January 2, 2022

How effective is cognitive training for preschool children?

A German team of researchers performed a comprehensive search of the medical literature and identified 35randomized controlled trials (RCTs) published in English that explored this question. Participating children were between three and six years old. Children with intellectual disabilities, sensory disabilities, or specific neurological disorders such as epilepsy were excluded.

The total number of participating preschoolers was over three thousand, drawn almost exclusively from the general population, meaning these studies were not specifically evaluating effects on children with ADHD. But given that ADHD results in poorer executive functioning, evidence of the effectiveness of cognitive training would suggest it could help partially reverse such deficits.

RCTs assign participants randomly to a treatment group and a group not receiving treatment but often receiving a placebo. But RCTs themselves vary in risk of bias, depending on:

  • whether the control condition was passive (i.e. waiting list or no treatment) or active/sham (an activity of similar duration and intensity to the treatment condition)
  • whether the outcome was measured by subjective rating (e.g. by questionnaires, susceptible to reporting biases) or more objective neuropsychological testing;
  • whether the assessment of outcome was by blinded assessors unaware of participants' treatment conditions;
  • whether there was a risk of bias from participants dropping out of the trial.

After evaluating the RCTs by these criteria, the team performed a series of meta-analyses.

Combining the 23 RCTs with over 2,000 children that measured working memory, they found that cognitive training led to robust moderate improvements. Looking only at the eleven most rigorously controlled studies strengthened the effect, with moderate-to-large gains.

Twenty-six RCTs with over 2,200 children assessed inhibitory control. When pooled, they indicated a small-to-moderate improvement from cognitive training. Including only the seven most rigorously controlled studies again strengthened the effect, boosting it into the moderate effect zone.

Twelve RCTs with over 1,500 participants tested the effects of cognitive training on flexibility. When combined, they pointed to moderate gains. Looking at only the four well-controlled studies boosted the effect to strong gains. Yet here there was evidence of publication bias, so no firm conclusion can be drawn.

Only four studies with a combined total of 119 preschoolers tested the effects on ADHD ratings. The meta-analysis found a small but non-significant improvement, very likely due to insufficient sampling. As the authors noted, "some findings of the meta-analysis are limited by the insufficient number of eligible studies. Specifically, more studies are needed which use blinded assessments of subjective ratings of ADHD ... symptoms ..."

The authors concluded that their meta-analyses revealed significant, mostly medium-sized effects of the preschool interventions on core EFs [executive functions] in studies showing the low risk of bias."

Ursula Pauli" Pott, Christopher Mann, Katja Becker, "Do cognitive interventions for preschoolers improve executive functions and reduce ADHD and externalizing symptoms?

A meta" analysis of randomized controlled trials," European Child & Adolescent Psychiatry(2020),https://doi.org/10.1007/s00787-020-01627-z.

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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