How Successful Is AI in Developing Postsurgical Wound Care Education Material?
Journal:
Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society
PMID:
40357563
Abstract
ChatGPT can be used as an aid in education, research and clinical management. This study was conducted using the ChatGPT 4.0 program to develop artificial intelligence-supported wound care education material that can be read and understood by patients discharged after surgery. In this methodological study, while creating wound care education material, the education needs of the patients were determined first. Then, the education content was created in the ChatGPT 4 program. Expert opinion was taken for the clarity, applicability, accuracy and quality of the education content. The Turkish readability index of the education material was found to be 68.9 and easily understandable. The Automated Readability Index was found to be 9.29, the Simple Measure of Gobbledygook 7.89, the Flesch-Kincaid 8.07, the Flesch Reading Ease 59.0 and the Average Reading Level Consensus 9.99, which are frequently used in health literature. The PEMAT understandability and applicability score averages were determined 93.90 ± 6.11 (84-100) and 90.20 ± 8.66, respectively. The Global Quality Scale score average was found to be 4.40 ± 0.69. This study reveals that ChatGPT provides understandable, applicable, accurate and high-quality postoperative wound care education material.