Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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Sibling interactions are natural contexts for learning about the appropriate expression of emotions. The emotionally charged nature of sibling interactions creates a convenient context to explore emotional reactivity and regulation. The purpose of this study was to examine the relations among parent-reported sibling relationship quality, observed sibling prosocial and antisocial behaviors displayed when playing a competitive marble game, and children's emotions coded from videotape. The sample consisted of 58 twin children who are currently participating in the longitudinal Arizona Twin Project. Parents completed the Sibling Relationship Questionnaire online at 5 and 8 years. Additionally, a competitive marble game interaction between the siblings took place in the home at 8 years and was videotaped for objective coding of prosocial, antisocial, and control behavior. Facial expressions were also coded from videotape using Emotient FACET software across the marble game interaction. Three mean composites of emotion were created, including positive and negative emotional facial expressions. Results showed that parent reported warmth did not predict the occurrence of positive emotions during the sibling interaction. However, siblings with high conflict showed less fear during the interaction. Parent reports of warmth predicted the extent to which siblings differed on emotion expression, however conflict did not. Parent ratings of conflict and warmth did not predict the extent to which the sibling dyad was emotionally intense. Findings regarding genetic and environmental effects were in line with previous reports of genetic influence on prosocial behavior and negative emotion, and expressions of joy being influenced by the environment. This study investigated noteworthy aspects of the sibling relationship that appear to promote children's adaptive development.
ContributorsGanase, Anaelle Shelina (Co-author) / Oro, Veronica (Co-author) / Roth, Winter (Co-author) / Doane, Leah (Co-author) / Lemery-Chalfant, Kathryn (Co-author, Thesis director) / Miadich, Samantha (Committee member) / Davis, Mary (Committee member) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Hand-coding systems of measuring facial expressions were developed to study and analyze human emotions, but they are time-intensive and thus seldom used. As technology has advanced, new computer software programs, such as Affectiva, were developed to code facial expressions automatically using artificial intelligence and machine learning. Since this technology is still new, Affectiva and its validity remain understudied, and no psychological research has been conducted to compare Affectiva computer coding and hand coding of children’s emotions. The purpose of this study was to compare hand and computer coding of children’s expressions of emotion during a videotaped parent-child interaction. The study answered the following questions: 1) Do hand and computer coding agree?; and 2) Are hand and computer coding in higher agreement for some emotions than others? The sample included 25 pairs of twins from the Arizona Twin Project. Facial expressions were coded from videotape by a trained and reliable human coder and using the software Affectiva. The results showed that hand and computer coded emotion were in agreement for positive, but not negative emotions. Changing the context of the interaction to elicit more negative emotion, and using the same indicators of each emotion in computer and hand coding are suggested to improve the comparison of computer and hand coding.
ContributorsKwok, Connie (Author) / Lemery-Chalfant, Kathryn (Thesis director) / Davis, Mary (Committee member) / Miadich, Samantha (Committee member) / Department of Psychology (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05