October 20, 2021

Systematic review finds association between ADHD and gaming disorder

The specific type of gaming disorder (GD) that is the focus of this review is "disordered video-gaming," or more precisely the addictive potential of interactive video games played on mobile phones, gaming consoles, individual computers, and over networks. Certain characteristics of such games, including structured rewards and multi-modal sensory stimulation, contribute to that addictive potential. Networked games also allow for direct social engagement through role playing and cooperation with others. They also lead to further opportunities for participation in a wider community of players on forums outside gameplay, such as discussion platforms, video play-through analyses, or live-streaming.

The authors performed a systematic search of the peer-review literature, and identified 29 studies exploring the relationship between Addend GD.

All studies found a positive association between ADHD and GD. Of studies reporting effect sizes, seven reported small effect sizes, three reported medium ones, and three reported large ones. There was a similarly wide variety of reported effect sizes among studies that reported correlations between ADHD scales and GD scales. These ranged from r = .12 (small) to r = .45(large).

Three studies examined longitudinal outcomes. One reported that lower ADHD scores at baseline predicted positive long-term recovery. Another noted that GD was more likely to develop into significant psychiatric symptoms and poorer educational outcomes two years later. The third study found that higher ADHD and GD scores were associated with higher incidences of delinquent or aggressive behaviors and externalizing problems, as compared to a sample with ADHD but not GD. All three studies reported that ADHD was a risk factor for the development of problematic gaming behavior. There was no clear indication of the reverse relationship - GD predicting ADHD.

The authors concluded, "This review found a consistent positive association between ADHD and GD, particularly for the inattention subscale. The strength of the association between ADHD and GD was variable. On symptom severity ratings, there was a positive relationship between scores measuring GD and ADHD pathology in some studies. Fewer studies in this review showed hyperactivity was commonly associated with GD. It is well known that hyperactivity in ADHD tends to improve significantly with age. It is possible that the natural progression of the disorder resulted in lower rates of hyperactivity. Such a hypothesis is strengthened by findings of a stronger association with hyperactivity among children aged between 4 and 8."

Ideas for policy interventions to address disordered video gaming include:

·        Parental controls on games.
·        Warning messages similar to those on cigarette packaging.
·        Organizing help services for gamers.

The authors called for further study on:

·        Effectiveness of intervention strategies.
·        The contribution of GD to the dysfunction associated with ADHD.
·        The relationship between the content of play (e.g., violence) and motivation to play (e.g., escapism) and ADHD symptoms.
role-playin·        The role of depression, anxiety, and another comorbidity in mediating the relationship between ADHD and GD

"Clinicians should beware that ADHD is common in GD," the authors emphasized, "and we, therefore, recommend that ADHD is screened for when evaluating GD as part of routine practice. This would ensure interventions aimed at ADHD can be successfully combined with GD treatment, potentially improving patient outcomes."

Pravin Dullur, Vijay Krishnan, Antonio MendozaDiaz, "A systematic review of the intersection of attention-deficit hyperactivity disorder and gaming disorder," Journal of Psychiatric Research133 (2021), 212-222, https://doi.org/10.1016/j.jpsychires.2020.12.026.

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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