ChatGPT-Assisted Hypertension Knowledge in Nursing Students

Официальное название

ChatGPT-Assisted Hypertension Knowledge in Nursing Students: Assessment of Accuracy, AI Anxiety, and Cognitive Load

Обзор

ChatGPT provides quick access to information, research support, and study materials, but concerns remain regarding its reliability, accuracy, and inability to offer personalized care principles essential in nursing. Although previous studies show its high accuracy in clinical responses, over-reliance on AI-generated medical information necessitates cautious use. The study will explore both the benefits and limitations of ChatGPT in nursing education, particularly in hypertension learning.

Подробное описание

The use of artificial intelligence (AI) tools in education is increasing rapidly. ChatGPT, developed by OpenAI, is an AI-based chatbot that provides an interactive learning environment. It generates fluent and knowledge-based responses based on books, online sources, and articles published until 2021. The widespread adoption of ChatGPT across various fields has sparked debates about its role and limitations. In nursing education, students frequently use ChatGPT for quick access to information, research support, and exam preparation. However, concerns regarding its reliability arise due to the unknown sources of its responses and the potential for misinformation. ChatGPT also has limitations in interpreting complex, context-dependent answers and lacks the ability to apply the principle of individualized care, which is fundamental in nursing practice.

Studies have demonstrated ChatGPT's varying performance in the healthcare field. Hypertension, a chronic disease affecting over a billion people worldwide, is a critical topic for nursing students, as their understanding of the condition can positively impact patient care. Previous research has shown that ChatGPT provides clinically appropriate answers to hypertension-related questions with a high accuracy rate of 92.5%. Additionally, the GPT-4 version of ChatGPT correctly answered over 86% of the questions in the United States Medical Licensing Examination (USMLE).

This randomized controlled study aims to assess the effectiveness of ChatGPT in teaching hypertension to nursing students while also evaluating their levels of AI-related anxiety and cognitive load. Given the increasing presence of AI tools in education, understanding both their advantages and limitations is crucial for their optimal integration into nursing education.

The study population consists of students enrolled in the nursing program at a private university. The study aims to reach the entire population, specifically 96 students who have completed the Internal Medicine Nursing course. Students meeting the inclusion criteria will be informed about the study and invited to participate. Volunteers will complete an Introductory Information Form and be randomly assigned to intervention (ChatGPT) or control groups in a 1:1 ratio using computer-based randomization (48 students per group). The intervention group will answer questions from the Hypertension Prevention Attitude Scale using ChatGPT, while the control group will use traditional methods. Afterward, both groups will complete the Artificial Intelligence Anxiety Scale and Cognitive Load Scale, concluding data collection. All collected data will be analyzed using the SPSS for Windows 22.0 statistical software package.

Вмешательства

• Другое ChatGPT
  Students in the intervention group will answer the questions from the Hypertension Prevention Attitude Scale using ChatGPT.

Первичные конечные точки

• Hypertension Prevention Attitudes Scale [Срок оценки: At the beginning of the study first admission.]
• Artificial Intelligence Anxiety Scale [Срок оценки: Immediately after the intervention (answering the scale questions)]
• Cognitive Load Scale [Срок оценки: Immediately after the intervention (answering the scale questions)]

Критерии участия

Критерии включения

• To be enrolled in the nursing program at a private university, during the 2024-2025 academic year.
• To have taken the Internal Medicine Nursing course (In this course, students receive 4 hours of theoretical lessons on nursing care for hypertension patients).
• To be willing to volunteer for participation in the study.

Критерии исключения

• Students who wish to withdraw from the research at any stage will not be included in the study.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Да

Дизайн исследования

Распределение

Рандомизированное

Модель

Параллельные группы

Маскирование

Простое слепое

Основная цель

Другое

Центры проведения

Список центров уточняется — проверьте первичный протокол.

Публикации

• Alkhaqani, A. L. (2023). Can ChatGPT help researchers with scientific research writing. Journal of Medical Research and Reviews, 1(1), 9-12. https://doi.org/10.5455/JMRR.20230626013424
• Branum C, Schiavenato M. Can ChatGPT Accurately Answer a PICOT Question? Assessing AI Response to a Clinical Question. Nurse Educ. 2023 Sep-Oct 01;48(5):231-233. doi: 10.1097/NNE.0000000000001436. Epub 2023 Apr 28. PMID 37130197
• Abdulai AF, Hung L. Will ChatGPT undermine ethical values in nursing education, research, and practice? Nurs Inq. 2023 Jul;30(3):e12556. doi: 10.1111/nin.12556. Epub 2023 Apr 26. No abstract available. PMID 37101311
• Goktas, P., Kucukkaya, A., & Karacay, P. (2024). Utilizing GPT 4.0 with prompt learning in nursing education: A case study approach based on Benner's theory. Teaching and Learning in Nursing, 19(2), e358-e367.
• Sallam M. ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns. Healthcare (Basel). 2023 Mar 19;11(6):887. doi: 10.3390/healthcare11060887. PMID 36981544
• Wang, Y. Y. & Wang, Y. S. (2019). Development and validation of an artificial intelligence anxiety scale: an initial application in predicting motivated learning behavior. Interactive Learning Environments, 1-16. https://doi.org/10.1080/10494820.2019.1674887

Идентификаторы

NCT: NCT06863792 · 2025-2

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

Открыть это исследование на ClinicalTrials.gov ↗