Recognizing emotion from facial expressions is an essential skill for effective social functioning and establishing interpersonal relationships. Asperger's Disorder (AD) and Social Phobia (SP) are two clinical populations showing impairment in social skill and perhaps emotion recognition. Objectives: The primary objectives were to determine the uniqueness of facial emotion recognition abilities between children with AD and SP relative to typically developing children (TD) and to examine the role of expression intensity in determining recognition of facial affect. Method: Fifty-seven children (19 AD, 17 SP, and 21 TD) aged 7-13 years participated in the study. Reaction times and accuracy were measured as children identified neutral faces and faces displaying anger, disgust, fear, happiness, and sadness at two different intensity levels. Results: Mixed model ANOVAs with group and emotion type revealed that all children responded faster and more accurately to expressions of happiness, but there were no other group differences. Additional analyses indicated that intensity of the displayed emotion influenced facial affect detection ability for several basic emotions (happiness, fear, and anger). Across groups, there was no pattern of specific misidentification of emotion (e.g., children did not consistently misidentify one emotion, such as disgust, for a different emotion, such as anger.) Finally, facial affect recognition abilities were not associated with behavioral ratings of overall anxiety or social skills effectiveness in structured role play interactions. Conclusions: Distinct facial affect recognition deficits in the clinical groups emerge when the intensity of the emotion expression is considered. Implications for using behavioral assessments to delineate the relationship between facial affect recognition abilities and social functioning among clinical populations are discussed.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-5337 |
| Date | 01 January 2010 |
| Creators | Wong, Nina |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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