Integracja sztucznej inteligencji w praktyce pielęgniarskiej: rozwój i ocena kliniczna modelu opieki NURSYA opartego na zasadach zachowania Levine'a

BACKGROUND: Although artificial intelligence (AI) is increasingly used in healthcare, its integration with established 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 improvements 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 patient-centered nursing practice, although patient-level outcomes require further investigation.