Immersive Real-Time Biofeedback Optimized With Enhanced Expectancies Improves Motor Learning: A Feasibility Study

摘要

Context: An Optimizing Performance through Intrinsic Motivation and Attention for Learning theory-based motor learning intervention delivering autonomy support and enhanced expectancies (EE) shows promise for reducing cognitive-motor dualtask costs, or the relative difference in primary task performance when completed with and without a secondary cognitive task, that facilitate adaptive injury- resistant movement response. The current pilot study sought to determine the effectiveness of an autonomy support versus an EE-enhanced virtual reality motor learning intervention to reduce dual-task costs during single-leg balance. Design: Within-subjects 3 x 3 trial. Methods: Twenty-one male and 24 female participants, between the ages of 18 and 30 years, with no history of concussion, vertigo, lower-extremity surgery, or lower-extremity injuries the previous 6 months, were recruited for training sessions on consecutive days. Training consisted of 5 x 8 single-leg squats on each leg, during which all participants mimicked an avatar through virtual reality goggles. The autonomy support group chose an avatar color, and the EE group received positive kinematic biofeedback. Baseline, immediate, and delayed retention testing consisted of single-leg balancing under single- and dual-task conditions. Mixed- model analysis of variances compared dual-task costs for center of pressure velocity and SD between groups on each limb. Results: On the right side, dual-task costs for anteriorposterior center of pressure mean and SD were reduced in the EE group (mean Delta = -51.40, Cohen d = 0.80 and SD Delta = -66.00%, Cohen d = 0.88) compared with the control group (mean Delta = -22.09, Cohen d = 0.33 and SD Delta = -36.10%, Cohen d = 0.68) from baseline to immediate retention. Conclusions: These findings indicate that EE strategies that can be easily implemented in a clinic or sport setting may be superior to task-irrelevant AS approaches for influencing injury- resistant movement adaptations.