The Roles of Artificial Intelligence and Computational Modeling on Anxiety Diagnosis and Intervention
The interest from researchers on artificial intelligence and computational psychiatry is rising and studies on these topics are leading to great promises to transform theoretical and practical domains of psychiatry and mental health.
Yiqun Gan, School of Psychological and Cognitive Sciences, Peking University, Email: firstname.lastname@example.org
Yujia Peng,School of Psychological and Cognitive Sciences, Peking University,Email: email@example.com
Special issue information:
The traditional methods of diagnosis of a wide array of distress and mental disorders mostly involve self-reported questionnaires and clinical interviews; limitations of the former lies on its reliance on participants’ subjective judgments and willingness to report symptoms, whereas the latter tends to be costly, time consuming, and requires the participation of professionals in the field. These limitations bring forth the need for more efficient, lower-cost, and objective measures that synthesize multimodal information, which are crucial for the prevention and treatment of anxiety disorders including Post Traumatic Stress Disorder, Obsessive Compulsive Disorder, and health anxiety/illness anxiety disorder. In fact, there is a current need for more interdisciplinary and timely research combining mental health, computational models, and artificial intelligence. This interdisciplinary approach aims to achieve a better understanding of the mechanisms and behavioral manifestations of anxiety, as well as assessments and interventions with greater effectiveness.
This background raises the following questions that will be targeted in the current special issue "VSI: AI in Anxiety Diagnosis & Intervention":
How can artificial intelligence and computational modeling contribute to the integration of the neuroscience and cognitive sciences about anxiety disorders and then inform the psychopathology of related disorders?
How can artificial intelligence and computational modeling technologies facilitate identification and diagnosis of anxiety disorders?
What are the implications and innovations that artificial intelligence and computational modeling bring forth for research methodology, theory development, and clinical practice related to anxiety disorders?
How do artificial intelligence and machine learning tools (e.g., machine learning-based multimodal assessments) affect the prevention, treatment, and public awareness of anxiety disorders, as well as associated social attitudes and decision-making?