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Intolerance of Ambiguity Mediates the Links Between Systems Thinking With Dichotomous Thinking and Attributional Complexity in a Canadian Sample

Bibliographic Data

ID21652038
AuthorsAdam C Davis (0000-0003-1200-1230, Department of Social Science Canadore College North Bay Ontario Canada, corresponding author), Mirella L Stroink (0000-0002-8311-0939, Department of Psychology Lakehead University Thunder Bay Ontario Canada)
Year2026
Volume43
Issue1
Pages34-41
Publication date2026-01-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSystems Research and Behavioral Science (JOURNAL)
Journal identifiersISSN: 1092-7026 • E-ISSN: 1099-1743
PublisherWiley (PUBLISHER • GB)
DOI10.1002/sres.3130
OpenAlexW4406803938
LanguageEN
References cited68

Dichotomous thinking is often employed to break down and simplify wicked problems (e.g., climate change) arising from complex adaptive systems (CASs). However, these dilemmas display emergent properties that cannot be reduced to the individual systemic parts. In contrast, systems thinking is considered to be essential in understanding the behaviour of CASs. The capacity to work with the ambiguity of CASs and wicked problems has been posited to be an integral aspect of a systems mindset. If so, this may help to explain why systems thinkers are believed to be disinclined towards dichotomous thinking and why they prefer multicausal explanations for complex phenomena. Across 359 Canadian undergraduate participants, results showed that systems thinking negatively predicted dichotomous thinking and positively predicted attributional complexity. Intolerance of ambiguity partially mediated both of these associations. Therefore, systems thinkers may avoid using dichotomous modes of thought and prefer multicasual attributions because they are comfortable dealing with ambiguity

Ambiguity · Cognitive psychology · Systems thinking · Cognitive Science and Mapping · Complex Systems and Decision Making · Computer Science · Organizational Learning and Leadership · Psychology · Social Psychology · Artificial Intelligence

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