LLM-Facilitated Cognitive Debiasing in Musculoskeletal Care

This study focuses on improving how patients interpret and manage musculoskeletal pain or dysfunction. Often, people quickly form beliefs about their symptoms that may not align with the actual medical condition, leading to unnecessary stress and medical procedures. The trial aims to test whether using a Large Language Model (LLM)-facilitated cognitive debiasing strategy can help patients understand their symptoms better compared to just receiving LLM-generated diagnostic feedback. This approach could lead to more accurate symptom evaluation and improve the overall healthcare experience by addressing the common challenge of misinterpretation in musculoskeletal care. Participants in this study will engage with an LLM, such as ChatGPT, which processes their symptom descriptions and beliefs to create clear summaries that help them identify and reconsider their thought patterns. The LLM can also assist healthcare providers by highlighting any potentially unhelpful beliefs before consultations, promoting better communication. The study compares this structured debiasing intervention with standard LLM-generated diagnostic feedback to see which method more effectively supports accurate symptom understanding and improves patient care. There are no specified risks or benefits outlined for participants, but the study aims to enhance the quality of decision-making and patient experiences.