Identifying Individual Cognitive Factors Influencing Human-Robot Collaboration in Industrial Settings: An Integrated Approach Utilizing Delphi and Meta-Synthesis Methodologies

Abstract

Background: Human-robot collaboration in industrial environments is influenced by various human factors and cognitive ergonomics. Numerous categories of these factors have been examined in research within this field. This study systematically consolidates individual factors that affect cognitive performance in users of industrial robots. Methods: This study employed a hybrid approach combining the Delphi method with a seven-stage meta-synthesis as the primary qualitative strategy to identify cognitive factors affecting cognitive performance in industrial robot users. The stages included formulating the research question, conducting a systematic literature review, screening relevant research articles, extracting research data, analyzing and synthesizing qualitative findings, performing quality control, and presenting the findings. Findings: A total of 23 articles were screened through phased analyses, and an in-depth examination of these articles led to the identification of 15 distinct cognitive factors as primary dimensions influencing cognitive performance. To validate the agreement on the extracted items, the Kappa index was calculated at 0.857, indicating a satisfactory level of reliability. In this study, "cognitive fatigue" emerged as the most significant and impactful cognitive factor in the context of cognitive interactions between humans and industrial robots. Conclusion: Various factors significantly influence the cognitive performance of industrial robot users. By improving these factors, it is possible to enhance their cognitive abilities. © 2026, Isfahan University of Medical Sciences(IUMS). All rights reserved.