February 22, 2021

How to Improve Driving Safety for Teens and Adults With ADHD

Drivers with ADHD are far more likely to be involved in crashes, to be at fault in crashes,to be in severe crashes, and to be killed in crashes. The more severe the ADHD symptoms, the higher the risk. Moreover, ADHD is often accompanied by comorbid conditions such as oppositional-defiant disorder, depression, and anxiety that further increase the risk.

What can be done to reduce this risk? A group of experts has offered the following consensus recommendations:

·   Use stimulant medications. While there is no reliable evidence on whether non-stimulant medications are of any benefit for driving, there is solid evidence that stimulant medications are effective in reducing risk. But there is also a rebound effect in many individuals after the medication wears off, in which performance actually becomes worse than if had been prior to medication. It is therefore important to time the taking of medication so that its period of effectiveness corresponds with driving times. If one has to drive right after waking up, it makes sense to take a rapid acting form. The same holds for late night driving that may require a quick boost.

·   Use a stick shift vehicle wherever possible. Stick shifts make drivers pay closer attention than automatic transmissions. The benefits in alertness are most notable in city traffic. But using a stick shift is far less beneficial in highway driving, where shifting is less frequent.

·  Avoid cruise control. Highways can be monotonous, making drivers more prone to boredom and distraction. That is even more true for those with ADHD, so it is best to keep cruise control turned off.

·   Avoid alcohol. Drinking and driving is a bad idea for everyone, but, once again, it's even worse for those with ADHD. Parents should consider a no-questions-asked policy of either picking up their teenager anytime and anywhere, or setting up an account with a ride-sharing service.·   Place the smartphone out of reach and hearing. Cell phone use is as about as likely to impair as alcohol. Hands-free devices only reduce this risk moderately, because they continue to distract. Texting can be deadly. Sending a short text or emoticon can be the equivalent of driving 100 yards with one's eyes closed. Either turn on Do Not Disturb mode, or, for even greater effectiveness, place the smart phone in the trunk.

·   Make use of automotive performance monitors. These can keep track of maximum speeds and sudden acceleration and braking, to verify that a teenager is not engaging in risky behaviors.

·   Take advantage of graduated driver's licensing laws wherever available. These laws forbid the presence of peers in the vehicle for the first several (for example, six) months of driving. Parents can extend that period for teenagers with ADHD, or set it as a condition in states that lack such laws.

·  Encourage practicing after obtaining a learner's permit. Teenagers with ADHD generally require more practice than those without. A pre-drive checklist can be a good place to start. For example:check the gas, check the mirrors, make sure the view through the windows is unobstructed, put cell phone in Do Not Disturb mode and place it out of reach, put on seat belt, scan for obstacles.

·   Consider outsourcing. Look for a driving school with a professional to teach good driving skills and habits.

Experts do not agree on whether to delay licensing for those with ADHD. On the one hand, teenagers with ADHD are 3-4 years behind in the development of brain areas responsible for executive functions that help control impulses and better guide behavior. Delaying licensing can reduce risk by about 20 percent. On the other hand, teens with ADHD are more likely to drive without a license, and no one wants to encourage that, however inadvertently. Moreover, graduated driver's licensing laws only have legal effect on teens who get their licenses at the customary age.

Paula A. Aduen, Daniel J. Cox, Gregory A.Fabiano, Annie A. Garner, Michael J. Kofler, "Expert Recommendations for Improving Driving Safety for Teens and Adult Drivers with ADHD," ADHD Rep. (2019) 27(4): 8-14.doi:10.1521/adhd.2019.27.4.8.

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Using Video Analysis and Machine Learning in ADHD Diagnosis

NEWS TUESDAY: Machine Learning and The Possible Future of Diagnosing ADHD

Typically, clinicians rely on both subjective and objective observations, patient interviews and questionnaires, as well as reports from family and (in the case of children) parents and teachers, in order to diagnose ADHD. 

A group of researchers are aiming to find a diagnostic test that is purely objective and utilizes recent technological advancements. The method they developed involves analyzing videos of children in outpatient settings, focusing on their movements. The study included 96 children, half of whom had ADHD and half who did not.

How It Works

  1. Video Recording: Children were recorded during their outpatient visits.
  2. Skeleton Detection: Using a tool called OpenPose, the researchers detected and tracked the children's skeletons (essentially a map of their body's movements) in the videos.
  3. Movement Analysis: The researchers analyzed these movements, looking at 11 different movement features. They specifically focused on the angles of different body parts and how much they moved.
  4. Machine Learning: Six different machine learning models were used to see which movement features could best distinguish between children with ADHD and those without.

Key Findings

  • Movement Differences: Children with ADHD showed significantly more movement in all the features analyzed compared to children without ADHD.
  • Thigh Angle: The angle of the thigh was the most telling feature. On average, children with ADHD had a thigh angle of about 157.89 degrees, while those without ADHD had an angle of 15.37 degrees.
  • High Accuracy: Using thigh angle alone, the model could diagnose ADHD with 91.03% accuracy. It was very sensitive (90.25%) and specific (91.86%), meaning it correctly identified most children with ADHD and correctly recognized most children without it.

This new method could potentially provide a more objective way to diagnose ADHD, reducing the reliance on subjective observations and reports. It can help doctors make more accurate diagnoses, ensuring that those who need help get it and that those who don't aren't misdiagnosed.

May 28, 2024

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