Effect of AI-Assisted Anatomical Visualization on Anxiety and Kinesiophobia in Knee Arthroplasty Patients

Total knee arthroplasty (TDA) is an effective surgical method applied to reduce pain, improve joint function, and enhance quality of life in patients with advanced osteoarthritis or joint degeneration. However, it is known that surgical success is not limited to the operation itself; pre- and post-operative processes are at least as important as the surgical technique. In particular, active patient participation, early mobilization, and adherence to exercises during the rehabilitation period directly affect treatment outcomes.

Patient education plays a critical role in this process. Accurate and sufficient information reduces patients' anxieties about the surgical process and increases their confidence in the recovery process. It also prevents the development of kinesiophobia (fear of movement), supporting patients in participating in physical activity more quickly and safely.

Patient education can be provided through various methods. Traditional approaches include face-to-face clinical training, verbal information provided by nurses or physiotherapists, written brochures, and visual materials. While this standard clinical training is effective in conveying basic information, it may have limitations in patients' ability to recall information and adapt it to daily life.

In recent years, technology-based training methods have gained increasing importance. In particular, AI-assisted video-based anatomical visualization training can present the structure of the surgery, the placement of the prosthesis, and the movement mechanism to patients in a more understandable and visual way. Such interactive and visually rich training offers advantages in terms of increasing patients' knowledge levels, reducing anxiety, and strengthening their participation in treatment.

In conclusion, success after total knee arthroplasty depends not only on the surgical intervention but also on effective patient education. Comparing standard clinical training with AI-assisted visual training methods constitutes an important area of research for improving patient outcomes.