Adoption of artificial intelligence–based precision mental health technologies among psychology trainees: mixed methods cross-sectional survey study

Abstract

Despite the significant benefits of artificial intelligence (AI) in mental health, real-world implementation remains limited, making it essential to understand the factors that influence adoption. Findings suggest a layered framework that may inform future implementation research and training program design, addressing (1) predisposing dispositional and emotional profiles; (2) precipitating fear and perceived risk via transparent regulation, explainable design, and policies that strengthen professional agency; and (3) maintenance through high-quality early experiences, usability, and sustained institutional support. This theory-guided model clarifies how psychological, contextual, and experiential factors jointly shape adoption and sustained use of AI-PMHTs among psychologists in training, informing targeted educational and implementation strategies for this population.