Trapeziometacarpal osteoarthritis (TMC OA) is a common condition affecting the base of the thumb that causes pain, weakness, and difficulty with daily hand use. Current clinical assessment often focuses on physical findings alone, without considering psychological and social factors that also influence patient outcomes.
This study has three objectives organized as interrelated work packages:
OBJECTIVE 1 (Clinical Assessment): To comprehensively assess individuals with TMC OA using the International Classification of Functioning, Disability and Health (ICF) framework. This includes evaluating pain, joint mobility, grip strength, daily activity limitations, social participation, psychological factors (anxiety, depression, fear of movement, pain beliefs), and environmental factors (family support, ergonomic adaptations).
OBJECTIVE 2 (AI Knowledge Evaluation): To compare the medical knowledge performance of four large language models (Claude, ChatGPT, Gemini, LLaMA) in answering clinical questions about TMC OA, using criteria such as accuracy, reproducibility, comprehensiveness, clinical relevance, and readability.
OBJECTIVE 3 (AI-Based Prediction): To analyze whether the best-performing large language model can predict multidimensional ICF-based patient profiles using only a limited set of core clinical parameters.
Diagnosis of trapeziometacarpal osteoarthritis (TMC OA) confirmed by an orthopedic surgeon and/or hand surgeon
TMC OA-related symptoms persisting for more than 3 months
Aged between 25 and 74 years
Literate in Turkish
Unwillingness to participate
Presence of a different orthopedic condition or prior surgery involving the thumb on the unilateral upper extremity
Uncontrolled systemic diseases (chronic obstructive pulmonary disease, congestive heart failure, endocrine system disease, history of stroke)
Diagnosis of any major psychopathology and currently receiving psychiatric or psychological treatment