The impact of AI usage, literacy and proactive innovation behavior on scholars' mental health

Abstract

Purpose This study investigates the multifaceted impact of generative artificial intelligence (GenAI) usage on scholars' mental health. It examines the mediating role of proactive innovation behavior (PIB) and the moderating impact of artificial intelligence (AI) literacy, focusing on how AI usage intensity and diversity relate to anxiety, stress and depression. Design/methodology/approach The study analyzes survey data collected from 586 Chinese academic scholars. Structural Equation Modeling methods were employed to test the direct relationships between AI usage dimensions and mental health outcomes, the mediating effect of PIB and the moderating effect of AI literacy on these relationships. Findings AI usage intensity is negatively associated with anxiety and stress, while greater AI tools diversity predicts lower depression. Both usage intensity and diversity foster PIB, which mediates the relationship with reduced anxiety, stress and depression. AI literacy moderates these links, strengthening the direct mental health benefits of intensity but weakening the intensity-PIB link and the adverse effects of diversity on anxiety/depression. Originality/value The study highlights the complex interplay between AI engagement dimensions, scholars' innovative behaviors and AI proficiency concerning mental health. It contributes a nuanced understanding to the technology and mental health literature regarding AI integration in academia, offering theoretical insights into innovation's mediating role and digital literacy's conditional effect.

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