{"title":"Public opinion outweighs knowledge: A dual-process framework for understanding acceptance of genetic modification among scientists and laypeople.","authors":"Anfan Chen, Xing Zhang, Jianbin Jin","doi":"10.1111/risa.17704","DOIUrl":null,"url":null,"abstract":"<p><p>Communication research on scientific issues has traditionally relied on the deficit model, which posits that increasing scientific knowledge leads to public acceptance. However, this model's effectiveness is questioned due to inconclusive impacts of knowledge on acceptance. To address this, we propose a dual-process framework combining the deficit model (with scientific knowledge as a key predictor) and a normative opinion process model (where perceived majority opinion plays a crucial role) to predict people's risk/benefit perceptions and their support for genetic modification (GM). Using two national surveys in mainland China-Study 1 with 5145 laypeople and Study 2 with 12,268 scientists-we found positive and significant correlations between scientific knowledge or perceived majority opinion and GM support, mediated by risk/benefit perceptions. Importantly, the normative pathway-represented by perceived majority opinion-exerts a stronger direct and indirect impacts on GM support than scientific knowledge across both scientists and laypeople. Moreover, while the normative process shows a greater influence than the informative process on individuals' perceptions of both benefits and risks associated with GM, its prominence differs between scientists and laypeople depending on the types of perceptions-scientists are more sensitive to risk-related social norms, whereas laypeople are more concerned with norms related to benefits. The paper concludes with a discussion on the theoretical and practical implications of these findings.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":" ","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Risk Analysis","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/risa.17704","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Communication research on scientific issues has traditionally relied on the deficit model, which posits that increasing scientific knowledge leads to public acceptance. However, this model's effectiveness is questioned due to inconclusive impacts of knowledge on acceptance. To address this, we propose a dual-process framework combining the deficit model (with scientific knowledge as a key predictor) and a normative opinion process model (where perceived majority opinion plays a crucial role) to predict people's risk/benefit perceptions and their support for genetic modification (GM). Using two national surveys in mainland China-Study 1 with 5145 laypeople and Study 2 with 12,268 scientists-we found positive and significant correlations between scientific knowledge or perceived majority opinion and GM support, mediated by risk/benefit perceptions. Importantly, the normative pathway-represented by perceived majority opinion-exerts a stronger direct and indirect impacts on GM support than scientific knowledge across both scientists and laypeople. Moreover, while the normative process shows a greater influence than the informative process on individuals' perceptions of both benefits and risks associated with GM, its prominence differs between scientists and laypeople depending on the types of perceptions-scientists are more sensitive to risk-related social norms, whereas laypeople are more concerned with norms related to benefits. The paper concludes with a discussion on the theoretical and practical implications of these findings.
期刊介绍:
Published on behalf of the Society for Risk Analysis, Risk Analysis is ranked among the top 10 journals in the ISI Journal Citation Reports under the social sciences, mathematical methods category, and provides a focal point for new developments in the field of risk analysis. This international peer-reviewed journal is committed to publishing critical empirical research and commentaries dealing with risk issues. The topics covered include:
• Human health and safety risks
• Microbial risks
• Engineering
• Mathematical modeling
• Risk characterization
• Risk communication
• Risk management and decision-making
• Risk perception, acceptability, and ethics
• Laws and regulatory policy
• Ecological risks.