in the comorbidity between ADHD and reading disorder [ 116 ], the combined effect of which may produce more severe learning problems than when each of these disorders occurs on its own [ 11 , 117 , 118 ]. High rates of comorbidity are also reported between ADHD and other SpLDs (e.g., dyscalculia and dysgraphia), and other disorders such as DCD and ASD, with similar combined effects as those surmised between ADHD and RD, but a paucity of research limits understanding of the severity of cognitive deficits in these comorbidities and their impact on academic functioning [ 8 , 14 , 70 , 119 , 120 , 121 ].

Recommendation 2. ADHD and SpLDs

Comorbidity between ADHD and other neurodevelopment disorders, which include SpLDs, adversely impacts on academic functioning. The expert group therefore recommends screening for ADHD as part of routine practice for university students who report learning difficulties that seem to be associated with dyslexia, dyscalculia, dysgraphia, dyspraxia and/or ASD, not only because these conditions are highly likely to co-occur [ 8 , 11 , 14 ], but ADHD can be missed if a student is only screened for SpLDs and/or ASD. For students that screen positive for ADHD, a referral for treatment and management by a suitably qualified mental health professional (e.g., student health GP, psychiatrist, or mental health nurse/practitioner) is important. Although ADHD on its own can provide an explanation for learning problems within higher education, it can also add complexity to the learning problems associated with SpLDs, DCD or ASD. These complexities need to be considered when assessing for, and/or awarding reasonable adjustments. Screening tools that are used in routine practice are listed in Table 8 .

What are the differences between ADHD and other mental health conditions?

It is equally important to differentiate ADHD from other mental health conditions and to consider the impact of these conditions on university students with ADHD when they do co-occur. Year-on-year increases in the number of students declaring a mental health condition at university have been observed, with current prevalence estimates of 27% amongst university students who declare a mental health disability before or during their programme of studies (see Fig. 1 ). A study by Anastopoulos et al. [ 16 ] examined rates and patterns of co-occurring disorders in 443 university students with ADHD. The findings of this study revealed that 55% of these students had at least one comorbidity whilst 32% had two or more, and that commonly reported comorbidities with ADHD were depressive and anxiety disorders. These elevated rates differ from rates reported in an epidemiological study conducted in 20 high, medium, and low-income countries involving 26,774 adults with ADHD. This study found that 23% of these adults with ADHD had at least one mental health comorbidity, while 14% had two or three comorbidities, and that commonly reported comorbidities with ADHD were also anxiety disorders (34%), mood disorders (22%), as well as behavioural disorders (15%) and substance use disorders (11%) [ 10 ]. Similar findings were reported in qualitative studies, although the participants in these studies, also reported positive aspects of ADHD such as high levels of energy and drive, creativity, hyper-focus, agreeableness, empathy, self-acceptance, and a willingness to assist others [ 132 , 133 ].

During the consensus meeting the discussion mostly focused on university students who frequently reported anxiety and depression. Different types of anxiety (e.g., generalised anxiety disorder, social anxiety, specific phobias, agoraphobia, panic disorder, substance/medication induced anxiety ), or depressive disorders (e.g., mood dysregulation disorder, major depressive disorder, dysthymia, premenstrual dysphoria, substance/medication induced depression ), were discussed in relation to ADHD. Major depressive disorder (MDD) does show some overlap with ADHD symptoms such as poor concentration and working memory performance, but in MDD these characteristics are episodic and only arise during periods of low mood, anhedonia (loss of interest/enjoyment in ordinary experiences), or when there are ruminations dominated by negative content, and appetite disturbances, which are not characteristic of ADHD [ 134 ]. In contrast, people with ADHD usually present with attention regulation problems. This means they may be able to focus during highly stimulating or interesting tasks and activities, but problems with concentration will remain regardless of mood state [ 19 ]. Poor concentration and restlessness are also symptoms that are shared between anxiety disorders and ADHD. Anxiety disorders are characterised by fluctuations in pathologic worry, fear, and somatic symptoms, which drive concentration problems, whereas in ADHD, problems with attention and restlessness, drive concentration problems and reflect persistent traits that are independent of anxiety [ 134 ].

University students with ADHD can present to medical, counselling, and disability services with problems related to anxiety and/or depression, because challenges of university life can also play an important role in affected mental health. Both anxiety and depression are frequently co-occurring conditions in adults with ADHD [ 10 ], as well as in university students with ADHD [ 16 ]. However, it is still important to be aware that symptoms of ADHD can mimic both anxiety and depression [ 19 ], and that anxiety and depression can in turn affect attention, concentration, processing speed, and motivation, giving rise to poor performance on reading, writing, attending classes and group work [ 135 ]. University students with ADHD can also be prone to “test anxiety” and experience disabling levels of worry, emotional and somatic symptoms, that exacerbates their ability to focus and perform during evaluative assessments such as examinations. This may further increase the risk that they achieve poor grades, or delay completing their programme of studies [ 136 , 137 ]. More generally, symptoms of ADHD can be misdiagnosed for anxiety, mood, or personality disorders. This may be an issue for females with ADHD whose symptoms are more likely to reflect internalising symptoms and emotional dysregulation [ 138 ].

Emotional dysregulation is a prominent feature in ADHD and is listed in the DSM-5 as a characteristic that supports the diagnosis of ADHD [ 6 ]. Research suggests that up to 80% or more adults with ADHD report significant levels of emotional dysregulation/lability marked by irritability, volatility, a hot temper, low frustration tolerance and sensitivity to criticism [ 139 , 140 , 141 ]. These attributes do reflect a part of the normal range of mood symptoms for people with ADHD, but if severe, then they can also be misconstrued for MDD, bipolar disorder or a personality disorder. Emotional lability (EL) in adults with ADHD tends to manifest as short-lived emotional outbursts, or feelings of irritability, frustration, or anger that is often (but not always) in response to daily events [ 140 ]. Studies on EL in adults with ADHD also suggest that it is more closely linked to the development of low self-esteem and poor self-concept, when compared to the other core features of ADHD [ 140 , 142 ]. University students with ADHD who have problems with EL are more likely to encounter additional challenges with making and maintaining academic and social relationships [ 143 ], or with participating in group work, team sports, societies, or other activities at university, especially if they frequently express anger, sadness, or anxiety when with others [ 144 ].

University students with ADHD who do not cope well with anger or sadness may also use tobacco, alcohol, cannabis, or other drugs; sex, gambling, or gaming as coping strategies [ 145 , 146 , 147 ]. Some students with ADHD may not be able to control their alcohol intake for instance, and binge drink often or report more drinking-induced blackouts, loss of friends or romantic partners as a result of their drinking habits [ 147 ]. In the study by Rooney et al., [ 148 ], although students with ADHD did not report higher levels of alcohol use, they did report more dangerous/hazardous use. In another study when university students with ADHD escalated their substance use, they increasingly skipped classes and reductions in their academic grades were observed [ 149 ]. Although similar problems are seen in clinical practice with other drugs of abuse such as cocaine [ 150 ], some drugs are used to control symptoms of ADHD. For example, cannabis may help reduce some ADHD related problems such as restlessness, EL and problems getting to sleep [ 151 ]. In contrast to poor mental health, emotional wellbeing is increasingly being viewed as important for enhancing a student’s motivation to learn, academic performance and interpersonal skills. Studies have shown that reducing stress, and increasing enthusiasm, contentment, joy, hope, pride, exuberance, and elatedness are linked to improvements in academic self-efficacy, interest, effort, engagement, performance, and achievement [ 152 , 153 , 154 , 155 , 156 ]. There are also positive aspects of ADHD that can be useful at university [ 133 ].

Recommendation 3. ADHD and mental health conditions

The expert group recommends that university students who present with enduring anxiety and depression, and report persistent problems with learning or studying, should be screened for ADHD. ADHD can mimic these conditions, and likewise, anxiety and depression can mimic ADHD. Anxiety and depression may also reflect a normal stress response to the educational and psychosocial impairments of ADHD. Screening for ADHD should therefore be conducted in all students diagnosed with, or frequently complaining about, anxiety or depression (or other chronic mental health problems), particularly when they are taking medication and there is no or only limited improvements in their mental state. For students that screen positive for ADHD, a referral for treatment and management by a suitably qualified mental health professional (e.g., student health GP, psychiatrist, or mental health nurse/practitioner), is important.

What is the impact of stigma on university students with ADHD?

Stigmata are the beliefs, attitudes and structures that interact at an individual, group, or institutional level, to discriminate against a person based on a perceivable social characteristic that sets them aside from others [ 157 ]. ADHD, a diagnostic label, is a perceivable social characteristic that can be stigmatised as laziness, bad behaviour, or as having “special needs” [ 158 , 159 ]. There are lingering myths, misconceptions, negative stereotypes, and labels associated with ADHD [ 160 ]. Some medical professionals in the UK, Europe, and Australia, have expressed doubts about whether ADHD is real, over-emphasising the aetiological role of parenting, or questioning the role of stimulant medication in its treatment [ 161 ]. In one study a group of university students were asked to rate the likelihood of interacting with, collaborating on a group project with, getting to know, becoming friends with, living with, working with, or dating a peer with either ADHD, a general medical condition, or an ambiguous flaw such as perfectionism. Peers with ADHD were rated as less socially desirable than peers in the other two groups [ 162 ]. In young people with ADHD, although self-stigma can present as a sense of feeling different from same age peers or by negative self-evaluations, some young people have also challenged ADHD related stigma by openly disclosing and talking about their diagnosis [ 163 ].

Some professionals may fear treating a “fake disease” or causing a drug dependency by prescribing stimulant medication, even though there is no empirical evidence to support these views [ 50 , 158 , 164 ]. Missing or failing to identify ADHD is more likely to happen in university students who are intellectually gifted, getting good grades, or in those, particularly females, who may be misdiagnosed with anxiety, depression, eating or personality disorders [ 50 , 138 , 158 ]. Some studies from the USA suggest that university students without ADHD can malinger for the purposes of obtaining a prescription for stimulant medication for use as “study drugs” [ 165 , 166 ]. Malingering with ADHD for this purpose may be a phenomenon more often observed in the USA, where ADHD is more commonly diagnosed and treated in primary care. This is not the same as in the UK and Europe more generally, where ADHD in adults is an under-diagnosed and under-treated condition and suitably qualified and trained medical or non-medical prescribers (e.g. mental health nurses or pharmacists) treat ADHD [ 19 ]. From the perspective of the expert group, concerns about malingering can further stigmatise university students with ADHD in the UK, as well as discourage disclosure, bias the way a screening or diagnostic assessment is conducted and result in a failure to recognise a legitimate disorder with an effective treatment. The experience of the expert group is that malingering with ADHD is not common (even unusual) for university students in the UK. Instead, they tend to work exceptionally hard to overcome their deficits associated with ADHD and still experience academic outcomes that fall below that expected from their general intellectual ability. The need to tackle the stigma associated with ADHD was discussed during the consensus meeting, in terms of how it deterred disclosure, seeking a formal diagnosis, taking medication, or seeking additional support. Concerns about disclosing ADHD (or other mental health conditions) were also noted in the Institute for Employment Studies report to the Office for Students [ 52 ].

Recommendation 4. ADHD and stigma

The expert group recommends that targeted programmes of training for university student support staff should include psychoeducation, how to screen for ADHD and use recommended strategies for supporting university students with ADHD. This training can also be used to raise awareness about the potential stigma associated with ADHD, its consequences and potential impact on the screening and diagnostic process, willingness to disclose ADHD at university and accept treatment.

What is best practice for supporting university students with ADHD?

In the UK, clinical guidance recommends that the medical diagnosis of ADHD must be done by a suitably qualified practitioner, and with primary care staff providing support through shared care protocols [ 50 ]. The expert group is aware that at present, waiting times for access to treatment via specialist NHS adult ADHD clinics can be anything of up to two years or longer in some areas of the country. Given the high cost of tuition fees for university and living expenses, plus added pressures to complete a university degree on time, students with ADHD simply cannot afford to wait two or more years to access treatment in specialist NHS services, without risking poor academic performance, failure, drop-out or increased burden of illness. For some of these students the misuse of caffeine products, cannabis, alcohol, or stimulants (licit or illicit) may seem like attractive options for self-medication. Seeking an educational diagnosis of a SpLD, funded through the university disability service, maybe an attractive option that can enable access to educational support. But if the core symptoms of ADHD remain untreated, students with ADHD can continue to experience learning (and possibly other) problems during their time at university.

In one systematic review of 176 studies about the long-term educational outcomes of untreated versus treated ADHD, academic outcomes were found to be worse in students with untreated ADHD when compared to their non-ADHD peers, after controlling for IQ [ 18 ]. Another finding was that academic outcomes improved significantly when multimodal treatment was used, in comparison to when pharmacological or non-pharmacological treatments were used alone [ 18 ]. The provision of rapid access to treatment for university students with ADHD maybe challenging for clinicians working in specialist NHS services. But the expert group has found that some HEIs are using funds from their disability services budget to fund private diagnostic assessments for their students, and are commissioning medical treatment (e.g., bespoke services through the NHS or privately). These HEIs in turn note these initiatives in their “access and participation plans” (APPs) for the OfS, to demonstrate how they are improving equality of opportunity for students with ADHD, who traditionally experience poor educational access, achievement, and attainment [ 21 ].

Recommendation 5. Service provision

The expert group recommends that a rapid access pathway of care for university students with ADHD be developed collaboratively between university central support services, and NHS primary and secondary care, or private providers. University disability services currently fund diagnostic assessments for SpLDs. This budget could also be made available to university students with ADHD to enable them to at least obtain a diagnostic assessment and reasonable adjustments. The expert group provides an example of a potential support pathway for university students with ADHD, which is presented in Fig. 4 .

Potential Support pathway for university students with ADHD

Which screening tools and diagnostic assessments are useful?

Screening tools are used to indicate if symptoms of ADHD and/or any other co-occurring conditions that are likely to complicate the learning problems that university students with ADHD are present or not. Screening for ADHD and other potential comorbidities is done routinely in clinical practice, because it’s important to differentiate the conditions underlying the student’s presenting symptoms and consider whether they may or may not require additional reasonable adjustments or support from other services (e.g., GP, mental health, or counselling). A widely used screening tool for ADHD based on DSM-5 diagnostic criteria, is the World Health Organisation Adult ADHD Self-Report Scale (ASRSv1.1) [ 122 ], now updated to an online DSM-5 version (see Table 8 for further details and weblinks). The 18-item ASRS consists of all the diagnostic symptoms of ADHD and is useful as a screener for gathering information about ADHD symptoms that can be examined more in-depth during a diagnostic assessment. If the ASRS screener is positive for ADHD, and there are indications of sustained difficulties with attention, motor restlessness/overactivity or impulsive behaviour, then it must trigger a full diagnostic assessment by a suitably qualified practitioner.

The SpLD Assessment and Standards Committee (SASC) guidance for the assessment of ADHD, also states that “ practitioner psychologists and specialist teacher assessors who have relevant training can identify specific learning difficulties and patterns of behaviour that together would strongly suggest a student has ADHD; and in this situation they can make relevant recommendations for support at Further and or Higher Education institutions. Such diagnostic assessments should be accepted by SFE in support of an application for Disabled Students’ Allowance ” [ 167 ], p.2). This means university students can have indicators of ADHD identified as part of a SpLD diagnostic assessment and then use their diagnostic report to apply for reasonable adjustments and DSA (Disabled Student Allowance). However, even with additional educational support in place (e.g., DSA, reasonable adjustments, or sessions of study skills), ADHD can continue to impair academic functioning if it remains untreated [ 18 ]. In a few cases it can be hard to tell if ADHD with or without co-occurring learning disorders or mental health symptoms, including intellectual giftedness, are different facets of the same condition or reflect separate disorders [ 168 ]. For instance, a student with undiagnosed ADHD who keeps performing badly academically, despite studying extra hard, may start to worry excessively or feel like a failure and then become depressed. This student may seek help because they are feeling anxious or depressed, but in fact the underlying condition is ADHD.

There are effective screening tools for anxiety, depression and substance misuse that can be used with university students with ADHD. The 10-item Kessler Psychological Distress Scale (K10) can be used to screen for anxiety and depression [ 125 ], or the 16-item Penn State Worry Questionnaire (PSWQ) can be used to screen for pathological worry, which is a dominant feature in generalised anxiety disorder [ 126 ]. There are useful screening tools in the appendices of the Improving Access to Psychological Therapies (IAPT) manual, including the Generalised Anxiety Disorder scale (GAD-2, GAD-7), Panic Disorders Severity Scale (PDSS), and the Patient Health Questionnaire (PHQ-9, for depression) [ 128 ]. The Simple Screening Instrument for Substance Abuse (SSI-SA) (Center for Substance Abuse Treatment, 1994) is widely used as a brief screen by practitioners and assessors with little experience of substance misuse [ 127 ]. NICE clinical guidance [CG123] also offers very clear advice and guidance for screening common mental health disorders, and recommends that if a practitioner conducting the screen identifies a possible anxiety disorder or depression, and they are not competent to perform a full mental health assessment, then they must refer the student to an appropriate healthcare professional [ 169 ].

Some students may have additional problems related to a SpLD (e.g., dyslexia) or ASD. Useful screeners for these conditions are the Adult Dyslexia Checklist which is available for free from the British Dyslexia Association website [ 124 ], and the Autism-Spectrum Quotient (AQ-10), is also available for free download [ 123 ]. If a student with ADHD screens positive for a SpLD or ASD, then a shared decision with the student can be made about the usefulness or value of a referral for a diagnostic assessment of these comorbid conditions. It might be for example, that a positive screen of either condition and careful questioning about functional impairments, will be enough to assess their impact on studying and how best to mitigate them with additional support (e.g., counselling, specialist mentoring, academic coaching, extra writing time for examinations). There is also evidence which suggests that once the core symptoms of ADHD are treated, problems related to co-occurring SpLDs, ASD traits, anxiety or depression may in turn improve [ 9 , 158 , 170 ]. During the shared decision-making process, an agreement with the student can be also reached about whether to include results of a positive screen for a SpLD and/or ASD in their diagnostic report, which can include a write-up about the potential complexities these conditions might add to a student’s ability to study effectively. Further details and weblinks for the screening tools are provided in Table 8 .

At present there are no neuroimaging, genetic, neurochemical, or neuropsychological diagnostic tests for ADHD that are sufficiently sensitive or specific. Neuropsychological tests such as Stop Signal Reaction Time, IQ, or various computerised tests of executive functions (e.g., CANTAB) or QB-Test, can however, complement a diagnostic assessment for ADHD and provide additional information about cognitive performance [ 171 ]. Some authors (e.g., Brown [ 98 ], conceptualise ADHD as a disorder of executive function (EF), and many learning problems that university students with ADHD experience may be due to deficits in EF (e.g., poor organisation, planning and time management skills, inattention, or emotional lability) [ 172 ]. Although these EF deficits are not well reflected in cognitive performance tests [ 173 ], an assessment of EF behaviours such as those captured by the BRIEF questionnaire are strongly related to ADHD and associated functional impairments [ 174 ]. The recommendation of the expert group (and all national/international guidelines) is that a diagnostic assessment for adults with ADHD should be based on self-reported symptoms, which are best obtained by using a semi-structured in-depth diagnostic interview. An example of such a tool is the “Diagnostic Interview for Adult ADHD” (DIVA-5), which is based on the symptom and impairment criteria of the DSM-5 [ 129 ]. The ACE+ is another diagnostic tool that can be useful, and it has the option to use either DSM-5 or ICD-11 diagnostic criteria [ 130 ]. The DIVA-5 is available for a one-off fee of 10 Euro whereas the ACE+ is free to download, with digital versions in English and other languages (see Table 8 for further details and weblinks). Collateral information can also be obtained from informants such as close friends or relatives, and school records, especially for the evaluation of age of onset.

ADHD in adults is diagnosed when 5 or more symptoms of inattention and/or hyperactivity-impulsivity are present, and with several of them being present before 12 years old. These core symptoms must have persisted for at least 6 months, and in clinical practice the expectation is of a chronic trait-like course from the age of onset during childhood or early adolescence. The symptoms of ADHD should be to a degree that is inconsistent with the developmental level for that individual and must cause functional impairments in 2 or more settings (e.g., at home, university, work, with friends or relative, or in other activities) [ 6 ]. During the diagnostic process conducting a detailed evaluation of how the student’s presenting symptoms impact on their academic productivity is essential. Potential education-related impairments due to ADHD are listed in Table 9 . Individually assessing and writing about education-related problems in the student’s diagnostic report will help practitioners working in student disability services to devise personalised support, as well as allow for the effectiveness of this support to be evaluated. The Weiss Functional Impairment Rating Scale – Self Report (WFRIS-S), is a useful tool for assessing and monitoring changes in functional impairments associated with ADHD in different domains [ 131 ].

Practitioners and assessors need to be aware that ADHD symptoms and functional impairments present differently in each student and their impact can also change over the course of their programme of studies [ 19 ]. The experience of the expert group is that some students meeting diagnostic criteria for ADHD may not want to take prescribed medication in the first instance. But as their programme of studies progresses this may change, and the student may want and require medication to reduce core symptoms of the disorder. While psychoeducation, and environmental modifications (including reasonable adjustments) can help support university students with ADHD (and may be sufficient in some cases), only medication has been found to reduce core symptoms [ 89 ]. It is the experience of the expert group that university students with ADHD often have well developed compensatory strategies such as being overly organised, almost in an obsessive manner, or studying extra hard for long periods of time to ensure adequate performance. They may also have lost the usual structured support of parents and school when they were younger, so that impairments can increasingly accrue as their course develops. During diagnostic assessments, some students can find it hard to remember what their ADHD symptoms and impairments may have been like during childhood. When this happens, it is best to focus on their presenting symptoms and establish whether at least 5 or more of them are currently present and cause impairment, then track back in time to establish as far as possible an age at which current symptoms started.

In most cases of ADHD an individual is unable to identify a clear age of onset and they have the perception that the symptoms were always present. A typical response is that the symptoms have been present for as long as they can recall. Remembering symptomatic behaviours in childhood is especially hard when the student’s parents or other care givers have given them a lot of support during their academic career, or provided them with structure and routine, or when the student, had predominantly inattentive symptoms in childhood, that were not noticed either by their parents or teachers. This is more likely in females (and some men) with ADHD, who tend to present with predominantly inattentive symptoms and few hyperactive-impulsive symptoms or less disruptive behaviour [ 50 , 138 , 175 ]. The gender bias in ADHD seems to become less skewed in adulthood when women with ADHD may be diagnosed, often for the first time [ 138 ]. Practitioners and assessors conducting a diagnostic assessment need to be aware that female students can present with study related problems due to ADHD for the first time whilst at university. These students may or may not have a previous diagnosis of another mental health condition, which will need to be reviewed if they are diagnosed with ADHD [ 138 ].

During face-to-face diagnostic assessments, compensatory strategies can be minimised. For instance, the student may not recognise that sustaining attention or organisation is problematic for them, when a more objective appraisal suggests that this is a persistence problem. This can occur because symptoms of ADHD reflect lifelong traits, or because the student has well developed compensatory strategies. When this happens, it’s best to assess the degree of effort that the student needs to put into maintaining a compensatory strategy (for example, if the student did not put in extra effort to be organised then what would happen ?). Students with severe ADHD may be easier to screen and diagnostically assess, but if these students have developed good compensatory strategies (as discussed in the section on intellectual giftedness), it can be hard to determine how severe and impairing their ADHD symptoms are in other functional domains (e.g., social relationships). It may also be at a time when compensatory strategies are sufficient to mitigate ADHD related impairments, but this may not always be the case as their programme of studies progresses. Some students may present with “subthreshold symptoms” of ADHD (i.e., symptoms just below the threshold for a diagnosis of ADHD to be made), yet they appear to be significantly impaired by these symptoms and therefore need additional support, and perhaps treatment. The experience of the expert group is that impairments are also informed by co-morbidities and that several sub-threshold comorbidities (particularly of neurodevelopmental disorders) can be more impactful than a single disorder above the diagnostic threshold [ 176 ].

Recommendation 6. Screening tools and diagnostic assessments

The expert group recommends that practitioners and assessors be given training in how to screen for and diagnostically assess ADHD using robust and evidence-based rating scales, screening tools, and standardised clinical interviews. This training should include how to conduct a detailed evaluation of education related functional impairments, write up a diagnostic report with recommendations for reasonable adjustments and make a direct referral for medical treatment if requested, to a suitably qualified practitioner with expertise in the management and treatment of ADHD in adults (e.g., a psychiatrist or mental health nurse/pharmacist non-medical prescriber). A list of standardised screening and diagnostic tools are presented in Table 8 below.

What pharmacological and non-pharmacological interventions are useful?

Following initial psychoeducation about ADHD and its impact, NICE guidance [ 50 ] recommends making “environmental modifications”. In the context of university students with ADHD environmental modifications can take the form of “reasonable adjustments” to programmes of study under the Equality Act 2010. Potential learning problems associated with ADHD and potential reasonable adjustments are listed in Table 9 . Adjustments can also be made to study environments (e.g., making available a quiet study room in the library, recommend taking frequent breaks when studying, breaking down daily targets, using digital diaries and reminders, regular forms of exercise) [ 172 ]. If these adjustments/ modifications have been applied and functional impairments continue in at least one domain (e.g. academic performance, or studying/learning difficulties), then medication should be considered.

NICE guidance [ 50 ] recommends psychostimulant medication (i.e., methylphenidate or lisdexamphetamine) as first-line medical treatment for ADHD in adults. Psychostimulant medications are among the most effective medications in use within adult mental health [ 89 ], and among the most efficacious of all common medical drugs [ 177 ]. Stimulant medications often produce a substantial reduction in ADHD symptoms and associated impairments. However, stimulant medications can also have adverse effects, which in most cases are either dose-related, mild, or transient such as headache, reduced appetite, nausea, palpitations, difficulty falling asleep and dry mouth [ 89 ]. In a few cases, these adverse effects may be undesirable, and an individual may decide to stop using stimulant medication. Stimulant medications can also increase blood pressure and heart rate, therefore people who take these medications are assessed at baseline and monitored during their treatment [ 50 ]. Empirical research about the efficacy of treating university students with ADHD is rare and the extent to which prescribers consider the unique demands of university life when prescribing medication to students is unknown [ 178 ].

The first randomised controlled trial of lisdexamphetamine with a sample of 24 university students diagnosed with ADHD was conducted by DuPaul et al., [ 179 ]. In this study, lisdexamphetamine was administered over a 5-week period and large reductions in the students ADHD symptoms were observed, alongside improvements in their task management, planning, organisation, use of study skills and working memory. Although the short duration of this study precluded an assessment of academic functioning over the long-term, in other studies, university students with ADHD who took medication did report improvements in their note taking, scores on tests, writing output and completion of course work [ 180 ]. In a pharmaco-epidemiological study from Sweden young people with ADHD taking medication were also found to have better scores in standardised university entrance examinations when compared to peers with ADHD not taking medication [ 181 ]. It is noted, however, that a substantial number of university students with ADHD do not take their medication as prescribed [ 182 ]. Some university students with ADHD may use their medication flexibly, with optimum dosing during times of writing assignments or studying for examinations and then no medication on days without academic work, e.g., at weekends or during holidays [ 183 ]. When treating university students with ADHD, prescribing practitioners therefore need to be open to discussing the benefits and drawbacks of flexible dosing with students and be willing to offer appropriate guidance and advice [ 184 , 185 ].

Non-pharmacological interventions

The view of the expert group is that non-pharmacological interventions are particularly important for university students who want or need to learn how to best manage their ADHD and overcome the learning difficulties that they experience. Medication alone maybe sufficient for a subgroup of university students, but persistent difficulties are more often seen, and additional support maybe required. Non-pharmacological interventions begin with psychoeducation. The experience of the expert group is that newly diagnosed students are keen to have a conversation about their diagnosis, including whether or not to disclose it to academic staff or future employers, the benefits, and drawbacks of taking medication, including flexible dosing, “drug holidays”, effects of medication on alcohol or other drugs, the positive attributes of ADHD (e.g., creativity), psychological interventions and reasonable adjustments. Research about the effectiveness of non-pharmacological interventions for adults with ADHD is mixed and inconclusive, but positive effects have been reported for mindfulness on core symptoms of ADHD including mind wandering [ 186 ], dialectical behaviour therapy (DBT) and cognitive behavioural therapy (CBT) [ 187 , 188 , 189 ].

Although research about non-pharmacological interventions for university students with ADHD is limited, new studies have been published. For instance, Anastopoulos et al. [ 190 ] and Eddy et al. [ 191 ] reported on the findings of a randomised controlled trial (RCT) that examined the efficacy of a CBT based program called ACCESS (Accessing Campus Connections and Empowering Student Success) for university students with ADHD. During the ACCESS program - psychoeducation, cognitive and behavioural strategies targeting executive function (EF) and patterns of maladaptive thinking, were delivered. Participants, who met DSM-5 diagnostic criteria for ADHD and were taking medication, were recruited from two large public universities in the USA and randomly assigned to either the ACCESS program group ( n  = 119) or a Delayed Treatment Control (DTC) group ( n  = 131). The findings revealed that the ACCESS program group participants self-reported significant improvements in their knowledge of ADHD, symptoms of inattention, EF, utilisation of disability accommodations (or reasonable adjustments), as well as a moderate decline in maladaptive thinking, when compared to DTC group participants. However, neither ACCESS program and DTC group participants reported significant improvements in their interpersonal functioning and educational outcomes (grade point average/GPA and course grade completion). The authors concluded that the ACCESS program made a large difference to the participants core symptoms of ADHD and EF.

Indeed, as noted previously, EF deficits have been shown to mediate the association between ADHD and impairments in academic functioning [ 100 ]. The finding that the ACCESS program positively impacted on the participants EF is therefore encouraging. It also supports the findings of an earlier pilot study about a CBT based group intervention to enhance EF functioning in university students with ADHD [ 172 ], and strengthens a more recent finding about how steep temporal discounting may play a key role in the daily life challenges that university students with ADHD encounter. Temporal discounting (TD) describes how the subjective value of a reward significantly declines when the said reward is delayed [ 192 ]. In a pilot study by Scheres and Solanto [ 193 ], steep TD was not only associated with combined type ADHD, specifically the hyperactivity-impulsivity symptom domain, but also with poor utilisation of learning and/or study skills. TD was therefore postulated to be an important target for EF interventions for university students with or without ADHD [ 193 ], more so for interventions that were designed to activate and sustain motivation to pursue a long-term goal for a reward, such as pursuing and completing a university degree [ 194 ]. Findings like this could be useful for enhancing the effectiveness of CBT based interventions for university students with ADHD like the ACCESS program, by for example, tailoring EF interventions to also target TD. Maybe this could improve educational outcomes and perhaps interpersonal functioning of university students with ADHD, which in the study reported by Anastopoulos et al. [ 190 ] showed no significant improvements.

The report that the ACCESS program made a large difference to the students’ core symptoms of ADHD, seems to contradict what the World Federation of ADHD international consensus statement acknowledged about good treatments for ADHD being available, but even the best treatments are only partially effective [ 164 ]. Overall, there is only low-quality evidence that CBT interventions might be beneficial for treating core symptoms of ADHD in adults, in the short-term, or for improving co-occurring symptoms of anxiety and depression [ 164 , 195 ]. It was noted by Anastopoulos et al., [ 190 ], that participants in both study groups increased their use of ADHD medications over the course of the study. Perhaps this was the real reason that the participants core symptoms of ADHD improved. After all, this is what ADHD medications are designed to do and treatments for ADHD usually become more effective when medication is combined with a CBT intervention [ 195 ], or when multimodal interventions are used [ 196 ].

Hence academic coaching, which tends to be a derivative of CBT, could be another useful intervention for optimising coping strategies in university students with ADHD. For instance, coaching has been used to help identify study goals, develop study plans and strategies for achieving these plans, monitoring their progress towards attaining them and to foster self-determination [ 197 ]. In one study, academic coaches helped university students with ADHD to develop better time management, organisational skills, pay more attention in classes and to take good notes, and improvements in these skills were observed after 8 weeks [ 198 ]. In another study, university students with ADHD reported that academic coaching had helped to enhance their self-discipline, self-efficacy, study skills, ability to formulate realistic goals and to think more about long-term goals and maintain motivation to achieve them [ 199 ]. Additional benefits of coaching can be in helping university students with ADHD feel more in control of their emotions and behaviours in the face of external demands [ 200 ]. Academic coaching (or specialist mentoring, or specialist one-to-one study skills support), can also be funded via DSA as specialist access and learning facilitators (Band 4). Academic coaching, supportive counselling and/or CBT, whether delivered face-to-face or online can be effective non-pharmacological interventions for university students with ADHD [ 188 , 189 , 201 ], and the potential of these interventions to improve academic performance is evident in the promising results of recent studies e.g. [ 172 , 190 ].

Recommendation 7. Multimodal interventions

The expert group recommends multimodal interventions for university students with ADHD, that comprise a variety of interventions including environmental modifications, psychoeducation, medication, academic coaching, DBT, CBT, counselling and/or mindfulness-based interventions. University counselling and disability services do tend to offer a range of psychosocial interventions for students, whether delivered online, face-to-face or in a group.

What are the staff training and developmental needs?

In the Institute for Employment Studies report to the Office for Students, practitioners working in university disability services identified a need for training and development to enable them to both support university students with ADHD and the academic staff working with them [ 52 ]. The SpLD Assessments and Standards Committee (SASC) [ 167 ], also recommended that practitioner psychologists and specialist teacher assessors require appropriate training to identify “ specific learning difficulties and patterns of behaviour that together would strongly suggest that a student has ADHD ” (p.11). The need for staff training and development was discussed during the consensus meeting, and it included training in how to liaise with and refer university students with ADHD to a suitably qualified practitioner for a diagnostic assessment (e.g., a psychiatrist, mental health nurse/ pharmacist non-medical prescriber). Practitioners and assessors seemed keen to receive “certified training” as a way to achieve the SASC recommendations for “appropriate training”. A certified educational programme about ADHD at university level 6 or 7, could be developed and delivered for example online, as a post-qualification professional training or continuous professional development (CPD). But at present, no such course/programme exists in the UK. UKAAN offers training for healthcare professionals and can deliver bespoke training to practitioners and assessors who work with university students, and some disability services have already done so. During the consensus meeting some practitioners and assessors said they often gained relevant experience by having previously worked, or currently working, with university students with ADHD or through their own personal lived experiences, and that they made use of these experiences in their role.

Recommendation 8. Training and development

The expert group recommends that staff training, and development be prioritised under the inclusive practice agenda in higher education. This training should include psychoeducation, procedures for screening and assessing for ADHD, and useful strategies for supporting university students with ADHD. This will enhance the knowledge and skills of practitioners and assessors who work with and/or support university students with ADHD.

Discussion & conclusion

This was a report of the UKAAN expert consensus meeting about university students with ADHD, which was held before the COVID-19 pandemic. Since then, the pandemic has altered higher education in a monumental way. When lockdown was first imposed in the UK, university campuses were suddenly closed. Students and staff had to quickly adapt to online delivery of lectures and classes, and there was uncertainty about being able to access digital technologies and quite places to study or work at home. There was also confusion among students about study expectations, assessments, workloads, retention, and completion [ 202 , 203 , 204 ]. Undoubtedly the pandemic has caused much suffering, frustration, fear, loss and other negative thoughts, emotions, and experiences for many people, including university students with ADHD [ 205 ]. However, findings about the impact of the pandemic on university students has been mixed. Frampton and Smithies [ 206 ], reported on a Students Minds survey about life during the pandemic involving 1100 university students. The findings of this survey revealed that 74% of respondents reported that the pandemic had a negative impact on their mental health and wellbeing, whilst only 10% of respondents reported positive effects. In this survey, disabled and non-disabled students were also asked whether they agreed or disagreed with the statement “ online learning has allowed me to engage with my course more positively ”, and the findings revealed that 59% of disabled students compared with 55% of non-disabled students disagreed with the statement. This also suggests that just under-half of these students agreed with the statement. In another study, 79 university students in one Faculty of Life Sciences were surveyed and participated in focus groups about how they experienced the sudden shift to online learning during the lockdown [ 207 ]. This study found that 75% of the students who participated in the study, reported that their life had become more difficult and 50% reported that learning outcomes would be hard to achieve, but after 12 weeks into the lockdown, corresponding rates changed to 57 and 71% respectively [ 207 ].

The findings of existing studies do suggest that during the COVID-19 lockdown, virtual learning for some university students may have had benefits such as enabling greater attendance, engagement, and participation in teaching sessions, especially for students who previously felt anxious about asking questions in front of others or some disabled students [ 202 ]. Students who were used to spending time online – on the Internet including social media platforms for example, seemed to exhibit strong motivation for eLearning, and reported lower levels of distress during the pandemic [ 208 ]. However, there are also concerning reports about ADHD being a risk factor for COVID-19 infection [ 209 , 210 ]. These reports are perhaps pertinent for university students with ADHD who may have participated in demonstrations during the pandemic such as Black Lives Matter (BLM), living arrangements in student halls of residence, sexual harassment, assault and “rape culture” in UK universities [ 206 , 211 ], or illegal COVID raves [ 212 ], or the COVID anti-vaccine and lockdown protests [ 213 ]. It can be argued that the pandemic may have longer-term negative consequences on current and future career prospects for university students with ADHD, but outside of this, no firm conclusions from the existing research can be drawn.

Evidence is stronger for poor education (or academic) performance and achievement having a long-term negative impact on mental health, wellbeing, and socio-economic outcomes [ 214 ]. Even though there is a paucity of research about university students with ADHD in the UK and rest of Europe, the importance of attending to the mental health of university students in the UK has been recognised. The Royal College of Psychiatrists recently published a college report on the mental health of higher education students, and Sedgwick-Müller et al., contributed a section on ADHD in this report [ 1 ]. The expert group is also aware that ADHD is a hidden disability within UK HEIs and its categorisation as a SpLD may be contributing to this, therefore university students with ADHD continue to be at risk of marginalisation and disadvantage. The expert group recommends that ADHD should be catered for under a separate category within UK HEIs, as this may enable greater recognition of ADHD and for its impact on learning within higher education to be adequately assessed and mitigated. With aspirations towards widening participation and inclusive practices in higher education [ 52 ], understanding exactly “what works” best for university students with ADHD is imperative. The four key stages in a student’s lifecycle are access to higher education (the extent to which students can gain entrance to different types of HEIs), retention (the likelihood of continuing or withdrawing from a programme of studies), attainment (the extent to which university students are enabled to achieve their full academic potential) , and progression (successful transitions within a programme of studies and afterwards into employment or further study )” [ 215 ], p.5). Each of these 4 key stages in a student’s lifecycle can be adversely affected by either having and/or not recognising ADHD, and by delaying access to a screening, diagnostic assessment, treatment, and educational support. Interventions in a student’s first year at university, according to Clery and Topper, should focus on enhancing their academic achievement because retention, attainment, and progression tends to be more favourable for university students who perform well academically in their first year [ 216 ].

In summary, UKAAN convened an expert consensus meeting to provide an informed understanding about the impact of ADHD on the educational (or academic) outcomes of university students and to highlight an urgent need for timely access to treatment and management. An overview of key issues, as well as expert advice and guidance has been offered. In Table 10 below, the main recommendations of the expert group are summarised. There is little doubt that university students with ADHD are struggling with long delays in accessing a diagnostic assessment, treatment, and personalised educational support. The provision of rapid access treatment and care pathways can be challenging for clinicians working in specialist NHS ADHD clinics, but examples of good practice are also beginning to emerge, with some university disability services drawing on their own budgets to support their students. Further work is needed to develop and evaluate efficient and cost-effective treatment and care pathways for university students with ADHD (for example see Fig. 4 ), and to adopt models of best practice across the sector. University students, including those with ADHD, are at a crucial transitioning stage in life and their success at university is likely to determine their success in highly competitive employment markets. This strengthens the argument to support all university students in an inclusive manner. Methods for inclusive teaching and learning are also likely to cater to disabled students, including university students with ADHD.

Availability of data and materials

Data sharing is not applicable to this article as no data sets were generated or analysed during the study.

Abbreviations

ADHD Child Evaluation

Association for Higher Access & Disability

Attention Deficit Hyperactivity Disorder

American Psychiatric Association

Autism-Spectrum Quotient

Autism Spectrum Disorder

Adult ADHD Self-report Rating Scale

Canadian ADHD Practice Guidelines

Cognitive Behavioural Therapy

Diagnostic Interview for ADHD in adults

Dialectical Behavioural Therapy

Disabled Students Allowance

Developmental co-ordination disorder

Diagnostic and Statistical Manual of Mental Disorders version 5

Emotional lability

Executive Functions

Institutions of Higher Education

The Higher Education Statistical Authority

Improving Access to Psychological Therapies

Institute of Employment Studies

Major Depressive Disorder

Math Disability

National Health Service

National Institute for Health and Care Excellence

Office for Students

Panic Disorders Severity Scale

Patient Health Questionnaire

Processing Speed

Penn State Worry Questionnaire

Quantified Behavior Test

Reding Disability

Special Educational Needs and Disabilities

Special Educational Needs

Specific Learning Disorders

SpLD Assessment and Standards Committee

Specific learning differences

The Simple Screening Instrument for Substance Abuse

UK Adult ADHD Network

United Kingdom of Great Britain and Northern Ireland

Wechsler Adult Intelligence Scale

Weiss Functional Impairment Rating Scale – Self Report

World Health Organisation

Working Memory

Writing Disability

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Acknowledgements

We acknowledge JSM for facilitating the consensus meeting and preparing this manuscript, PA, UMS, for assistance in reviewing and editing drafts of this manuscript. We are grateful to Ms. Sue Curtis for recording the meeting and preparing the transcripts from the meeting.

This research did not receive any funding from public, private, or not-for-profit organisations or agencies.

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Jane A. Sedgwick-Müller

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Ulrich Müller-Sedgwick

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JSM conceived the work; PA, MC, RC were keynote speakers during the meeting; JSM, PA and UMS were involved in drafting the manuscript and critically revising it. A final draft was circulated by JSM to UMS, MA, MC, RC, GG, DH, MP, SY and PA, who endorsed the consensus and approved the manuscript.

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YES, “JSM, USM, MP, SY, PA have received honoraria and pharmaceutical funding for consultation, research awards, educational talks, study days and/or conference support. JSM is in receipt of an educational grant from the Royal College of Nursing (RCN) Foundation towards PhD tuition fees and received the 2020 RCN Muriel Fleet Award for outstanding professional development and 2020 Genius Within Award for Neurodiverse Research of the Year and all other authors have no other competing interests to disclose.”

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Sedgwick-Müller, J.A., Müller-Sedgwick, U., Adamou, M. et al. University students with attention deficit hyperactivity disorder (ADHD): a consensus statement from the UK Adult ADHD Network (UKAAN). BMC Psychiatry 22 , 292 (2022). https://doi.org/10.1186/s12888-022-03898-z

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NIH Researchers Identify Brain Connections Associated With ADHD in Youth

Large study finds atypical interactions between the frontal cortex and information processing centers deep in the brain

March 13, 2024 • Media Advisory

Researchers at the National Institutes of Health (NIH) have discovered that symptoms of attention-deficit/hyperactivity disorder (ADHD) are tied to atypical interactions between the brain’s frontal cortex and information processing centers deep in the brain. The researchers examined more than 10,000 functional brain images of youth with ADHD and published their results in the American Journal of Psychiatry . The study was led by researchers at NIH’s National Institute of Mental Health (NIMH) and National Human Genome Research Institute.

Luke Norman, Ph.D., a staff scientist in the NIMH Office of the Clinical Director, and colleagues analyzed brain images supplied by more than 8,000 youth with and without ADHD sourced from six different functional imaging datasets. Using these images, the researchers examined associations between functional brain connectivity and ADHD symptoms.

They found that youth with ADHD had heightened connectivity between structures deep in the brain involved in learning, movement, reward, and emotion (caudate, putamen, and nucleus accumbens seeds) and structures in the frontal area of the brain involved in attention and control of unwanted behaviors (superior temporal gyri, insula, inferior parietal lobe, and inferior frontal gyri).

While neuroscience researchers have long suspected that ADHD symptoms result from atypical interactions between the frontal cortex and these deep information-processing brain structures, studies testing this model have returned mixed findings, possibly due to the small nature of the studies, with only 100 or so subjects. Researchers suggest that the smaller studies may not have been able to reliably detect the brain interactions leading to the complex behaviors seen in ADHD.

The findings from this study help further our understanding of the brain processes contributing to ADHD symptoms—information that can help inform clinically relevant research and advancements.

Luke Norman, Ph.D., staff scientist in the NIMH Office of the Clinical Director and lead author of the paper

Norman, L. J., Sudre, G., Price, J., & Shaw, P. (2024). Subcortico-cortical dysconnectivity in ADHD: A voxel-wise mega-analysis across multiple cohorts. American Journal of Psychiatry .  https://ajp.psychiatryonline.org/doi/10.1176/appi.ajp.20230026  

About the National Institute of Mental Health (NIMH): The mission of the NIMH  is to transform the understanding and treatment of mental illnesses through basic and clinical research, paving the way for prevention, recovery and cure. For more information, visit the NIMH website .

About the National Institutes of Health (NIH) : NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH  and its programs, visit the NIH website  .

NIH…Turning Discovery Into Health ®

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

• Original Paper
• Open access
• 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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Authors and affiliations.

Centre for Clinical Brain Sciences, Child Life and Health, University of Edinburgh, Edinburgh, United Kingdom

Emily McDougal, Claire Tai & Sinéad M. Rhodes

Moray House School of Education and Sport, University of Edinburgh, Edinburgh, United Kingdom

Tracy M. Stewart & Josephine N. Booth

School of Psychology, University of Surrey, Guildford, United Kingdom

Emily McDougal

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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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About this article

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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Accepted : 06 June 2022

Published : 01 July 2022

Issue Date : September 2023

DOI : https://doi.org/10.1007/s10803-022-05639-3

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College students with adhd: a selective review of qualitative studies.

1. Introduction

1.1. qualitative research methods, 1.2. the present study, 2. materials and methods, 2.1. search strategy, 2.2. study selection, 2.3. variable identification, 3.1. quantitative results, 3.2. qualitative results, 3.2.1. the college experience of students with adhd, 3.2.2. interventions, 3.2.3. cognitive and academic functioning, 3.2.4. self-functioning, 4. discussion, 5. conclusions, author contributions, conflicts of interest, appendix a. summaries of included studies, appendix a.1. the college experience of students with adhd, appendix a.1.1. college transitions, appendix a.1.2. adhd as an identity, appendix a.1.3. race, appendix a.1.4. community college, appendix a.2. interventions, appendix a.2.1. coaching, appendix a.2.2. strategies, appendix a.2.3. medication, appendix a.3. cognitive and academic functioning, appendix a.4. self-functioning.

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Cohen, S.L.; Shavel, K.; Lovett, B.J. College Students with ADHD: A Selective Review of Qualitative Studies. Disabilities 2024 , 4 , 658-677. https://doi.org/10.3390/disabilities4030041

Cohen SL, Shavel K, Lovett BJ. College Students with ADHD: A Selective Review of Qualitative Studies. Disabilities . 2024; 4(3):658-677. https://doi.org/10.3390/disabilities4030041

Cohen, Shira L., Katie Shavel, and Benjamin J. Lovett. 2024. "College Students with ADHD: A Selective Review of Qualitative Studies" Disabilities 4, no. 3: 658-677. https://doi.org/10.3390/disabilities4030041

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• Data and Statistics on ADHD
• Free Materials on ADHD
• Attention-Deficit / Hyperactivity Disorder Articles
• Clinical Care and Treatment
• View All Home

At a glance

• CDC uses datasets from parent surveys and healthcare claims to understand diagnosis and treatment patterns for attention-deficit/hyperactivity disorder (ADHD).
• Estimates for diagnosis and treatment can vary depending on the source.
• This page includes ADHD data from different sources.

ADHD diagnosis

Millions of u.s. children have been diagnosed with adhd. 1.

An estimated 7 million (11.4%) U.S. children aged 3–17 years have ever been diagnosed with ADHD, according to a national survey of parents using data from 2022.

Did you know?‎

Adhd estimates by sex, race, and ethnicity: 1.

• Boys (15%) were more likely to be diagnosed with ADHD than girls (8%).
• Black children and White children were more often diagnosed with ADHD (both 12%) than Asian children (4%). American Indian/Alaska Native children (10%) were also more often diagnosed with ADHD than Asian children.
• Approximately 6% of Native Hawaiian/Pacific Islander children were diagnosed with ADHD.
• Overall, non-Hispanic children (12%) were diagnosed with ADHD more often than Hispanic children (10%).

ADHD symptoms can vary in severity.

• About 6 in 10 children had moderate or severe ADHD.
• Children with both ADHD and another co-occurring condition, such as behavioral or conduct problems, learning disorders, anxiety, or depression, more often had severe ADHD than children with ADHD without other co-occurring conditions.

Estimates for ADHD diagnosis and treatment vary by state. 3

• ADHD diagnosis estimates among U.S. children aged 3–17 years vary from 6% to 16% across states.
• Estimates for receiving any ADHD treatment among children with current ADHD vary from 58% to 92% across states. ADHD treatments include:

Other concerns and conditions with ADHD

Many children with adhd also have other co-occurring conditions. 1.

According to a national 2022 parent survey, nearly 78% of children with ADHD had at least one other co-occurring condition:

• Almost half of the children with ADHD had a behavior or conduct problem.
• About 4 in 10 of the children with ADHD had anxiety.

Other conditions affecting children with ADHD include depression , autism spectrum disorder , and Tourette syndrome.

Co-occurring Conditions with ADHD – Interactive Data Charts 1

Treatment of adhd, nearly 2 million u.s. children with adhd did not receive adhd-specific treatment in 2022. 1.

A national parent survey from 2022 reported on medication and behavior treatment for children 3–17 years of age with current ADHD:

• About 30% of children with ADHD did not receive medication treatment or behavior treatment , compared with 23% of children 2–17 years of age with ADHD in 2016. 1 3
• About 32% children with ADHD received both medication treatment and behavior treatment.
• Overall, the total number of children receiving behavior treatment increased from 2016 (2.5 million) to 2022 (2.8 million).

Treatment of ADHD – Interactive Data Charts 1

Children with adhd receive different types of services..

There are many treatment options for ADHD, and what works best can depend on the person, their family, and their environment. Different types of behavioral treatment or skills training for ADHD include:

• Parent-delivered behavior therapy
• Social skills training
• Peer interventions
• Cognitive behavior therapy (CBT)

ADHD care is provided by many different healthcare professionals. 4

In addition to parent-reported data, healthcare claims data from Medicaid or employer-sponsored insurance provide another way to understand treatment patterns. In 2021, among U.S. children ages 3–17 years:

• Many children received ADHD care from a primary care clinician, such as a pediatrician or family doctor. Almost half of children covered through private insurance and about 1 in 4 children with Medicaid received ADHD care from a pediatrician.
• Nurse practitioners and psychiatric nurses also play an important role in ADHD care for children, providing care for nearly 1 in 5 children with Medicaid.
• Children with Medicaid were less likely to receive ADHD care from a healthcare specialist, such as a psychologist or psychiatrist.

More information on ADHD data trends in the United States

• Facts About ADHD Throughout the Years | Attention-Deficit / Hyperactivity Disorder (ADHD) | CDC
• State-based Prevalence of ADHD Diagnosis and Treatment 2016–2019 | Attention-Deficit / Hyperactivity Disorder (ADHD) | CDC

Where the data come from

• MarketScan® Commercial Claims and Encounters (CCE) Database & MarketScan® Multi-State Medicaid Database | Merative ™
• National Survey of Children's Health (NSCH) | MCHB (hrsa.gov)
• National Survey of the Diagnosis and Treatment of ADHD and Tourette Syndrome
• Danielson ML, Claussen AH, Bitsko RH, et al. ADHD Prevalence Among U.S. Children and Adolescents in 2022: Diagnosis, Severity, Co-Occurring Disorders, and Treatment. J Clin Child Adolesc Psychol. Published online May 22, 2024.
• Bitsko RH, Claussen AH, Lichstein J, et al.  Mental health surveillance among children—United States, 2013–2019. MMWR Suppl. 2022;71(2):1-48.
• Danielson ML, Holbrook JR, Bitsko RH, et al. State-Level Estimates of the Prevalence of Parent-Reported ADHD Diagnosis and Treatment Among U.S. Children and Adolescents, 2016 to 2019. J Atten Disord. 2022;26(13):1685-1697.
• Danielson ML, Claussen AH, Arifkhanova A, Gonzalez MG, Surman C. Who Provides Outpatient Clinical Care for Adults With ADHD? Analysis of Healthcare Claims by Types of Providers Among Private Insurance and Medicaid Enrollees, 2021. J Atten Disord. 2024;28(8):1225-1235.

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ADHD Research Roundup: New Studies, Findings & Insights

Adhd research continues to reveal new insights about attention deficit — its relationship to trauma, race, emotional dysregulation, rejection sensitive dysphoria, and treatments ranging from medication to video games. we’ve curated the most significant news of the past year., adhd research continues to reveal new truths.

ADHD research has produced groundbreaking and impactful discoveries in the past year. Our understanding of the relationship between health care and race has deepened. Alternative treatments, like video games and neurofeedback, are showing encouraging promise while ADHD stimulant medication continues to demonstrate benefits for patients of all ages. The connections between comorbid conditions, gender, and ADHD are better understood than ever before. And we are encouraged by the ongoing work coming from the world’s leading research teams.

Read below to catch up on the most significant news and research from 2020, and stay updated on new findings as they are published by subscribing to ADDitude’s free monthly research digest .

General ADHD Research

Study: Long-Term Health Outcomes of Childhood ADHD are Chronic, Severe November 24, 2020 Childhood ADHD should be considered a chronic health problem that increases the likelihood of adverse long-term health outcomes, according to a population-based birth cohort study of children with ADHD and psychiatric disorders. Further research on the impact of treatment is needed.

Study: Living with ADHD Causes Significant Socioeconomic Burden October 21, 2020 Living with ADHD poses a significant economic burden, according to a new study of the Australian population that found the annual social and economic cost of ADHD was $12.76 billion, with per person costs of $15,664 over a lifetime.

Study: Unmedicated ADHD Increases the Risk of Contracting COVID-19 July 23, 2020 The COVID-19 infection rate is nearly 50% higher among individuals with unmedicated ADHD compared to individuals without ADHD , according to a study of 14,022 patients in Israel. The study found that ADHD treatment with stimulant medication significantly reduces the risk of virus exposure among individuals with ADHD symptoms like hyperactivity and impulsivity.

[ Does My Child Have ADHD? Take This Test to Find Out ]

Study: Poverty Increases Risk for ADHD and Learning Disabilities March 23, 2020 Children from families living below the poverty level, and those whose parents did not pursue education beyond high school, are more likely to be diagnosed with ADHD or learning disabilities, according to a new U.S. data brief that introduces more questions than it answers.

ADHD and Children

Study: Diagnosed and Subthreshold ADHD Equally Impair Educational Outcomes in Children December 21, 2020 Children with diagnosed and subthreshold ADHD both experienced impaired academic and non-academic performance compared to controls used in an Australian study examining the two community cohorts.

Study: Children with ADHD More Likely to Bully — and to Be Bullied November 23, 2020 Children with ADHD are more likely than their neurotypical peers to be the bully, the victim of bullying, or both, according to a new study.

Study: ADHD Symptoms in Girls Diminish with Extracurricular Sports Activity October 16, 2020 Consistent participation in organized sports reliably predicted improved behavior and attentiveness in girls with ADHD, according to a recent study of elementary school students active — and not active — in extracurricular activities. No such association was found for boys with ADHD.

[ Do I Have ADHD? Take This Test to Find Out ]

Study: ADHD in Toddlers May Be Predicted by Infant Attentional Behaviors August 12, 2020 Infants who exhibit behaviors such as “visually examining, acting on, or exploring nonsocial stimuli including objects, body parts, or sensory features” may be more likely to demonstrate symptoms of ADHD as a toddler, according to a new study that also found a correlation between this Nonsocial Sensory Attention and later symptoms of executive dysfunction.

Study Shows Gender Disparities in ADHD Symptoms of Hyperactivity and Poor Response Inhibition June 26, 2020 Girls with ADHD are less physically hyperactive than are boys with the condition, and experience fewer problems with inhibition and cognitive flexibility, according to a new meta-analysis that says more accurate screening tools are needed to recognize the subtler manifestations of ADHD in girls.

Study: Raising a Child with ADHD Negatively Impacts Caregivers’ Mental Wellbeing July 27, 2020 Caring for a child with ADHD negatively impacts caregivers’ quality of sleep, relationships, and satisfaction with free time, among other indicators of mental wellbeing, according to a recent study from the United Kingdom. The significant deficit in sleep and leisure satisfaction led researchers to conclude that caregivers may benefit from greater support — for example, coordinated health and social care — that focuses on these areas.

Study: ADHD, Diet, Exercise, Screen Time All Directly or Indirectly Impact Sleep July 27, 2020 A child with ADHD is more likely to experience sleep problems, in part because ADHD symptoms influence diet and physical activity — two factors that directly impact sleep. This finding comes from a new study that also shows how screen time impacts exercise, which in turn impacts sleep. Understanding these interwoven lifestyle factors may help caregivers and practitioners better treat children with ADHD.

ADHD and Adolescents

Teens with ADHD Should Be Regularly Screened for Substance Use Disorder: International Consensus Reached July 17, 2020 Adolescents with ADHD should be regularly screened for comorbid substance use disorder, and vice versa. This was one of 36 statements and recommendations regarding SUD and ADD recently published in the European Research Addiction Journal.

Study: Girls with ADHD Face Increased Risk for Teen Pregnancy February 12, 2020 Teenagers with ADHD face an increased risk for early pregnancy, according to a new study in Taiwan. However, long-term use of ADHD medications does reduce the risk for teen pregnancies. Researchers suggested that ADHD treatment reduces the risk of any pregnancy and early pregnancy both directly by reducing impulsivity and risky sexual behaviors and indirectly by lowering risk and severity of the associated comorbidities, such as disruptive behavior and substance use disorders.

Study: Teens with ADHD Face Increased Risk for Nicotine Addiction January 27, 2020 Young people with ADHD find nicotine use more pleasurable and reinforcing after just their first smoking or vaping experience, and this may lead to higher rates of dependence, according to findings from a new study published in the Journal of Neuropsychopharmacology .

Study: Adolescent Health Risks Associated with ADHD Go Unmonitored by Doctors February 27, 2020 The health risks facing adolescents with ADHD — teen pregnancy, unsafe driving, medication diversion, and more — are well documented. Yet, according to new research, primary care doctors still largely fail to address and monitor these urgent topics during their patients’ transition to young adulthood.

Study: Emotional Dysregulation Associated with Weak, Risky Romantic Relationships Among Teens with ADHD May 20, 2020 Severe emotional dysregulation increases the chances that an adolescent with ADHD will engage in shallow, short-lived romantic relationships and participate in unprotected sex, according to a new study that suggests negative patterns developed in adolescence may continue to harm the romantic relationships and health of adults with ADHD .

ADHD and Adults

Study: Discontinuing Stimulant Medication Negatively Impacts Pregnant Women with ADHD December 17, 2020 Women with ADHD experience negative impacts on mood and family functioning when they discontinue stimulant medication use during pregnancy, according to a new observational cohort study that suggests medical professionals should consider overall functioning and mental health when offering treatment guidance to expectant mothers.

New Study: Adult ADHD Diagnosis Criteria Should Include Emotional Symptoms April 21, 2020 The ADHD diagnosis criteria in the DSM-5 does not currently include emotional symptoms, despite research indicating their importance. Now, a new replication analysis has found that ADHD in adults presents in two subtypes: attentional and emotional. Researchers suggest that this system offers a more clinically relevant approach to diagnosing ADHD in adults than does the DSM-5 .

Study: Stimulant ADHD Medication Relatively Safe and Effective for Older Adults June 30, 2020 Older adults with ADHD largely experience symptom improvement when taking a low dose of stimulant medication, which is well tolerated and does not cause clinically significant cardiovascular changes. This is the finding of a recent study examining the effects of stimulant medication among adults aged 55 to 79 with ADHD, some of whom had a pre-existing cardiovascular risk profile.

ADHD, Race, and Culture

Study Explores Medication Decision Making for African American Children with ADHD June 23, 2020 In a synthesis of 14 existing studies, researchers have concluded that African American children with ADHD are significantly less likely than their White counterparts to treat their symptoms with medication for three main reasons: caregiver perspectives on ADHD and ADHD-like behaviors; beliefs regarding the risks and benefits associated with stimulant medications; and the belief that ADHD represents a form of social control.

Culturally Adapted Treatment Improves Understanding of ADHD In Latinx Families August 31, 2020 Latinx parents are more likely to recognize and understand ADHD after engaging in culturally adapted treatment (CAT) that includes parent management training sessions adapted to be more culturally appropriate and acceptable, plus home visits to practice skills. This recent review of ADHD knowledge among Latinx parents found that CAT outperformed evidence-based treatment (EBT) in terms of parent-reported knowledge of ADHD.

Treating ADHD

Study: New Parent Behavior Therapy Yields Longer ADHD Symptom Control in Children October 6, 2020 ADHD symptom relapse was significantly reduced in children of parents who participated in a new schema-enhanced parent behavior therapy, compared to those whose parents participated in standard PBT.

Research: Physical Exercise Is the Most Effective Natural Treatment for ADHD — and Severely Underutilized January 22, 2020 A new meta-analysis shows that physical exercise is the most effective natural treatment for controlling ADHD symptoms such as inhibition, attention, and working memory . At the same time, a comprehensive study reveals that children with ADHD are significantly less likely to engage in daily physical activity than are their neurotypical peers.

A Video Game Prescription for ADHD? FDA Approves First-Ever Game-Based Therapy for Attention June 18, 2020 Akili Interactive’s EndeavorRx is the first game-based digital therapeutic device approved by the FDA for the treatment of attention function in children with ADHD. The history-making FDA OK followed a limited-time release of the device during the coronavirus pandemic, and several years of testing the device in randomized controlled trials.

Study: Neurofeedback Effectively Treats ADHD April 9, 2020 Neurofeedback is an effective treatment for ADHD , according to a new quantitative review that used benchmark studies to measure efficacy and effectiveness against stimulant medication and behavior therapy. These findings relate to standard neurofeedback protocols, not “unconventional” ones, for which significant evidence was not found.

Study: Mindfulness-Enhanced Behavioral Parent Training More Beneficial for ADHD Families June 29, 2020 Behavioral parent training (BPT) enhanced with mindfulness meditation techniques provides additional benefits to parents of children with ADHD, such as improved discipline practices and parental behavioral regulation. This is the finding of a new randomized control trial conducted by researchers who compared mindfulness-enhanced to standard BPT.

Mapping the ADHD Brain: MRI Scans May Unlock Better Treatment and Even Symptom Prevention March 9, 2020 Brain MRI is a new and experimental tool in the world of ADHD research. Though brain scans cannot yet reliably diagnose ADHD, some scientists are using them to identify environmental and prenatal factors that affect symptoms, and to better understand how stimulant medications trigger symptom control vs. side effects.

New Clinical Guidelines: Holistic Treatment Is Best for Children with ADHD and Comorbidities February 3, 2020 The Society for Developmental and Behavioral Pediatrics (SDBP) says that children and teens with ADHD plus comorbidities should receive psychosocial treatment, such as classroom-based management tools, in addition to ADHD medication.

Study: Mindfulness Exercises Effectively Reduce Symptoms in Boys with ADHD and ODD May 19, 2020 Boys with both ADHD and ODD were less hyperactive and more attentive after attending a multi-week mindfulness training program, according to a new study that finds promise in this treatment as a viable complement or alternative to medication.

ADHD and Comorbid Conditions

Study: Risk for Diabetes 50% Higher for Adults with ADHD October 23, 2020 A diagnosis of ADHD increased the likelihood of diabetes by as much as 50% for adults with ADHD, according to a recent study from the National Health Interview Survey that found the strong correlation independent of BMI.

Study: ADHD Symptoms Associated with More Severe Gambling Disorder and Emotional Dysregulation January 28, 2020 Roughly one-fifth of individuals diagnosed with gambling disorder in the study also tested positive for ADHD symptoms. This population is more likely to experience severe or acute symptoms of gambling disorder, which is tied to higher emotional dysregulation, according to a new study of 98 Spanish men.

ADHD Research: Next Steps

• Read: New Insights Into Rejection Sensitive Dysphoria
• Download: The All-Time Best Books on ADHD
• Learn: What Is ADHD? Definition, Myths & Truths

ADHD News & Research: Read These Next

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Higher ADHD diagnosis and prescriptions for children born in July and August, research finds

by University of York

Children born in July and August are at least 40% more likely to be diagnosed with—and to receive prescriptions for—attention deficit hyperactivity disorder (ADHD), than children born in September and October, new research has found.

This research is being presented at the European Association of Labour Economics on September 7 and is published as a discussion paper by the IZA Institute of Labour Economics .

In England, most children start school full-time in the September after their fourth birthday, resulting in almost a year's difference in age between children who are in the same school year , but either born just before and after September 1.

The team analyzed anonymized data from GP surgeries and hospitals, focusing on 96,698 children born between 2002 and 2010 in either July, August, September or October. Half were boys and half girls, with a representative mix of ethnicities.

The researchers found that by age 15, around 1.6% of the children were diagnosed with ADHD and about 1.25% were also prescribed drugs for ADHD.

The researchers then compared ADHD diagnoses and prescriptions between the early starters born in July and August and the late starters born in the following months.

They found that by age 15, around 1.5% of early starters were receiving prescriptions for ADHD, compared to just 1% of late starters. This equates to an increase of 50% in ADHD prescriptions for early compared to late starters.

Even after controlling for differences in characteristics between children within the two groups, the researchers still found a large percentage increase in ADHD prescriptions for children born in July and August. This equates to a 40% greater likelihood of an ADHD prescription for early, compared to late, starters.

Similarly, they found that by age 15, children are 40% more likely to be diagnosed with ADHD if born in July and August. These gaps in ADHD rates are even larger for young children.

This finding alone didn't surprise the researchers, according to Professor Cheti Nicoletti from the University of York: "We've seen this disparity in previous research in other countries, so we expected to see something similar here," she said. "What we really need to understand is what causes such a disparity."

The study highlights that the disparity in ADHD prescriptions between children born in July–August and in September–October is mainly explained by a peer-comparison bias caused by differences in relative age among classmates.

The study also finds that the gap in ADHD prescriptions, observed from age 9 onward, is mainly driven by drug prescriptions initiated in the first years of primary school and by the fact that children tend to continue ADHD pharmacological treatment for several years after its initiation.

Indeed, the authors found that among children who initiated prescriptions between ages 5 and 8, 86.16% are still prescribed drugs for ADHD at age 9; 83.98% at 10; 81.29% at 11; 82.75% at 12; 74.63% at 13; 70.21% at 14; 64.20% at 15.

Co-author Dr. Catia Nicodemo from the University of Oxford said, "The good news is that from age nine onward, there is no difference in the initiation of ADHD prescriptions between children born in July–August and in September–October, which means that the peer-comparison bias disappears with age."

"The bad news is that potential biases in pharmacological treatments initiated in the first years of primary school persist at a later age."

Co-author Dr. Joaquim Vidiella-Martin from the University of Oxford said, "We can't definitively identify whether there is an over-diagnosis of children born in July–August or an under-diagnosis of children born in September–October or just more marginal diagnoses for July–August born, but we can say that a gap in pharmacological treatment between between children born in July–August and in September–October suggests an inefficient and unfair use of medical resources."

Drawing on their findings, the researchers then provide some suggestions on how to reduce the gap in prescriptions . They say that delaying school for children born over the summer months would not work as a blanket policy, as it could mean ADHD is even more likely to be overlooked in some already under-diagnosed groups of children.

Instead, they offer two other recommendations for parents, teachers and policymakers.

The first is to make parents and teachers more aware of ADHD symptoms and improve diagnosis, particularly between the ages of 5 and 8, when the discrepancy between groups is the greatest.

The second is that when four-year-olds first begin full-time school, there are at least two start dates across the year, so children can be grouped with others they are closest to in age with a maximum of six months difference between them.

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Recent advances in understanding of attention deficit hyperactivity disorder (ADHD): how genetics are shaping our conceptualization of this disorder

Tetyana zayats.

1 Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA

2 Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA

Benjamin M Neale

Version changes, revised. amendments from version 1.

It was brought to our attention that an erroneous examples of FDA-approved ADHD drugs were made in the article. This new version corrects that oversight.

Editorial Note on the Review Process

F1000 Faculty Reviews are commissioned from members of the prestigious F1000 Faculty and are edited as a service to readers. In order to make these reviews as comprehensive and accessible as possible, the referees provide input before publication and only the final, revised version is published. The referees who approved the final version are listed with their names and affiliations but without their reports on earlier versions (any comments will already have been addressed in the published version).

Attention deficit hyperactivity disorder (ADHD) is a clinically defined disorder, and inattention and hyperactivity/impulsivity are its main symptom domains. The presentation, lifelong continuation and treatment response of ADHD symptoms, however, is highly heterogeneous. To better define, diagnose, treat and prevent ADHD, it is essential that we understand the biological processes underlying all of these elements. In this review, given the high heritability of ADHD, we discuss how and why genetics can foster such progress. We examine what genetics have taught us so far with regard to ADHD definition, classification, clinical presentation, diagnosis and treatment. Finally, we offer a prospect of what genetic studies on ADHD may bring in the future.

Introduction

Attention deficit hyperactivity disorder (ADHD) is a clinically defined disorder, and inattention and hyperactivity/impulsivity are its main symptom domains 1 . The presentation, life-long continuation and treatment response of ADHD symptoms, however, is highly heterogeneous, underscored by the wide array of psychiatric and somatic comorbidities.

To better define, diagnose, treat and prevent ADHD, it is essential that we understand the biological processes underlying all of these elements. As family and twin studies revealed that genetics contribute to the etiology of ADHD (heritability estimates range from 60 to 90% 1 , 2 ), the conceptualization of this disorder moved away from being a consequence of early brain damage to being a multifactorial phenotype, with both genetics and environment affecting its development, trajectory and outcome. Here, we discuss why and how the recent genetic findings on ADHD may shape our understanding of its definition, diagnosis, treatment and prevention.

Why study genetics in attention deficit hyperactivity disorder?

The view of ADHD as a multifactorial disorder with a genetic component comes from the clinical complexity observed in ADHD’s symptomatology. ADHD runs in families and co-occurs in identical twins at a much higher rate than in fraternal twins 3 , 4 . This familial aggregation suggests that genetics can serve as a tool to identify the main biological drivers behind ADHD development as well as its lifetime trajectory. Furthermore, genetics can be used to probe the genetic overlap between ADHD and various psychiatric and somatic disorders and traits. These kinds of analyses can aid the definition and classification of this disorder and lead to a better understanding of its comorbidity. Evaluation of the degree of genetic susceptibility to ADHD phenotypes can help the establishment of genetic counselling today and, in the future, lead to improved evaluation of prognosis and provision of effective treatment options that act at the etiological level of ADHD. This notion was recently affirmed by a genome-wide association (GWA) study that revealed the first genome-wide significant loci associated with ADHD 5 , offering possibilities to further our understanding of this disorder. Perhaps the most important one is that ADHD appears to be a disorder of central nervous system–specific regulatory elements.

What have we learned from genetics so far?

Definition and classification.

Traditionally, ADHD has been classified as an externalizing behavioral disorder. However, as genetic epidemiological studies have shown high familial overlap between ADHD and autism spectrum disorder (ASD) and between ADHD and intellectual disability (ID), the classification shifted toward neurodevelopmental disorders 2 . This notion has recently been further affirmed by observations of ADHD displaying genetic correlation and overlap with ASD at the levels of both common and rare genetic variation 6 , 7 . In addition, common genetic factors have been shown to contribute to the overall correlation between ADHD and ID (except for profound ID) 8 . Another observation in favor of ADHD being a neurodevelopmental disorder is the higher prevalence of ADHD among boys compared to girls 9 . Nonetheless, ADHD also shows genetic overlap with behavioral problems 5 , 10 , 11 , and recent genetic study notes that common genetic variation may not explain the sex differences in its diagnosis 12 , suggesting that the clear-cut classification of ADHD is still an open question.

Also, traditionally, ADHD has been defined as a unitary disorder with a number of subtypes (that is, inattentive, hyperactive and combined subtypes). One way to evaluate such a definition is to explore the notion that ADHD cases may be defined as extremes of the distribution of ADHD symptoms (both inattention and hyperactivity/impulsivity) 2 , 5 , 11 , much in the way that hypertension is defined to be the extreme end of blood pressure distribution in a population. To define ADHD in that fashion, we must consider whether ADHD symptoms (that is, inattention and hyperactivity/impulsivity) display consistent co-occurrence with sufficient degree of intensity and duration to form a biologically and clinically meaningful entity of ADHD. The early (and under-powered) GWA studies of these traits revealed both unique and shared genetic influences on these dimensions of ADHD 13 , 14 . A more recent GWA study of these traits, in more than 37,500 children, showed high genetic correlation between continuous measures of inattention and hyperactivity in children (rg = 73%) and between those two traits and ADHD diagnosis in both children and adults (rg inattention+ADHD = 93%, rg hyperactivity/impulsivity+ADHD = 91%). The exploration of genetic correlations of these dimensions with common psychiatric disorders and traits revealed two distinct patterns of correlations—inattention correlated more with neurodevelopmental phenotypes and hyperactivity/impulsivity correlated more with behavioral problems 15 —highlighting the dual nature of ADHD as it is defined today. Thus, on the basis of the recent genetic studies, ADHD may be defined not as a unitary disorder with several subtypes but rather as a spectrum disorder whose core symptoms (inattention or hyperactivity/impulsivity or both) interfere with an individual’s functioning in important life aspects. In fact, such change in conceptualization of ADHD may already be seen in the latest version of the Diagnostic and Statistical Manual of Mental Disorders (DSM), where the three ADHD “subtypes” have been substituted by three ADHD “representations” (potentially also reflecting the fluidity of the ADHD symptomatology over a life span) 16 .

Diagnosis and clinical representation

The diagnosis of ADHD relies heavily on how we define it. The two diagnostic systems of contemporary psychiatry—the International Statistical Classification of Diseases and Related Health Problems (currently, ICD-10 17 ) and the DSM (currently, DSM-5 16 )—base a clinical diagnosis of ADHD (or hyperkinetic disorder (HKD) in ICD-10) on the two sets of symptom domains: inattention and hyperactivity/impulsivity. Although ICD-10 and DSM-5 operate with the same two symptom domains to define ADHD/HKD, the diagnosis of ASD or bipolar disorder precludes the diagnosis of HKD in ICD-10, whereas DSM-5 does allow the presence of diagnoses of both ADHD and ASD. The diagnostic criterion of ICD-10 is in direct conflict with recent findings that ADHD and ASD do have a common genetic (and possibly etiological) component 6 , 7 . This highlights the recent perception that the current diagnostic scheme for ADHD (and many other major psychiatric disorders) is not reflective of its underlying biological foundation and that the eventual goal is to move away from clinically defined diagnoses to molecularly defined ones 18 , 19 .

Reflecting the view of ADHD as an extreme on the continuum of its two main domains (inattention and hyperactivity/impulsivity), the diagnosis of ADHD faces the questions of which symptoms to consider and to what extent. In ICD-10, for example, the HKD is a unity of symptoms (all three sets of symptoms must be present to diagnose ADHD), all symptoms must be exhibited in more than one setting (for example, home and school) and the presence of comorbidities is practically not allowed. In contrast, the DSM-5 distinguishes three different diagnostic ADHD presentations (not all three sets of symptoms must be present in order to diagnose ADHD), the symptoms need to be present in only some settings and the presence of comorbidities is freely allowed (as exemplified by ASD above). Given this discordant view of ADHD diagnosis between the two major diagnostic systems and given that recent genetic studies on ADHD revealed that it exhibits an extensive genetic overlap with a wide range of psychiatric disorders 5 , 11 , the two main symptom domains of ADHD may be a non-specific component in a variety of conditions and the diagnosis of ADHD may be a quantitative rather than a qualitative entity.

It has been reported that the current pharmacological ADHD treatment is effective in about 70% of cases 20 . The major obstacle to developing a more effective treatment for ADHD is our limited understanding of what causes the disorder and the mechanism (or mechanisms) through which the current pharmaceuticals are acting on ADHD. The barriers to progress are many and varied, but the inaccessibility of live human brain tissues makes progress in the neurobiological basis of ADHD particularly challenging. One option to circumvent this challenge is to use induced pluripotent stem cells that could provide a promising avenue for downstream molecular interrogation of genome-wide significant loci 21 . Although arguably a clinician could treat a disorder without understanding it, we must make a distinction between symptom alleviation and a cure. Currently, all of the existing treatment options for ADHD (both pharmacological and behavioral) offer symptomatic relief only 22 .

With the recent technological advances and large collaborative efforts, more and more large-scale GWA studies are becoming available on a variety of somatic and psychiatric phenotypes, including ADHD. These studies are an important source of information for the rapidly evolving field of ADHD pharmacogenetics 23 , 24 that may help to circumvent the current limitations of drug development and re-purposing. Using data from the first well-powered GWA study on ADHD 5 , the examination of the association between ADHD and the genes encoding the targets of the first-line US Food and Drug Administration (FDA)-approved pharmacological agents for ADHD treatment revealed no significant findings 22 , suggesting that those pharmaceuticals may act through mechanisms other than the ones underlying ADHD (although currently the largest ADHD GWA study still does not capture the biology of ADHD in its entirety).

The current FDA-approved treatments for ADHD are primarily thought to enhance catecholamine signaling. However, such a narrow pharmacological target stands in contrast to the complexity of emerging genetic findings, which suggest that other avenues of therapeutic intervention may be possible. As we learn more about the biological basis of ADHD, these findings could enable the development of new drugs through different mechanisms of actions. Furthermore, drug re-purposing of already-approved compounds and treatments may be a faster path to improving the quality of care for patients. One way to nominate such potential treatments might be to evaluate treatment options for traits with high genetic correlation to ADHD, motivating the systematic evaluation of genetic overlap between ADHD and other phenotypes 25 .

A potentially successful example of drug re-purposing guided by genetic studies of ADHD is the trial use of fasoracetam as a treatment for this disorder. Originally developed as pharmacotherapy for vascular dementia, fasoracetam has been successfully used in a clinical trial to treat ADHD in adolescents with disrupted glutamatergic signaling that has been shown to be associated with ADHD 26 .

Although the re-purposing and development of new pharmacotherapeutics for ADHD takes time, it is important to note that the mere shift in understanding of ADHD as a multifactorial disorder with a genetic component may help patients in their management of the disorder 27 .

Diagnostic screening and prevention

To reliably screen individuals for ADHD on the basis of common genetic variants, we first need to establish the true effect sizes of the variants associated with the disorder. So far, only one relatively well-powered GWA study on ADHD has provided estimates of these effects 5 , but those estimates are not accurate enough for diagnostic purposes in clinical settings. As the power of genetic studies improves, the assessment of the number and the effect sizes of genetic variants robustly associated with ADHD will also improve, increasing the potential of common variants to become a helpful tool in a clinical setting, much in the way that polygenic risk score (PRS) is used in coronary heart disease 28 – 30 . In the meantime, although the diagnostic usefulness of common genetic variants is still far from reality for ADHD, the genetic profile of a cumulative number of ADHD risk alleles (PRS) can be of benefit for patients whose ADHD has already been diagnosed as, in the near future, PRS is more likely to aid the prognosis of ADHD, especially in combination with additional non-genetic information (for example, family history).

The clinical utility of rare genetic variants, in contrast to that of common ones, tends to be stronger as their penetrance (that is, the chance of developing the disorder) tends to be much higher. However, despite recent studies showing genetic overlap between ADHD and neurodevelopmental disorders 7 , 8 , 31 , there is little evidence to support the need for genetic testing based on rare variants, especially as none of those variants is ADHD-specific.

What can genetics of attention deficit hyperactivity disorder tell us in the future?

Following in footsteps of the first genome-wide significant ADHD loci discovery, we must next replicate and understand these findings. GWA studies in independent large(r) samples are expected to shed light on the validity of these loci and examination of their functionality will aid our understanding of biological processes underlying ADHD. Thus, further work at the molecular level of neural cells, systems and circuits can be anticipated from both bioinformatics and experimental systems biology.

There is a growing interest in investigation of ADHD across the life span as it has been noted that persistence of ADHD symptoms is associated with a high number of genetic ADHD risk variants that an individual may possess 32 . As large phenotypically informative and genotyped cohorts become more available, it will be possible to address questions of biological background of ADHD continuation throughout life (for example, longitudinal studies) and determine periods critical for the development, lifelong trajectory and treatment of this disorder.

In addition, such cohorts will allow the examination of the causal impact of loci associated with ADHD that may help elucidate the reasons behind high correlations between ADHD and a wide range of psychiatric and somatic disorders and traits.

One branch of genetics that has received little attention in ADHD so far is the examination of direct and indirect (environmental) genetic effects influencing ADHD. To date, all genome-wide genetic studies on ADHD, except for one carried out by Wang and colleagues 33 , assumed that this disorder can be influenced only by the genetics of an individual with ADHD (direct genetic effects). However, the expression of a phenotype in an individual is influenced not only by their own genotype (direct genetic effect) but also by the genotype of people in their environment, such as their mother, father, or siblings (indirect genetic effects) 34 . The evaluation of environment’s role in the development of ADHD could also benefit from gene–environment interaction studies. However, probing the environmental effects in ADHD is often limited by gene–environment correlation where the association between ADHD and an environmental factor can be the result of inherited confounds 35 . The disentangling of these direct and indirect (environmental) effects has the potential to advance our understanding of such long-standing observations as missing heritability (the difference in heritability estimates between genetic and epidemiological studies), sex differences in ADHD prevalence, variability in persistence of ADHD symptoms across a life span and non-Mendelian forms of ADHD inheritance and aid in ADHD prevention and treatment.

Finally, the recently evolving branches of genetics can also elucidate the pharmacology of ADHD (pharmacogenetics) and environmental effects critical for clinical aspects of ADHD (geno-economics, geno-epidemiology, epigenetics, and parent-of-origin effects).

[version 2; peer review: 3 approved]

Funding Statement

The authors are supported by the Gerstner Family Foundation (NIMH 1R01MH094469- Quantifying the impact of rare mutations on attention deficit hyperactivity disorder [ADHD]) and by the Psychiatric Genomics Consortium: Finding Actionable Variation (NIMH 5U01MH109539-03-2/7).

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.