Abstract
Background:
The research on ChatGPT-generated nursing care planning texts is critical for enhancing nursing education through innovative and accessible learning methods, improving reliability and quality.
Purpose:
The aim of the study was to examine the quality, authenticity, and reliability of the nursing care planning texts produced using ChatGPT.
Methods:
The study sample comprised 40 texts generated by ChatGPT selected nursing diagnoses that were included in NANDA 2021-2023. The texts were evaluated by using a descriptive criteria form and the DISCERN tool to evaluate health information.
Results:
DISCERN total average score of the texts was 45.93 ± 4.72. All texts had a moderate level of reliability and 97.5% of them provided moderate quality subscale score of information. A statistically significant relationship was found among the number of accessible references, reliability (r = 0.408), and quality subscale score (r = 0.379) of the texts (P < .05).
Conclusion:
ChatGPT-generated texts exhibited moderate reliability, quality of nursing care information, and overall quality despite low similarity rates.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Subject
Review and Exam Preparation,LPN and LVN,Fundamentals and skills,Education
Reference26 articles.
1. Müşteri Hizmetleri Yönetiminde Yapay Zeka Temelli Chatbot Geliştirilmesi;işeri;EJOSAT,2021
2. ChatGPT and other large language models are double-edged swords;Shen;Radiology,2023
3. Comparing scientific abstracts generated by ChatGPT to original abstracts using an artificial intelligence output detector, plagiarism detector, and blinded human reviewers;Gao;Biorxiv,2023
4. ChatGPT is fun, but not an author;Thorp;Science,2023
5. ChatGPT: evolution or revolution?;Gordijn;Med Health Care Philos,2023
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献