Nurse Educ. 2023 Nov 22. doi: 10.1097/NNE.0000000000001566. Online ahead of print.
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.
PMID:37994523 | DOI:10.1097/NNE.0000000000001566
