Background:: Every human action begins with decision-making. Stress is a significant source of biases that can influence human decision-making. In order to understand the relationship between stress and decision-making, stress quantification is fundamental. Different methods of measuring and quantifying stress in decision-making have been described in the literature while an up-to-date systematic review of the existing methods is lacking. Moreover, mental stress, mental effort, cognitive workload, and workload are often used interchangeably but should be distinguished to enable in-depth investigations of decision-mechanisms. Our objectives are to clarify stress related concepts and review the measurement, quantification, and application of stress during decision making activities.Methods:: We developed and followed a systematic reviews protocol to analyze the literature related to stress in decision-making. We systematically searched Web of Science, Scopus, PubMed, and ERIC (EBSCO) between 1990 and 2020 with English language. We will include any literature reporting measurable stress-related outcomes, including stress, workload, cognitive workload, mental effort during the decision-making process. All research designs investigating the quantification and measurement of stress for healthy adults are eligible for this review. Research postulates are proposed based on the stress-effort model. Two reviewers will independently screen the articles for inclusion and assess for study quality using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. We will extract data from each study including research objective, research method, research domain, triggering method, objective measure, subjective measure, and research results for knowledge syntheses.Discussion:: The physiological responses to stress are proposed for verification. This systematic review will provide knowledge on decision mechanisms under stress and stress related concepts. The improved understanding on stress measurement, quantification, and application in specific research context will advance methods to study and optimize decision making.