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Facial Expressions Depicting Compassionate and Critical Emotions: The Development and Validation of a New Emotional Face Stimulus Set

Overview of attention for article published in PLOS ONE, February 2014
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Title
Facial Expressions Depicting Compassionate and Critical Emotions: The Development and Validation of a New Emotional Face Stimulus Set
Published in
PLOS ONE, February 2014
DOI 10.1371/journal.pone.0088783
Pubmed ID
Authors

Kirsten McEwan, Paul Gilbert, Stephane Dandeneau, Sigrid Lipka, Frances Maratos, Kevin B. Paterson, Mark Baldwin

Abstract

Attachment with altruistic others requires the ability to appropriately process affiliative and kind facial cues. Yet there is no stimulus set available to investigate such processes. Here, we developed a stimulus set depicting compassionate and critical facial expressions, and validated its effectiveness using well-established visual-probe methodology. In Study 1, 62 participants rated photographs of actors displaying compassionate/kind and critical faces on strength of emotion type. This produced a new stimulus set based on Nā€Š=ā€Š31 actors, whose facial expressions were reliably distinguished as compassionate, critical and neutral. In Study 2, 70 participants completed a visual-probe task measuring attentional orientation to critical and compassionate/kind faces. This revealed that participants lower in self-criticism demonstrated enhanced attention to compassionate/kind faces whereas those higher in self-criticism showed no bias. To sum, the new stimulus set produced interpretable findings using visual-probe methodology and is the first to include higher order, complex positive affect displays.

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Geographical breakdown

Country Count As %
United States 3 3%
Mexico 1 1%
Luxembourg 1 1%
Unknown 90 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 17%
Student > Bachelor 15 16%
Researcher 12 13%
Student > Master 12 13%
Student > Doctoral Student 7 7%
Other 16 17%
Unknown 17 18%
Readers by discipline Count As %
Psychology 53 56%
Neuroscience 4 4%
Nursing and Health Professions 3 3%
Agricultural and Biological Sciences 3 3%
Computer Science 2 2%
Other 7 7%
Unknown 23 24%