The application of Generative Artificial Intelligence in mental health care: A bibliometric and visualized analysis

Generative Artificial Intelligence (GAI) has emerged as a promising and innovative technological advancement that can increase access to mental health care services with its powerful natural language processing capabilities. Preliminary findings suggest that GAI has great potential in the field of mental health care. This study aims to elaborate and predict the trajectory of the discipline, identify research hotspots and emerging trends, and provide a comprehensive framework for the application of GAI in mental health care.

The analyzed papers were obtained from the Web of Science core database and were searched from the beginning of the database to December 14, 2024. Bibliometric and visualization analyses were performed for sources, institutions, countries, author collaboration networks, and keywords. We used Bibliometrix (version 4.4.2), CiteSpace (version 6.4.R1 Basic) and Excel (WPS 6.2.2.8394).

A total of 79 articles published by 118 authors were retrieved from the Web of Science Core Collection database. The number of published articles showed an increasing trend. "JMIR Mental Health" was the journal with the most publications, and the United States, China, and the United Kingdom were the top three contributors and the countries with the most publications. In addition, the high-frequency keywords identified in this study include Artificial Intelligence, Mental Health, Machine Learning, Large Language Models, Natural Language Processing, Care, Depression. Large Language Model, ChatGPT, Challenges.

The application of GAI in the field of mental health care revolves around two main themes: (1) exploring applications in key areas such as emotional support, psychological assessment, and personalized psychological interventions; (2) issues of privacy protection, reliability of generated content, and associated risks. Future research can engage in multidisciplinary collaboration to further optimize the adaptability and standardization of GAI technology applications.