Background: Understanding the influence of stress on human performance is of theoretical and practical importance. An individual's reaction to stress predicts their subsequent performance; with a “challenge” response to stress leading to better performance than a “threat” response. However, this contention has not been tested in truly stressful environments with highly skilled individuals. Furthermore, the effect of challenge and threat responses on attentional control during visuomotor tasks is poorly understood. Design: Thus, this study aimed to examine individual reactions to stress and their influence on attentional control, among a cohort of commercial pilots performing a stressful flight assessment. Methods: Sixteen pilots performed an “engine failure on take-off” scenario, in a high-fidelity flight simulator. Reactions to stress were indexed via self-report; performance was assessed subjectively (flight instructor assessment) and objectively (simulator metrics); gaze behavior data were captured using a mobile eye tracker, and measures of attentional control were subsequently calculated (search rate, stimulus driven attention, and entropy). Results: Hierarchical regression analyses revealed that a threat response was associated with poorer performance and disrupted attentional control. Conclusion: The findings add to previous research showing that individual reactions to stress influence performance and shed light on the processes through which stress influences performance.

Although prosthetic hand rejection rates remain high, evidence suggests that effective training plays a major role in device acceptance. Receiving training early in the rehabilitation process also enhances functional prosthetic use, decreases the likelihood of developing an overreliance on the intact limb, and reduces amputation-related pain. Despite these obvious benefits, there is a current lack of evidence regarding the most effective training techniques to facilitate myoelectric prosthetic hand control, and it remains unknown whether training is effective in facilitating the acquisition and transfer of prosthetic skill. In this scoping review, we introduced and summarized key motor learning principles related to attentional focus, implicit motor learning, training eye–hand coordination, practice variability, motor imagery, and action observation, and virtual training and biofeedback. We then reviewed the existing literature that has applied these principles for training prosthetic hand control before outlining future avenues for further research. The importance of optimizing early and appropriate training cannot be overlooked. While the intuition and experience of clinicians holds enormous value, evidence-based guidelines based on well-established motor learning principles will also be crucial for training effective prosthetic hand control. While it is clear that more research is needed to form the basis of such guidelines, it is hoped that this review highlights the potential avenues for this work.

Two experiments examined the roles of the dimensions of movement-specific reinvestment (movement selfconsciousness and conscious motor processing) on performance under demanding conditions. In Experiment 1, novice golfers practiced a golf putting task and were tested under low- and high-anxiety conditions. Conscious motor processing was not associated with putting proficiency or movement variability; however, movement self-consciousness was positively associated with putting proficiency and appeared to be negatively associated with variability of impact velocity in low-anxiety conditions, but not in high-anxiety conditions. Increased anxiety and effort possibly left few attention resources for movement self-consciousness under high anxiety. In Experiment 2, participants performed a quiet standing task in single- and dual-task conditions. Movement self-consciousness was positively associated with performance when attention demands were low (single task) but not when attention demands were high (dual task). The findings provide insight into the differential influence of the two dimensions of movement-specific reinvestment under demanding conditions.