## 2 Literature Review
The former is defined as the extent to which the person believes that using a particular system would improve job performance, while the latter is represented as the extent to which the person believes that using the system would be free of effort [39]. Both elements have a direct influence on the user's attitude, which is an important determinant of the individual acceptance or rejection of the system. Previous studies in HRC highlighted the importance of robot motion planning in increasing user acceptance, as the human co-agent is able to predict the robot's movements quickly and accurately [40; 41]. These properties are reflected in point-to-point MJTs, which produce psychologically acceptable motions without causing disturbing or uncomfortable feelings in the operators [42; 43]. In addition, previous authors highlighted the importance of automated notifications that can change the users' awareness of the situation [44]. For example, ref. [45] found that installing a visual status indicator on the robot's wrist could improve HRI efficiency and effectiveness, which are two key elements of usability, which is a construct that strongly correlates with acceptability. Trust was considered an external predictor in many extended versions of TAM over the last decade, especially as a key factor influencing the perception of usefulness: the more the worker trusts the innovative tool, the more valuable it is perceived to be and the more likely it is to be used. An acceptable level of trust must be obtained to avoid failure: a dysfunctional calibration could turn trust into a risk factor that leads to safety-related problems for both the organisation and the operator [46]. Over-trust occurs when the operator trusts the system too much and delegates tasks that exceed the robot's capabilities, while under-trust arises when the operator does not count on the robot's capabilities. Previous authors emphasised the importance of specific design elements of the robot, such as size and appearance, and the robot's performance in influencing the operator's trust [47; 48; 49]. As highlighted in another study [22], human trust in a robot is determined by the degree of autonomy of the robot, which affects task efficiency and workload. We can thus assume that trust might moderate the relationship between cognitive workload and perceived stress. Trust can, in fact, influence how individuals perceive and respond to situations. In the case of a disproportion between the operator's available cognitive resources and the cognitive demands of the task, individuals who trust a robotic system may be more likely to believe that the system is competent and able to handle complex tasks, which could reduce their perceived stress. On the other hand, individuals who do not trust a robotic system may be more likely to doubt their abilities and may, therefore, experience higher levels of perceived stress, which could lead to human errors. The aims of this study were threefold. First, we investigated the impact of workstation and interaction design guidelines [24] on users' cognitive workload by combining subjective measures with eye-tracker data. As the guidelines are implemented in different scenarios,we expected to see a decrease in participants' cognitive workload, indicating that they could handle the demands of the tasks more efficiently. Second, we aimed to understand the relationship between cognitive workload and perceived stress in collaborative tasks, as well as the association between cognitive workload and the acceptance of cobots. We expected that participants with a higher acceptance of cobots will have improved cognitive workload and lower levels of perceived stress. Third, we tested a moderation model to investigate the potential moderating effect of trust on the relationship between cognitive workload and perceived stress. We hypothesised that higher levels of trust will result in a weaker association between the two variables.