Clinical trial NCT06863792: ChatGPT-Assisted Hypertension Knowledge in Nursing Students
Official title: ChatGPT-Assisted Hypertension Knowledge in Nursing Students: Assessment of Accuracy, AI Anxiety, and Cognitive Load
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Nursing Students
Artificial Intelligence
Hypertension
Keywords: nursing students
artificial intelligence
Hypertension
nursing education
Lead sponsor: Ankara University
Sponsor class: OTHER
First posted: 2025-03-07
Enrollment: 96
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Students will be randomly assigned to the intervention (ChatGPT) and control groups in a 1:1 allocation ratio. Group assignments will be determined using a computer-based randomization table, with 48 students in the intervention group and 48 in the control group, placed in separate classrooms. Students in the intervention group will answer the questions from the Hypertension Prevention Attitude Scale using ChatGPT, while those in the control group will respond using traditional methods.
Primary purpose: OTHER

Brief summary: 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.

Detailed description: 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.

Eligibility criteria: Inclusion Criteria:

* 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.

Exclusion Criteria:

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

Primary outcomes:
measure: Hypertension Prevention Attitudes Scale
timeFrame: At the beginning of the study first admission.
measure: Artificial Intelligence Anxiety Scale
timeFrame: Immediately after the intervention (answering the scale questions)
measure: Cognitive Load Scale
timeFrame: Immediately after the intervention (answering the scale questions)
Secondary outcomes:
Other outcomes:
Locations:
Study officials:
affiliation: Ankara University
name: Nursemin UNAL, Assoc. Prof.
role: PRINCIPAL_INVESTIGATOR
References:
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citation: 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.
citation: 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.
citation: 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