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Cited by 1,428

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Attention and Performance

Pashler, Harold, Johnston, James C., Ruthruff, Eric·2001·Annual Review of Psychology

Abstract

▪ Abstract Recent progress in the study of attention and performance is discussed, focusing on the nature of attentional control and the effects of practice. Generally speaking, the effects of mental set are proving more pervasive than was previously suspected, whereas automaticity is proving less robust. Stimulus attributes (e.g. onsets, transients) thought to have a “wired-in” ability to capture attention automatically have been shown to capture attention only as a consequence of voluntarily adopted task sets. Recent research suggests that practice does not have as dramatic effects as is commonly believed. While it may turn out that some mental operations are automatized in the strongest sense, this may be uncommon. Recent work on task switching is also described; optimal engagement in a task set is proving to be intimately tied to learning operations triggered by the actual performance of a new task, not merely the anticipation of such performance.

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Metadata

Authors
Pashler, H., Johnston, J. C., & Ruthruff, E.
Venue
Annual Review of Psychology
Published
2001-02
Volume
52
Issue
1
Pages
629-651
ISSN
  • 0066-4308 (ISSN-L)
  • 1545-2085
OpenAlex
W2102812780
Cited by
1,428
References
10
FWCI
2.16
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Attention and Performance. https://app.cochat.ai/papers/10.1146/annurev.psych.52.1.629
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Pashler, H., Johnston, J. C., & Ruthruff, E. (2001). Attention and Performance. Annual Review of Psychology. https://doi.org/10.1146/annurev.psych.52.1.629

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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.