Clinical Research Directory

Flipped Classroom vs. Flip-Jigsaw in Theoretical Physiotherapy Education

Study Summary: This quasi-experimental pre-test-post-test study aims to compare the effects of Flipped Classroom (FC) and Flip-Jigsaw instructional models on theoretical knowledge acquisition, academic motivation, and class engagement among 86 third-year physiotherapy undergraduates enrolled in a theory-based public health course. Primary Questions: How does the hybrid Flip-Jigsaw model impact learning and motivation outcomes compared to FC alone? Do FC and Flip-Jigsaw differ in enhancing theoretical knowledge, motivation, and participation? Comparison: Researchers will compare the FC group (pre-class videos + in-class discussions) with the Flip-Jigsaw group (video-based pre-learning + structured peer teaching) to evaluate differences in outcomes. Participant Tasks: Attend lectures and complete pre-/post-knowledge tests. Engage in practical sessions (FC: group discussions; Flip-Jigsaw: peer-led jigsaw activities). Complete motivation surveys and participation assessments. Significance: Addresses the gap in understanding Flip-Jigsaw's efficacy in physiotherapy education, despite prior reports on FC and Jigsaw's individual benefits.

Digital Gamification vs. Traditional Training for Hip Replacement Instrument Table Setup (ORNurse)

This randomized controlled trial aims to compare the effectiveness of a digital gamification-based training method and a traditional training method on instrument table layout skills in total hip replacement surgery. Nursing students will be randomly assigned to either a game-based learning group or a control group receiving conventional education. The primary outcome is the accuracy of surgical instrument placement. The study will be conducted at Bozok University in Turkey.

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.

Integrated Learning Support System Based on Immersive Simulated Training for Nursing Students

This study aims to evaluate the effectiveness of an Integrated Learning Support System (ILSS) in preparing undergraduate nursing students for immersive simulated training in managing drug-induced nephrotoxicity. The study hypothesizes that the ILSS, which accommodates different learning styles, will be more effective in reducing stress and anxiety compared to the standard learning model (SLM). The research will involve a parallel randomized controlled trial with 96 students from two Brazilian institutions. The students will be divided into control and experimental groups, with the latter using the ILSS in addition to SLM during preparation. The study will assess outcomes such as knowledge acquisition, skill development, and stress reduction using various instruments, including the Lasater Clinical Judgment Rubric and DASS-21. The study's findings aim to validate the ILSS as a tool to enhance learning outcomes and reduce stress and anxiety, thereby promoting better professional development and patient safety in nursing practice.