The advent of computer simulation to identify symptoms in children with attention deficit / hyperactivity disorder (ADHD) has the potential to offer Ohio State University researchers in a new publication suggest an additional objective tool to assess the presence and measure the severity of behavioral problems.
Most mental disorders are diagnosed and treated using clinical interviews and questionnaires. For about a century, data from cognitive tests has been included in the diagnostic process to help doctors learn more about how and why people behave in certain situations.
Cognitive tests in ADHD are used to identify a variety of symptoms and deficits, including selective attention, poor working memory, altered time perception, difficulty maintaining attention, and impulsive behavior. In the most common class of achievement tests, children are advised to either press a computer key or avoid pressing a key when they see a specific word, symbol, or other stimulus.
However, in ADHD, these cognitive tests often fail to capture the complexity of the symptoms. The advent of computational psychiatry – the comparison of a computer-simulated model of normal brain processes with dysfunctional processes seen in tests – could be an important addition to the diagnostic process for ADHD, Ohio state researchers report in a new review published in the journal Psychological Bulletin was published.
The research team reviewed 50 studies of cognitive tests for ADHD and described how three popular types of computational models could complement these tests.
It is generally accepted that children with ADHD take longer to make decisions while performing tasks than children who do not have the disorder. Tests relied on average response times to explain the difference. However, there are complications with this disorder that a computational model can pinpoint by providing information that doctors, parents, and teachers can use to make life easier for children with ADHD.
« We can use models to simulate the decision-making process and see how decisions are made over time – and to better find out why children with ADHD take longer to make decisions, » said Nadja Ging-Jehli , Lead reviewer and a graduate student in psychology at Ohio State.
Ging-Jehli completed the review with Roger Ratcliff, Professor of Psychology, and L. . Eugene Arnold, Professor Emeritus of Psychiatry and Behavioral Health.
The researchers make recommendations for testing and clinical practice to achieve three main goals: better characterizing ADHD and all related mental health diagnoses such as anxiety and depression, improving patient outcomes (about a third of patients with ADHD are unresponsive medical treatment) and possibly predicting which children will « lose » the diagnosis of ADHD as adults.
The decision-making behind the steering wheel of a car illustrates the problem: Drivers know that they can pass an intersection when a red light turns green – but not everyone steps on the accelerator at the same time.
A general cognitive test of this behavior would repeatedly expose drivers to the same red-green-green-light scenario to get an average response time and use that average and deviations from it to categorize the typical versus disordered driver.
This approach was used to determine that people with ADHD typically « start driving » more slowly than people without ADHD. However, that determination leaves out a number of ways that explain why they are slower – they might be distracted, dreaming, or feeling nervous in a laboratory setting. The wide distribution of responses captured by computer modeling could provide more and useful information.
« In our review, we show that this method has several problems that prevent us from understanding the underlying characteristics of a mental disorder such as ADHD and also prevent us from finding the best treatment for different people » So went- said Jehli.
« We can use computer models to think about the factors that produce the observed behavior. These factors will broaden our understanding of a disorder and recognize that there are different types of people with different deficits who also require different treatments.
« We suggest using the full distribution of response times, considering the slowest and fastest response times, to differentiate between different types of ADHD. «
The review also identified a complicating factor for future ADHD research – a wider range of outwardly obvious symptoms, as well as subtle features that are difficult to detect with most popular testing methods.
Understanding that children with ADHD have so many biological differences suggests that a single task-based test isn’t enough to make a meaningful diagnosis of ADHD, the researchers say.
« ADHD isn’t just that kid wriggling and restless in a chair. It is also the child who is inattentive because of daydreaming. Although this child is more introverted and does not show as many symptoms as a child with hyperactivity, that doesn’t mean the child isn’t suffering, « said Ging-Jehli. Daydreaming is especially common among girls who don’t participate nearly as often in ADHD studies as boys, she said.
Ging-Jehli described computer psychiatry as an instrument which – continuation of the analogy – also takes into account mechanical differences in the car and how this could influence driver behavior. These dynamics can make ADHD difficult to understand, but it can also open the door to a wider range of treatment options.
« We need to consider the different types of drivers and understand the different conditions we are exposing them to. We cannot draw conclusions about diagnostic and treatment options based on just one observation, « she said.
« However, cognitive tests and computer models should not be viewed as attempts to replace existing clinical interviews and questionnaire-based procedures, but rather as additions that create added value by providing new information. «
According to the researchers, a set of tasks that measure social and cognitive characteristics should be assigned for a diagnosis, not just one. More consistency is needed across all studies to ensure that the same cognitive tasks are used to assess the appropriate cognitive concepts.
Finally, combining cognitive tests with physiological tests – particularly eye tracking and EEGs that record electrical activity in the brain – could provide meaningful, objective and quantifiable data to help make a diagnosis more reliable and help doctors better predict which drugs are most effective.
Ging-Jehli puts these suggestions to the test in her own research and applies a computational model in a study of a specific neurological intervention in children with ADHD.
The purpose of our analysis was to show that there is a lack of standardization and complexity, and that symptoms are difficult to measure with existing tools. We need to understand ADHD better so that children and adults have a better quality of life and receive the treatment that is most appropriate. «
Nadja Ging-Jehli, Review Journal director and PhD student in Psychology at Ohio State University
Ging-Jehli, N.. . R.. . et al. (2021) Improving Neurocognitive Testing Using Computational Psychiatry – A Systematic Review for ADHD. Psychological bulletin. doi. org / 10. 1037 / bul0000319.
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Attention Deficit Hyperactivity Disorder, Computers, Psychiatry
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