ICF-Based Biopsychosocial Assessment With AI-Assisted Profile Prediction: Trapeziometacarpal Osteoarthritis Model

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.

NCT Number	NCT07458971
Lead Sponsor	Hacettepe University
Conditions	Trapeziometacarpal Osteoarthritis, Thumb Osteoarthritis, Carpometacarpal Osteoarthritis, Thumb Basal Joint Osteoarthritis
Enrollment	93 participants
Start Date	2026-02
Primary Completion	2026-04 (estimated)
Study Completion	2027-07 (estimated)
Updated on ClinicalTrials.gov	2026-03-09