Chen Jing, Yuan Dongfeng, Dong Ruotong, Cai Jingyi, Ai Zhongzhu, Zhou Shanshan
Wuhan University China Institute of Boundary and Ocean Studies, Wuhan, China.
Faculty of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China.
Front Psychol. 2024 Mar 7;15:1375294. doi: 10.3389/fpsyg.2024.1375294. eCollection 2024.
College students are currently grappling with severe mental health challenges, and research on artificial intelligence (AI) related to college students mental health, as a crucial catalyst for promoting psychological well-being, is rapidly advancing. Employing bibliometric methods, this study aim to analyze and discuss the research on AI in college student mental health.
Publications pertaining to AI and college student mental health were retrieved from the Web of Science core database. The distribution of publications were analyzed to gage the predominant productivity. Data on countries, authors, journal, and keywords were analyzed using VOSViewer, exploring collaboration patterns, disciplinary composition, research hotspots and trends.
Spanning 2003 to 2023, the study encompassed 1722 publications, revealing notable insights: (1) a gradual rise in annual publications, reaching its zenith in 2022; (2) and emerged were the most productive and influential sources in this field, with significant contributions from China, the United States, and their affiliated higher education institutions; (3) the primary mental health issues were depression and anxiety, with machine learning and AI having the widest range of applications; (4) an imperative for enhanced international and interdisciplinary collaboration; (5) research hotspots exploring factors influencing college student mental health and AI applications.
This study provides a succinct yet comprehensive overview of this field, facilitating a nuanced understanding of prospective applications of AI in college student mental health. Professionals can leverage this research to discern the advantages, risks, and potential impacts of AI in this critical field.
大学生目前正面临严峻的心理健康挑战，而与大学生心理健康相关的人工智能（AI）研究作为促进心理健康的关键催化剂正在迅速发展。本研究采用文献计量方法，旨在分析和讨论人工智能在大学生心理健康方面的研究。
从科学网核心数据库中检索与人工智能和大学生心理健康相关的出版物。分析出版物的分布情况，以衡量主要的生产力。使用VOSViewer对国家、作者、期刊和关键词的数据进行分析，探索合作模式、学科构成、研究热点和趋势。
该研究涵盖了2003年至2023年期间的1722篇出版物，揭示了以下显著见解：（1）年度出版物逐渐增加，在2022年达到顶峰；（2） 和 成为该领域最具生产力和影响力的来源，中国、美国及其附属高等教育机构做出了重大贡献；（3）主要的心理健康问题是抑郁和焦虑，机器学习和人工智能的应用范围最广；（4）加强国际和跨学科合作势在必行；（5）研究热点包括探索影响大学生心理健康的因素和人工智能的应用。
本研究对该领域进行了简洁而全面的概述，有助于更细致地理解人工智能在大学生心理健康方面的潜在应用。专业人员可以利用这项研究来识别人工智能在这一关键领域的优势、风险和潜在影响。
