The relation between state and trait risk taking and problem-solving View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-02-12

AUTHORS

Carola Salvi, Edward Bowden

ABSTRACT

People can solve problems in two main styles: through a methodical analysis, or by a sudden insight (also known as 'Aha!' or 'Eureka!' experience). Analytical solutions are achieved primarily with conscious deliberation in a trial-and-error fashion. 'Aha!' moments, instead, happen suddenly, often without conscious deliberation and are considered a critical facet of creative cognition. Previous research has indicated an association between creativity and risk taking (a personality trait); however, few studies have investigated how a short-term situational state of risk modulates these two different problem-solving styles. In this research, we looked at how both state and trait risks taking is related to different problem-solving styles. To measure risk as a personality trait, we administered the Balloon Analog Risk Task. To investigate risk as a state, we created a scenario, where people had to bet on their problem-solving performance at the beginning of each trial, and we compared the performance of this group with a control group that did not have to bet. The results show no association between risk as a trait and problem-solving style; however, the risk state scenario did produce a shift in dominant problem-solving style with participants in the risk scenario group solving more problems via analysis. We also found that two factors are related to problem-solving accuracy: the amount bet (i.e., when people place higher bets, they solve more problems), and success on the previous trial, especially if the solution was achieved via analysis. Furthermore, the data reveal that when under risk, females are better problem solvers than males. More... »

PAGES

1-14

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00426-019-01152-y

DOI

http://dx.doi.org/10.1007/s00426-019-01152-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112094305

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30756178


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