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Cited by 1,092

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

The Influence of Trust and Perceptions of Risks and Benefits on the Acceptance of Gene Technology

Siegrist, Michael·2000·Risk Analysis

Abstract

A causal model explaining acceptance of gene technology was tested. It was hypothesized that trust in institutions using gene technology or using modified products has a positive impact on perceived benefit and a negative influence on perceived risk of this technology. Furthermore, perceived benefit and perceived risk determine acceptance of biotechnology. In other words, trust has an indirect influence on the acceptance of the technology. The postulated model was tested using structural equation modeling procedures and data from a random quota sample of 1001 Swiss citizens between 18 and 74 years old. Results indicated that the proposed model fits the data very well. The same causal model explains females' and males' acceptance of gene technology. Gender differences were found for the latent variables trust, perceived benefit, and acceptance of gene technology. Females indicated more trust, perceived less benefit, and demonstrated less acceptance than did males. No significant difference was observed for perceived risk. The implications of the results are discussed.

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Metadata

Authors
Siegrist, M.
Venue
Risk Analysis
Publisher
Wiley
Published
2000-04
Volume
20
Issue
2
Pages
195-204
ISSN
  • 0272-4332 (ISSN-L)
  • 1539-6924
OpenAlex
W2076518901
Cited by
1,092
References
2
FWCI
40.54
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Influence of Trust and Perceptions of Risks and Benefits on the Acceptance of Gene Technology. https://app.cochat.ai/papers/10.1111/0272-4332.202020
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Siegrist, M. (2000). The Influence of Trust and Perceptions of Risks and Benefits on the Acceptance of Gene Technology. Risk Analysis. https://doi.org/10.1111/0272-4332.202020

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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.