STRESS REGULATION SKILLS AMONG ENGINEERS WORKING IN HIGH-RISK INDUSTRIAL ENVIRONMENTS

Abstract

This research focuses on stress coping mechanisms of engineers in high-stake industries such as oil, chemicals, and nuclear energy. Increasing complexity of tasks and integration of smart automation systems in these industries make the work highly intellectually and emotionally demanding. Engineers often work in physically and mentally demanding environments, which places great stress on them, threatening both personal and collective safety. An often-overlooked area in workplace evaluations is the relationship of stress and cognitive function, often called the stress-cognition nexus. This study utilizes a multimodal approach combining physiological, behavioral, and subjective data to examine engineers' stress regulation in multiple simulated operational scenarios. The real-time stress response and coping mechanisms were assessed using wearable biosensors like EEG and heart rate variability (HRV) devices, alongside training history and environmental factors. The data suggested stress responses in real-time and the study tested various coping mechanisms. It was found that engineers with coping skills who actively regulated (through cognitive reframing and controlled breathing) demonstrated decreased physiological arousal, faster recovery, and better performance. EEG data showing increased frontal theta and decreased parietal alpha alongside HRV trends of sympathetic dominance corroborated the results. Accuracy of the physiological indicators was confirmed by the post-simulation interviews and NASA-TLX self-reports.

These adaptive support systems and monitoring tools that offer real-time tracking of cognitive strain and provide recommendations for interventions would mitigate cognitive overload. Ergonomic interfaces and resilience training programs cater to the individual user's unique ergonomics and adaptive needs. Furthermore, biometric monitoring is critiqued for ethical issues like informed consent and data privacy and needs to be responsibly deployed to be socio-technically mindful. Biometric monitoring and real-time data tracking enables the confidential assessment of cognitive load and intervention strategies; thus, the research proposes a workforce support model that integrates mental health needs with operational demands. It adds a layer of safety and health to high-risk engineering contexts. This model combines continuous tracking of mental and emotional states with behavioral data and tailored feedback. This framework shifts the narrative of high-risk engineering fields towards more humane-centered design and multi-disciplinary workflows, integrating Industry 4.0 with human factors, cognitive ergonomics, cognitive resilience, and socio-technics.