Hidden in plain sight: how individual ADHD stakeholders have conflicting ideas about ADHD but do not address their own ambivalence.

Psychiatric classifications refer to clusters of behavioral symptoms. We know much about how psychiatric classifications are intended to be used in theory. Yet the scientific study of the practice of classification to date is limited. We aimed to explore how individuals navigate and make sense of the complexity surrounding an ADHD classification. We used thematic analysis to analyse stakeholder perspectives from seven focus groups: adults classified with ADHD, adolescents classified with ADHD, parents of children classified with ADHD, clinicians, researchers, teachers, and policy makers. We found seven themes in how stakeholders navigate the classification ADHD. Yet, what stood out was an overarching discursive pattern: individual stakeholders expressed highly ambivalent ideas about ADHD but did not address their own ambivalence. We suggest that promoting a social kinds perspective on ADHD may help us navigate the complexity and ambivalence associated with ADHD more competently.

Lost in explanation: internal conflicts in the discourse of ADHD psychoeducation.

BACKGROUND: Psychiatric classifications are understood in many different ways. For children with ADHD and their parents, psychoeducation is an important source of information for shaping their understanding. Moreover, psychoeducation is often taken by children and parents to represent how their story is understood by the therapist. As a result, the way psychoeducation is formulated may affect the therapeutic alliance, one of the most robust mediators of treatment outcome. In addition, psychoeducation may indirectly influence the way we understand psychological differences as a society. METHODS: To better understand how the classification ADHD is given meaning through psychoeducation, we analyzed 41 written psychoeducational materials from four different countries; the USA, UK, Netherlands and Hungary. RESULTS: We identified five patterns of how the materials construct the discourse on ADHD. Notably, tension between biomedical and psychosocial perspectives resulted in conflict within a single thematic stance on ADHD as opposed to a conflict between parties with a different vision on ADHD. There were only few differences between countries in the way they constructed the discourse in the materials. CONCLUSIONS: These conflicts cause confusion, misrepresentation and decontextualization of ADHD. Ultimately, for those diagnosed with ADHD and their parents, conflicting information in psychoeducation materials may hamper their ability to understand themselves in the context of their difficulties.

Which Child Will Benefit From a Behavioral Intervention for ADHD? A Pilot Study to Predict Intervention Efficacy From Individual Reward Sensitivity.

Objective: This article aims to assess whether individual differences in reward sensitivity can be used to predict which children with attention-deficit/hyperactivity disorder (ADHD) will benefit most from behavioral interventions that include reinforcement. Methods: A 12-week behavioral intervention was offered to 21 children with ADHD and their parents. Reward sensitivity was assessed prior to the intervention using a combination of psychological and physiological measures. ADHD symptoms were assessed pre- and posttreatment using the Strengths and Weaknesses of ADHD and Normal behavior (SWAN) rating scale. Results: Lower scores on one of the questionnaire scales were associated with greater pre/posttreatment differences in ADHD symptoms. Conclusion: We found that pre/posttreatment change was associated with one measure of parent-rated reward sensitivity. Children with low impulsive negative behavior toward gaining reward improved most during treatment. This result suggests that aspects of reward-related behaviors in ADHD may be useful to predict the effectiveness of treatment.

Can we use neuroimaging data to differentiate between subgroups of children with ADHD symptoms: A proof of concept study using latent class analysis of brain activity.

BACKGROUND: Multiple pathway models of ADHD suggest that multiple, separable biological pathways may lead to symptoms of the disorder. If this is the case, it should be possible to identify subgroups of children with ADHD based on distinct patterns of brain activity. Previous studies have used latent class analysis (LCA) to define subgroups at the behavioral and cognitive level and to then test whether they differ at the neurobiological level. In this proof of concept study, we took a reverse approach. We applied LCA to functional imaging data from two previously published studies to explore whether we could identify subgroups of children with ADHD symptoms at the neurobiological level with a meaningful relation to behavior or neuropsychology. METHODS: Fifty-six children with symptoms of ADHD (27 children with ADHD and 29 children with ASD and ADHD symptoms) and 31 typically developing children performed two neuropsychological tasks assessing reward sensitivity and temporal expectancy during functional magnetic resonance imaging. LCA was used to identify subgroups with similar patterns of brain activity separately for children with ADHD-symptoms and typically developing children. Behavioral and neuropsychological differences between subgroups were subsequently investigated. RESULTS: For typically developing children, a one-subgroup model gave the most parsimonious fit, whereas for children with ADHD-symptoms a two-subgroup model best fits the data. The first ADHD subgroup (n = 49) showed attenuated brain activity compared to the second subgroup (n = 7) and to typically developing children (n = 31). Notably, the ADHD subgroup with attenuated brain activity showed less behavioral problems in everyday life. CONCLUSIONS: In this proof of concept study, we showed that we could identify distinct subgroups of children with ADHD-symptoms based on their brain activity profiles. Generalizability was limited due to the small sample size, but ultimately such neurobiological profiles could improve insight in individual prognosis and treatment options.

Children with ADHD symptoms show deficits in reactive but not proactive inhibition, irrespective of their formal diagnosis.

BACKGROUND: Attenuated inhibitory control is one of the most robust findings in the neuropsychology of attention-deficit/hyperactivity disorder (ADHD). However, it is unclear whether this represents a deficit in outright stopping (reactive inhibition), whether it relates to a deficit in anticipatory response slowing (proactive inhibition), or both. In addition, children with other development disorders, such as autism spectrum disorder (ASD), often have symptoms of inattention, impulsivity, and hyperactivity similar to children with ADHD. These may relate to similar underlying changes in inhibitory processing. METHODS: In this study, we used a modified stop-signal task to dissociate reactive and proactive inhibition. We included not only children with ADHD, but also children primarily diagnosed with an ASD and high parent-rated levels of ADHD symptoms. RESULTS: We replicated the well-documented finding of attenuated reactive inhibition in children with ADHD. In addition, we found a similar deficit in children with ASD and a similar level of ADHD symptoms. In contrast, we found no evidence for deficits in proactive inhibition in either clinical group. CONCLUSIONS: These findings re-emphasize the role of reactive inhibition in children with ADHD and ADHD symptoms. Moreover, our findings stress the importance of a trans-diagnostic approach to the relationship between behavior and neuropsychology.

What to expect and when to expect it: an fMRI study of expectancy in children with ADHD symptoms.

Changes in cognitive control and timing have both been implicated in ADHD. Both are involved in building and monitoring expectations about the environment, and altering behavior if those expectations are violated. In ADHD, problems with expectations about future events have high face validity, as this would be associated with behavior that is inappropriate only given a certain context, similar to symptoms of the disorder. In this fMRI study, we used a timing manipulated go/nogo task to assess brain activity related to expectations about what (cognitive control) and when (timing) events would occur. We hypothesized that problems in building expectations about the environment are a more general, trans-diagnostic characteristic of children with hyperactive, impulsive and inattentive symptoms. To address this, we included children with ASD and symptoms of ADHD, in addition to children with ADHD and typically developing children. We found between-group differences in brain activity related to expectations about when (timing), but not what events will occur (cognitive control). Specifically, we found timing-related hypo-activity that was in part unique to children with a primary diagnosis of ADHD (left pallidum) and in part shared by children with similar levels of ADHD symptoms and a primary diagnosis of ASD (left subthalamic nucleus). Moreover, we found poorer task performance related to timing, but only in children with ASD and symptoms of ADHD. Ultimately, such neurobiological changes in children with ADHD symptoms may relate to a failure to build or monitor expectations and thereby hinder the efficiency of their interaction with the environment.

Children with ADHD symptoms show decreased activity in ventral striatum during the anticipation of reward, irrespective of ADHD diagnosis.

BACKGROUND: Changes in reward processing are thought to be involved in the etiology of attention-deficit/hyperactivity disorder (ADHD), as well as other developmental disorders. In addition, different forms of therapy for ADHD rely on reinforcement principles. As such, improved understanding of reward processing in ADHD could eventually lead to more effective treatment options. However, differences in reward processing may not be specific to ADHD, but may be a trans-diagnostic feature of disorders that involve ADHD-like symptoms. METHODS: In this event-related fMRI study, we used a child-friendly version of the monetary incentive delay task to assess performance and brain activity during reward anticipation. Also, we collected questionnaire data to assess reward sensitivity in daily life. For final analyses, data were available for 27 typically developing children, 24 children with ADHD, and 25 children with an autism spectrum disorder (ASD) and ADHD symptoms. RESULTS: We found decreased activity in ventral striatum during anticipation of reward in children with ADHD symptoms, both for children with ADHD as their primary diagnosis and in children with autism spectrum disorder and ADHD symptoms. We found that higher parent-rated sensitivity to reward was associated with greater anticipatory activity in ventral striatum for children with ADHD symptoms. In contrast, there was no relationship between the degree of ADHD symptoms and activity in ventral striatum. CONCLUSIONS: We provide evidence of biological and behavioral differences in reward sensitivity in children with ADHD symptoms, regardless of their primary diagnosis. Ultimately, a dimensional brain-behavior model of reward sensitivity in children with symptoms of ADHD may be useful to refine treatment options dependent on reward processing.

Reward Anticipation in Ventral Striatum and Individual Sensitivity to Reward: A Pilot Study of a Child-Friendly fMRI Task.

Reward processing has been implicated in developmental disorders. However, the classic task to probe reward anticipation, the monetary incentive delay task, has an abstract coding of reward and no storyline and may therefore be less appropriate for use with developmental populations. We modified the task to create a version appropriate for use with children. We investigated whether this child-friendly version could elicit ventral striatal activation during reward anticipation in typically developing children and young adolescents (aged 9.5-14.5). In addition, we tested whether our performance-based measure of reward sensitivity was associated with anticipatory activity in ventral striatum. Reward anticipation was related to activity in bilateral ventral striatum. Moreover, we found an association between individual reward sensitivity and activity in ventral striatum. We conclude that this task assesses ventral striatal activity in a child-friendly paradigm. The combination with a performance-based measure of reward sensitivity potentially makes the task a powerful tool for developmental imaging studies of reward processing.

Developmental differences in intra-individual variability in children with ADHD and ASD.

BACKGROUND: Intra-individual variability reflects temporal variation within an individual's performance on a cognitive task. Children with developmental disorders, such as ADHD and ASD show increased levels of intra-individual variability. In typical development, intra-individual variability decreases sharply between the ages 6 and 20. The tight link between intra-individual variability and age has led to the suggestion that it may be marker of neural development. As there is accumulating evidence that ADHD and ASD are characterised by atypical neurodevelopmental trajectories, we set out to explore developmental changes in intra-individual variability in subjects with ADHD and ASD. METHOD: We used propensity score matching to match a cross-sectional sample of children with ADHD, ASD and control subjects (N = 405, aged 6-19 years old) for age, IQ and gender. We used ex-Gaussian distribution parameters to characterise intra-individual variability on fast responses (sigma) and slow responses (tau). RESULT: Results showed that there was a similar decrease in mean response times with age across groups, and an interaction between age and group for measures of variability, where there was a much lower rate of change in the variability parameters (sigma and tau) for subjects with ASD compared with the other two groups. Subjects with ADHD had higher intra-individual variability, reflected by both sigma and tau, but the rate of decrease in variability with age was similar to that of the controls. CONCLUSION: These results suggest that subjects with ADHD, ASD and controls differ in the rate at which intra-individual variability decreases during development, and support the idea that intra-individual variability may be a marker of neural development, mimicking the neurodevelopmental changes in these disorders.