Individual Differences in Emotional Experience and Cognitive Performance
Abstract
Emotional experiences, including those identified by a single emotion word (e.g., anger), vary dramatically both across people and within a person across different contexts in their everyday lives. For example, when they are angry, a person might yell, so heart rate and blood pressure will sometimes rise (say, when one driver cuts another off in traffic). But not all instances of an emotion referred to by the same word (e.g., ÒangerÓ) will look alike, feel alike, or involve the same bodily activity (e.g., an increase in heart rate or blood pressure). A person feeling anger also might sit very still and smile while being insulted, or tease a friend instead of criticize them. During these instances, the personÕs blood pressure and heart rate might go up, go down, or stay the same. Nevertheless, the scientific study of emotions has mostly treated this variation as error or ignored the immense variability in emotional experiences even for experiences referred to by the same emotion word. The lack of scientific understanding of this important variability represents a critical barrier to understanding how emotions influence behavior and decision making in a person s everyday life. The goal of this project is to map variability in emotional experiences both within a person and across different people as emotions are experienced in the context of a person s everyday life. This will include measuring self-reported emotional experience and measures of bodily changes associated with emotional experience (e.g., heart rate, sweat gland activity, respiration rate). To achieve this goal, we will conduct a multi-part experiment over three years using experience sampling (i.e., momentary report of experience in every day life using a mobile phone) and ambulatory (i.e., in-the-world) physiological monitoring. Participants will wear an ambulatory monitor that will record their bodily activity (e.g., heart rate, respiration) while they go about their daily lives. They will also receive brief prompts on their mobile phone throughout multiple days asking them to report their current emotional experience and their current environment (e.g., where are they are and who are they with). They will also be asked to perform a short cognitive task to assess their decision-making ability in the moment. We will collect behavioral, self-report, and bodily activity data from the same people in the lab following standard emotion induction procedures. We plan to use the large amount of self-report and biological data collected for each person to create new classifications of experience using novel machine learning techniques. These classifications will be based on consistent patterns of biological activity (i.e., consistent changes in bodily activity like changes in heart rate and respiration) for each person instead of classifications based solely on experience (as reflected in the report of specific emotion words such as anger, fear, sadness) as is typically done. The data to be collected will help us to meet three scientific aims: (1) to identify new biologically-based categories of experience, (2) to examine whether these categories generalize across people, and (3) to examine whether these biologically-based categories of experience can be used to improve our ability to predict changes in decision making that occur under experiences of intense emotion both within and across people. In meeting these aims, we hope to greatly expand the scientific understanding of how highly variable emotional experiences relate to decision making and behavior in everyday life. The study findings will inform future research efforts aimed at translating basic research in emotion science to real-world applications including providing the basis for future studies that aim to devise and test brief assessment methods for measuring individual differences in performance for use in Army hiring or in determining aptitudes for leadership or military occupational specialties.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 12, 2017
- Source ID
- W911NF1610191
Entities
People
- Karen S Quigley
Organizations
- Army Contracting Command
- Northeastern University
- United States Army