The mediation of trust on artificial intelligence anxiety and continuous adoption of artificial intelligence technology among primacy nurses: a cross-sectional study
Qi Zhou, Lili Yang, Yue Tang, Jiekai Yang, Wanting Zhou, Wenqing Guan, Lihui Yan, Yutong Liu
Abstract
BACKGROUND: AI learning anxiety and job substitution anxiety hinder the use of AI in healthcare. Primary nurses lack training resources, a strong sense of substitution risk, and weak organizational support. Trust is the key to solving AI anxiety and using AI among primary nurses. Therefore, this study aimed to validate the mediating role of AI trust between AI anxiety and the continuous adoption of artificial intelligence technology. METHODS: This study was a cross-sectional survey, using purposive sampling to select 550 nurses. Measurement tools included a demographic information questionnaire, an AI trust scale, an organizational trust scale, an artificial intelligence anxiety scale, and continuous adoption of an artificial intelligence technology scale. RESULTS: Organizational trust and AI trust mediate AI anxiety and continuous adoption of artificial intelligence technology. CONCLUSION: Primary institutions should enhance AI education and training to alleviate learning anxiety, optimize the human-computer collaboration process to diminish nurses' feelings of substitution, and bolster nurses' AI and organizational trust by fostering organizational support and technological transparency, increasing their willingness to maintain adoption.