Abstract Although generative AI tools are increasingly used in college students’ academic activities, their role in stress-related maladaptive coping remains unclear. This study focuses specifically on maladaptive AI dependence as a potential mediator linking academic stress to academic burnout and anxiety. A total of 1,623 college students completed an online survey using the Academic Stress Scale, the AI Dependence Scale, the General Self-Efficacy Scale, the Academic Burnout Scale, and the GAD-7. PROCESS Model 6 was used to examine direct, indirect, and sequential mediation effects separately for academic burnout and anxiety. The results showed that academic stress positively predicted both academic burnout and anxiety. Sequential mediation analyses revealed that academic stress was associated with increased AI dependence, which may reduce students’ mastery experiences and encourage reliance on external support, thereby undermining self-efficacy and ultimately contributing to higher levels of burnout and anxiety. These findings suggest that excessive reliance on AI as a stress-coping strategy may weaken students’ sense of competence and increase their vulnerability to academic burnout and anxiety. Educational interventions should therefore promote reflective and autonomy-supportive AI use, positioning AI as a learning scaffold rather than a substitute for students’ own cognitive engagement.
Wang et al. (Sat,) studied this question.