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Cited by 225

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

The relationship between traffic congestion, driver stress and direct versus indirect coping behaviours

HENNESSY, DWIGHT A., WIESENTHAL, DAVID L.·1997·Ergonomics

Abstract

Drivers experiencing rush hour congestion were interviewed using cellular telephones to study stress and coping responses. Measures were taken of each driver's predisposition to stress (trait stress) as well as their reactions to the experience of either low or high traffic congestion (state stress). Two interviews were conducted during the trip when drivers experienced both low and high congestion conditions. Although state stress was greatest for all drivers experiencing the high congestion condition, a trait X situation interaction was obtained, indicating that stress levels were highest for high trait stress drivers experiencing the congested roadway. In terms of trait coping behaviours, participants indicated a preference for direct over indirect behaviours. A greater variety of direct and indirect behaviours were reported in high congestion. Reports of aggressive behaviours showed the greatest increase from low to high congestion. Comments on the use of cellular telephones in methodology are offered.

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Metadata

Authors
HENNESSY, D. A., & WIESENTHAL, D. L.
Venue
Ergonomics
Published
1997-03
Volume
40
Issue
3
Pages
348-361
ISSN
  • 0014-0139 (ISSN-L)
  • 1366-5847
OpenAlex
W2052908944
Cited by
225
References
1
FWCI
17.17
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The relationship between traffic congestion, driver stress and direct versus indirect coping behaviours. https://app.cochat.ai/papers/10.1080/001401397188198
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HENNESSY, D. A., & WIESENTHAL, D. L. (1997). The relationship between traffic congestion, driver stress and direct versus indirect coping behaviours. Ergonomics. https://doi.org/10.1080/001401397188198

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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.