The effectiveness of control algorithms for teleoperated systems is typically evaluated through experimental performance measures, post-experimental user surveys, and theoretical analysis. However, none of these methods provide an objective assessment of teleoperation algorithms with respect to the real-time changes of human users during teleoperated tasks in terms of physiological, kinematic, or cognitive metrics. In this study, we recruited subjects to control robotically steered needles in a randomized experiment, using four different teleoperation mappings (joint space control, steering control, and Cartesian space control with and without force feedback). We investigated how the choice of these algorithms affect both performance and user response. Our novel steering control mapping, which mimics hub-centered steering, is significantly correlated with decreased cognitive stress and improved teleoperation performance when compared to joint space control. Overall, user experience and teleoperation performance were significantly improved with Cartesian space control, resulting in faster needle insertion, higher targeting accuracy, lower cognitive load, and smoother movements. Furthermore, while additional haptic feedback in Cartesian space provided an improved performance, it may increase user cognitive workload and muscle fatigue. These results highlight the importance of considering human-centric metrics when designing novel teleoperation strategies for complex systems.