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- Creators: Barrett, The Honors College
Methods: 191 middle-aged adults from a community-based study on resilience were asked to complete 30 daily diaries assessing positive and negative affect. At least 6 months later, participants completed a phone interview that assessed distress (i.e., depressive and anxiety symptoms), well-being (i.e., WHO-5 well-being, vitality, social functioning), physical functioning, and perceived stress.
Results: A three-factor solution with latent factors representing overall, negative, and positive EC was identified. Overall EC significantly predicted enhanced physical functioning, but was not associated with distress or well-being. Contrary to study hypotheses, positive and negative EC were not associated with future distress, well-being, or physical functioning, though a trend toward improved physical functioning was noted for positive EC. In contrast, positive and negative ED were both associated with less distress, and better well-being and physical functioning. Overall ED was unexpectedly related to worse outcomes (i.e., more distress, less well-being, decreased physical functioning). Stress did not moderate the relationship between emotional complexity and the outcome variables.
Conclusions: Different indicators of EC represent distinct aspects of emotional experience. Partial support of the hypotheses found. Physical functioning was the only outcome influenced by EC. The inclusion of stress did not change the results. The discrepancy between the findings and those in the literature may be related to reliability of EC indicators and absence of contextual factors. Further exploration of ED revealed a potentially important construct of emotional experience that is deserving of further inquiry.
Affective computing allows computers to monitor and influence people’s affects, in other words emotions. Currently, there is a lot of research exploring what can be done with this technology. There are many fields, such as education, healthcare, and marketing, that this technology can transform. However, it is important to question what should be done. There are unique ethical considerations in regards to affective computing that haven't been explored. The purpose of this study is to understand the user’s perspective of affective computing in regards to the Association of Computing Machinery (ACM) Code of Ethics, to ultimately start developing a better understanding of these ethical concerns. For this study, participants were required to watch three different videos and answer a questionnaire, all while wearing an Emotiv EPOC+ EEG headset that measures their emotions. Using the information gathered, the study explores the ethics of affective computing through the user’s perspective.