Social acceptance of genetic engineering technology

Genetic engineering of animals has been proposed to address societal problems, but public acceptance of the use of this technology is unclear. Previous work has shown that the source of information proposing the technology (e.g. companies, universities), the term used to describe the technology (e.g. genome editing, genetic modification), and the genetic engineering application (e.g. different food products) affects technology acceptance. We conducted three mixed-method surveys and used a causal trust-acceptability model to understand social acceptance of genetic engineering (GE) by investigating 1) the source of information proposing the technology, 2) the term used to describe the technology, and 3) the GE application for farm animals proposed. Further, participants expressed their understanding of technology using a range of terms interchangeably, all describing technology used to change an organism's DNA. We used structural equation modelling and confirmed model fit for each survey. In each survey, perceptions of benefit had the greatest effect on acceptance. Following our hypothesized model, social trust had an indirect influence on acceptance through similar effects of perceived benefit and perceived risk. Additional quantitative analysis showed that the source of information and technology term had little to no effect on acceptance. Applications involving animals were perceived as less beneficial than a plant application, and an application for increased cattle muscle growth was perceived as more risky than a plant application. When assessing the acceptability of applications participants considered impacts on plants, animals, and people, trust in actors and technologies, and weighed benefits and drawbacks of GE. Future work should consider how to best measure acceptability of GE for animals, consider contextual factors and consider the use of inductive frameworks.

Automated summary

Through three mixed-method surveys, we found that the source of information, technology term, and application domain all affect the social acceptance of genetic engineering (GE). The perception of benefits has the greatest impact on acceptance, with social trust influencing acceptance through perceived benefits and risks. The source of information and technology term had minimal effect on acceptance. Applications involving animals were seen as less beneficial and more risky compared to plant applications. Assessing the acceptability of GE applications requires considering the impacts on plants, animals, and people, as well as trust in actors and technologies, and weighing the benefits and drawbacks of GE. Future research should focus on measuring acceptability of GE for animals, considering contextual factors, and utilizing inductive frameworks.