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ICF-Based Biopsychosocial Assessment With AI-Assisted Profile Prediction: Trapeziometacarpal Osteoarthritis Model
Sponsor: Hacettepe University
Summary
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.
Official title: ICF-Based Biopsychosocial Assessment With Artificial Intelligence-Assisted Profile Prediction: Trapeziometacarpal Osteoarthritis Model
Key Details
Gender
All
Age Range
25 Years - 74 Years
Study Type
OBSERVATIONAL
Enrollment
93
Start Date
2026-02
Completion Date
2027-07
Last Updated
2026-03-09
Healthy Volunteers
No
Conditions
Locations (1)
Hacettepe University, Faculty of Physical Therapy and Rehabilitation, Hand Surgery Rehabilitation Unit
Ankara, Turkey (Türkiye)