The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Pathways to Persuasion: Cognitive and Experiential Responses to Health-Promoting Mass Media Messages
Abstract
The experience of transportation—being absorbed in a narrative—and its relationship to persuasion were considered in two studies exploring responses to health-promoting mass media messages. Following Epstein’s (1994) cognitive-experiential self-theory, two pathways to persuasion were considered: cognitive and experiential. In Study 1 ( n = 121), smokers who experienced increased transportation in response to antismoking messages reported that they would make a greater effort to quit smoking, and this effect was mediated by both experiential (emotional and self-referencing) and cognitive responses to the messages. In Study 2 ( n = 110), experiential responses to magazine messages promoting skin protection were related to intentions to protect oneself, and this effect was mediated by feelings of risk.The implications of these results are discussed in terms of principles for effective health communication campaigns as well as theoretical advances in narrative persuasion in the context of health communication.
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Cites
Lazarus, R. S. (1991) · doi:10.1093/oso/9780195069945.001.0001 · Cited by 12,691
The Elaboration Likelihood Model of Persuasion
Petty, R. E., & Cacioppo, J. T. (1986) · Advances in Experimental Social Psychology · doi:10.1016/s0065-2601(08)60214-2 · Cited by 8,822
The Health Belief Model: a decade later.
Janz, N. K., & Becker, M. H. (1984) · Health Education Quarterly · doi:10.1177/109019818401100101 · Cited by 8,437
Episodic memory: from mind to brain
Tulving, E. (2002) · Annual Review of Psychology · doi:10.1146/annurev.psych.53.100901.135114 · Cited by 4,950
The role of transportation in the persuasiveness of public narratives.
Green, M. C., & Brock, T. C. (2000) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.79.5.701 · Cited by 4,861
Putting the fear back into fear appeals: the extended parallel process model
Witte, K. (1992) · Communication Monographs · doi:10.1080/03637759209376276 · Cited by 3,880
A Meta-Analysis of Fear Appeals: Implications for Effective Public Health Campaigns
Witte, K., & Allen, M. (2000) · Health Education & Behavior · doi:10.1177/109019810002700506 · Cited by 3,216
Integration of the cognitive and the psychodynamic unconscious
Epstein, S. (1994) · American Psychologist · doi:10.1037/0003-066x.49.8.709 · Cited by 2,883
The Function of Fiction is the Abstraction and Simulation of Social Experience
Mar, R. A., & Oatley, K. (2008) · Perspectives on Psychological Science · doi:10.1111/j.1745-6924.2008.00073.x · Cited by 1,345
Stalking the elusive “vividness” effect
Taylor, S. E., & Thompson, S. C. (1982) · Psychological Review · doi:10.1037/0033-295x.89.2.155 · Cited by 913
Cited by
Impact of narratives on persuasion in health communication: a meta-analysis
Shen, F., Sheer, V. C., & Li, R. (2015) · Journal of Advertising · doi:10.1080/00913367.2015.1018467 · Cited by 574
Braddock, K., & Dillard, J. P. (2016) · Communication Monographs · doi:10.1080/03637751.2015.1128555 · Cited by 568
The Transportation Scale–Short Form (TS–SF)
Appel, M., Gnambs, T., Richter, T., & Green, M. C. (2015) · Media Psychology · doi:10.1080/15213269.2014.987400 · Cited by 309
Perceived Realism: Dimensions and Roles in Narrative Persuasion
Cho, H., Shen, L., & Wilson, K. (2014) · Communication Research · doi:10.1177/0093650212450585 · Cited by 244
Automating the News: How Personalized News Recommender System Design Choices Impact News Reception
Beam, M. A. (2014) · Communication Research · doi:10.1177/0093650213497979 · Cited by 159
Metadata
- Authors
- Dunlop, S. M., Wakefield, M., & Kashima, Y.
- Venue
- Communication Research
- Publisher
- SAGE Publications
- Published
- 2009-12-01
- Volume
- 37
- Issue
- 1
- Pages
- 133-164
- ISSN
- 0093-6502 (ISSN-L)
- 1552-3810
- OpenAlex
- W2143785320
- Cited by
- 237
- References
- 12
- FWCI
- 200.79
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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