Using Artificial Intelligence to Increase Patient Awareness: Evaluating ChatGPT's Responses to Common Patient Questions About Lateral Epicondylitis
DOI:
https://doi.org/10.58542/jbota.v62i1.174Keywords:
ChatGPT, artificial intelligence in medicine, patient education, lateral epicondylitisAbstract
Patients usually have multiple questions related to the diagnosis, treatment options, and expected prognosis. In view of the growing popularity and widespread use of ChatGPT, it is logical to assume that more and more patients will independently seek answers to their medical queries through the chatbot. The current study aims to evaluate the potential of ChatGPT as an additional tool for raising awareness in patients with lateral epicondylitis. Methods: Ten hypothetical questions were asked to the free version of ChatGPT-3.5, with the aim of simulating a consultation between a doctor and a patient diagnosed with lateral epicondylitis. Each response generated by ChatGPT was evaluated by two independent orthopedics and traumatology specialists on two separate four-point Likert scales – one for factual accuracy and the other for content relevance. Results: The results show that in most cases, ChatGPT generates content with a high degree of factual accuracy and relevance, especially in questions related to symptomatology, causes, and non-operative treatment. Responses related to more specific or expert topics – such as differential diagnosis and surgical treatment – showed some limitations in both accuracy and relevance. Especially important is the result that ChatGPT adapts its responses depending on the level of education indicated by the patient. Conclusions: The study shows that ChatGPT can be a useful source of basic medical information on the topic of lateral epicondylitis. However, the use of AI chatbots in a medical context requires clearly stated goals, content verification, and strict adherence to privacy and personal data protection requirements. Additional studies with a broader scope, involving real patients and a variety of clinical trials, are needed cases in order to assess the actual applicability of such technologies in the field of healthcare.
