Integrating artificial intelligence into nursing practice: Development and clinical evaluation of the NURSYA care model based on Levine's Conservation Principles

Abstract

Background: Although artificial intelligence (AI) is increasingly used in healthcare, its integration with estab lished nursing theories remains limited. Levine's Conservation Model provides a holistic framework for nursing care, yet its routine application can be challenging without structured decision support. Purpose: This study aimed to develop and evaluate NURSYA, a theory-based AI-supported nursing care system grounded in Levine's Conservation Model, and to examine changes in nursing outcomes following its implementation. Methods: A single-group pre-post intervention study was conducted with 300 nurses working in diverse clinical settings in Türkiye. Nurses used NURSYA for three months. Data were collected using a nursing model evaluation scale assessing planning, implementation, evaluation, and usability. Paired t-tests and effect size analyses were performed. Results: Perceived effectiveness scores increased significantly after implementation (p < 0.001), with improve ments observed across all domains. The evaluation scale showed high internal consistency (Cronbach's α = 0.92). Conclusion: NURSYA was associated with significant improvements in nurses' perceived effectiveness in care planning and clinical decision-making. Theory-based AI systems may support evidence-based and patientcentered nursing practice, although patient-level outcomes require further investigation.