人工智能在大学生心理健康教育中的应用：机遇、挑战与策略应对
Artificial intelligence in college students' mental health education: opportunities, challenges, and strategic responses.
摘要(中文译文)
大学生心理健康问题已成为全球日益关注的议题，给高等教育系统带来越来越大的压力，要求其提供有效、可扩展且公平的心理健康教育与支持。本叙述性综述考察了将人工智能（AI）融入大学生心理健康教育所涉及的机遇、挑战与战略应对。为提高概念清晰度，本综述将有教育导向的AI应用与相邻领域加以区分，包括以预防为导向的支持、早期识别与筛查，以及支持性准临床干预。本综述识别出三个主要机遇领域：对自我调节与心理健康学习的个性化支持、AI辅助的早期觉察与预防，以及可及性与机构覆盖范围的扩展。本综述还强调了与伦理治理和隐私、准确性与可靠性，以及数字鸿沟与包容性议题相关的关键挑战。对此，本综述强调需要加强伦理框架、提升系统可靠性与文化回应性，并在高等教育中促进数字素养与AI素养。总体而言，现有证据表明，AI可作为专业服务和以人为本的教育实践的有价值补充。然而，证据基础在很大程度上仍属短期且依赖具体情境，凸显了开展纵向研究、加强机构治理以及采取更具包容性的实施策略的必要性。因此，负责任的AI融合需要一种平衡的、以教育为中心的方法，并与公平、学生福祉和机构责任相一致。
Abstract
Mental health challenges among college students have become a growing global concern, placing increasing pressure on higher education systems to provide effective, scalable, and equitable mental health education and support. This narrative review examines the opportunities, challenges, and strategic responses associated with integrating artificial intelligence (AI) into college students' mental health education. To improve conceptual clarity, it distinguishes educationally oriented AI applications from adjacent domains, including prevention-oriented support, early detection and screening, and supportive quasi-clinical intervention. The review identifies three main opportunity domains: personalized support for self-regulation and mental health learning, AI-assisted early awareness and prevention, and expanded accessibility and institutional reach. It also highlights key challenges related to ethical governance and privacy, accuracy and reliability, and digital divide and inclusivity issues. In response, the review emphasizes the need to strengthen ethical frameworks, improve system reliability and cultural responsiveness, and promote digital and AI literacy within higher education. Overall, current evidence suggests that AI can serve as a valuable complement to professional services and human-centered educational practices. However, the evidence base remains largely short-term and context-dependent, underscoring the need for longitudinal research, stronger institutional governance, and more inclusive implementation strategies. Responsible AI integration therefore requires a balanced, education-centered approach aligned with equity, student well-being, and institutional responsibility.
如何引用
AMA
Rui Wang, Xiaobo Sun, Yuqi Sun, Jing Wang. Artificial intelligence in college students' mental health education: opportunities, challenges, and strategic responses.. Frontiers in psychology. 2026; doi:10.3389/fpsyg.2026.1794568.
APA
Rui Wang, Xiaobo Sun, Yuqi Sun, Jing Wang (2026). Artificial intelligence in college students' mental health education: opportunities, challenges, and strategic responses.. Frontiers in psychology. https://doi.org/10.3389/fpsyg.2026.1794568
GB/T 7714
Rui Wang, Xiaobo Sun, Yuqi Sun, Jing Wang. Artificial intelligence in college students' mental health education: opportunities, challenges, and strategic responses.[J]. Frontiers in psychology, 2026 doi:10.3389/fpsyg.2026.1794568.
在 PubMed增强版 阅读全文
翻译全文 · AI 文献问答 · PDF 原文下载 · 引用导出