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The rapid advancement of artificial intelligence (AI) technologies in language services, education, and knowledge production has imposed substantial occupational displacement pressures on English majors, thereby triggering significant AI-related anxiety. However, existing research rarely systematically explores the formation mechanisms of AI anxiety among English majors, especially lacking an in-depth analysis of the protective role of career adapt-abilities and their internal heterogeneity. This study adopts a dual-perspective approach-integrating variable-centered and person-centered analyses-to investigate how career adapt-abilities influence AI anxiety and the mediating role of core self-evaluations. A total of 444 English major students from four comprehensive universities in Sichuan, China, were recruited during July and August 2025. Measurements included the Career Adapt-Abilities Scale, Core Self-Evaluation Scale, and AI Anxiety Scale. Results show that career adapt-abilities significantly and negatively predict AI anxiety, with core self-evaluations partially mediating this relationship. Latent profile analysis identified three distinct career adapt-abilities subgroups-low, medium, and high-with significant differences in core self-evaluations and AI anxiety levels among them. Notably, the low career adapt-abilities group exhibited the highest AI anxiety, while the high group showed the lowest. Both analytic strategies converge to demonstrate that career adapt-abilities constitute an essential psychological resource mitigating AI anxiety in English majors, with core self-evaluations serving as a key cognitive mechanism. This study reveals a dual-pathway influence of career adapt-abilities on AI anxiety, offering a novel theoretical framework for understanding technological anxiety formation. Moreover, the pronounced heterogeneity of career adapt-abilities underscores the necessity for stratified career development education and psychological interventions tailored to diverse student groups, providing practical guidance for optimizing talent cultivation in English major programs.
X. Christine Wang (Fri,) studied this question.