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- Publisher Website: 10.1111/bjop.12693
- Scopus: eid_2-s2.0-85182154527
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Article: Understanding anxiety through uncertainty quantification
Title | Understanding anxiety through uncertainty quantification |
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Authors | |
Keywords | anxiety Bayesian theory intolerance of uncertainty research domain criteria uncertainty quantification |
Issue Date | 12-Jan-2024 |
Publisher | Wiley |
Citation | British Journal of Psychology, 2024 How to Cite? |
Abstract | Uncertainty has been a central concept in psychological theories of anxiety. However, this concept has been plagued by divergent connotations and operationalizations. The lack of consensus hinders the current search for cognitive and biological mechanisms of anxiety, jeopardizes theory creation and comparison, and restrains translation of basic research into improved diagnoses and interventions. Drawing upon uncertainty decomposition in Bayesian Decision Theory, we propose a well-defined conceptual structure of uncertainty in cognitive and clinical sciences, with a focus on anxiety. We discuss how this conceptual structure provides clarity and can be naturally applied to existing frameworks of psychopathology research. Furthermore, it allows formal quantification of various types of uncertainty that can benefit both research and clinical practice in the era of computational psychiatry. |
Persistent Identifier | http://hdl.handle.net/10722/348381 |
ISSN | 2023 Impact Factor: 3.2 2023 SCImago Journal Rankings: 1.490 |
DC Field | Value | Language |
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dc.contributor.author | Hedley, Friederike Elisabeth | - |
dc.contributor.author | Larsen, Emmett | - |
dc.contributor.author | Mohanty, Aprajita | - |
dc.contributor.author | Liu, Jeremiah Zhe | - |
dc.contributor.author | Jin, Jingwen | - |
dc.date.accessioned | 2024-10-09T00:31:08Z | - |
dc.date.available | 2024-10-09T00:31:08Z | - |
dc.date.issued | 2024-01-12 | - |
dc.identifier.citation | British Journal of Psychology, 2024 | - |
dc.identifier.issn | 0007-1269 | - |
dc.identifier.uri | http://hdl.handle.net/10722/348381 | - |
dc.description.abstract | <p>Uncertainty has been a central concept in psychological theories of anxiety. However, this concept has been plagued by divergent connotations and operationalizations. The lack of consensus hinders the current search for cognitive and biological mechanisms of anxiety, jeopardizes theory creation and comparison, and restrains translation of basic research into improved diagnoses and interventions. Drawing upon uncertainty decomposition in Bayesian Decision Theory, we propose a well-defined conceptual structure of uncertainty in cognitive and clinical sciences, with a focus on anxiety. We discuss how this conceptual structure provides clarity and can be naturally applied to existing frameworks of psychopathology research. Furthermore, it allows formal quantification of various types of uncertainty that can benefit both research and clinical practice in the era of computational psychiatry.</p> | - |
dc.language | eng | - |
dc.publisher | Wiley | - |
dc.relation.ispartof | British Journal of Psychology | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | anxiety | - |
dc.subject | Bayesian theory | - |
dc.subject | intolerance of uncertainty | - |
dc.subject | research domain criteria | - |
dc.subject | uncertainty quantification | - |
dc.title | Understanding anxiety through uncertainty quantification | - |
dc.type | Article | - |
dc.identifier.doi | 10.1111/bjop.12693 | - |
dc.identifier.scopus | eid_2-s2.0-85182154527 | - |
dc.identifier.eissn | 2044-8295 | - |
dc.identifier.issnl | 0007-1269 | - |