Integrating Human Factors into Protocol Design: Decision Strategies in Digitalized Simulation Environments

INTRODUCTION: In high-stakes industrial and operational contexts, such as aerospace, human factors heavily influence effectiveness under uncertain and dynamic conditions. Integrating simulation-based environments and digital tools in protocol development provides a valuable lens through which to assess cognitive and behavioural responses. As digitalization and Industry 4.0 accelerate the shift toward cyber-physical and human-in-the-loop systems, it becomes essential to understand how decision-making is affected in such digitalized settings. OBJECTIVES: This study aims to analyse the impact of uncertainty, time pressure, and cognitive complexity on human decision-making during protocol implementation in a simulated space mission. It also explores the implications of these insights for the design of digitalized, human-centred protocols pertinent to industrial transformation scenarios. METHODS: A mixed-methods approach was employed. Participants took part in a simulated space mission scenario using pre-defined protocols within a controlled, uncertainty-driven environment. Behavioural responses, timing, deviations, and verbal feedback were recorded and analysed. The quantitative data were supplemented with qualitative insights from participant interviews and session logs. RESULTS: Findings indicate operational uncertainty and time constraints significantly influenced participants’ decision pathways. Deviations from scripted protocols revealed how stress and perceived role clarity influence real-time choices. Furthermore, the analysis contextualizes these findings within Industry 4.0 frameworks, highlighting parallels with decision-making challenges in smart manufacturing, digital twin monitoring, and automated safety systems. CONCLUSION: The results underscore the necessity of embedding human-centred principles in protocol design, particularly when deploying digital technologies in complex, mission-critical environments. The study provides strategic recommendations for integrating adaptive, resilient, and cognitively compatible decision support tools into digitally transformed industrial processes.