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Cited by 198

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Fear and anxiety as separable emotions: An investigation of the revised reinforcement sensitivity theory of personality.

Perkins, Adam M., Kemp, Samantha E., Corr, Philip J.·2007·Emotion

Abstract

The Gray and McNaughton (2000) theory draws on a wide range of animal data to hypothesize that the emotions of fear and anxiety are separable. The authors tested their hypothesis in two studies. The first study examined associations between scores on questionnaire measures of fear, anxiety, and neuroticism; correlational analysis revealed that fear and anxiety are not interchangeable constructs. The second study examined associations between scores on questionnaire measures of fear/anxiety and performance in a military training setting; regression analysis revealed that fear captured significant variance in performance that was not shared with anxiety. These results imply that hypotheses derived from nonhuman animal data may hold important implications for understanding human emotion and motivation, especially in relation to fear and anxiety.

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Metadata

Authors
Perkins, A. M., Kemp, S. E., & Corr, P. J.
Venue
Emotion
Published
2007
Volume
7
Issue
2
Pages
252-261
ISSN
  • 1528-3542 (ISSN-L)
  • 1931-1516
OpenAlex
W2165522458
Cited by
198
References
9
FWCI
12.10
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Fear and anxiety as separable emotions: An investigation of the revised reinforcement sensitivity theory of personality. https://app.cochat.ai/papers/10.1037/1528-3542.7.2.252
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Perkins, A. M., Kemp, S. E., & Corr, P. J. (2007). Fear and anxiety as separable emotions: An investigation of the revised reinforcement sensitivity theory of personality. Emotion. https://doi.org/10.1037/1528-3542.7.2.252

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.