Examining self-relevance as a factor in the attentional bias in induced dysphoria using self-generated pictures
- UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
- Tamara Foxworth (Creator)
- Institution
- The University of North Carolina at Greensboro (UNCG )
- Web Site: http://library.uncg.edu/
- Advisor
- Kari Eddington
Abstract: The proposed study investigated an attentional bias in experimentally-induced dysphoria using self-relevant pictures in a dot probe study design. Participants generated their own photographs, using digital cameras to capture stimuli that are self-relevant and emotional to them. It was hypothesized that individuals with induced dysphoria would exhibit a greater attentional bias to negative stimuli than participants with induced happiness when self-generated pictures were used in a dot-probe paradigm. In addition, exploratory analyses were conducted to examine possible gender effects. To examine the first hypothesis, a MANOVA was conducted including the priming groups and gender as the predictors and the bias scores as the dependent variables. Results did not support the primary hypothesis. Regarding gender effects, females responded longer on all trials, and the interaction of gender and priming condition neared significance for negative attentional bias scores. It was also hypothesized that the importance and valence ratings of the pictures would significantly predict response latency, but this prediction was not supported by the data. The findings of this study are discussed in terms of cognitive theories of attentional biases in depression as well as methodological issues in this line of work.
Examining self-relevance as a factor in the attentional bias in induced dysphoria using self-generated pictures
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Created on 5/1/2011
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Additional Information
- Publication
- Thesis
- Language: English
- Date: 2011
- Keywords
- Attentional bias, Dysphoria, Mood induction
- Subjects
- Memory $x Testing
- Cognition
- Cognitive psychology
- Recognition (Psychology)
- Perception $x Testing