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The Merits of Unconscious Thought in Rule Detection

Overview of attention for article published in PLOS ONE, August 2014
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Title
The Merits of Unconscious Thought in Rule Detection
Published in
PLOS ONE, August 2014
DOI 10.1371/journal.pone.0106557
Pubmed ID
Authors

Jiansheng Li, Yawen Zhu, Yang Yang

Abstract

According to unconscious thought theory (UTT), unconscious thought is more adept at complex decision-making than is conscious thought. Related research has mainly focused on the complexity of decision-making tasks as determined by the amount of information provided. However, the complexity of the rules generating this information also influences decision making. Therefore, we examined whether unconscious thought facilitates the detection of rules during a complex decision-making task. Participants were presented with two types of letter strings. One type matched a grammatical rule, while the other did not. Participants were then divided into three groups according to whether they made decisions using conscious thought, unconscious thought, or immediate decision. The results demonstrated that the unconscious thought group was more accurate in identifying letter strings that conformed to the grammatical rule than were the conscious thought and immediate decision groups. Moreover, performance of the conscious thought and immediate decision groups was similar. We conclude that unconscious thought facilitates the detection of complex rules, which is consistent with UTT.

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The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Luxembourg 1 2%
Unknown 50 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 16%
Student > Master 8 16%
Student > Bachelor 8 16%
Researcher 6 12%
Student > Doctoral Student 5 10%
Other 8 16%
Unknown 8 16%
Readers by discipline Count As %
Psychology 23 45%
Business, Management and Accounting 7 14%
Social Sciences 3 6%
Computer Science 2 4%
Neuroscience 2 4%
Other 5 10%
Unknown 9 18%