April 23, 2021
With the growth of the Internet, we are flooded with information about attention deficit hyperactivity disorder from many sources, most of which aim to provide useful and compelling "facts" about the disorder. But, for the cautious reader, separating fact from opinion can be difficult when writers have not spelled out how they have come to decide that the information they present is factual.
My blog has several guidelines to reassure readers that the information they read about ADHD is up-to-date and dependable. They are as follows:
Nearly all the information presented is based on peer-reviewed publications in the scientific literature about ADHD. "Peer-reviewed" means that other scientists read the article and made suggestions for changes and approved that it was of sufficient quality for publication. I say "nearly all" because in some cases I've used books or other information published by colleagues who have a reputation for high-quality science.
When expressing certainty about putative facts, I am guided by the principles of evidence-based medicine, which recognizes that the degree to which we can be certain about the truth of scientific statements depends on several features of the scientific papers used to justify the statements, such as the number of studies available and the quality of the individual studies. For example, compare these two types of studies. One study gives drug X to 10 ADHD patients and reported that 7 improved. Another gave drug Y to 100 patients and a placebo to 100 other patients and used statistics to show that the rate of improvement was significantly greater in the drug-treated group. The second study is much better and much larger, so we should be more confident in its conclusions. The rules of evidence are fairly complex and can be viewed at the Oxford Center for Evidenced Based Medicine (OCEBM;http://www.cebm.net/).
The evidenced-based approach incorporates two types of information: a) the quality of the evidence and b) the magnitude of the treatment effect. The OCEBM levels of evidence quality are defined as follows (higher numbers are better:
Non-randomized, controlled studies. In these studies, the treatment group is compared to a group that receives a placebo treatment, which is a fake treatment not expected to work.
It is possible to have high-quality evidence proving that a treatment works but the treatment might not work very well. So it is important to consider the magnitude of the treatment effect, also called the "effect size" by statisticians. For ADHD, it is easiest to think about ranking treatments on a ten-point scale. The stimulant medications have a quality rating of 5 and also have the strongest magnitude of effect, about 9 or 10.Omega-3 fatty acid supplementation 'works' with a quality rating of 5, but the score for the magnitude of the effect is only 2, so it doesn't work very well. We have to take into account patient or parent preferences, comorbid conditions, prior response to treatment, and other issues when choosing a treatment for a specific patient, but we can only use an evidence-based approach when deciding which treatments are well-supported as helpful for a disorder.
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Previous studies have examined how stimulant medications affect the brain in controlled settings, but less is known about their impact in real-world conditions, where children may not always take their medication consistently or may combine it with other treatments. A new study leverages data from the Adolescent Brain Cognitive Development (ABCD) study to explore how real-world stimulant use impacts brain connectivity and ADHD symptoms over two years.
Changes in Brain Connectivity Researchers used brain imaging data from the ABCD study to examine the functional connectivity—communication between brain areas—of six regions within the striatum, a brain area involved in motivation and movement control. They focused on how stimulant use influenced connectivity between the striatum and other networks involved in executive functioning and visual-motor control.
The study found that stimulant exposure was linked to reduced connectivity between key striatal areas (such as the caudate and putamen) and large brain networks, including the frontoparietal and visual networks. These changes were more pronounced in children taking stimulants compared to those who were not medicated, as well as compared to typically developing children. Importantly, this reduction in connectivity seemed to regulate certain brain networks that are typically altered in children with ADHD.
Symptom Improvement In addition to brain changes, 14% of children taking stimulants experienced a significant reduction in ADHD symptoms over the two-year period. These children showed the strongest connectivity reductions between the right putamen and the visual network, suggesting that stimulant-induced connectivity changes may contribute to improvements in visual attentional control, which is a common challenge for children with ADHD.
Why This Matters This study is one of the first to examine how stimulant use in real-world conditions affects brain networks in children with ADHD over time. The findings suggest that stimulants may help normalize certain connectivity patterns associated with ADHD, particularly in networks related to attention and control. These insights could help clinicians better understand the potential long-term effects of stimulant treatment and guide personalized approaches to ADHD management.
Conclusion Stimulant medications appear to alter striatal-cortical connectivity in children with ADHD, with some changes linked to symptom improvement. This research highlights the potential for stimulant medications to impact brain networks in ways that support attention and control, highlighting the importance of understanding how real-world medication use influences ADHD treatment outcomes.
The Neuroeconomic Perspective
Neuroeconomics combines neuroscience, psychology, and economics to understand how people make decisions. Neuroeconomic studies suggest that brain regions responsible for evaluating risk and reward, including the prefrontal cortex and dopamine pathways, function differently in individuals with ADHD. These insights are crucial for developing more tailored interventions. For example, understanding how ADHD affects reward processing might inform strategies that help individuals resist impulsive choices or increase motivation for delayed rewards.
Understanding Decision-Making in ADHD
We know that decision-making is a sophisticated process involving various cognitive procedures. It’s not just about choosing between options but also about how to weigh risks, rewards, and potential future outcomes; Attention, motivation, and cognitive control are core to this process. For individuals with ADHD, however, this neural framework is affected by impairments in attention and impulse control, often resulting in “delay discounting”—the tendency to prefer smaller, immediate rewards over larger, delayed ones.
This propensity for impulsive decisions is more than a personal challenge; it has broader societal and economic implications. Previous studies have shown that these tendencies in ADHD can lead to issues in academics, work, finances, and personal relationships, emphasizing the need for targeted support and interventions.
Implications and Future Directions
This review highlights a need for continued research to bridge the gaps in understanding how ADHD-specific cognitive deficits influence decision-making. Viewing ADHD through a neuroeconomic lens clarifies how cognitive and neural differences affect decision-making, often leading to impulsive choices with economic and social impacts. This perspective opens doors to more effective interventions, improving decision-making for individuals with ADHD. Future policies informed by this approach could enhance support and reduce associated societal costs.
Children with ADHD face significant challenges in academic and social settings, often including difficult interactions with teachers. This meta-analysis investigates the quality of student-teacher relationships for children with ADHD, focusing on two key dimensions: closeness and conflict. By synthesizing data from 27 studies encompassing 17,236 participants, the study aims to provide a comprehensive understanding of these dynamics and inform interventions to support both students and teachers.
A systematic review was conducted using databases such as PsycInfo, ERIC, and ProQuest. Researchers identified 47 effect sizes from 27 studies, examining the association between ADHD symptoms and the quality of student-teacher relationships. Relationship quality was assessed through two primary dimensions:
Eight moderator analyses were also performed to explore how factors like grade level, gender, ADHD presentation, and comorbid conditions influenced these relationships.
The findings reveal that children with ADHD symptoms typically experience relationships with teachers characterized by lower levels of closeness and higher levels of conflict. Notably, externalizing behaviors such as hyperactivity and impulsivity are more strongly associated with conflict than inattentive symptoms. Moderator analyses showed that factors like gender, ADHD presentation, and age influence the severity of these relationship dynamics. For instance, younger children and those with hyperactive-impulsive presentations tend to have higher conflict levels with teachers.
Additionally, the research emphasizes the reciprocal nature of these relationships: ADHD symptoms may exacerbate teacher frustration, while negative teacher-student interactions can intensify student behavioral challenges.
Conclusion
This meta-analysis highlights the critical role of student-teacher relationships in the development of children with ADHD. The findings underline the need for targeted interventions that foster positive teacher-student interactions and reduce conflict. Addressing these relationship dynamics could enhance academic performance, social integration, and emotional well-being for children with ADHD. Future research should explore the causal pathways between ADHD symptoms and relationship quality to better inform educational strategies and support systems.
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