Clinical reasoning is a fundamental skill for physical therapy students, enabling them to collect and interpret patient information to make accurate diagnoses and treatment decisions. Traditional training methods often limit students' exposure to a diverse range of clinical cases, which can restrict the development of these skills. The integration of Large Language Models (LLMs), such as ChatGPT, into physical therapy education offers a novel approach to enhance clinical reasoning by simulating interactive and realistic patient scenarios. This randomized controlled trial aims to evaluate the effectiveness of an LLM-based educational intervention in improving clinical reasoning skills in physical therapy students. The study will recruit a total of 200 third-year physiotherapy students from multiple university institutions. Participants will be randomly assigned to one of two groups: 1. Experimental Group - Students will receive LLM-based training, engaging with a conversational artificial intelligence model to solve clinical cases over an 8-week period. The model will provide real-time responses to their questions, allowing them to refine their diagnostic and treatment reasoning. 2. Control Group - Students will follow the standard curriculum, participating in conventional case-based learning and supervised clinical reasoning exercises without AI-based assistance. The primary outcome of the study is the improvement in clinical reasoning skills, assessed through standardized written case evaluations and structured practical examinations. Secondary outcomes include changes in digital competence, student engagement levels, overall satisfaction with the educational approach, and cost-effectiveness of the intervention. By assessing the impact of LLMs on clinical reasoning training, this study seeks to determine whether AI-driven educational tools can effectively complement traditional physiotherapy education and improve student preparedness for real-world clinical practice.
Age range
18 Years – 30 Years
Sex
ALL
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
Clinical Reasoning Performance
Timeframe: Assessed at the beginning and end of the 8-week intervention through case-based assessments and practical evaluations.