IJSEA Volume 15 Issue 8

Analysis and Implementation Path of Comprehensive Intervention for Anxiety and Academic Stress Among Vocational College Students

Yan Haisheng
10.7753/IJSEA1508.1005
keywords : vocational college students; anxiety; academic stress; comprehensive intervention; implementation path

PDF
As a vital group within the higher education system, vocational college students suffer from dual disturbances of academic stress and anxiety, whose mental health has attracted growing academic and social attention. Against the backdrop of the new media era, this paper systematically sorts out the current characteristics and contributing factors of anxiety and academic stress among vocational college students, and further explores the interaction mechanisms between academic stress, psychological resilience, self-efficacy, sleep quality and anxiety. The research reveals that academic stress of vocational college students mainly stems from curriculum learning, skill assessments, employment competition and miscellaneous daily stressors. There exists a significantly positive correlation between anxiety and academic stress, with psychological resilience acting as a critical moderator, while self-efficacy and sleep quality serve as key mediating variables. On this basis, this study constructs a comprehensive intervention strategy system from four dimensions: individual cognitive restructuring, institutional systematic support, collaborative social education and new media empowerment, and proposes a three-level implementation framework of "Prevention–Early Warning–Intervention". It intends to provide theoretical references and practical guidance for mental health education of vocational college students in the new era.
@artical{y1582026ijsea15081005,
Title = "Analysis and Implementation Path of Comprehensive Intervention for Anxiety and Academic Stress Among Vocational College Students ",
Journal ="International Journal of Science and Engineering Applications (IJSEA)",
Volume = "15",
Issue ="8",
Pages ="19 - 23",
Year = "2026",
Authors ="Yan Haisheng "}