Behavioral Disorders (CD) is a common but complex mental illness characterized by aggressive and destructive behavior. Factors contributing to CD development include the biological, psychological, and social spheres. Researchers have identified a number of risk factors that may help predict CD, but they are often considered separately. Now, a new study is using a machine learning method for the first time to assess risk factors in all three domains together and predict the further development of a CD with high accuracy.
Research in Biological Psychiatry: Cognitive Neurology and Neuroimagingpublished by Elsevier.
The researchers used baseline data from more than 2,300 children aged 9 to 10 years enrolled in the Adolescent Cognitive Developmental Study (ABCD), a long-term study following the biopsychosocial development of children. The researchers “trained” their machine learning model using previously identified risk factors from all different biopsychosocial domains. For example, measures were brain (biological) perceptions, cognitive (psychological) abilities, and familial (social) characteristics. The model predicted CD development two years later with more than 90% accuracy.
Cameron Carter, MD, Editor Biological Psychiatry: Cognitive Neurology and Neuroimaging“These remarkable results using task-based functional MRI to examine the function of the reward system show that the risk of later depression in children of depressed mothers may be more related to maternal responses to their children’s emotional behavior than to mood swings,” the study said. mother for yourself. “
The ability to accurately predict who can develop CDs will help researchers and healthcare professionals in developing programs for at-risk youth with the potential to reduce the harmful effects of CDs on children and their families.
“The findings of our study demonstrate the added value of combining neurological, social, and psychological factors to predict behavioral disorders, a serious psychological problem in young people,” said senior author Ariel Baskin-Sommers, PhD at Yale University, New Haven, CT, USA. “These findings promise to develop specific approaches and interventions that take into account the many factors that contribute to this disease. collected at the levels, emphasize. analysis. “
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