JMIR Publications

ABSTRACT

Background:

Industry 5.0 emphasizes human-centricity, by prioritizing human well-being alongside technological advancements. Collaborative robots (cobots) in industrial settings represent one such advancement and their integration, particularly in manufacturing, is reshaping production processes. Despite investigations into these aspects, there is yet no systematic review exploring their impact on the affective well-being and cognitive workload of human operators.

Objective:

This study specifically addresses these psychological dimensions, filling a crucial gap in the existing literature, which has predominantly focused on physical and cognitive workload over affective states.

Methods:

A comprehensive systematic search of the literature was conducted through several databases, such as Web of Science, Scopus, ACM Digital Library, and IEEE Xplore.

Results:

A total of 46 studies were included in this review. Findings indicated a significant increase in publications from 2020 onwards, reflecting the growing interest in human-cobot collaboration. Most studies were conducted in controlled laboratory settings with university students or researchers, highlighting a gap in real-world industrial research. Results showed that while cobots have been shown to alleviate physical fatigue and enhance job satisfaction, they also introduce new psychological challenges, including stress and anxiety symptoms due to concerns about job security and the pressures of high-paced operations. The speed at which cobots operate represents a factor affecting operators’ affective well-being and cognitive workload, alongside the proximity of cobots, the system usability, and the complexity of tasks assigned. As regards the latter, studies using physiological and self-report measures consistently found that higher task complexity and dual-task conditions significantly increase cognitive workload and stress levels.

Conclusions:

Therefore, this study identified key factors influencing the affective well-being and cognitive workload of operators working with cobots, by providing insights that could guide the development of longitudinal research and intervention strategies, ensuring that the integration of cobots supports both operational efficiency and the well-being of operators in manufacturing environments.