Clinical Research Directory

Objectıve Structured Clınıcal Examınatıon Stress For Intravenous Perıpheral Catheterızatıon

In this planned study, the stress levels of nursing students regarding intravenous access during the OSCE (Objective Structured Clinical Examination) will be measured using self-report questionnaires and smartwatches. Stress levels will be compared with those of another student group who did not undergo the OSCE assessment but performed intravenous access procedures.

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

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.

Enhancing Nursing Skills With SimCapture Technology

The action research aims to enhance clinical nursing skills of nursing students through the implementation of the SimCapture cloud management system. Research has found that traditional teaching methods are insufficient in cultivating students' clinical skills, and students' learning characteristics and technological developments have also placed new demands on teaching. Although the research team previously attempted blended learning and simulation-based teaching, students' technical grades have shown a declining trend. To address this issue, the researchers plan to implement the SimCapture system and, based on observational learning theory, design teaching activities to enhance students' learning motivation and self-efficacy, ultimately improving their clinical skills.