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

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.

NCT Number	NCT07263724
Lead Sponsor	Hasan Kalyoncu University
Conditions	Coronary Artery Bypass Graft Surgery (CABG), Patient Education
Enrollment	30 participants
Start Date	2026-07-01
Primary Completion	2027-06-01 (estimated)
Study Completion	2027-12-01 (estimated)
Updated on ClinicalTrials.gov	2026-04-02