Clinical Research Directory

Applying Interactive E-books on Breastfeeding to Enhance Nursing Students' Learning

This study aims to explore the impact of interactive breastfeeding e-books on nursing students' breastfeeding learning outcomes. The subjects are third-year nursing students from a university in central Taiwan. A randomized controlled design will be adopted. The experimental group will use interactive breastfeeding e-books for learning, while the control group will use traditional face-to-face courses to evaluate the changes in students' breastfeeding knowledge, skills, and learning motivation. The expected results can provide a reference for innovative teaching models in nursing education and promote the future clinical promotion of breastfeeding.

Online RPG Interactive Adventure Games Combined With an E-book Learning Obstetric Fetal Heart Rate Monitoring Technology

One of the main goals of nursing education is to cultivate essential clinical skills in students to ensure they can provide safe, effective, and compassionate care within a medical environment. In the field of obstetric nursing, the precise mastery of fetal heart rate monitoring is crucial as it significantly impacts the students' future ability to assess the health conditions of both the mother and the fetus in clinical settings. This becomes increasingly important in today's context of declining birth rates. However, traditional nursing education, which mainly relies on knowledge transmission and simulation demonstrations, not only struggles to stimulate students' interest but often leads to ineffective learning outcomes. With the rapid advancement of technology, these limitations no longer meet the current needs of nursing education and students. Therefore, this study proposes to build and explore a new teaching model based on the ARCS motivation theory, integrating online role-playing games (RPGs) and interactive e-books to enhance nursing students' learning motivation and effectiveness.

AI-Powered Interview Simulation to Improve Employability and Reduce Anxiety in Nursing and Midwifery Students

This randomized controlled trial aims to evaluate the effectiveness of a ChatGPT-based job interview simulation on the employment perceptions and interview-related anxiety of senior nursing and midwifery students. Transitioning from education to professional practice in healthcare is a critical phase that directly influences employability and career readiness. Particularly for nursing and midwifery students, the ability to navigate job interviews with confidence plays a pivotal role in shaping their future career paths. As such, innovative and digital interventions are needed to better prepare students for this process. Grounded in Bandura's Social Cognitive Theory and the Technology Acceptance Model (TAM), the study explores how AI-driven simulations affect students' self-efficacy, perceived utility, and usability, and ultimately their career-related outlook. The intervention involves a structured, text-based job interview simulation powered by ChatGPT-4o, during which students respond to a series of nine professionally tailored questions. These questions are aligned with international competency frameworks such as those from ICN (2008) and ICM (2024), focusing on themes like professionalism, teamwork, evidence-based care, communication, and leadership. At the end of the simulation, the chatbot provides brief, constructive feedback to the participant. A total of 102 final-year students from Koç University and Istanbul University-Cerrahpaşa will be recruited using stratified randomization. Participants will be assigned to either an intervention group, which will complete the ChatGPT simulation, or a control group, which will not receive any interview intervention but will complete the same pre- and post-test questionnaires. Key outcome measures include the Perceived Future Employability Scale (PFE), the Interview Anxiety Scale (MASI-T), and a simulation experience form for the intervention group. Quantitative data will be analyzed using SPSS with appropriate parametric and non-parametric tests based on data distribution, and an intention-to-treat (ITT) approach will be adopted. To ensure the integrity of the experiment, blinding procedures, strict confidentiality, and group separation protocols will be applied. The simulation will be conducted individually on research-owned devices in private rooms, and no personal or textual data will be saved from the AI interactions. Ethical approval has been obtained from Koç University Social and Behavioral Ethics Committee. Participation is voluntary, informed consent will be collected, and all processes will comply with the Helsinki Declaration and Turkish Personal Data Protection Law. Ultimately, this study seeks to offer evidence on the pedagogical utility of AI-based simulation tools in preparing healthcare students for employment, while also contributing to the broader field of digital transformation in health education.

The Effect of SBAR Communication Program on Nursing Students' Perceptions of Clinical Decision Making and Medical Error Prevention Levels: A Mixed Methods Study

In clinical settings, teamwork plays a vital role in improving patient care outcomes. Effective and structured communication within the team ensures that a holistic service is provided to patients. However, unclear and inadequate communication between healthcare professionals is a common problem. Such communication problems can be one of the main factors that compromise patient safety and lead to medication errors. Nurses play a key role in this process as they are the healthcare professionals who interact most with patients. Nurses need to not only correctly understand the instructions to be given to the patient, but also to convey information about the patient clearly and accurately to other nurses, doctors and other members of the healthcare team. In this context, opportunities to communicate using a common language and develop these skills form an essential part of the education of nursing students. The use of structured communication tools, especially SBAR, can play an important role in the prevention of medical errors while improving the clinical decision-making skills of future nurses. The SBAR (Situation, Background, Assessment, Recommendation) communication tool is a structured model used to ensure effective communication in healthcare. "The Effect of SBAR Communication Program on Clinical Decision Making and Medical Error Awareness Levels of Nursing Students: A Mixed Method Study" is a mixed method research using experimental and qualitative research designs. The data of the research will be collected with the "Student Information Form", "Clinical Decision Making Scale in Nursing" and "Medical Error Scale for Nursing Students" "Semi-Structured Interview Form". Quantitative data processing and statistical analysis will be done with SPSS (Statistical Package for the Social Sciences) software. Qualitative data analysis will be done using hand coding and content analysis method. As a result, this research will clearly demonstrate the benefits of integrating communication tools such as SBAR into nursing education, contribute to the development of new methods in education and the reduction of medical errors.

A Mobile Chatbot with ARCS-V Motivation Theory on Learning Motivation

This study will implement a smartphone chatbot in medical-surgical nursing education to enhance nursing students' learning motivation and academic performance. T