Measurement and Quantification of Stress in the Decision Process: A Model-Based Systematic Review

This systematic literature review comprehensively assesses the measurement and quantification of decisional stress using a model-based, theory-driven approach. It adopts a dual-mechanism model capturing both System 1 and System 2 thinking. Mental stress, influenced by factors such as workload, affect, skills, and knowledge, correlates with mental effort. This review aims to address 3 research questions: (a) What constitutes an effective experiment protocol for measuring physiological responses related to decisional stresses? (b) How can physiological signals triggered by decisional stress be measured? (c) How can decisional stresses be quantified using physiological signals and features? We developed a search syntax and inclusion/exclusion criteria based on the model. The literature search we conducted in 3 databases (Web of Science, Scopus, and PubMed) resulted in 83 papers published between 1990 and September 2023. The literature synthesis focuses on experiment design, stress measurement, and stress quantification, addressing the research questions. The review emphasizes historical context, recent advancements, identified knowledge gaps, and potential future trends. Insights into stress markers, quantification techniques, proposed analyses, and machine-learning approaches are provided. Methodological aspects, including participant selection, stressor configuration, and criteria for choosing measurement devices, are critically examined. This comprehensive review describes practical implications for decision-making practitioners and offers insights into decisional stress for future research.