The Effect of Artificial Intelligence-Supported Intramuscular and Subcutaneous Injection Training on Nursing Students

Официальное название

The Effect of Artificial Intelligence-Supported Intramuscular and Subcutaneous Injection Training on Knowledge, Reasoning, and Skill Development in Nursing Students: A Quasi-Experimental Study

Обзор

The complexity of healthcare services and technological advances today have necessitated the adoption of innovative approaches in nursing education. Among these innovative approaches, artificial intelligence (AI) has established itself as a technology that is increasingly present in nursing education processes, offering a supportive, personalized, and interactive learning experience. AI's contributions to nursing students' acquisition of fundamental competencies such as clinical decision-making, skill development, and critical thinking are rapidly increasing. Especially in high-risk, invasive, and clinically skill-intensive applications, AI-supported educational models both enhance learning quality and support patient safety. Intramuscular and subcutaneous injections are among the basic invasive skills that nursing students must learn. These applications require a high level of cognitive and psychomotor competence from students. Incorrect injection practices can lead to complications such as drug absorption problems, nerve damage, hematoma, or infection, making it critically important to teach these skills correctly and safely. In this context, AI-supported education systems stand out as an effective tool for teaching injection skills. Artificial intelligence-based chatbots provide students with both theoretical knowledge and practical guidance. For example, before injecting a muscle group, a student can learn about the anatomy of the muscle, determine the correct angle, and remember precautions against potential complications through the chatbot. Artificial intelligence also reinforces the learning process by instantly answering students' questions, preventing the acquisition of incorrect information. Recent studies emphasize that AI-supported learning tools positively influence students' attitudes toward learning, increasing their motivation and academic satisfaction levels. Accordingly, the integration of AI-based technologies in the process of training future nurses is no longer an option but a necessity. Particularly in complex and delicate skills such as intramuscular and subcutaneous injections, AI-supported chatbots can facilitate student learning, increase skill accuracy, and support clinical safety. Therefore, it is crucial for nursing education programs to combine artificial intelligence technologies with pedagogical foundations to provide student-centered, safe, and effective learning environments.

Подробное описание

A comprehensive review on the use of AI in nursing education has revealed that publications in this field have rapidly increased since 2021 and that chatbots have transformative effects in enriching the learning experience. These studies indicate that AI-based learning tools are still in the early stages of development but offer significant contributions in providing active and personalized support in learning processes. AI-supported chatbots can contribute in various ways to skill-based topics such as IM and SC injection training. For example, a chatbot-based digital instructor can have the student repeat the steps of the injection step by step through questions and provide immediate feedback on correct or incorrect actions. When the student types questions such as "What should the needle length be when injecting into the deltoid region?" in the chat window, the chatbot can quickly provide information, ensuring uninterrupted learning. Another strength of AI is that it can be used as intelligent educational systems. These systems can detect errors made by the student during the application, analyze whether they have selected the correct injection site, and offer suggestions to fill in any gaps in theoretical knowledge. One of the important advantages of chatbot-supported teaching is that it provides accessibility and continuity. Students can continue learning by interacting with the chatbot even when they are outside the classroom or laboratory. For example, they can get answers to their questions or have the injection steps repeated aloud while studying individually during free time outside of school. This makes learning independent of time and place. In application-based skills such as IM and SC injections, AI and chatbots do not completely replace traditional education; however, they enhance it as a complementary and supportive learning component. For example, after receiving practical training from an instructor in class, a student can take a mini knowledge test with a chatbot at home, repeat the application steps, and analyze their weak points. Chatbot systems can analyze students' learning data (frequent mistakes, repeated questions, learning time, etc.) and provide digital feedback to the instructor. This data enables the individualization of teaching programs, the repetition of topics, and the more accurate identification of students' learning needs. For example, a student who wants to remember the steps of an IM injection can visualize the process by asking questions such as "Where is the deltoid region located?" or "Is aspiration necessary?" via a chatbot. This type of technological support offers opportunities for individualized learning, especially in crowded classrooms. In this context, AI-powered education supported by chatbots is poised to play a critical role in the future of IM and SC injection teaching in nursing. Initial findings show that these technologies increase students' self-confidence, boost learning motivation, and support retention. This study aims to use an AI-based chatbot system to teach students critical topics in IM and SC injection practices, such as infection control, anatomical site selection, proper injection technique, and complication management, through a structured and interactive scenario flow. Thus, both students' knowledge level will increase and the mental preparation process prior to psychomotor skills will be supported through virtual repetitions. At the same time, the 24/7 availability of the chatbot will allow students to progress at a pace suitable for their individual learning speeds. This will meet the need for "learner-centered individualized education," which is lacking in traditional methods.

The use of AI-based chatbot systems in nursing education, particularly in skills training, is relatively new, and studies in this area are limited. Although there are findings in the international literature that chatbots may be effective in teaching certain theoretical topics in nursing education, scientific data on the use of AI-based chatbots in the teaching of direct nursing skills (e.g., injection) is quite limited. In Turkey, there are no original studies investigating the use of AI-based chatbots in teaching basic practical skills such as injections to nursing students. The strength and originality of this study lies in the fact that AI-based chatbot systems have not yet been used in IM and SC injection training, which is very important in nursing education, in the national and international literature.

Вмешательства

• Устройство Training of IM and SC injection skills via Chatbot
  The chatbot software to be used in this study will operate through the API service of ChatGPT, a generative artificial intelligence language model developed by OpenAI. The chatbot will be designed to support nursing students' theoretical knowledge, reasoning, and practical skills in intramuscular and subcutaneous injection training. The chatbot will be specifically fed with scientific content, teaching materials, and documents provided by faculty members related to injection practices; consiste

Первичные конечные точки

• Objective Structured Clinical Examination score [Срок оценки: A week after IM and SC injections training in control group; a week and a month after IM and SC training in study group]
• Clinically Oriented Reasoning Exam score [Срок оценки: A week after IM and SC injections training in control group; a week and a month after IM and SC training in study group]
• Subcutaneous and Intramuscular Injection Theoretical Knowledge Pre-Test [Срок оценки: Before IM and SC injections training in control and study groups.]
• Subcutaneous and Intramuscular Injection Theoretical Knowledge Post-Test [Срок оценки: A week after IM and SC injections training in control and study groups; a month after IM and SC training in only study group.]
• Productive Artificial Intelligence Usage and Competence Scale Score [Срок оценки: A month after IM and SC injections training in only study group.]

Критерии участия

Критерии включения

• Being a first-year nursing student,
• Taking the Fundamentals of Nursing-I course for the first time,
• Encountering the topic of intramuscular and subcutaneous injections for the first time,
• Agreeing to participate in the research voluntarily and willingly,
• Having a smart device and internet access to use the chatbot application regularly,
• Committing to participate in the research process at least 80% of the time (ensuring at least 2 uses per week for 4 weeks)

Критерии исключения

• Having previously taken the Fundamentals of Nursing-I course or having received formal training in injection techniques
• Being unable to participate in theoretical or practical training during the research process
• Being unable to continue interactions with the chatbot for technical reasons
• Incomplete research data or being unable to complete the pre-test/post-test process .

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

Здоровые добровольцы: Да

Дизайн исследования

Распределение

Нерандомизированное

Модель

Параллельные группы

Маскирование

Двойное слепое

Основная цель

Организация здравоохранения

Центры проведения

Turkey (Türkiye) · 1 центр

• Akdeniz University — Antalya

Идентификаторы

NCT: NCT07253571 · TBAEK-599

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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