Artificial Intelligence in Mental Health Nursing: A Bibliometric Analysis of Research Trends, Knowledge Structures and Emerging Themes.

INTRODUCTION: Artificial intelligence technologies are increasingly transforming mental healthcare through predictive analytics, language-based systems and digital innovations. Mental health nurses play a central role in implementing and evaluating these technologies. AIM/QUESTION: This bibliometric review aimed to analyse publication trends, knowledge structures, influential contributions and emerging themes in artificial intelligence research within mental health nursing. METHOD: A comprehensive search of the Scopus database was conducted in May 2026. After eligibility screening following the PRISMA 2020 reporting framework, 141 English-language articles and reviews published between 2018 and 2026 were included. Bibliometric mapping and keyword co-occurrence analyses were performed using VOSviewer. RESULTS: Publication output increased substantially after 2023, with 72.3% of studies published in 2025-2026. The United States, China and Türkiye were the most productive countries. Five thematic clusters emerged: prediction and risk assessment, nursing education and simulation, nurses' attitudes and workforce impact, generative artificial intelligence applications and ethical-professional issues in mental health nursing. DISCUSSION: Findings indicate a transition from traditional predictive modelling toward implementation-focused, generative artificial intelligence and ethically informed research. IMPLICATIONS FOR PRACTICE: Mental health nurses require enhanced artificial intelligence literacy, critical appraisal skills and ethical competencies to support safe implementation. RECOMMENDATIONS: Future research should evaluate clinical effectiveness, implementation outcomes, cross-cultural validation, international collaboration and ethical governance of artificial intelligence technologies in mental health nursing.