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Updated: Jan 17, 2026

Reducing State Anxiety Using Working Memory Maintenance
Published on: July 19, 2017
A Data-Driven Decomposition of Anxiety
Andreas Buchmann1,2, Adrian Hase1, Christopher Johannes Ritter3,4
1Unit of Psychiatry Research, University of Fribourg, Fribourg, Switzerland.
Introduction:
The present paper identified key components of anxiety and fear based on a large community sample of 387 psychiatrically healthy or depressed participants.
Methods:
Subfactors were defined based on a principal component analysis with promax rotation and characterized via correlations with other psychiatric as well as physiological and volumetric indicators collected in this large study.
Results:
The key components were labeled "discomfort," "fright," "nervousness," "lack of self-confidence," and "worry." We discuss the components according to their organizational complexity, but also in terms of their affective and motivational content.
Conclusion:
The components may be useful for future research, as they are based on three of the most-used psychiatric questionnaires assessing anxiety and fear symptoms.
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