Use of Artificial Intelligence in Planning Postoperative Nursing Care in Laparoscopic Cholecystectomy Patients: Comparison of ChatGPT and Student Practice

Abstract

Aim: This study aims to compare student-generated nursing care plans with ChatGPT-generated care planning texts for patients undergoing laparoscopic cholecystectomy surgery. Background: Given the increasing significance of technology in nursing education, the integration of AI-driven tools into educational methodologies demonstrates potential for enhancing nursing students' preparation for clinical practice by providing access to more comprehensive and current information sources. Methods: This descriptive comparative study evaluated 14 nursing care plans developed by nursing students for laparoscopic cholecystectomy patients alongside care plans generated by ChatGPT for identical patient scenarios, using the DISCERN scale as the assessment instrument. Results: The quality of student-generated care plans was determined to be satisfactory, whereas the quality of ChatGPT-generated texts was assessed as moderate. Both student care plans and ChatGPT-generated texts demonstrated moderate reliability and information quality regarding nursing care. Students exhibited the highest accuracy rate in formulating correct nursing diagnoses (90.22 %), while ChatGPT-generated texts demonstrated superior performance in correctly establishing nursing goals (90.35 %) and developing appropriate nursing interventions (91.07 %). Conclusions: The findings indicate that while student-generated care plans demonstrated generally acceptable quality, ChatGPT's performance in this domain was moderate, particularly in formulating surgical nursing goals and interventions. Although clinical outcomes were not evaluated in this study, the results suggest that ChatGPT may serve as a valuable supplementary resource for surgical nursing education and care plan development. Further research is warranted to determine its impact on patient care quality and clinical effectiveness.