Clinical Research Directory

VR Goggles-Supported Virtual Reality Model in Midwifery Basic Clinical Skills Training

This randomized controlled trial aims to evaluate the effectiveness of a virtual reality (VR)-based training model supported by VR goggles in improving basic clinical skills among midwifery students. Traditional skills training in midwifery education can be limited by time, instructor availability, and opportunities for repeated practice. VR technology offers an immersive, standardized, and repeatable learning environment that may enhance skill development and learner engagement. In this study, midwifery students will be randomly assigned to either the VR training group or the traditional training group. Participants in the VR group will practice selected basic clinical skills using a VR goggle-supported simulation model, while the control group will receive standard skills laboratory training. Both groups will be evaluated through objective structured clinical examinations (OSCEs), self-confidence scales, and skill performance checklists. The study aims to determine whether VR-enhanced training improves clinical skill acquisition, performance accuracy, and learner confidence compared with traditional methods. Findings from this research may help inform modern, technology-supported approaches to midwifery education.

The Effect of Hand Sewing Practices on Suturing Skills

The overall aim of this study was to evaluate the effects of hand-held suture exercises on non-locking continuous suture skills used in episiotomy repair in midwifery students. The study, conducted with a randomized, single-blind, controlled design, aimed to generate evidence of psychomotor skill transfer using Objective Structured Assessment of Technical Skills based performance scores and secondary indicators (time, number of errors, etc.).

Video vs Model Training for Leopold Maneuver Skills

This randomized controlled study aims to compare the effectiveness of video-based and model-based training methods in improving Leopold maneuver skills among second-year midwifery students. The study will be conducted at the Faculty of Health Sciences, Kahramanmaraş Sütçü Imam University. Eligible students will be randomly assigned into three groups: video-supported training, model-supported training, and control. All participants will first receive a 2-hour theoretical training session. Then, the video group will watch an instructional video, the model group will perform hands-on practice using anatomical models, and the control group will receive no additional intervention. Skill acquisition will be evaluated through practical assessments conducted a few days and two months after training. At the end of the study, compensatory training will be provided to all groups to ensure educational equity. Data collection tools include a psychomotor skills assessment form, a student satisfaction scale, and the Spielberger State Anxiety Inventory. Statistical analyses will be performed using SPSS software.

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.

Gamified and Form-Based Reinforcement in Midwifery Education: A Quasi-Experimental Study

This quasi-experimental study aims to evaluate the effect of reinforcement using Kahoot (a gamification tool) and Google Forms (an interactive quiz platform) on the academic achievement and motivation of midwifery students enrolled in the "Normal Birth and Postpartum Period" course. The study involves two intervention groups: one using Kahoot and the other using Google Forms. A total of 39 third-year midwifery students will participate. Academic success will be measured through pre- and post-tests, motivation levels through a validated motivation scale, and qualitative feedback will be obtained through student opinion forms. The study seeks to explore how different digital reinforcement tools affect learning outcomes and student engagement in midwifery education.