Validity and Reliability of Mixed Reality-Based Performance Tests in Overweight and Obese Adults

This study aims to evaluate the validity and reliability of mixed reality (MR)-based adaptations of functional mobility and performance tests developed using the Meta Quest 3 platform by comparing their outcomes with conventional clinical assessments. Virtual and mixed reality technologies have gained increasing attention in clinical measurement due to their potential advantages, including assessment standardization, enhanced user interaction, and automated data collection. Previous studies have demonstrated that virtual reality-based performance assessments can provide high reliability and show meaningful associations with traditional clinical measures across different populations. However, visual and vestibular stimuli, depth perception, and changes in movement strategies may cause performance in virtual environments to differ from performance in conventional settings. Therefore, the validity and reliability of each virtual or mixed reality adaptation should be established within the target population. Overweight and obese individuals exhibit biomechanical and physiological characteristics that may affect balance, gait mechanics, joint loading, and physical performance. Consequently, measurement properties established in other populations cannot be assumed to apply directly to overweight and obese individuals. In addition, factors related to head-mounted displays and motion-tracking systems may influence assessment outcomes. The purpose of this study is to evaluate the concurrent validity and test-retest reliability of mixed reality-based performance tests developed using the Meta Quest 3 platform. Measurement error parameters will also be determined to assess the clinical applicability of these MR-based assessments. The findings of this study are expected to contribute to the development of safe, standardized, digital, and potentially remote assessment approaches for evaluating functional performance in overweight and obese individuals. Furthermore, the results may strengthen the scientific evidence supporting the use of digital assessment technologies in clinical practice.

Inclusion Criteria: * Body Mass Index (BMI) ≥ 25 kg/m² (overweight or obesity), * Ability to ambulate independently, * Aged between 18 and 65 years, * Willingness to participate voluntarily in the study and provide written informed consent. Exclusion Criteria: * Use of anti-obesity medication, * Pregnancy, * Latent autoimmune diabetes in adults (LADA), * Chronic kidney disease, * Active or severe infections, * Liver failure, * Recent major cardiovascular events, * Unstable angina, * Heart failure classified as New York Heart Association (NYHA) Class III-IV, * Respiratory failure, cardiac arrhythmias, neoplastic diseases, or neurological or musculoskeletal disorders that may limit the safe performance of the tests.