The application of artificial intelligence in the field of mental health: a systematic review

Abstract

IntroductionThe integration of artificial intelligence in mental health care represents a transformative shift in the identification, treatment, and management of mental disorders. This systematic review explores the diverse applications of artificial intelligence, emphasizing both its benefits and associated challenges.MethodsA comprehensive literature search was conducted across multiple databases based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses, including ProQuest, PubMed, Scopus, and Persian databases, resulting in 2,638 initial records. After removing duplicates and applying strict selection criteria, 15 articles were included for analysis.ResultsThe findings indicate that AI enhances early detection and intervention for mental health conditions. Various studies highlighted the effectiveness of AI-driven tools, such as chatbots and predictive modeling, in improving patient engagement and tailoring interventions. Notably, tools like the Wysa app demonstrated significant improvements in user-reported mental health symptoms. However, ethical considerations regarding data privacy and algorithm transparency emerged as critical challenges.DiscussionWhile the reviewed studies indicate a generally positive trend in AI applications, some methodologies exhibited moderate quality, suggesting room for improvement. Involving stakeholders in the creation of AI technologies is essential for building trust and tackling ethical issues. Future studies should aim to enhance AI methods and investigate their applicability across various populations.ConclusionThis review underscores the potential of AI to revolutionize mental health care through enhanced accessibility and personalized interventions. However, careful consideration of ethical implications and methodological rigor is essential to ensure the responsible deployment of AI technologies in this sensitive field.