Author ORCID Identifier

0000-0003-1490-8768

Defense Date

2021

Document Type

Thesis

Degree Name

Master of Science

Department

Clinical Psychology

First Advisor

Scott Vrana, Ph.D.

Abstract

The attentional processing of emotional faces has interested researchers over the past thirty years. However, differing methodology has led to inconsistent findings. It has been suggested that using emotional faces as task-irrelevant distractors and varying perceptual load of the primary task can create an experimental framework that will allow attentional capture by emotional face processing to be better identified and differentiated from other processes. Furthermore, the effects of time on-task on attentional processing of emotional faces are currently not well understood, in part because traditional statistical analyses, such as the ANOVA, are insufficient for finding longitudinal trends in the data. In the present study, 103 undergraduate students completed a computerized letter search task identifying one of two target letters (X or Z) from a circular arrangement of different letters (high load) or dots (low load). In 20% of trials, an emotional (happy or angry) or neutral distractor face would appear at the center of the screen. Attention was measured by the time it took for participants to identify the target letter (RT). Multilevel modeling (MLM) was used to investigate how attentional capture by distractor faces during a letter search task was affected by the emotionality of the distractor face, perceptual load, and time on-task. Results showed that emotional faces captured attention more effectively than neutral faces under low load conditions, but not at high load. Additionally, at low load, fatigue effects were found to increase the distractibility of emotional faces at low load and decrease distractibility at high load. These findings support existing theories regarding the evolutionary significance of emotional faces.

Rights

© Nina Plotnikov

Is Part Of

VCU University Archives

Is Part Of

VCU Theses and Dissertations

Date of Submission

2-1-2021

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