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Cited by 173

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Risk Assessment and Animal Models of Anxiety

Blanchard, D. C., Blanchard, R. J., Rodgers, R. J.·1991·Animal Models in Psychopharmacology

Abstract

Analysis of the pattern of defensive behaviours in semi-natural situations suggests a long-duration process in which high level freezing/movement arrest gradually gives way to active risk assessment activities, terminating with a gradual return to nondefensive behaviours. Risk assessment is conceptualized as the key feature in this process, with the information obtained by these oriented scanning and exploratory activities providing feedback to reduce the subject’s initial high level of defensiveness. Risk assessment measures derived from this analysis are selectively responsive to classic anxiolytics. Examination of a range of commonly used measures of anxiolytic action suggest that many of these contain clear elements of the risk assessment process. Furthermore, variation in the results obtained in these tests might be profitably analyzed in terms of some of the features of risk assessment and other aspects of the defense pattern seen to partial or potential threat stimuli.

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Metadata

Authors
Blanchard, D. C., Blanchard, R. J., & Rodgers, R. J.
Venue
Animal Models in Psychopharmacology
Published
1991
Pages
117-134
OpenAlex
W2103243304
Cited by
173
References
3
FWCI
5.48
Type
book chapter
Language
en
Open access
closed

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CoChat. (2026). Citation check: Risk Assessment and Animal Models of Anxiety. https://app.cochat.ai/papers/10.1007/978-3-0348-6419-0_13
The paper
Blanchard, D. C., Blanchard, R. J., & Rodgers, R. J. (1991). Risk Assessment and Animal Models of Anxiety. Animal Models in Psychopharmacology. https://doi.org/10.1007/978-3-0348-6419-0_13

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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.