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Supporting Risk-Related Decision Making Under Emotional Loads in Multitask Environments
Abstract
Affective responses can influence different aspects of human decision-making and these influences can be especially pronounced in naturalistic contexts. While affective responses often serve as reliable cues for decision-making, misdirected and elevated affective responses (e.g., rage) can alter the perception of risk and risk-taking behaviors in a manner that can be deleterious to the performance and safety of a system. Such effects on risk-taking and decision-making behaviors can be limited by employing interventions to regulate these elevated affective responses.
Such interventions need to effectively regulate affective responses while imposing minimal additional cognitive loads on the user. This dissertation examines the influence of affective responses on risk-related decision-making and assesses the efficacy of using emotion regulation techniques (ERT) in the context of driving under emotional loads. Key requirements toward this goal were identified through extensive literature exploration and were addressed in a series of studies.
Results from the experiments addressing the first requirement, for a reliable and realistic emotion elicitation, show that increasing immersion in the affective media may be more effective in eliciting realistic emotions that persist for relatively longer durations and have relatively stronger influences on an individual’s cognitive processes.
The second requirement, for an emotion assessment tool that can be embedded into the primary task environment and can be used concurrently with the task, was addressed through the development of an iconic emotion assessment tool (ICE) that is presented using a mobile application. This tool leverages the superiority of human facial processing by using emoticons and can be reliably used for assessing basic emotions.
Finally, three ERTs using different sensory modalities and imposing varying levels of cognitive demand were compared for use in the context of driving under the influence of emotions. Results suggest that using ERTs to regulate elevated emotions, like anger and happiness, could contribute positively to the safety and performance of the system. Even an intervention requiring competing visual resources (with driving) may be more beneficial compared to driving under emotional loads with no regulation intervention. Using interventions may reduce the outward expressions of elevated emotions that are reflected in risky, aggressive driving behaviors.
Subject
naturalistic decision makingemotion regulation
affective engineering
driving safety
emotion assessment
emotion elicitation
Citation
Susindar, Sahinya (2022). Supporting Risk-Related Decision Making Under Emotional Loads in Multitask Environments. Doctoral dissertation, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /198735.