Exploring Nurses’ Perspectives on the Use of Artificial Intelligence Chatbots for Mental Health Support: A Cross-Sectional Study in Greece

Background/Objectives: Artificial intelligence (AI) has transformed healthcare delivery by revolutionizing the offering opportunities in prognosis, diagnosis, personalized treatment, and improving patient outcomes. However, little is known about the nurses’ attitudes toward the integration of AI-driven conversational technology and AI chatbots into clinical practice. The aim of our study was to investigate nurses’ attitudes regarding the use of AI chatbots as a tool for mental health support. Additionally, the study aimed to evaluate their levels of acceptance and fear toward AI, while examining the influence of demographic variables on these attitudes. Methods: A cross-sectional study was conducted. We employed the Artificial Intelligence in Mental Health Scale (AIMHS) to measure attitudes toward the use of AI-powered chatbots for mental health support. Additionally, we utilized the Attitudes Towards Artificial Intelligence Scale (ATAI) to assess nurses’ levels of acceptance and fear regarding artificial intelligence. Results: Technical advantages score in the AIMHS reflected low positive attitudes toward the technical aspect of AI chatbots for mental health support, while personal advantages score showed moderate positive attitudes toward the personal aspect of chatbots. ATAI scores indicated a moderate level of acceptance and fear toward AI. Results from multivariable analysis showed that increased age (b = 0.011, p-value = 0.018) and increased daily engagement with social media and websites (b = 0.058, p-value = 0.002) were significantly associated with more favorable technical attitudes towards AI-based mental health chatbots. Also, male nurses exhibited significantly more favorable attitudes toward AI-based mental health chatbots in terms of perceived personal benefits (b = 0.548, p-value < 0.001). Higher levels of digital technology competence were significantly associated with greater acceptance of artificial intelligence (b = 0.164, p = 0.032). Additionally, male nurses reported significantly higher acceptance of AI compared to their female counterparts (b = 1.587, p < 0.001). We found that lower financial status was significantly associated with heightened fear of AI (b = −0.329, p < 0.001). Conclusions: Nurses generally held moderately positive attitudes toward both AI-based mental health chatbots and AI more broadly. Several demographic factors were found to significantly influence these attitudes.