Integrating artificial intelligence into nursing practice: Development and clinical evaluation of the NURSYA care model based on Levine's Conservation Principles
Year: 2026
Type: article
Study design: Clinical Trial
Abstract: 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. 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. 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. 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). 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. • A theory-based AI nursing care model grounded in Levine's Conservation Model was developed. • NURSYA significantly improved nurses' care planning and clinical decision-making. • Overall effectiveness of nursing care improved significantly after NURSYA implementation. • High usability and reliability supported the clinical applicability of NURSYA.
Source: Applied Nursing Research
Authors: Şeyda Öztuna, Cihangir Işık
Institutions: Balıkesir University, Balıkesir Atatürk City Hospital
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,690
OpenAlex ID: W7135397111