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- MakaleYalnız künye2026Integrating Artificial Intelligence Into Nursing Care Planning: A Comparative Evaluation of Psychosocial Care for Patients With a Stoma
Kulakaç, Nurşen; Tuncer, Metin
This methodological study evaluated and compared the content quality and appropriateness of nursing care plans developed by nurses and artificial intelligence (AI) for addressing the psychosocial problems of patients with stomas. Two nursing care plans addressing the psychosocial needs of a patient with a stoma were developed: 1 generated by nurses and 1 generated by an AI system. The content quality and appropriateness of the care plans were independently evaluated by 12 experts, including nursing academics and clinical nurses, using the DISCERN measurement tool. Inter-rater reliability was assessed using the intraclass correlation coefficient (ICC). The mean DISCERN score of the nurse-generated care plan was significantly higher than that of the AI-generated care plan (P=.008). Inter-rater agreement demonstrated good agreement. The findings indicate that nurse-generated care plans demonstrate superior content quality and overall integrity compared to AI-generated plans. AI-generated care plans exhibit potential as supportive tools in nursing care planning.
- MakaleYalnız künye2024The data analysis of the functional health patterns model for nursing care plans
Aydin, Aydanur; Serpici, Ayse; Simsek, Perihan; Gürsoy, Ayla; Çilingir, Dilek; Yavuz, Melek Erturk; Altinbas, Bahar Candas
Introduction:Clinical practices constitute an important part of nursing education and students are expected to gain the ability to plan patient care during nursing education.Aim:It aimed to construct North American Nursing Diagnosis Association (NANDA) nursing diagnoses in nursing students' patient care plans according to the Functional Health Patterns model and to evaluate them according to the Nursing Intervention Classification (NIC) and Nursing Outcomes Classification (NOC) classification systems.Methods:The descriptive study's population included 198 second-year nursing students from a university. Students' care plans were used as a data gathering form, and 176 care plans were included in the research. The data was gathered from functional health patterns, NIC, and NOC system questionnaires.Results:Nursing diagnoses were listed as infection risk (88.6%), fall risk (79.5%), and bleeding (56.8%). Nursing diagnoses belonging to sexuality-reproductive, coping-stress tolerance, and value-belief sub-categories of functional health patterns could not be reached from the care plans.Conclusion:There is a need for classification methods to objectively evaluate nursing practices, make quantifiable contributions to care, and improve the profession's scientific underpinnings. It is hoped that evidence-based care can be provided by raising pupils' knowledge of classification systems.