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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

NCT07263724 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 30

Last updated 2026-04-02

No results posted yet for this study

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.

Conditions

  • Coronary Artery Bypass Graft Surgery (CABG)
  • Patient Education

Sponsors & Collaborators

  • Hasan Kalyoncu University

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-07-01
Primary Completion
2027-06-01
Completion
2027-12-01

Countries

  • Turkey (Türkiye)

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07263724 on ClinicalTrials.gov