AI Applications Integrating Legal and Regulatory Perspectives in Mental Health: Systematic Review

Abstract
BackgroundArtificial intelligence (AI) offers new methods to improve diagnosis and treatment in mental health. However, its use raises legal and ethical concerns.
ObjectiveAI is increasingly being used for mental health care, but its clinical prominence and ethical implications are yet to be determined. This systematic review discusses the clinical efficacy and the ethical issues of AI in mental health treatment and is trying to focus on the main conclusions with regard to the diagnostic accuracy and the therapeutic efficacy.
MethodsThe review encompasses an exhaustive analysis of 35 studies in the narrow time frame of 2013‐2024. It allows for multidatabase exploration and follows the systematic and well-established practice of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. This review searched PubMed (biomedical emphasis), IEEE Xplore (engineering or AI), PsycINFO (psychological literature), Scopus (multidisciplinary focus), and Cochrane Library (evidence-based treatment) from January 1, 2013, to December 31, 2024. Studies include those that focused on AI applications for diagnosis, treatment, or patient engagement, excluding tangential uses (eg, administrative tasks). Only English-language publications were searched to mitigate language bias, though this introduces potential geographic bias.
ResultsAI-enabled interventions of natural language processing models showed up to 89% accuracy for depression detection. The wearables, as in the Empatica E4, showed an F1
ConclusionsIn addressing mental health, AI has the potential to revolutionize mental health treatment, offering cost-saving, personalized, and culturally sensitive interventions while protecting privacy, equity, and human agency.