Inclusive-Oriented, AI-Driven Mental Health Services for All Age Groups: Research on Challenges and Optimization Strategies

Abstract

Against the background of the normalized and large-scale development of global mental health problems and the imbalance between supply and demand for mental health services in China, artificial intelligence (AI) technology provides a new pathway for achieving inclusivity in mental health services for all age groups. This study focuses on the development of an AI-driven intelligent agent for mental health detection and counseling services under an inclusive orientation. Based on an analysis of 107 valid samples collected through online questionnaires, the study systematically identifies core challenges, including low cognitive awareness and acceptance of AI mental health services among different demographics, shortcomings in service adaptability (e.g., operational difficulty, age-specific adaptation) and trust (e.g., privacy protection, accuracy of results), and the underexploration of potential mental health needs. Guided by the Hierarchy of Needs Theory, Social Support Theory, and Human-Machine Collaboration Theory, this paper proposes a dual-pillar framework for the agent's application, encompassing personalized psychological education and support across the entire lifespan—from childhood and adolescence to adulthood, the workplace, and old age—and deep empowerment of the educational ecosystem as embedded infrastructure for curriculum innovation, teacher training, and data-driven management decision-making. Furthermore, the paper rigorously analyzes the current limitations of the technology, including the depth of emotional interaction, professional competence boundaries, and challenges in ecological integration. It outlines targeted improvement directions involving multimodal affective computing, human-machine collaborative intervention networks, and advanced personalized adaptation. The study concludes with a future-oriented vision where AI-driven mental health support evolves from passive response to proactive prevention, ultimately functioning as a lifelong “Psychological Radar” and promoting absolute inclusivity in mental health education resources. The findings aim to provide practical references for grassroots mental health service institutions, relevant enterprises, and social organizations, promoting the deep integration of AI technology with mental health services and contributing to the development of a more psychologically resilient society.