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Cited by 383

The DOI matches its Crossref record; 109 of the 109 references it cites were found in a registry or an index.

Contributions of Psychophysiology to Media Research: Review and Recommendations

Ravaja, Niklas·2004·Media Psychology
DOI 10.1207/s1532785xmep0602_4
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Abstract

Despite the increasing use of psychophysiological measures in various research areas, there is a relative paucity of studies on communication, media, and media interfaces that have taken advantage of this approach. This article provides an overview of the use of psychophysiological measures of attention and emotion in media research with the focus on 3 most commonly used measures: heart rate, facial electromyography, and electrodermal activity. Selected media studies that have used psychophysiological methods to test theory-based predictions regarding the role of attentional and emotional factors in message processing are critically reviewed. The article also highlights some methodological and other issues critical for the successful application of psychophysiological methods to problems in media research. In particular, respiratory sinus arrhythmia (RSA), a selective index of parasympathetic nervous system activity, is introduced as a measure that holds particular promise for media research, given that RSA is highly sensitive to changes in attention.

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Metadata

Authors
Ravaja, N.
Venue
Media Psychology
Publisher
Informa UK Limited
Published
2004-05
Volume
6
Issue
2
Pages
193-235
ISSN
  • 1521-3269 (ISSN-L)
  • 1532-785X
DOI
10.1207/s1532785xmep0602_4
OpenAlex
W2040004674
Cited by
383
References
109
FWCI
6.61
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Contributions of Psychophysiology to Media Research: Review and Recommendations. https://app.cochat.ai/papers/10.1207/s1532785xmep0602_4
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Ravaja, N. (2004). Contributions of Psychophysiology to Media Research: Review and Recommendations. Media Psychology. https://doi.org/10.1207/s1532785xmep0602_4

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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.