Attention-deficit hyperactivity disorder (ADHD) is a diverse condition characterised by symptoms of inattention, hyperactivity and impulsivity; and can have a significant impact on patients’ lives.This website provides educational resources intended for healthcare professionals outside the US with an interest in ADHD.
Over the past 20 years, there has been a significant increase in the body of research on ADHD. This may be due to a number of factors, including increased awareness of the impact of ADHD, technological and methodological advances, as well as increased pharmaceutical company interest. In this selective review,* the authors examined what they considered to be the most important advances in ADHD research during this period.
Changes to diagnostic criteria
The publication of the Diagnostic and Statistical Manual of Mental Disorders – 5th Edition (DSM-5™) in 2013 introduced significant changes to the diagnostic criteria for ADHD:
Changes in the threshold for ADHD symptoms and age of onset: in older adolescents and adults, the number of symptoms necessary for an ADHD diagnosis was reduced from 6 to 5. Additionally, the required age of onset was changed from ‘prior to 7’ to ‘prior to 12’. The authors emphasised that although the purpose of these changes was well intended, they are limited by a lack of empirical evidence. Furthermore, more focus should be placed on precisely defining functional impairment rather than the number of symptoms.
Dual diagnosis of ADHD and autism spectrum disorders (ASD): until the publication of the DSM-5™, the diagnosis of ADHD was excluded in the presence of ASD; this change in guidelines was supported by a significant body of empirical evidence.
‘Subtypes’ of ADHD replaced by ‘presentations’: this change in diagnostic criteria acknowledged the instability in the phenotypic manifestation of inattention or hyperactive/impulsive symptoms, in contrast to the more ‘static’ notion of a subtype.
Differences in the prevalence of ADHD have been reported between countries (Faraone et al. 2003), with differential rates of diagnosis in North America and Europe (Taylor et al. 1984). These findings suggest that ADHD may be more a social construct than a ‘real’ disorder, which has attracted considerable controversy and further investigation over the past two decades. A meta-analysis published in 2007 found that a number of diagnostic variables, including diagnostic criteria, source of information, requirement of impairment for diagnosis, and geographical region, had a significant impact on the estimated pooled rate of ADHD (5.29%). In fact, a significant difference in prevalence only emerged between North America and both Africa and the Middle East, with no difference reported between North America and Europe (Polanczyk et al. 2007). Another recent meta-analysis found no evidence to support an increase in the epidemiological prevalence of ADHD over the past 30 years when standardised diagnostic procedures were followed (Polanczyk et al. 2014). The authors stated that these results suggest the trend for increased rates of ADHD diagnosis may be explained by cultural and social factors, rather than actual increases in prevalence of the disorder.
The majority of the epidemiological studies performed to date focus on school-aged children from North America and Europe; therefore, the authors emphasised the need for further population-based studies from other continents and different age groups. In the authors’ opinion, longitudinal studies aimed at better understanding predictors of remission and persistence of ADHD in adulthood, as well as development of standardised definitions of remission and persistence, are needed to derive conclusive findings from the current body of evidence.
Genetic and environmental causes of ADHD
Significant advances in technology have led to the emergence of novel approaches to identify the genes underpinning the high heritability of ADHD. However, these efforts have perhaps been more challenging than originally anticipated, largely due to the complex genetic and environmental aetiology of ADHD:
Candidate gene approach: aims to identify variant genes involved in the pathophysiology of ADHD; however, to date, the approach has only identified 10 genes as having a significant role.
Genome-wide association studies: allow the analysis of a large number of common single-nucleotide polymorphisms across the entire genome. Initial efforts were unsuccessful, but a recent breakthrough led to the identification of 12 independent loci.
Copy number variants (CNVs): defined as replications or deletions of DNA with a length of at least 1kb. Although CNVs over-represented in ADHD have been identified, studies suggest that their contribution can only explain 0.2% of ADHD heritability.
Environmental factors: considerable data suggest that prenatal and postnatal factors, including maternal smoking and alcohol use, low birth weight, premature birth and exposure to environmental toxins, are associated with increased risk of ADHD. However, apart from preterm birth, genetic studies have implicated a number of confounding familial factors, which do not support a causal role of environmental factors.
The authors expressed the opinion that more research is needed to better understand the interplay between environmental factors and genes. Despite this, genetic research thus far has the potential to pave the way for promising areas of research, including the use of pluripotent stem cells to model brain circuits and the use of zebrafish and fruit fly models to replace currently available animal models of ADHD.
Pathophysiological models of ADHD have changed considerably over the past two decades, with a major paradigm shift from alterations in a limited number of individual brain regions to dysfunction in larger brain networks:
Structural magnetic resonance imaging (MRI) studies: meta-analyses and mega-analyses have consistently reported alterations in the basal ganglia, as well as a number of other subcortical areas.
Functional MRI studies: a comprehensive meta-analysis demonstrated that the majority of ADHD-related hypoactivated areas fell within the ventral attention and frontoparietal networks. Conversely, hyperactivated areas were related to the default mode network or visual network. These findings are in line with the default mode network hypothesis of ADHD, which the authors described as one of the most inspiring proposals in the neuroscience of ADHD over the past two decades.
Although studies have gained further insight into the brain networks that are dysfunctional in ADHD, the authors stated that they look forward to the next generation of neuroimaging studies, which bring promise of translating these findings into clinical practice.
Over the past two decades, there has been a marked increase in the number of randomised controlled trials (RCTs) aimed at testing the short-term efficacy and tolerability of pharmacological treatments for ADHD. Additionally, several lines of research into non-pharmacological interventions have also been developed:
Pharmacological interventions: a comprehensive network meta-analysis of 133 RCTs was conducted to investigate the efficacy and safety of different medications compared with placebo. Evidence from this meta-analysis supported methylphenidate as the preferred first-choice medication for the short-term treatment of ADHD in children/adolescents, and amfetamines for adults (Cortese et al. 2018).
Non-pharmacological interventions: the European ADHD Guidelines Group has conducted a series of meta-analyses to investigate the role of non-pharmacological interventions in ADHD treatment. Overall, results from these meta-analyses suggest that some interventions, including behavioural intervention or cognitive training, may be effective to reduce associated ADHD impairments. Additionally, some dietary interventions, including fatty acid supplementation and exclusion of artificial food colours, are only associated with a small effect size (Sonuga-Barke et al. 2013). Considering the current body of research, the authors suggest that further evidence is needed to recommend the routine use of non-pharmacological interventions as highly effective treatment for ADHD core symptoms. Despite this, behavioural interventions and cognitive training may be effective for important ADHD-associated impairments.
In the future, the authors noted that it will be important to further evaluate the long-term efficacy and safety of treatments using RCTs with withdrawn designs, as well as additional population-based studies with self-controlled methodologies and longitudinal follow-up studies.
The authors concluded that the multiple scientific advances over the past 20 years have successfully answered many questions in the ADHD field. Despite this, many questions remain unanswered. Strengthening multidisciplinary collaborations, utilising large data sets in the spirit of Open Science and the support of research activities in less-advantaged countries will be key in facing these challenges.
*This selective review relied mostly on meta-analyses, retrieved with a search in PubMed using the following syntax/terms (update: 8 August 2018): (ADHD OR Attention Deficit OR Hyperkinetic Disorder) AND (meta-analy* or metaanaly)
Research has shown that individuals with ADHD demonstrate an increased risk for developing addiction, including alcohol, nicotine and gaming dependence (Fuemmeler et al. 2007; Kessler et al. 2006; Kuss et al. 2012). The mechanism underlying the comorbidity of ADHD with addiction is not clear. One hypothesis suggests that the increased risk could be explained by ADHD and addiction sharing another comorbidity, such as conduct disorder (Biederman et al. 1997). Despite this, studies performed to date do not provide sufficient evidence to support the role of conduct disorder in the relationship between ADHD and addiction. Using a causal discovery algorithm, this exploratory analysis aimed to build a causal model of the relationships between ADHD, comorbid conduct problems, substance use and gaming habits.
This study included 362 participants (81% male; aged 16±2.4 years) with ADHD, who had been recruited by the Belgian, Dutch and German sites of the 2003–2006 International Multicentre ADHD Genetics (IM-AGE) study. ADHD symptoms and conduct problems were rated at baseline using the Parental Account of Childhood Symptoms (PACS), the Strengths and Difficulties Questionnaire (SDQ), and the Long Versions of the Conners’ Parent (CPRS-R:L) and Teacher Rating Scale Revised (CTRS-R:L). The severity of alcohol, nicotine and other drug habits was assessed by patient questionnaires and a number of rating tools.* The exploratory analysis was performed using the Bayesian Constraint-based Causal Discovery (BCCD) algorithm.†
Results demonstrated that the mean symptom count for ADHD-hyperactive/impulsive subtype (ADHD-HI) and ADHD-inattentive subtype (ADHD-In) was 7.8±1.6 and 8.0±1.1, respectively, and the mean conduct problem score was 83±36. ADHD-HI and ADHD-In symptom counts showed a causal dependence with a joint reliability estimate of 52%. Both ADHD-HI and ADHD-In symptom counts were independently linked to conduct problems (joint reliability estimate: ADHD-HI and conduct problems, >99%; ADHD-In and conduct problems, 62%). Importantly, ADHD-HI and ADHD-In were not directly connected to the substance-abuse variables; instead, conduct problems mediated the connection between both ADHD-HI and ADHD-In and nicotine use (joint reliability estimate, 85%), but not alcohol or drug use. Furthermore, ADHD-In demonstrated a directional link to gaming habit (joint reliability estimate, 86%), suggesting that more severe ADHD-In symptoms lead to more severe gaming habits.
Findings from this study should be interpreted in the context of some limitations. Despite the fact that the design of the study tried to account for the effects of stimulant treatment, it remained difficult to examine its effects in the causal model. Furthermore, the ADHD ratings employed in this study could be based on previous medication-free periods; in these instances, ratings relied on parental reporting of symptoms, which could have resulted in a source of bias. Flooring effects due to the low variance in substance abuse may have also biased this analysis. Furthermore, the BCCD does not provide estimates of effect size of the causal influence and, therefore, only reliability estimates are provided in the model. Finally, as the study aimed to identify pathway components that may benefit from further investigation, no conclusions can be made about any underlying biological mechanisms.
The authors concluded that conduct problem severity may mediate the connection between ADHD severity and nicotine use, but not severe alcohol or substance use. Furthermore, ADHD-In severity was a risk factor for gaming, suggesting that this variable has a different causal pathway to substance dependence and should be treated differently. The authors suggested that this work could facilitate further research into the overlap between ADHD and addiction, and help researchers and clinicians to develop more effective treatments.
*Participants >12 years old completed questionnaires to assess the severity of alcohol, nicotine and other drug habits, as well as the severity of gaming habit; continuous scores were used for all measures to increase discriminatory power. Alcohol dependence was assessed using the Alcohol Use Disorders Identification test (scores ranging from 0–40). Nicotine dependence was assessed using the Fagerström Test for Nicotine Dependence (scores ranging from 0–10). Other drug dependence was assessed using the Drug Abuse Screening Test-20 (scores ranging from 0–20). There was no universally accepted standard to assess pathological gaming; therefore, a 24-item gaming questionnaire was constructed from an existing questionnaire and supplemented with additional questions (scores ranging from 0–92)
†The analysis steps of the BCCD were as follows:
1. Data: accepted both discrete and continuous data
2. Preprocessing: input was mapped through a Gaussian transform into a correlation matrix
3. Search: an efficient search was performed to obtain Bayesian reliability scores based on the BGe metric, resulting in a list of weighted independence constraints
4. Logical causal inference engine: local independence constraints were used together with background knowledge to create model
5. Model: coherent output causal model was generated
Individuals with ADHD are at increased risk of developing a number of comorbid psychiatric disorders, including borderline personality disorder (BPD) (Bernardi et al. 2012). Emotional dysregulation has been shown to play a role in the development of BPD and, more recently, ADHD. Despite this, large-scale family studies on the co-occurrence of ADHD and BPD are lacking. This population-based study aimed to estimate the co-occurrence and familial co-aggregation of clinically diagnosed ADHD and BPD in a Swedish population.
This register-based cohort study included 2,113,902 individuals born in Sweden during 1979–2001,* with individuals linked with their relatives using the Multi-Generation Register and Twin Register. Individuals with ADHD were identified using the Swedish National Patient Register (NPR) and Prescribed Drug Register, while individuals with BPD were identified from the NPR only.† Associations were estimated using logistic regression. Co-occurrence within individuals was assessed by analysing the within-individual associations between ADHD and BPD to obtain crude and covariate-adjusted odds ratiosǂ (ORs and aORs, respectively). Co-aggregation within relatives was assessed by estimating the risk of BPD in individuals according to their relative’s ADHD and again obtaining ORs and aORs. ORs were also calculated in the full sibling subsample stratified by sex combinations.
Results from the study demonstrated that:
During follow-up, 82,593 (3.9%) and 9,544 (0.5%) individuals were diagnosed with ADHD and BPD, respectively. Males were more commonly diagnosed with ADHD, while females were more likely to be diagnosed with BPD.
Individuals with an ADHD diagnosis were at an increased risk of BPD, with an aOR of 19.4 (95% confidence interval [CI] 18.6–20.4).
Individuals who had a relative with an ADHD diagnosis were also at increased risk of a BPD diagnosis. Monozygotic twins with ADHD had a lower risk of BPD (aOR 11.2, 95% CI 3.0–42.2) than within individuals, suggesting that factors not shared by family members were likely to influence co-occurrence.
At least part of the association between ADHD and BPD was due to genetic factors: full siblings had a significantly lower aOR of 2.8 (95% CI 2.6–3.1) compared with monozygotic twins (p=0.041), whereas half-siblings had a significantly lower aOR compared with full siblings (maternal: aOR 1.4, 95% CI 1.2–1.7; paternal: aOR 1.5, 95% CI 1.3–1.7; p<0.001 for both).
In full siblings, females with a sister diagnosed with ADHD were at increased risk of having a BPD diagnosis compared with females who had a brother diagnosed with ADHD (aOR 2.9 [95% CI 2.6–3.4] vs 2.5 [95% CI 2.3–2.8]). Males with a sister diagnosed with ADHD also exhibited increased risk compared with males having a brother with ADHD (aOR 3.9 [95% CI 2.9–5.4] vs 3.6 [95% CI 2.7–4.8]). However, neither of these differences were statistically significant (females, p=0.087; males, p=0.682). These findings do not support the presence of aetiological sex differences.
This is the largest study of ADHD and BPD co-occurrence and, to the authors’ knowledge, the only study to date that has evaluated the familial co-aggregation of clinically diagnosed ADHD and BPD. Despite this, the study was limited by a number of factors that could have led to potential sources of bias. First, the diagnoses observed in the study are likely under-reported, which could have biased results towards the null. Second, correlated detection bias may have been present in individuals with one diagnosis, which could have biased estimates upwards. Additionally, misdiagnosis may have occurred due to an overlap in symptoms between ADHD and BPD, leading to a spurious association between the two disorders.
The authors concluded by stating that ADHD and BPD co-occur in individuals, and also co-aggregate in relatives; this pattern reflects both shared genetic risk factors and individually unique risk factors. Furthermore, the strength of individual and familial associations between ADHD and BPD was similar across sexes, suggesting that the presence of aetiological sex differences was not robustly supported. The authors stated that these findings are important to promote awareness of the increased risk of BPD in individuals with ADHD, as well as their relatives, and vice versa.
*Exclusion criteria included stillbirths, congenital malformations, and deaths during infancy (total of 108,079). Individuals who died (6283) or emigrated (72,337) before their 12th birthday were excluded using the Cause of Death Register and the Total Population Register, respectively. Individuals who did not have both parents known (19,093) were also excluded using the Multi-Generation Register
†The NPR comprises diagnoses from inpatient healthcare, and from outpatient visits to specialist care from 2001 and onwards; the authors used International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) diagnoses from 1 January 1997 (when the ICD-10 was introduced in Sweden) to 31 December 2013. The authors used data from PDR on all dispensed medications from 1 June 2005 to 31 December 2014
ǂCovariates included sex, birth year and birth order, as they are potential confounders associated with both ADHD and BPD. Adjusted ORs were adjusted for sex, sex of relative, birth year, birth year of relative and birth order, wherever applicable
Reports suggest there has been a significant increase in the incidence of ADHD among children and adolescents over the past 40 years (Akinbami et al. 2011; Visser et al. 2014; Nigg 2006). It has been suggested that this increase could be linked to the violent and fast-paced nature of screen media entertainment. Despite this, a comprehensive view of the literature is limited, as much of it is dispersed across different fields of research. In an effort to consolidate the evidence base, the authors performed a review to investigate the relationship between children and adolescents’ screen media use and ADHD-related behaviours.
In this review, the authors first compared the results of two meta-analyses, performed by Nikkelen et al. and Ferguson, on media use and ADHD-related behaviours (Nikkelen et al. 2014; Ferguson 2015). The authors reported small but statistically significant pooled zero-order correlations between screen media use and ADHD-related behaviours, with effect sizes of r+ = 0.12 and r+ = 0.10 yielded by Nikkelen et al. and Ferguson, respectively. The authors stated that these findings were consistent with other meta-analyses assessing media effects, which typically reported effect sizes ranging from r+ = 0.10 to r+ = 0.20. The authors noted that there were clear differences between the two meta-analyses. First, the meta-analysis by Nikkelen et al. was based on studies assessing the effects of television (38 studies) and video games (17 studies), whereas that by Ferguson was based on video games only (9 studies). Second, there was a difference in the conceptual approach between the two studies; Ferguson incorporated background variables (such as sex and age) as controls, whereas Nikkelen et al. treated the same background variables as moderators. The authors stated that there has been some concern that the approach employed by Nikkelen et al. could mask the true media effects for some subgroups of children. On the other hand, the authors postulated that the conceptualisation of background variables as moderators, rather than controlling for them, may promote better understanding as to which children are susceptible to media effects as a cause of ADHD-like behaviour, and, equally important, which children are not.
Next, three propositions provided by the Differential Susceptibility to Media effects Model (DSMM)* were used to examine the limitations associated with the current literature base, and to provide potential directions of future research.
Indirect media effects: mechanisms underpinning the screen media–ADHD relationship
The first proposition of the DSMM postulates that media effects can be explained by a combination of three types of response states:
Cognitive – the attention to and processing of certain media content
Emotional – affective reactions such as fear and joy while watching and playing
Excitative – physiological arousal while or after watching or playing.
In line with the DSMM, most explanatory hypotheses in the current literature conceptualise cognitive, emotional and excitative response states as the underlying mechanisms in the screen media–ADHD relationship. Research has also been conducted to determine whether the fast pace and violent nature of screen media may play a role in children’s media-induced response rates, which could increase the likelihood of ADHD-related behaviours:
Effects of programme pacing: the authors’ review of the literature showed that studies on the effects of pacing on ADHD-related behaviours have yielded inconsistent results. The authors suggested that this could be due to multiple factors. First, fast pace is often linked to action and/or violence in popular children’s entertainment. Although researchers may remove this element from fast-paced stimuli to ensure the ecological validity of their experiments, this may render the materials too dull to evoke a true response. Second, ethical constraints mean that it is impossible to expose children to age-inappropriate content; therefore, the stimuli used in experiments may differ substantially from the favourite programmes typically watched by a particular age group, which could reduce the ecological validity of an experiment. Finally, programme pacing was conducted using a number of different approaches across studies (e.g. changes in camera angle, scene or voice), which could complicate valid comparisons between studies.
Effects of violent media content: the authors’ review of the literature demonstrated that several studies indicated a positive correlation between exposure to violent television and gaming and ADHD-related behaviours. However, the majority of studies were correlation surveys, which meant that a conclusion could not be made regarding the direction of the relationship between media use and ADHD-related behaviours.
Conditional media effects: susceptible individuals in the screen media–ADHD relationship
The second proposition of the DSMM is that any media effect can be modulated by specific person-based or environmental factors. In line with this, several media-effects theories propose that some individuals are more susceptible to the effects of screen media than others. Studies have been performed to determine if the use of screen media on ADHD-related behaviours may be linked with developmental, dispositional and social factors:
Developmental susceptibility: a review of the literature found that although a number of theories suggest age differences in the relationship between screen media and ADHD-related behaviours, research to date has not provided consistent evidence for such differences. Some studies suggest that compared with older children and adolescents, younger children may be more susceptible to media-induced arousal and subsequent ADHD-related behaviours; however, more research is needed before these findings are considered conclusive.
Dispositional susceptibility: a number of person-based characteristics have been investigated for their role in susceptibility to media effects, including gender, level of aggression and genetic disposition. The authors’ review of the literature suggested that boys may be more susceptible to the effects of media on ADHD-related behaviours than girls, which may also apply for aggressive adolescents. More research is required to establish the role of gender as a potential moderator, as well as the effect of other dispositional variables.
Social susceptibility: the authors noted that only a handful of studies have investigated the role of social susceptibility in the relationship between screen media and ADHD-related behaviours. Results from these studies have suggested that parenting style, demographic factors and parental well-being may enhance the effects of children’s media use on ADHD-related behaviours. However, further studies are needed to develop a more robust evidence base.
Transactional media effects: the directional nature of the screen media–ADHD relationship
The third proposition of the DSMM is that many media effects are transactional or reciprocal. Despite the fact that transactional effects are likely for outcome variables such as ADHD-related behaviours, the authors’ review of the literature found that only a small number of studies have actually considered transactional effects and, furthermore, these studies reported inconsistent results.
The authors concluded that there is a statistically small relationship between screen media use and ADHD-related behaviours among children and adolescents. However, review of the literature base demonstrates that although there are many media-effects hypotheses to explain how and why media use and ADHD-related behaviours may be linked, empirical research to support these arguments is somewhat lacking. The authors, therefore, stated that there is a clear need for further research to establish the causality, underlying mechanisms and differential susceptibility to the effects of screen media use and ADHD-related behaviours, as well as the direction of the relationship.
*The DSMM is an integrative model that aims to improve understanding of media effects, distinguishing three types of susceptibility to media effects: dispositional, developmental and social susceptibility (Valkenburg and Peter 2013)
Following systematic literature reviews and expert opinion, the Canadian Paediatric Society has developed three position statements on ADHD in children and adolescents. The objectives of these position statements are threefold: (i) to provide a summary of the current clinical ADHD evidence base; (ii) to establish a standard for ADHD care; and (iii) to facilitate clinicians in making well-informed, evidence-based decisions to promote optimal management of ADHD in children and adolescents.
Position statement 1 – ADHD in children and youth: aetiology, diagnosis and comorbidity
In the first position statement, the symptoms, features and impairments associated with ADHD are first discussed, with focus on the highly heritable nature of the condition and the role of neurological, environmental and psychosocial factors in maintaining and worsening any associated impairments.
Furthermore, practical advice is also provided to facilitate optimal assessment procedures and clinical diagnosis, including the following practice points (Bélanger et al. 2018):
Schedule several office visits to complete diagnostic evaluation
Obtain information regarding prenatal and perinatal events
Obtain developmental/behavioural history
Evaluate family medical and mental health
Evaluate for comorbid psychiatric, neurodevelopmental and physical disorders
Review academic progress
Obtain any standardised behaviour rating scale that evaluates Diagnostic and Statistical Manual of Mental Disorders – 5th Edition (DSM-5TM) from primary caregivers, teachers and the adolescent being assessed.
Position statement 2 – ADHD in children and youth: treatment
In the second position statement, the authors provide a summary of the evidence-based treatments for ADHD, with a focus on patient and parent choice (Feldman et al. 2018):
Non-pharmacological treatment: often used as adjunct treatment options for symptoms not amenable to treatment. Current guidelines recommend the use of behaviour therapy over the use of medication in pre-school–aged children with ADHD. Despite this, the authors stated that further research is necessary into the long-term clinical effectiveness of non-pharmacological interventions, both as stand-alone interventions and in combination with medication.
Pharmacological treatment: both stimulant and non-stimulant medications play an important role in the ADHD multimodal treatment approach. Psychostimulant medications are considered most effective, while non-stimulants represent an alternative option to manage clinically significant ADHD symptoms.
Position statement 3 – ADHD in children and youth: assessment and treatment with autism spectrum disorder (ASD), intellectual disability or prematurity
In the third position statement, the authors discussed how ADHD demonstrates clinical and genetic overlap with other childhood neurodevelopmental disorders, including ASD, intellectual disability and prematurity (Clark and Bélanger 2018). Although there is an increase in the prevalence of these populations, the authors expressed the opinion that there is a need for long-term follow-up studies on the safety and efficacy of medications in children or adolescents with ADHD and ASD, those with intellectual disability or those born premature. Furthermore, it is important that clinicians are aware of high comorbidity and assess for ADHD symptoms in children and adolescents with these conditions. To ensure these objectives are met, training programmes for paediatricians and family physicians must incorporate behavioural, developmental and mental health training, including ADHD diagnosis and treatment.
There has been an increase in the use of ADHD medication in several countries, raising concerns about potential overdiagnosis of ADHD and/or inappropriate prescription of ADHD medication. The aim of this study was to determine the prevalence of ADHD medication use over time in children, adolescents and adults across countries in Asia, Australia, North America, and northern and western Europe.
Patient-level electronic data (obtained between 1 January 2001 and 31 December 2015) were collected from 15 participating sites in 13 different countries and one Special Administrative Region across four regions.* The study population consisted of all individuals aged ≥3 years during the study period (please note: ADHD medications are licensed for the treatment of children with ADHD who are aged 6 years and older), who were grouped as follows: kindergarten/pre-school (3–5 years old); primary school (6–11 years old)†; secondary school (12–16 years old); older adolescents (17–18 years old); and adults (≥19 years old). Using the World Health Organization Anatomical Therapeutic Chemical (ATC) classification, records for prescribed medication, dispensed medication or insurance claims were used to identify medication use. Medication use was investigated regardless of whether a diagnosis of ADHD was made; exposure to medication was defined as the presence of a medication record at least once in the relevant study year.
Prevalence of ADHD medication use in children and adolescents (3–18 years old)
Data were available from 154.5 million individuals. The overall pooled prevalence of ADHD medication use in children and adolescents was 1.95% (95% confidence interval [CI] 0.76–3.13) across all regions.
The highest regional prevalence was in North America (4.48% [95% CI 2.86–6.10]) followed by northern Europe (1.95% [95% CI 1.47–2.44]). Asia and Australia (0.95% [95% CI 0.35–1.56]) and western Europe (0.70% [95% CI 0.31–1.10]) had the lowest pooled regional prevalence.
In all regions, ADHD medication use in 3–12 year olds increased over time; the absolute increase per year ranged from 0.02% (France) to 0.26% (Sweden).
Canada had the highest yearly increase in medication use, with mean increases of 45.11% (95% CI 43.50–46.71) per year, followed by Hong Kong, Taiwan, Finland, Denmark and Sweden. The lowest average increase per year was observed at the two sites in the US; 3.16% (95% CI 3.14–3.18) for US Medicaid and 2.83% (95% CI 2.80–2.86) for US MarketScan.
Prevalence of ADHD medication use in adults (≥19 years old)
In adults, the overall pooled prevalence of ADHD medication use was 0.39% (95% CI 0.31–0.47).
Similar to the prevalence in children and adolescents, the highest regional prevalence was in North America (1.42% [95% CI 1.29–1.54]), followed by northern Europe (0.47% [95% CI 0.31–0.62]), Asia and Australia (0.05% [95% CI 0.004–0.10]), and western Europe (0.03% [95% CI 0.01–0.04]).
In all regions, ADHD medication use increased over time; the absolute increase per year ranged from 0.0006% (Hong Kong) to 0.12% (one site in the US).
Asia and Australia had the highest yearly increase in medication use (25.06% [95% CI 17.65–32.46]), followed by northern Europe (18.81% [95% CI 10.74–26.87]) and western Europe (17.01% [95% CI 11.83–22.19]). Both sites in the US had the lowest average yearly increase in medication use (11.66% [95% CI 11.62–11.69] for US MarketScan and 14.30% [95% CI 14.22–14.38] for US Medicaid).
Prevalence of ADHD medication in males and females and type of treatment
The overall male to female ratio of medication use across all countries was 2:1 and was greater in children than in adults (2.0–6.3:1 and 0.9–2.7:1, respectively).
Of all of the individuals who used ADHD medication, >90% used methylphenidate in Hong Kong, Taiwan, Canada, Finland and Spain; the second most commonly used medication was atomoxetine in these countries. Approximately 75–90% of individuals in Japan, Denmark, Iceland, Norway, Sweden and the UK used methylphenidate, whereas only 59% and 45% of individuals used this treatment in Australia and at one of the sites in the US (US Medicaid), respectively. The most commonly used medication at US MarketScan was amfetamine (41%), followed by methylphenidate (34%) then lisdexamfetamine (21%).
The authors acknowledged that this study contained several limitations. For instance, although the authors used a common protocol between countries, there may be differences in the accuracy and generalisability of these data, as the datasets came from different sources. In addition, several ADHD medications are used off-label and therefore would not have been included in the study. Moreover, as a diagnosis of ADHD was not included, the authors could not examine the clinical characteristics of individuals using ADHD medication, and as exposure to medication over time was not taken into account, no conclusions can be drawn regarding medication adherence.
In concluding, the authors stated that to date this is the most comprehensive analysis of ADHD medication use in children, adolescents and adults across several global regions. The authors suggested that further research is needed to investigate the safety and effectiveness of short- and long-term ADHD medication use to help develop evidence-based guidelines.
*These regions included Asia and Australia (Australia, Hong Kong, Japan and Taiwan), North America (Canada and two sites in the US), northern Europe (Denmark, Finland, Iceland, Norway and Sweden) and western Europe (France, Spain and the UK)
†Data provided from Canadian sites only included children aged ≤11 years; therefore Canada was excluded from age-specific analyses for individuals aged ≥12 years
Excess activity and deficits in attention, behaviour regulation and impulse control are characterised differently by the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM) and the World Health Organization’s International Statistical Classification of Diseases and Related Health Problems (ICD). The 4th and 5th Editions of the DSM (DSM-IV and DSM-5TM) classify this condition as ADHD, whereas the 10th Revision of the ICD (ICD-10) characterises this as hyperkinetic disorder (HKD) (Andrews at al. 1999; World Health Organization 2001; American Psychiatric Association 2013). Although both classification systems use similar behavioural criteria, they differ in diagnostic decisions, and comparison studies suggest that HKD is associated with greater severity than ADHD. Using data from the Multimodal Treatment of ADHD (MTA) study,* the long-term outcomes of children with a baseline diagnosis of HKD according to the ICD-10 were assessed.
The research criteria for HKD were utilised by applying HYPESCHEME† filters to baseline ratings from the Diagnostic Interview Schedule for Children (DISC)–Parent Interview and the Swanson, Nolan and Pelham (SNAP) Teacher Rating Scale; self- and parent-reports from the youth adult version of the DISC (DISC-YA) were used to determine adult HKD. To determine adult ADHD symptomatology at 12-, 14- and 16-year follow-ups, both the self- and parent-rated Conners’ Adult ADHD Rating Scale (CAARS) and the DISC-YA were used. Substance use, educational outcomes, occupational, emotional and socioeconomic functioning, sexual behaviour, justice involvement, medication use, impairment, height and car crashes were also assessed.
The original MTA study included 579 children with a diagnosis of combined-type ADHD. According to the ICD-10, 145 of these children met the criteria for HKD (“original HKD”), and in 109 children, this continued into adulthood. On the other hand, 434 children were identified as not having HKD, and this was also true in 367 of these children in adulthood. In the authors’ analyses, they also included individuals who had generalised anxiety disorder (GAD)/depression. In this instance, a total of 178 of the 579 children in the MTA study were characterised as having HKD (“expanded HKD”) according to the ICD-10, which continued into adulthood for most of these children (n=135); however 401 children did not have HKD and it was not present in adulthood for 341 of these children.
A comparison of children with and without HKD (n=109 versus n=367) from the “original HKD” sample showed that according to the DSM-IV and DSM-5TM, there were no differences in the severity of symptoms (p>0.05) or persistence of adult ADHD (p>0.05). This was also observed in the “expanded HKD” sample (n=135 versus n=341). The use of stimulants and rates of consistent medication use were comparable between all groups; however, children with comorbid anxiety or depression (analysed using the “expanded HKD” sample) were more likely to demonstrate symptoms of ADHD in adulthood (p<0.005). There were no major differences in adult functional outcomes in the “original HKD” group compared with those without HKD; however, emotional lability problems (mean 0.86 [standard deviation (SD) 0.47] versus mean 0.94 [SD 0.57]; p=0.005) and car accidents (mean 50 [SD 38.75] versus mean 209 [SD 53.58]; p=0.032) were more common in those without HKD, whereas job losses (mean 1.28 [SD 1.68] versus mean 1.09 [SD 1.4]; p=0.01) were higher in those in the “original HKD” group. Conversely, in the “expanded HKD” group, individuals with HKD were at a lower risk for car accidents (mean 60 [SD 38.5] versus mean 199 [SD 54.8]; p=0.006) and emotional lability (mean 0.89 [SD 0.49] versus mean 0.93 [SD 0.57]; p=0.003) than those without HKD, and there were no differences in job losses (mean 1.19 [SD 1.6] versus mean 1.11 [SD 1.43]; p=0.09) or use of stimulants (mean 19.3 [SD 20.63] versus mean 16.1 [SD 19.04]; p=0.17). Patterns of medication use throughout adolescence, stimulant use in adulthood, adult symptom severity, substance use, educational outcomes, socioeconomic functioning, sexual behaviour, justice involvement and height were not significantly different between groups (p>0.05); however, individuals in the “original HKD” group reported higher medication use than those without HKD (mean 20.3 [SD 21.21] versus mean 16.05 [SD 18.95]; p=0.08). Using the HYPESCHEME filters, 6/109 (5.5%) children in the “original HKD” group and 12/135 (8.9%) children in the “expanded HKD” group could be classified as having HKD in adulthood according to the ICD-10 criteria.
The authors indicated that a limitation of this study was that compared with those without HKD, individuals identified at baseline as having HKD had a higher rate of attrition. They stated that the apparent outcome of HKD relative to ADHD without HKD would be artificially improved if the most severe cases were lost to follow-up.
The authors concluded that despite their initial hypothesis, children from the MTA study who displayed a greater initial symptom severity and pervasiveness with an ICD-10 diagnosis of HKD at baseline did not have worse outcomes in young adulthood compared with those who did not meet the criteria for HKD.
*In brief, the MTA study included 579 children aged between 7 and 9 years old with a diagnosis of combined-type ADHD according to DSM-IV criteria. Individuals were randomly assigned to systematic medication management, comprehensive multicomponent behavioural treatment or a combination of both. Study treatment was provided for 14 months, and assessment occurred at 24 months, 36 months, and 6, 8, 10, 12, 14 and 16 years after baseline. A total of 476 (82.2%) of the original 579 children also had assessments in adulthood
†HYPESCHEME can generate an explicit category of HKD and ADHD as it is an algorithm used for coding information from a variety of different records and instruments. The HYPESCHEME applied filters relating to comorbidity, symptom domain, pervasiveness and impairment
ADHD and bipolar disorder (BD) share common symptomatology such as mood instability, distractibility, impulsivity, restlessness and irritability. Additionally, both are chronic disorders with lifelong impairment and strong familial and genetic links. ADHD and BD can co-occur, and it is easy for one diagnosis to be overlooked or misdiagnosed; therefore, patients diagnosed with ADHD should be screened for BD and vice versa. However, there are uncertainties about the relationship between ADHD and BD; therefore, this study aimed to provide a report on the co-occurrence of ADHD and BD in adults.
Data from adults with a diagnosis of BD (type I [BD-I] or type II [BD-II]) according to the Diagnostic and Statistical Manual of Mental Disorders – 4th Edition – Text Revision (DSM-IV-TR), who were treated at the Lucio Bini Mood Disorder Centres in Rome and Cagliari, Italy in the past 15 years, were included in this study. Each individual was assessed using a variety of rating scales,* including the Adult ADHD Self-Report Scale v1.1 (ASRS-v1.1), which was used to assess ADHD. Information on academic failures and school dropouts was also collected for this study.
A total of 703 individuals with BD (54.9% female; mean age 46.0 [95% confidence interval (CI) 44.8–47.1] years) were included in the study. The mean age of BD onset was 26.3 (95% CI 25.4–27.2) years and the average illness duration was 19.7 (95% CI 18.6–20.7) years. A lifetime diagnosis of ADHD was present in 24.6% (n=173) of individuals with BD (male/female prevalence ratio = 2.35). In this study, no individual had ever received psychostimulant treatment.
The analyses compared individuals with BD and ADHD with those with BD but without ADHD:
ADHD was associated with BD-I more than BD-II (59.0 [95% CI 51.2–66.4] versus 41.0 [95% CI 33.6–48.8]). A history of ADHD in BD was linked to a higher ASRS-v1.1 score for inattention in individuals with ADHD compared with those without (11.5 [95% CI 10.6–12.6] versus 10.1 [95% CI 9.5–10.7; p=0.01]), but this was not significant for impulsivity (20.8 [95% CI 17.0–24.6] versus 19.8 [95% CI 18.8–20.8; p=0.32).
Individuals with BD and ADHD were found to have more school dropouts (1.14 [95% CI 0.96–1.32] versus 0.29 [95% CI 0.23–0.35]; p<0.0001) and were less likely to be educated beyond high school compared with those with BD but without ADHD (19.1 [95% CI 13.5–25.7] versus 3.96 [95% CI 2.47–5.99]; p<0.0001).
Unemployment (20.2 [14.5–27.0] versus 11.1 [8.58–14.1]; p=0.002) and separation and divorce (32.4 [25.5–39.9] versus 19.6 [16.3–23.3]; p=0.0005) were more likely to be associated with individuals with BD and ADHD compared with those with only BD. In addition, high socioeconomic status was more common in individuals with BD but without comorbid ADHD compared with those with BD and ADHD (29.8 [2.53–33.9] versus 18.5 [13.0–25.1]; p=0.0004).
Compared with individuals with BD only, a family history of psychiatric illness (79.1 [75.3–82.4] versus 69.4 [61.9–76.1]; p=0.009), mood disorder (74.2 [70.2–77.8] versus 59.5 [51.8–66.9]; p=0.0003), BD (38.3 [34.1–42.6] versus 29.5 [22.8–36.9]; p=0.04) or suicide (10.9 [8.42–13.9] versus 4.62 [2.02–8.9]; p=0.01) was less likely to be associated with BD and ADHD.
Individuals with BD and ADHD were at a significantly higher risk for suicidal acts (p=0.008; but not suicidal ideation or acts [p=0.24]) and substance use (including alcohol [p=0.0001] and cigarettes [p=0.0006], but not caffeine [p=0.06]) and were significantly more likely to meet diagnostic criteria for other psychiatric comorbidities (p=0.02) compared with those with BD without ADHD.
Individuals with BD and ADHD also exhibited more [hypo]mania (1.17 [0.69–1.65] versus 0.70 [0.50–0.90]; p=0.02), and were found to be more irritable (2.49 [2.18–2.78] versus 1.62 [1.46–1.78]; p<0.0001) than those with only BD.
The authors acknowledged limitations of the study, as this was retrospective, and the precise timing of onset of ADHD relative to the start of BD was unknown. Additionally, using the Conners’ Adult ADHD Diagnostic Interview for DSM-IV may have provided more detailed information about the diagnosis of ADHD.
In concluding, the authors reported a prevalence of ADHD of a quarter of adults diagnosed with BD, with a higher prevalence associated with BD-I. In addition, the co-occurrence of ADHD and BD was associated with several unfavourable outcomes, as well as more [hypo]mania than those diagnosed with BD only.
*Individuals were assessed using the following rating scales and questionnaires: ASRS-v1.1; Hamilton Depression Rating Scale; Hamilton Anxiety Rating Scale; Young Mania Rating Scale; Mood Disorder Questionnaire; and the Italian short version of the Temperament Evaluation of Memphis Pisa, Paris and San Diego self-report questionnaire
Presentation of ADHD in childhood and adulthood is highly dynamic, and the development of preventative measures as well as age-related diagnoses and interventions require knowledge of these changes. In this review article, the authors summarised published literature and current knowledge on ADHD from a developmental and lifespan perspective.
The phenotype of ADHD
The characteristic profile of ADHD changes through development, with hyperactive/impulsive symptoms highly present in very young children and inattentive symptoms becoming more apparent in adolescence and persisting into adulthood. However, overt hyperactivity and impulsivity are still observed in some adults with ADHD, and particularly those with comorbid problems such as substance abuse and antisocial behaviour. There are also gender differences in ADHD throughout development, as typically more males than females present with symptoms in child and adolescent clinics, whereas in adult clinics, males and females are equally present. This could be attributed to the observation that in childhood, males are more likely to display greater hyperactivity and impulsivity, and therefore more disruptive behaviour, than females. However, in adulthood, it is known that females are more likely to seek support for mental health problems, which could explain why rates of ADHD are similar in adults.
Age of onset of ADHD
Individuals can present with symptoms of ADHD at any age; however, according to the Diagnostic and Statistical Manual of Mental Disorders – 5th Edition (DSM-5TM), the age of onset criterion for childhood-onset ADHD is 12 years. There is evidence to suggest that ADHD in adulthood can be secondary to traumatic brain injury, which is distinct from childhood-onset ADHD. However, the concept of adult-onset idiopathic ADHD is more controversial, and although population studies estimate high rates of adult-onset ADHD, the authors highlighted that each of these studies had serious limitations. Therefore, it has been suggested that apparent adult-onset ADHD is instead due to undiagnosed or subthreshold ADHD in adolescence.
Psychiatric comorbidities associated with ADHD
In addition to the phenotype of ADHD changing through a lifespan, the associated psychiatric comorbidities also change. In childhood, individuals may exhibit oppositional defiant disorder and conduct disorder, whereas in adolescence and adulthood, antisocial personality, anxiety, mood, sleep and substance-use disorders become more apparent.
Response to pharmacological and non-pharmacological treatment
Regardless of age, it is recommended that treatment of ADHD should be multimodal and should include psychoeducation, pharmacotherapy and disorder-orientated psychotherapy, encompassing cognitive behavioural therapy (CBT) and family or couple therapy if required. In most European countries, only methylphenidate, lisdexamfetamine and atomoxetine are officially approved for both childhood and adulthood ADHD, and the National Institute for Health and Care Excellence guidelines recommend methylphenidate as the first-choice treatment for adult ADHD. The effect size of pharmacotherapy can differ throughout the lifespan, and may differ due to the presence of comorbid psychiatric disorders. More research is needed to compare the effects of different ADHD treatments in adults, as well as the efficacy and safety of these treatments in adults with ADHD and psychiatric comorbidities.
Non-pharmacological treatments to manage ADHD are also available to individuals throughout the lifespan. In many countries, children and adolescents with mild ADHD are often recommended non-pharmacological interventions as first-line therapy; however, these approaches demonstrate less efficacy compared with pharmacological treatments, but may be very useful in reducing psychiatric comorbidities or behavioural problems. Moreover, CBT has demonstrated efficacy in adolescents and adults with ADHD, and both mindfulness-based interventions and neurofeedback are other non-pharmacological options being explored as treatments for ADHD.
Outcome of ADHD with and without treatment
It has been reported that ADHD is associated with poor academic outcomes, unemployment, financial difficulties, poor social outcomes and increased mortality. Evidence from systematic reviews has suggested that individuals with untreated ADHD in both childhood and adulthood have poorer long-term outcomes compared with treated individuals in relation to academic outcomes, antisocial behaviour, driving, non-medicinal drug use/addictive behaviour, obesity, occupation, services used, self-esteem and social function. However, pharmacoepidemiological analyses indicated that individuals with ADHD who are treated with medication have a reduced risk for criminality and serious traffic accidents, as well as substance-use disorders and depression.
Cognitive and neuroimaging profiles of ADHD
Cognitive differences and brain abnormalities have been observed between children and adults with ADHD in cross-sectional studies. Meta-analyses of cognitive studies indicate that ADHD may be linked with poor performance in inhibition-, working memory-, planning- and vigilance-related tasks during childhood, adolescence and adulthood. Moreover, using magnetic resonance imaging, meta-analyses have shown that individuals with ADHD have reduced brain volumes, most robustly across studies in the basal ganglia area linked to reward and processing. Large-scale neuroanatomical studies have also shown that there are differences in brain volume and connectivity between those who have persistent ADHD and those who have remitted ADHD.
Genetics and environmental factors affecting ADHD
ADHD has a strong genetic component and its heritability is stable across the lifespan. Linkage studies have demonstrated converging evidence for common biological pathways which underlie ADHD, thereby emphasising that both common and rare genetic polymorphisms account for a large proportion of the genetic susceptibility of ADHD. Different genetic loci and a few positional candidate genes have also been identified for ADHD, and genome-wide association studies have shown an enrichment of genes related to neurobiological functions, which may be relevant to ADHD. However, these studies have also highlighted that the genetic background of ADHD is similar to that of other disorders, such as major depressive disorder, migraine and obesity. The authors indicated that although it is clear that ADHD exhibits high heritability and has complex genetics, more research is needed to find specific genes which underlie ADHD and also what causes it to persist into adulthood.
In addition to the genetic risk factors associated with ADHD, pre- and perinatal risk factors such as maternal stress, smoking or alcohol consumption during pregnancy, low birth weight, unfavourable psychosocial conditions and nutritional factors may also be associated with the development of ADHD. Moreover, many studies have reported that environmental risk factors for ADHD can be influenced by genetic polymorphisms.
The authors concluded that the lifelong trajectory of ADHD is highly variable, and that although it may be a burden to many individuals, some people with ADHD may remit or funnel the associated deficits into adaptive behaviours to lead very successful lives. This suggests that recognising the signs of ADHD early and providing optimal treatment could improve the lives of individuals with ADHD. The authors admit that although challenging, more longitudinal, granular and multimodal studies are necessary in order to clarify the course of ADHD and identify those at risk of unfavourable outcomes, and to provide a tailored treatment programme.
Around one-fourth of the prison population meet the clinical diagnostic criteria for ADHD. There is also a high risk of comorbid psychiatric disorders amongst youth and adult prisoners with ADHD, and those with undiagnosed or untreated ADHD have poor clinical and functional outcomes. This report aimed to expand upon the consensus of the UK Adult ADHD Network to identify prison-system barriers preventing the appropriate management of ADHD. This study also provided a practical approach, based on expert consensus, to inform effective identification and treatment of prisoners with ADHD.
This report was developed by a multidisciplinary group of prescribing and non-prescribing clinical and academic experts with experience of working with prisoners with ADHD. The authors initially attended a meeting, hosted in November 2016 by the UK ADHD Partnership (UKAP; funded by Shire), which discussed how to identify and treat adult prisoners with ADHD. Researchers, prison staff, clinicians and patient representatives with expertise in offender mental health and ADHD also attended the UKAP meeting. The UKAP meeting included presentations,* discussions and group work, and attendees were tasked with providing practical solutions on a variety of topics, such as “Identification and assessment”, “Treatments and interventions” and “Care management and multi-agency liaison”. The consensus report was developed from the transcript of the UKAP meeting, in conjunction with the authors’ views and experiences, as well as published literature.
A brief summary of the key conclusions from the consensus report is presented below. The authors indicated that although these recommendations are mainly based upon experiences in the UK, they may also be applicable and adaptable to other countries.
Identification and assessment
Prison staff must have an awareness of ADHD symptoms and psychiatric comorbidities. They must also have training to understand ADHD treatments, the expected outcomes of treatments, and how these treatments may affect the prison regime. Prison staff should also understand that for many prisoners, many psychiatric comorbidities are often secondary to ADHD.
If rating scales are used, they must be sensitive to both inattention and hyperactivity/impulsivity symptoms, and a clinical diagnostic interview and a suitable primary screen must be used for both youths (Comprehensive Health Assessment Tool [CHAT]†) and adults (Brief Barkley Adult ADHD Rating Scale [B-BAARS]‡).
Interventions and treatment
Use of appropriate pharmacological and non-pharmacological treatment, as well as psychoeducation about ADHD (e.g. symptoms, psychiatric comorbidities, medication, side effects of medication and expected outcomes) should be provided to all prisoners.
Educational and occupational programmes, particularly those that advance vocational, creative, technical and/or athletic skills, should be made available to enhance engagement.
Care management and multi-agency liaison
Within the criminal justice system, educational and mental health services should work closely.
Each prisoner must have a care-plan coordinator whilst in prison, and a care plan should be established to aid with medication management.
To aid transition and ensure continuity of care and ADHD medication, a care plan for release should be provided for each prisoner. This care plan should also provide the prisoner with links to supportive services and agencies following their release from prison.
A critical time intervention approach should be determined to support the prisoner through the release process and aid implementation of the care plan and engagement in healthcare services.
The authors stated that although this consensus report identified a practical approach to treat prisoners with ADHD, future research is required to optimise these approaches and measure their success on health-, behaviour- and offence-related outcomes following implementation in prisoners with ADHD. Additionally, more research is required to assess the needs of female prisoners with ADHD. The authors also emphasised that future research should aim to determine the financial and societal benefits of effectively treating prisoners with ADHD, as this will demonstrate the cost-effectiveness of appropriate intervention and may lead to increased governmental support and subsequent changes in criminal justice and mental health service policies.
In concluding, the authors indicated that use of this consensus report will aid the identification and treatment of prisoners with ADHD, and they expect that if used appropriately, this will have a positive impact on both prisoners and society, leading to decreased utilisation of resources and reduced rates of re-offending.
*The meeting began with four presentations: “The Facts: what we know from empirical data”; “Needs, problems, and obstacles when assessing and treating ADHD in a young offender institution”; “Needs, problems, and obstacles when assessing and treating ADHD in an adult prison”; and “Beyond the gates: needs, multi-agency liaison, and the care pathway”
†The CHAT is mandated by the National Health Service England for use in youth offender institutions in England and Wales. The mental health section of the CHAT is a validated semi-structured interview designed to screen for all health issues amongst youth offenders and covers physical health, mental health, substance abuse and neurodisability. The CHAT takes approximately 1 hour to complete and is available electronically. Although the CHAT has poor specificity for ADHD, it is sensitive in identifying mental health problems including ADHD, so can be used as a primary screen to flag potential mental health issues before a more detailed assessment is conducted
‡The B-BAARS is a short, six-item screen with excellent specificity and sensitivity for predicting ADHD in offending adults, and is available for free. The authors indicated that, in their experience, the B-BAARS is more suitable for prison populations compared with the Adult ADHD Self-Report Scale