NDLI: Regulating Emotions during Difficult Multiattribute Decision Making: The Role of Pre-Decisional Coherence Shifting.

Content Provider	Directory of Open Access Journals (DOAJ)
Author	Stephanie M. Carpenter J. Frank Yates Stephanie D. Preston Lydia Chen
Abstract	Almost all real-life decisions entail attribute conflict; every serious choice alternative is better than its competitors on some attribute dimensions but worse on others. In pre-decisional "coherence shifting," the decision maker gradually softens that conflict psychologically to the point where one alternative is seen as dominant over its competitors, or nearly so. Specifically, weaknesses of the eventually chosen alternative come to be perceived as less severe and less important while its strengths seem more desirable and significant. The research described here demonstrates that difficult multiattribute decision problems are aversive and that pre-decisional coherence shifting aids individuals in regulating that emotional discomfort. Across three studies, attribute conflict was confirmed to be aversive (Study 1), and skin conductance responses and ratings of decision difficulty both decreased in participants who coherence shifted (Study 2). Coherence shifting was also diminished among decision makers who were depleted of regulatory resources, known to be required for common emotion regulation mechanisms. Further, coherence shifting was shown to be relatively common among people who reported strong suppression tendencies in everyday emotion regulation (Study 3). Overall, the data suggest that, at least in part, coherence shifting serves as a tool that helps decision makers manage the pre-decisional discomfort generated by attribute conflict. Theoretical and practical implications are discussed.
e-ISSN	19326203
DOI	10.1371/journal.pone.0150873
Journal	PLoS ONE
Issue Number	3
Volume Number	11
Language	English
Publisher	Public Library of Science (PLoS)
Publisher Date	2016-01-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Medicine Science
Content Type	Text
Resource Type	Article

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