The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
Virtual Self-Modeling: The Effects of Vicarious Reinforcement and Identification on Exercise Behaviors
Abstract
Social cognitive theory is often implemented when researchers develop treatments and campaigns for health behavior change. Immersive virtual environment technology (IVET) enables novel explorations of health behavior modeling. In Study 1, participants were randomly assigned to one of three treatments: vicarious reinforcement, in which a virtual representation of the physical self (VRS) gained or lost weight in accordance with participants' physical exercise; an unchanging VRS; or no virtual representation. The reinforcement group performed significantly more exercise in a voluntary phase than those in other conditions. Study 2 separated reward (weight loss) from punishment (weight gain) and also explored model identification by contrasting the effects of a VRS with a VRO (virtual representation of an other); participants exercised significantly more when they viewed the VRS, regardless of whether reward or punishment was shown. In Study 3, participants were exposed to either a VRS running on a treadmill, a VRO running, or a VRS loitering, and we examined effects 24 hours after the experiment. Follow-up surveys revealed that participants in the VRS-running condition demonstrated significantly higher levels of exercise than those in other conditions. We discuss implications for media use and health communication.
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How Immersive Is Enough? A Meta-Analysis of the Effect of Immersive Technology on User Presence
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Hershfield, H. E., Goldstein, D. G., Sharpe, W. F., Fox, J., Yeykelis, L., Carstensen, L. L., & Bailenson, J. N. (2011) · Journal of Marketing Research · doi:10.1509/jmkr.48.spl.s23 · Cited by 686
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Metadata
- Authors
- Fox, J., & Bailenson, J. N.
- Venue
- Media Psychology
- Publisher
- Informa UK Limited
- Published
- 2009-02-26
- Volume
- 12
- Issue
- 1
- Pages
- 1-25
- ISSN
- 1521-3269 (ISSN-L)
- 1532-785X
- OpenAlex
- W2117442693
- Cited by
- 493
- References
- 51
- FWCI
- 528.76
- 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).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.