May 17, 2021

Are Nonpharmacologic Treatments for ADHD Useful?

There are several very effective drugs for ADHD, and those treatment guidelines from professional organizations view these drugs as the first line of treatment for people with ADHD. The only exception is for preschool children where medication is only the first line of treatment for severe ADHD; the guidelines recommend that other preschoolers with ADHD be treated with non-pharmacologic treatments, when available. Despite these guidelines, some parents and patients have been persuaded by the media or the Internet that ADHD drugs are dangerous and that non-drug alternative are as good or even better. Parents and patients may also be influenced by media reports that doctors overprescribe ADHD drugs or that these drugs have serious side effects. Such reports typically simplify and/or exaggerate results from the scientific literature. Thus, many patients and parents of ADHD children are seeking non-drug treatments for ADHD. What are these non-pharmacologic treatments and do they work? My next series of blogs will discuss each of these treatments in detail. Here I'll give an overview of my evidenced-based taxonomy of non-pharmacologic treatments for ADHD described in more detail in a book I recently edited (Faraone, S. V. &Antshel, K. M. (2014). ADHD: Non-Pharmacologic Interventions. Child Adolesc Psychiatry Clin N Am 23, xiii-xiv.). I use the term "evidence-based" in the strict sense applied by the Oxford Center for Evidenced Based Medicine (OCEBM; http://www.cebm.net/). Most of the non-drug treatments for ADHD fall into three categories: behavioral, dietary, and neurocognitive. Behavioral interventions include training parents to optimize methods of reward and punishment for their ADHD child, teaching ADHD children social skills, and helping teachers apply principles of behavior management in their classrooms. Cognitive behavior therapy is a method that teaches behavioral and cognitive skills to adolescent and adult ADHD patients. Dietary interventions include special diets that exclude food coloring or eliminate foods believed to cause ADHD symptoms. Other dietary interventions provide supplements such as iron, zinc, or omega-3 fatty acids.  The neurocognitive interventions typically use a computer-based learning setup to teach ADHD patients cognitive skills that will help reduce ADHD symptoms. There are two metrics to consider when thinking about the evidence base for these methods. The first is the quality of the evidence. For example, a study of 10 patients with no control group would be a low-quality study, but a study of 100 patients randomized to either a treatment or control group would be of high quality and the quality would be even higher if the people's rating patient outcomes did not know who was in each group. The second metric is the magnitude of the treatment effect. Does the treatment dramatically reduce ADHD symptoms, or does it have only a small effect? This metric is only available for high-quality studies that compare people treated with the method and people treated with a 'control' method that is not expected to affect ADHD. I used a statistical metric to quantify the magnitude of the effect. Zero means no effect, and larger numbers indicate better effects on treating ADHD symptoms. For comparison, the effect of stimulant drugs for ADHD is about 0.9, which is derived from a very strong evidence base.  The effects of dietary treatments are smaller, about 0.4 to 0.5, but because the quality of the evidence is not strong, these results are not certain and the studies of food color exclusions apply primarily to children who have high intakes of such colorants. In contrast to the dietary studies, the evidence base for behavioral treatments is excellent, but the effects of these treatments on ADHD symptoms are very small, less than 0.1.  Supplementation with omega-3 fatty acids also has a strong evidence base, but the magnitude of the effect is also small (0.1 to 0.2). The neurocognitive treatments have modest effects on ADHD symptoms (0.2 to 0.4) but their evidence base is weak. This review of non-drug treatments explains why ADHD drug treatments are usually used first. The evidence base is stronger, and they are more effective in reducing ADHD symptoms. There is, however, a role for some non-drug treatments. I'll be discussing that in subsequent blog posts. See more evidence-based information about ADHD at www.adhdinadults.com

Faraone, S. V.&Antshel, K. M. (2014). ADHD: Non-Pharmacologic Interventions. ChildAdolescPsychiatr Clin N Am 23, xiii-xiv.
Faraone, S. V. &Antshel, K. M. (2014).Towards an evidence-based taxonomy of nonpharmacologic treatments for ADHD.Child AdolescPsychiatr Clin N Am 23, 965-72.

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Understanding Attention to Social Images in Children with ADHD and Autism

NEWS TUESDAY: Understanding Attention to Social Images in Children with ADHD and Autism

In the field of mental health, professionals often use a variety of tools to diagnose and understand neurodevelopmental disorders such as Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD). One such tool is the Autism Diagnostic Observation Schedule (ADOS), which is specifically designed to help diagnose autism. However, the ADOS wasn't originally intended for children who have both autism and ADHD, though this comorbidity is not uncommon.

A recent study aimed to explore how children with ADHD, autism, or both, pay attention to social images, such as faces. The study focused on using eye-tracking technology to measure where children direct their gaze when viewing pictures, and how long they look at certain parts of the image. This is important because differences in visual attention can provide insights into the nature of these disorders.

The researchers included 84 children in their study, categorized into four groups: those with ASD, those with ADHD, those with both ASD and ADHD, and neurotypical (NT) children without these conditions. During the study, children were shown social scenes from the ADOS, and their eye movements were recorded. The ADOS assessment was administered afterward. To ensure that the results were not influenced by medications, children who were on stimulant medications for ADHD were asked to pause their medication temporarily.

The results of the study showed that children with ASD, whether they also had ADHD or not, tended to spend less time looking at faces compared to children with just ADHD or NT children. The severity of autism symptoms, measured by the Social Communication Questionnaire (SCQ), was associated with reduced attention to faces. Interestingly, ADHD symptom severity, measured by Conners' Rating Scales (CRS-3), did not correlate with how children looked at faces.

These findings suggest that measuring visual attention might be a valuable addition to the assessment process for ASD, especially in cases where ADHD is also present. The study indicates that if a child with ADHD shows reduced attention to faces, it might point to additional challenges related to autism. The researchers noted that more studies with larger groups of children are needed to confirm these findings, but the results are promising. They hope that such measures could eventually enhance diagnostic processes and help in managing the complexities of cases involving comorbidity of ADHD and ASD.

This research opens up the possibility of using eye-tracking as a supplementary diagnostic tool in the assessment of autism, providing a more nuanced understanding of how attentional differences in social settings are linked to ASD and ADHD.

May 14, 2024

NEW STUDY: RASopathies Influences on Neuroanatomical Variation in Children

NEW STUDY: RASopathies Influences on Neuroanatomical Variation in Children

This study investigates how certain genetic disorders, called RASopathies, affect the structure of the brain in children. RASopathies are conditions caused by mutations in a specific signaling pathway in the body. Two common RASopathies are Noonan syndrome (NS) and neurofibromatosis type 1 (NF1), both of which are linked to a higher risk of autism spectrum disorder (ASD) and attention deficit and hyperactivity disorder (ADHD).

The researchers analyzed brain scans of children with RASopathies (91 participants) and compared them to typically developing children (74 participants). They focused on three aspects of brain structure: surface area (SA), cortical thickness (CT), and subcortical volumes.

The results showed that children with RASopathies had both similarities and differences in their brain structure compared to typically developing children. They had increased SA in certain areas of the brain, like the precentral gyrus, but decreased SA in other regions, such as the occipital regions. Additionally, they had thinner CT in the precentral gyrus. However, the effects on subcortical volumes varied between the two RASopathies: children with NS had decreased volumes in certain structures like the striatum and thalamus, while children with NF1 had increased volumes in areas like the hippocampus, amygdala, and thalamus.

Overall, this study highlights how RASopathies can impact the development of the brain in children. The shared effects on SA and CT suggest a common influence of RASopathies on brain development, which could be important for developing targeted treatments in the future.

In summary, understanding how these genetic disorders affect the brain's structure can help researchers and healthcare professionals develop better treatments for affected children.

April 30, 2024

News Tuesday: Integrating Cognition and Eye Movement

Integrating Cognitive Factors and Eye Movement Data in Reading Predictive Models for Children with Dyslexia and ADHD-I

In a recent study, researchers delved into the complex interplay of cognitive processes and eye movements in children with dyslexia and Attention-Deficit/Hyperactivity Disorder. Their findings shed light on predictive models for reading outcomes in these children compared to typical readers.

The study involved 59 children: 19 typical readers, 21 with ADHD, and 19 with developmental dyslexia (DD), all in the 4th grade and around 9 years old on average. Each group underwent thorough neuropsychological and linguistic assessments to understand their psycholinguistic profiles.

During the study, participants engaged in a silent reading task where the text underwent lexical manipulation. Researchers then analyzed eye movement data alongside cognitive factors like memory, attention, and visual processes.

Using multinomial logistic regression, the researchers evaluated predictive models based on three key measures: a linguistic model focusing on phonological awareness, rapid naming, and reading fluency; a cognitive neuropsychological model incorporating memory, attention, and visual processes; and an additive model combining lexical word properties with eye-tracking data, specifically examining word frequency and length effects.

By integrating eye movement data with cognitive factors, the researchers enhanced their ability to predict the development of dyslexia or ADHD, in comparison to typically developing readers. This approach significantly improved the accuracy of predicting reading outcomes in children with learning disabilities.

These findings have profound implications for understanding and addressing reading challenges in children. By considering both cognitive processes and eye movement patterns, educators and clinicians can develop more effective interventions tailored to the specific needs of children with dyslexia and ADHD.

April 30, 2024