Unveiling the impact of goal types: enhancing self-efficacy in rehabilitation robotics

In response to the growing need for effective and engaging stroke rehabilitation, this study examined how different goal-setting strategies influence self-efficacy and task performance during upper-limb motor learning with a soft pneumatic exoskeleton robot. One hundred participants practiced boccia while wearing the robot and were assigned to process (skill-focused), outcome (score-focused), shift (process-to-outcome), transform (feedback-based adjustment), or control conditions. Bayesian multivariate regression showed that self-efficacy was higher in the outcome ( b = 21.13, 95% CrI [7.94, 34.24]), shift ( b = 18.19, 95% CrI [4.84, 31.06]), and transform ( b = 21.22, 95% CrI [8.59, 34.21]) conditions relative to the process condition. Structural equation modeling further indicated that perceived robot softness was positively associated with general task self-efficacy and negatively associated with negative perceptions of the robot. These findings extend our understanding of how human-robot interaction contributes to self-efficacy and highlight the importance of aligning goal-setting strategies with robot design in rehabilitation contexts.