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Moderation of cognition‐intention and cognition‐behaviour relations: A meta‐analysis of properties of variables from the theory of planned behaviour

Cooke, Richard, Sheeran, Paschal·2004·British Journal of Social Psychology

Abstract

Meta‐analysis was used to quantify the moderating effects of seven properties of cognitions—accessibility, temporal stability, direct experience, involvement, certainty, ambivalence and affective‐cognitive consistency—on cognition‐intention and cognition‐behaviour relations. Literature searches revealed 44 studies that could be included in the review. Findings showed that all of the properties, except involvement, moderated attitude‐behaviour consistency. Similarly, all relevant moderators improved the consistency between intentions and behaviour. Temporal stability moderated PBC‐behaviour relations, certainty moderated subjective norm‐intention relations, and ambivalence, certainty, and involvement all moderated attitude‐intention relations. Overall, temporal stability appeared to be the strongest moderator of cognition‐behaviour relations.

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Metadata

Authors
Cooke, R., & Sheeran, P.
Venue
British Journal of Social Psychology
Publisher
Wiley
Published
2004-06
Volume
43
Issue
2
Pages
159-186
ISSN
  • 0144-6665 (ISSN-L)
  • 2044-8309
OpenAlex
W2119403113
Cited by
446
References
0
FWCI
16.82
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Moderation of cognition‐intention and cognition‐behaviour relations: A meta‐analysis of properties of variables from the theory of planned behaviour. https://app.cochat.ai/papers/10.1348/0144666041501688
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Cooke, R., & Sheeran, P. (2004). Moderation of cognition‐intention and cognition‐behaviour relations: A meta‐analysis of properties of variables from the theory of planned behaviour. British Journal of Social Psychology. https://doi.org/10.1348/0144666041501688

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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.