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Determining the Consistency Between Nurses and Artificial Intelligence (ChatGPT-5) in Delivering Scenario-Based Discharge Education to Coronary Artery Bypass Graft Patients: A Methodological Study
Sponsor: Hasan Kalyoncu University
Summary
This methodological study aims to determine the level of agreement between nurses and an artificial intelligence system (ChatGPT-4.0) in providing scenario-based discharge education for patients who have undergone coronary artery bypass graft (CABG) surgery. Thirty standardized patient scenarios representing different demographic, clinical, and psychosocial characteristics will be used. For each scenario, both expert nurses and ChatGPT-4.0 will prepare discharge education content based on six main domains and twenty-four subtopics identified from the literature and clinical guidelines. The educational materials will be independently evaluated by two blinded reviewers in terms of content accuracy, completeness, scientific consistency, and clarity of language. Agreement between nurses and AI-generated content will be analyzed using Cohen's Kappa coefficient and Fisher's Exact Test. The findings are expected to provide evidence for the reliability and applicability of AI-assisted discharge education systems in cardiac surgery nursing practice.
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
30
Start Date
2026-07-01
Completion Date
2027-12-01
Last Updated
2026-04-02
Healthy Volunteers
Yes
Locations (1)
Hasan Kalyoncu University Faculty of Nursing
Gaziantep, Gaziantep, Turkey (Türkiye)