Exploring the Intersection of Cognitive Load Theory, Cognitive Sciences, and Neuroscience in Construction Safety: A Systematic Literature Review and a Conceptual Framework

Abstract

Abstract The construction industry faces high injury and fatality rates due to human errors from cognitive overload, attention deficits, and stress. This review synthesizes the intersection of cognitive load theory (CLT), the cognitive sciences (CS), and neuroscience to enhance safety, with a focus on hazard recognition, accident prevention, and worker performance. Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and Mixed Methods Appraisal Tool (MMAT), databases including Scopus, Web of Science, PubMed, and the ASCE Library were searched for eligible peer-reviewed articles published between 2010 and 2025. Independent reviewers screened 2,396 records, titles, abstracts, and full texts, identifying 120 studies. The analysis employed bibliometrics for trend analysis and thematic analysis to extract methods, themes, and outcomes. Publications surged after 2015, with a focus on neuroergonomics in construction safety. Key themes included brainwave monitoring for fatigue detection, brain blood flow imaging for informed decision-making, and eye tracking for attention management. External burdens amplify hazards under stress, with tools enabling real-time assessments. The proposed conceptual framework integrates cognitive load theory’s intrinsic loads, stemming from task complexity, extraneous loads, resulting from distractions, and germane loads, arising from learning efforts, with neural activations in areas such as the prefrontal cortex and cognitive processes, including awareness and attention. This model shows how optimizing these elements reduces errors by linking brain functions to better hazard spotting and safer behaviors. This integration highlights the potential of cognitive optimization to reduce fatalities, which is vital for researchers to develop unified theories and for practitioners to implement targeted safety measures. Limitations include small sample sizes and subjective data; future work requires long-term studies, combined imaging, and technological applications. The framework guides training programs that minimize distractions and boost learning to prevent accidents. Managers can apply neuroscience tools for on-site monitoring, adjust workloads to maintain awareness, and integrate innovative systems for real-time hazard alerts, thereby fostering safer construction environments.