Augmented clinician and black box paradox AI in clinical decision-making: A qualitative study of nursing students and clinical nurses.

AIM: To explore the experiences of clinical nurses and nursing students in using artificial intelligence (AI) within clinical decision-making processes. BACKGROUND: AI holds significant promise for shaping clinical decision‑making processes in nursing practice. However, our understanding remains limited regarding how practicing clinical nurses and nursing students on clinical placements engage with AI systems and how they incorporate these tools into their professional decision‑making. DESIGN: Qualitative descriptive study. METHODS: The study was conducted at a public hospital with nurses working in the clinics and nursing students completing their clinical rotations in the same clinics. Face-to-face, semi-structured interviews were conducted with 10 clinical nurses and 10 nursing students. Their professional experience ranges from 1.5 to 10 years. The students' grade levels range from 3rd to 4th grade. Data were analyzed using thematic analysis and the study was reported in accordance with the Standards for Reporting Qualitative Research. RESULTS: The study revealed four themes: (I) Augmented Clinician, (II) Catalysts in Clinical Decision-Making, (III) Cultivating AI Literacy and (IV) Black Box Paradox. In addition, drawing on the Technology Acceptance Model, Benner's Novice-to-Expert Model and Tanner's Clinical Judgement Model, the study assessed how nurses and students evaluate AI. CONCLUSIONS: The findings indicate that nurses and nursing students perceive AI as a potentially useful tool in clinical decision-making and patient care processes. However, ethical concerns, the possibility of misinformation and the need for safe use highlight the importance of education, institutional support and appropriate protocols to promote the responsible use of AI in nursing practice.