Abstract
This survey was conducted in 2017 to investigate factors influencing social risk perception of biotechnologists and plant breeders in training toward GM food based on a conceptual model. A random sample of 210 biotechnologists and plant breeders in training was studied. Confirmatory factor analysis and the reliability tests (Cronbach’s alpha) have been used to verify the uni-dimensionality of the measurement scale, SEM also was carried out to determine the most parsimonious models with the best fit for social risk perception of GM foods and path analysis was conducted to understand the exogenous variables introduced in the research model. The findings revealed that the engineers in training had moderate social risk perception regarding GM foods. Moreover, the results of structural equation modeling showed the capability of the model in predicting the social risk perceptions of engineers in training. The psychological attributes of risks, social benefit perception, attitude toward using technology, level of religiosity, and moral and ethical beliefs emerged as the most powerful predictors of the social risk perception. The social benefit perception and attitude toward using technology also mediated the effects of psychological attributes of risks, level of religiosity, and moral and ethical beliefs. The social benefit perception also had an indirect influence on the engineers in training’s social risk perception of GM foods. Finally, we recommend the application of the model developed by this study for better understanding of social risk perception of stakeholders to have a more informed view of the development and promotion of GM foods.
Similar content being viewed by others
References
Aerni, P. (2005). Stakeholder attitudes towards the risks and benefits of genetically modified foods in South Africa. Environmental Science & Policy,8(5), 464–476.
Aiken, L. R. (1997). Psychological testing and assessment (9th ed.). Needham Heights, MA: Allyn & Bacon.
Amin, L., Azad, M. A. K., Gausmian, M. H., & Zulkifli, F. (2014). Determinants of public attitudes to genetically modified salmon. PLoS ONE,9(1), e86174. https://doi.org/10.1371/journal.pone.0086174.
Angulo, A. M., & Gil, J. M. (2007). Spanish consumers’ attitudes and acceptability towards GM food products. Agricultural Economics Review,8(1), 50–63.
Awang, Z. (2012). Structural equation modeling using AMOS graphic. Shah Alam: Penerbit Universiti Teknologi MARA Publication Center.
Azadi, H., Ghanian, M., Ghuchani, O. M., Rafiaani, P., Taning, C. N. T., Hajivand, R. Y., et al. (2015). Genetically modified foods: Towards agricultural growth, agricultural development, or agricultural sustainability? Food Reviews International,31(3), 195–221.
Azadi, H., Talsma, N., Ho, P., & Zarafshani, K. (2011). GM foods in Ethiopia: A realistic way to increase agricultural performance? Trends in Biotechnology,29(1), 6–8.
Balzekiene, A., Telesiene, A., & Butkeviciene, E. (2014). Food risk perceptions and purchasing behaviour in Lithuania: Towards a culture of fear? Corvinus Journal of Sociology and Social Policy,5(1), 61–88.
Barlett, J. E., Kotrlik, J. W., & Higgins, C. C. (2001). Organizational research: Determining appropriate sample size in survey research. Information Technology, Learning, And Performance Journal,19(1), 43–50.
Baruch, Y., & Holtom, B. (2008). Survey response rate levels and trends in organizational research. Human Relations,61(8), 1139–1160.
Beck, U., Bonss, W., & Lau, Ch. (2003). The theory of reflexive modernization: Problematic, hypotheses and research programme. Theory, Culture & Society,20(2), 1–33.
Bredahl, L. (2001). Determinants of consumer attitudes and purchase intentions with regard to genetically modified food–results of a cross-national survey. Journal of Consumer Policy,24(1), 23–61.
Brown, V. J. (2014). Risk perception: It’s personal. Environmental Health Perspectives,122(10), A276–A279. https://doi.org/10.1289/ehp.122-A276.
Bueno, P. B. (2008). Social risks in aquaculture. In M. G. Bondad-Reantaso, J. R. Arthur, & R. P. Subasinghe (Eds.), Understanding and applying risk analysis in aquaculture. FAO Fisheries and Aquaculture technical paper (no. 519, pp. 209–228). Rome: FAO.
Byrne, B. M. (2010). Structural equation modeling with AMOS: Basic concepts, applications, and programming (2nd ed.). Mahwah, NJ: Erlbaum.
Chen, M. F. (2008). An integrated research framework to understand consumer attitudes and purchase intentions toward genetically modified foods. British Food Journal,110(6), 559–579.
Chen, M. F., & Li, H. L. (2007). The consumer’s attitude toward genetically modified foods in Taiwan. Food Quality and Preference,18(4), 662–674.
Chern, W. S., Rickertsen, K., Tsuboi, N., & Fu, T. (2002). Consumer acceptance and willingness to pay for genetically modified vegetable oil and salmon: A multiple-country assessment. AgBioForum,5(3), 105–112.
Connor, M., & Siegrist, M. (2010). Factors influencing people’s acceptance of gene technology: The role of knowledge, health expectations, naturalness, and social trust. Science Communication,32(4), 514–538.
Dunlap, R. E., Van Liere, K. D., Mertig, A. G., & Jones, R. E. (2000). Measuring endorsements of the new ecological paradigm: A revised NEP scale. Journal of Social Issues,56(3), 425–442.
Fader, M., Gerten, D., Krause, M., Lucht, W., & Gramer, W. (2013). Spatial decoupling of agricultural production and consumption: Quantifying dependences of countries on food imports due to domestic land and water constraints. Environmental Research Letters,8(1), 1–15.
Fischhoff, B., Slovic, P., Lichtenstein, S., Read, S., & Combs, B. (2000). How safe is safe enough? A psychometric study of attitudes toward technological risks and benefits. In P. Slovic (Ed.), Perception of risk (pp. 80–103). London: Earthscan Publications Ltd.
Frewer, L. J., Van der Lans, I., Fischer, A. R. H., Reinders, M. J., Menozzi, D., Zhang, X., et al. (2013). Public perceptions of agri-food applications of genetic modification—A systematic review and meta-analysis. Trends in Food Science & Technology,30(2), 142–145.
Fritz, S., Husmann, D., Wingenbach, G., Rutherford, T., Egger, V., & Wadhwa, P. (2004). Awareness and acceptance of biotechnology issues among youth, undergraduates, and adults. AgBioForum,6(4), 178–184.
Gaskell, G., Allum, N., & Stares, S. (2003). Europeans and biotechnology in 2002, Eurobarometer 58.0. A report to the Directorate General for Research from the project “Life Sciences in European Society”. European Commission, Brussels.
Ghanian, M., Ghoochani, O. M., Kitterlin, M., Jahangiry, S. H., Zarafshani, K., Van Passel, S., et al. (2015). Attitudes of agricultural experts toward genetically modified crops: A case study in southwest Iran. Science and Engineering Ethics,21(4), 1–16.
Ghasemi, S., Karami, E., & Azadi, H. (2013). Knowledge, attitudes and behavioral intentions of agricultural professionals toward genetically modified (GM) foods: A case study in Southwest Iran. Science and Engineering Ethics,19(3), 1201–1227.
Goyal, P., & Gurtoo, S. (2011). Factors influencing public perception of genetically modified organisms. GMO Biosafety Research,2(1), 1–11.
Grunert, K. G., Bredahl, L., & Scholderer, J. (2003). Four questions on European consumers’ attitudes toward the use of genetic modification in food production. Innovative Food Science and Emerging Technologies,4(4), 435–445.
Guehlstorf, C. (2008). Understanding the scope of farmer perceptions of risk: Considering farmer opinions on the use of genetically modified (GM) foods as a stakeholder voice. Policy Journal of Agricultural and Environmental Ethics,21(6), 541–558.
Gursoy, D., & Rutherford, D. G. (2004). Host attitudes toward tourism: An improved structural model. Annals of Tourism Research,31(3), 495–516.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (pp. 1–816). New York: Pearson Prentice Hall.
Hair, J. F., Black, W. C. J. R., Babin, B., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.
Hall, C. (2010). Genetically modified foods and foods: Perceptions of risks. Ph.D. dissertation, The University of Edinburgh.
Hall, C., & Moran, D. (2006). Investigating GM risk perceptions: A survey of anti-GM and environmental campaign group members. Journal of Rural Studies,22(1), 29–37.
Hansen, J., Holm, L., Frewer, L., Robinson, P., & Sandoe, P. (2003). Beyond the knowledge deficit: Recent research into lay and expert attitudes to food risks. Appetite,41(2), 111–121.
Herrick, C. (2005). Cultures of GM: Discourses of risk and labeling of GMOs in the UK and the EU. Area,37(3), 286–294.
Hossain, F., Onyango, B., Schilling, B., Hallman, W., & Adelaja, A. (2003). Product attributes, consumer benefits and public approval of genetically modified foods. Consumer Studies,27(5), 353–365.
Hoyer, W. D., & Macinnis, D. J. (2009). Consumer behavior (5th ed.). Boston: Cengage Learning.
Jabareen, Y. (2015). Theorizing the risk city. In Risk city (Chapter 2, pp. 21–35). Springer. https://doi.org/10.1007/978-94-017-9768-9_2.
Jackson, J., Allum, N., & Gaskell, G. (2006). Bridging levels of analysis in risk perception research: The case of the fear of crime. Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, 7(1), Art. 20. http://nbnresolving.de/urn:nbn:de:0114fqs0601202.
Jacobsen, S. E., Sørensen, M., Pedersen, S. M., & Weiner, J. (2013). Feeding the world: Genetically modified foods versus agricultural biodiversity. Agronomy for Sustainable Development,33(4), 651–662.
Kasperson, R. E. (2012). A perspective on the social amplification of risk. The Bridge,42(3), 23–27.
Kim, R. B. (2012). Consumer attitude of risk and benefits toward genetically modified (GM) foods in South Korea: Implications for food policy. Engineering Economics,23(2), 189–199.
Latifah, A., Jamaluddin, M. J., Rahim, M. N. A., Mohamad, O., & Nor, M. M. (2006). Factors affecting public attitude toward genetically modified food in Malaysia. Sains Malaysiana,35(1), 51–55.
Maghari, B. M., & Ardekani, A. M. (2011). Genetically modified foods and social concerns. Avicenna Journal of Medical Biotechnology,3(3), 109–117.
Magnusson, M. K., & Hursti, U. K. (2002). Consumer attitudes towards genetically modified food. Appetite,39(1), 9–24.
Metoyer-Duran, C. (1993). Information gatekeepers. In M. Williams (Ed.), Annual review of information science & technology (Vol. 28, pp. 111–150). Medford, NJ: Learned Information.
Miles, S., & Frewer, L. J. (2003). Public perception of scientific uncertainty in relation to food hazards. Journal of Risk Research,6(3), 267–283.
Ng, R., & Rayner, S. (2010). Integrating psychometric and cultural theory approaches to formulate an alternative measure of risk perception. Innovation: The European Journal of Social Science Research,23(2), 85–100.
Nordgard, L., Bohn, T., Gillund, F., Gronsberg, I. M., Iversen, M., Myhr, A. I., et al. (2015). Uncertainty and knowledge gaps related to environmental risk assessment of GMOs. Genok biosafety report 2015/03. https://doi.org/10.13140/RG.2.1.1947.7847.
Nuffield Council on Bioethics. (2003). The use of genetically modified crops in developing countries. A follow-up discussion paper (Chapter 4, pp. 45–61). http://nuffieldbioethics.org/wp-content/uploads/GM-Crops-Discussion-Paper-2003.pdf.
Poncet, S. (2008). Biotechnology approaches to developing herbicide tolerance/selectivity in foods. http://team.univparis1.fr/teamperso/sponcet/SciencesPo/Slides_DevtEco1.pdf.
Poortinga, W., & Pidgeon, N. (2003). Public perceptions of risk, science and governance. Main findings of a British survey on five risk cases (technical report). Norwich: Centre for Environmental Risk. http://www.psych.cf.ac.uk/understandingrisk/docs/survey2002.pdf.
Prati, G., Pietrantoni, L., & Zani, B. (2012). The prediction of intention to consume genetically modified food: Test of an integrated psychosocial model. Food Quality and Preference,25(2), 163–170.
Renn, O. (2008). Risk governance: Coping with uncertainty in a complex world. London: Earthscan.
Salleh, A. (2008). The fourth estate and the fifth branch: The news media, GM risk, and democracy in Australia. New Genetics and Society,27(3), 233–250.
Schwartzman, R., Ross, D. G., & Berube, D. M. (2011). Rhetoric and risk. Poroi Journal,7(1), 1–9.
Shiva, V. (2000). Stolen Harvest: The hijacking of the global food supply. Cambridge: South End Press.
Siegrist, M. (2001). Poorer European countries are less concerned about biotechnology than richer countries. Risk: Health, Safety and Environment,12(1), 29–39.
Siegrist, M. (2003). Perception of gene technology and food risks: Results of a survey in Switzerland. Risk Research,6(1), 45–60.
Siegrist, M., Keller, C., & Kiers, H. A. (2005). A new look at the psychometric paradigm of perception of hazards. Risk Analysis,25(1), 211–222.
Siegrist, M., Keller, C., & Kiers, H. (2006). Lay people’s perception of food hazards: Comparing aggregated data and individual data. Appetite,47(3), 324–332.
Sjoberg, L. (2000). Factors in risk perception. Risk Analysis,20(1), 1–11.
Slovic, P. (2000). Perception of risk. London: Earthscan Publications Ltd.
Smith, C. M., Peterson, J. M., Leatherman, J. C., & Williams, J. R. (2012). Simulation of factors impeding water quality trading. The Journal of Regional Analysis and Policy,42(2), 162–176.
Spetsidis, N. M., & Schamel, G. (2002). A consumer based approach towards new product development through biotechnology in the agro-food sector. In V. Santaniello, R. E. Evenson, & D. Zilberman (Eds.), Market development for genetically modified foods (pp. 63–79). Wallingford: CABI Publishing.
Toms, B. (2013). Ethical concerns in plant biotechnological research. International Journal of Biotechnology and Bioengineering Research,4(3), 197–204.
Traill, W. B., Jaeger, S. R., Yee, W. M., Valli, C., House, L. O., Lusk, J. L., et al. (2005). Categories of GM risk-benefit perceptions and their antecedents. AgBioForum,7(4), 176–186.
Vicsek, L. (2013). Gene-fouled or gene-improved? Media framing of GM crops and food in Hungary. New Genetics and Society,32(1), 54–77.
Vilella-Vila, M., & Costa-Font, J. (2008). Press media reporting effects on risk perceptions and attitudes towards genetically modified (GM) food. The Journal of Socio-Economics,37(5), 2095–2106.
Wheeler, S. (2009). Exploring the influences on Australian agricultural professionals’ genetic engineering beliefs: An empirical analysis. Technology Transfer,34(4), 422–439.
Wickson, F. (2007). From risk to uncertainty in the regulation of GMOs: Social theory and Australian practice. New Genetics and Society,26(3), 325–339.
Wirz, C. D., Xenos, M. A., Brossard, D., Scheufele, D., Chung, J. H., & Massarani, L. (2018). Rethinking social amplification of risk: Social media and zika in three languages. Risk Analysis,38(12), 2599–2624. https://doi.org/10.1111/risa.13228.
Yang, J. (2013). A comparative study of American and Chinese college students’ social trust, conspiracy beliefs, and attitudes toward genetically modified crop. Graduate theses and dissertations. Paper 13282 (pp. 1–78). Iowa State University.
Zandvoort, H. (2005). Good engineers need good laws. European Journal of Engineering Education,30(1), 21–36.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Ghasemi, S., Ahmadvand, M., Karami, E. et al. Social Risk Perceptions of Genetically Modified Foods of Engineers in Training: Application of a Comprehensive Risk Model. Sci Eng Ethics 26, 641–665 (2020). https://doi.org/10.1007/s11948-019-00110-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11948-019-00110-6