AI-driven Methods for Detecting and Improving Mental Health Symptoms: An umbrella Review
Artificial intelligence (AI) is becoming increasingly advanced and has the potential to address challenges in mental health care, particularly around access and availability. With shortages in mental health professionals and barriers like stigma, cost, and geographic limitations, AI tools such as chatbots, virtual therapists, and predictive analytics may offer scalable, low-barrier support options. While not a replacement for traditional care, they can complement existing services and help reach underserved populations.
Our Work
Despite the presence of systematic reviews and meta-analyses on the use of AI in mental health, these reviews often focus on a narrow population or type of intervention and therefore hinder a broader understanding of the efficacy and diagnostic accuracy of diverse AI tools for various populations. Therefore, the purpose of this umbrella review is to bring evidence together and evaluate the existing meta-analyses on AI-driven methods for mental health, so we can better understand current trends in how AI is being used in mental health research, its efficacy, and diagnostic accuracy. We will also review various ethical AI aspects, including the reporting of adverse events. This review may generate useful information for future mental health research and relevant policy making.