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

Inclusion Criteria: * Patient scenarios representing individuals who have undergone coronary artery bypass graft (CABG) surgery. * Scenarios that include demographic, socioeconomic, clinical, and psychosocial information consistent with current literature and clinical guidelines. * Scenarios describing patients who underwent median sternotomy and on-pump CABG procedure. * Scenarios that include relevant postoperative complications (e.g., delirium, bleeding, wound infection, arrhythmia) and comorbidities (e.g., diabetes, hypertension, COPD). * Scenarios that enable both nurse and ChatGPT-5 to prepare discharge education materials under the same standardized framework. * Scenarios reviewed and validated by cardiovascular surgery experts and nurse academicians for content validity. Exclusion Criteria: * Patient scenarios not related to coronary artery bypass graft (CABG) surgery. * Scenarios lacking sufficient demographic, clinical, or psychosocial information to prepare individualized discharge education. * Scenarios that do not follow the standardized structure of six main domains and twenty-four subtopics. * Scenarios with inconsistent or contradictory medical data (e.g., incompatible diagnosis and treatment details). * Scenarios not validated by the expert review panel for clinical accuracy and content validity. * Scenarios that do not allow comparison between nurse-generated and ChatGPT-5-generated discharge education materials.