Protection Motivation and Communication through Nanofood Labels

Abstract

The development and use of nanotechnology in the food industry (nanofood) have grown steadily. While visions for nanofood suggest that the applications will improve quality and safety, they are also controversial for several reasons including potential health risks coupled with difficulty in assessing low-dosage nanoparticle risks as well as values-based objections. In recent years, debate over nanofoods has sparked inquiry into factors that predict public attitudes and purchase intentions. Such studies have investigated the roles of demographics and sociographics, value predispositions toward science and technology, preferences for natural products, trust in regulatory agencies, scientific knowledge, and media attention. This study assesses the role of each of these factors in shaping public attitudes toward nanofood and improves the predictive models by evaluating concepts from protection motivation theory. We find that incorporating threat and coping appraisals provides the best predictive models of public attitudes and intention to purchase nanofood products.

Keywords

nanofood food labels risk protection motivation

Emerging technologies that involve food often evoke controversy about safety and ethical standards of application (Yue, Zhao, Cummings, et al. 2015). The development and use of various nanotechnology applications in the food industry (nanofood) have been growing steadily in recent years (Zhou 2013). Globally, the food industry is worth well over US$4 trillion annually (Murray 2007), and efforts to improve the quality and safety of food through the use of nanotechnology are significant. The global market value for nano-enabled food products was estimated to be around US$20 billion in 2010, and nanofood developments are led by the United States, followed by Asian countries that are expected to become the biggest future markets for such food products (Helmut Kaiser Consultancy 2004). Current applications of nanotechnology to the food industry are being promoted among “the most promising technologies to revolutionize conventional food science and the food industry” (He and Hwang 2016, 671). In its entirety, nanotechnology is projected to have a global impact of around US$1 trillion by 2020 (Roco et al. 2011).

Nanotechnology is the application of engineered particles that fall within 1–100 nanometers in at least one dimension. Such particles are included in consumer goods to serve potentially useful purposes. While not as prevalent as the use of genetic modification in food, nanofood applications are developing rapidly and have been proposed for use or are currently being used to modify food production, food processing, food packaging, shelf life, nutrition, and taste (Shi et al. 2005; Chaudhry, Castle, and Watkins 2010; Chaudhry et al. 2008; Smolander and Chaudry 2010; Chaudhry and Castle 2011; Weiss, Takhistov, and McClemens 2006).

Nanotechnology and nanomaterials have a variety of novel functions and applications in the food industry. For instance, silver nanoparticles and other metal-oxide nanocomposites in food packaging are widely used in the food industry. When added to food packaging, these nanomaterials offer significant improvement over conventional packaging in protecting against biological deterioration and contamination, thus lowering the risks of pathogenic infection among consumers (He and Hwang 2016). Some applications seek to increase the nutritional value of food by using nanomaterials as mechanisms for increasing the bioavailability of supplements and vitamins (Wajda, Zirkel, and Schaffer 2007). Other applications seek to improve shelf life, and even taste, such as the use of nano–zinc-oxide coatings to improve shelf life and slow the oxidative process to control the browning of fresh-cut fruits (Rojas-Graü, Soliva-Fortuny, and Martín-Belloso 2009) or the use of nano-encapsulation techniques to improve sensory perceptions of taste for consumers (Nakagawa 2014).

While visions for nanofood suggest that the applications will improve product quality and safety, such food technologies are also likely to be controversial for several reasons, including potential long-term environmental and human health risks (Oberdörster, Oberdörster, and Oberdörster 2005; Bouwmeester et al. 2009). The small size and low dosage of nanomaterials and uncertainty regarding how such materials may agglomerate, transport, transform, or be taken up by other chemical or biological agents make them difficult to assess in situ and across the “life span” of nanofood products from creation to disposal. Such issues have become primary concerns for scientists and policy analysts who have ongoing efforts to assess risks and analyze, monitor, and predict the life cycle of these materials (Guinée et al. 2017). Nanofoods are also likely to be controversial due to individual values-based objections (Besley, Kramer, and Priest 2008; Yue et al. 2015).

Background and Literature Review

While nanofoods are being developed for use around the world, media coverage of nanotechnology and public understanding of nanotechnology remains low, with a majority (62 percent) of Americans reporting that they have only heard the term “nanotechnology” or that they know nothing at all about nanotechnology (Dudo, Dunwoody, and Scheufele 2011; Harrison 2012). Yet even without a high level of understanding about science or nanotechnology, consumers are faced with making potential health decisions about the products they consume (Berube et al. 2010).

Studies have assessed risk perceptions of nanotechnology and nanofoods in order to better meet the needs for future health and risk communication and governance. Berube et al. (2011) found that nanoparticle risk perceptions are low when compared to other potential health and safety risks, placing nineteenth of twenty-four hazards ranging from nuclear waste and chemical pollution to drinking alcohol, blood transfusions, and cell phone use. Stampfli, Siegrist, and Kastenholz (2010) noted that willingness to buy (WTB) nanofood was more strongly influenced by perceived benefits and lesser so by perceived risks of the product. Yue et al. (2015) noted that US consumers are generally willing to pay more to avoid nanofoods as compared to conventional food products, but consumers would pay even more to avoid genetically modified (GM) foods over other types of food products. Brown and Kuzma (2013) also noted that consumers often make use of values-based judgments when considering nanofood products and that a majority of consumers are reluctant to consume nanofoods but support greater information about nanofoods and would also favor labeling initiatives.

Nucci and Hallman (2015) noted that while nanotechnology is revolutionizing food packaging, the success of such promising technologies hinges upon public perceptions and concerns, and that communication about new developments is likely to play a significant role in public support for legislation and policy regarding the future of nanofood applications. Others have echoed a similar sentiment that individuals make risk decisions about nanotechnology even without a great deal of knowledge in the area and that scholarly understanding of perceptions and risk attitudes toward nanotechnology products is crucial for future health and risk communication initiatives and can inform health campaigning, public engagement initiatives, and decision-making (Berube et al. 2010).

It is from this premise that the current study seeks to expand on previous findings and evaluate how people come to make decisions about nanofoods, both in forming attitudes about nanofood applications and in their intentions to purchase nanofoods. We investigate the influence of many factors that have been previously examined, and we significantly improve upon previous predictive models by evaluating the role of the two major concepts from the protection motivation theory (PMT): threat and coping appraisal (Rogers 1975). Specifically, this study uses a representative sample of Singaporean adults to investigate the degree to which various antecedent personal characteristics, value predispositions, and motivations predict attitudes and purchase intentions of nanofood products.

The existing literature on public attitudes regarding nanofood is complex and includes a variety of investigated factors. We include these factors in our predictive models in order to assess the role of each factor and to investigate their comparative influences. Following the review of previously used factors, we provide information about our novel addition of threat and coping appraisal into the predictive models.

Value Predispositions toward Science and Technology

Attitudes and purchase intentions of nanotechnology applications in the food industry are likely to be influenced by individual beliefs about the broader enterprises of scientific and technological application in general (Yue et al. 2015). We conceptualize technocratic beliefs as an individual’s value predisposition toward the use of technology as a means for improving daily life. This conceptualization is distinct from deference to scientific authority, which is focused more squarely on governance and decision-making rather than reflecting a broader belief regarding the role of technology in society. Individual evaluations of emerging technologies seem to rely on such value predispositions in concert with other factors, such as personal knowledge about the technology itself (Siegrist, Keller, et al. 2007).

Similarly, the public’s attitude toward nanotechnology is also affected by their personal values and knowledge. However, when there is a lack of knowledge about nanotechnology, the general technocratic belief could affect attitudes toward nanotechnology (Siegrist, Keller, et al. 2007). Siegrist, Keller, et al. (2007) suggested that technocratic belief can be divided into two factors—technology benefits and technology fears. Studies found that technocratic belief affected nanotechnology risk perception among laypersons but not among experts (Siegrist 2007a). In addition, Stampfli, Siegrist, and Kastenholz (2010) revealed that perceived technocratic belief was positively associated with perceived benefit of nanotechnology applications, predicting the WTB nanoproducts. Based on the literature above, we propose that technocratic belief could predict attitudes toward nanofood applications and intentions to purchase nanofood.

Hypothesis 1a: Technocratic belief is positively associated with attitude toward nanofood applications.

Hypothesis 1b: Technocratic belief is positively associated with intention to purchase nanofood.

Deference to Scientific Authority

Deference to scientific authority refers to the trust in scientific leaders and institutions to make decisions that impact society (Ho, Brossard, and Scheufele 2008). Some members of society are likely to defer to domain-specific expertise about the use of a particular technology (Lee and Scheufele 2006). Deference to scientific authority may function as a decision heuristic that causes individuals to swiftly process or disregard mediated information when judging the new technology (Kim et al. 2014). Deference to scientific authority has been demonstrated to contribute to public support for nanotechnology (Ho, Scheufele, and Corley 2010; Lee and Scheufele 2006; Liang et al. 2015) as well as to influence risk and benefit perceptions of nanofoods (Siegrist et al. 2008). It follows that this study would similarly expect to find deference to scientific authority to be positively associated with attitudes toward nanofood applications and intentions to purchase nanofood. Our second set of hypotheses is as follows:

Hypothesis 2a: Deference to scientific authority is positively associated with attitude toward nanofood applications.

Hypothesis 2b: Deference to scientific authority is positively associated with intention to purchase nanofood.

Trust in Regulatory Agencies

Besides deference to scientific authority, previous studies have evaluated the influence of trust in regulatory agencies on public attitudes and intentions toward emerging science and technology (e.g., Brossard and Nisbet 2007; Stampfli, Siegrist, and Kastenholz 2010; Siegrist, Keller, et al. 2007; Siegrist, Cousin, et al. 2007; Siegrist et al. 2008). For example, researchers found that trust in biotechnology sponsors, such as government officials, industry representatives, and university scientist, positively affected the support for agricultural biotechnology (Brossard and Nisbet 2007). In the context of nanotechnology, Yue and colleagues (2015) found that trust in governing agencies to manage food technologies did not influence labeling preferences for either nanofoods or genetically modified food products, but that it did influence risk attitudes about the food technologies themselves. These findings were in line with the work of Stampfli and colleagues (2010), which found that social trust was positively associated with perceived benefit of nanotechnology applications and negatively associated with perceived risk of nanotechnology applications. They illustrated that people who have little experience with nanofood are more likely to rely on information presented by industry and regulatory agencies, especially when they are considering purchase intentions of nanofood (Stampfli et al. 2009). Thus, we hypothesize that increased trust in information provided by regulatory agencies will be positively associated with attitudes and purchase intentions of nanofoods:

Hypothesis 3a: Trust in regulatory agencies is positively associated with attitude toward nanofood applications.

Hypothesis 3b: Trust in regulatory agencies is positively associated with intention to purchase nanofood.

Preference for Natural Products

Moral and ethical concerns about the use of technology in the food industry have led to growing preferences for “natural” and organic food products worldwide (J. C. Anderson, Wachenheim, and Lesch 2006). Some researchers have found that individuals are more hesitant to purchase food products that claim nanotechnology additives provide health benefits to consumers (Siegrist, Stampfli, and Kastenholz 2009). They argued that “perceived naturalness,” or lack thereof, is a significant factor that influences willingness to purchase food products including nanofoods. Stampfli et al. (2010) also noted that people who have a preexisting preference for natural products tend to have a higher risk perception of nanofood than those who report no preference. Extending results of previous studies, we propose the following hypotheses:

Hypothesis 4a: Preference for natural products is negatively associated with attitude toward nanofood applications.

Hypothesis 4b: Preference for natural products is negatively associated with intention to purchase nanofood.

General Scientific Knowledge

In addition to values predispositions and preference of natural products, scientific knowledge has been previously considered as a factor contributing to attitudes and purchase intentions of nanofoods. Studies have noted that experts have significantly lower risk perceptions of nanotechnology as compared to nonexperts (Ho et al. 2010; Siegrist, Keller, et al. 2007), and this difference is likely due to the disparate levels of knowledge about nanotechnology (e.g., Lee and Scheufele 2006; Liang et al. 2015). Liang and colleagues (2015) found that specific knowledge about nanotechnology positively predicted public support for nanotechnology funding in Singapore but not in the United States. They found that Singaporeans are more knowledgeable and familiar with nanotechnology, leading to higher support for nanotechnology funding as compared to Americans (Liang et al. 2015). However, little research has focused on the relationship between general scientific knowledge and attitudes toward nanofood applications and intention to purchase nanofood. While not food-specific, Lee, Scheufele, and Lewenstein (2005) found that scientific knowledge was associated with support for nanotechnology in general. However, Ho et al. (2010) found that scientific knowledge did not predict the support for federal funding of nanotechnology. Given the discrepancies in previous findings, as well as this novel application to nanofoods, we believe it is important to further examine the effect of scientific knowledge on the intention to purchase nanofood. Hence, the present study includes a general scientific knowledge block as a potential predictive factor of attitudes and purchase intentions by proposing the following hypotheses:

Hypothesis 5a: Scientific knowledge is positively associated with attitudes toward nanofood applications.

Hypothesis 5b: Scientific knowledge is positively associated with intention to purchase nanofood.

Media Attention

Research has shown that media is the primary source of information about science and technology among the public (Friedman, Dunwoody, and Rogers 1986). Based on the agenda-setting effect (McCombs 2013) and framing effect (Tewksbury et al. 2009), media messages can influence the perceived importance of an issue among the audience as well as shape their attitudes toward the topic.

Results have indicated that newspaper coverage of nanotechnology has been predominantly positive in tone (A. Anderson and Anderson 2009; Lewenstein, Gorss, and Radin 2010; Kjølberg 2009), and its benefits were often highlighted as outweighing its risks (A. Anderson and Anderson 2009; Laing 2005; Stephens 2005). Other studies have demonstrated that nanotechnology is more often framed in terms of scientific discovery, science fiction, and business rather than in terms of risk (A. Anderson et al. 2005; Faber, Mackinnon, and Petroccione 2005; Te Kulve 2006).

Media reports have frequently noted nanotechnology-enabled food packing to be more desirable than when nanoparticles are used as food additives within the product itself (Siegrist, Cousin, et al. 2007; Siegrist et al. 2008). In the UK, media coverage of nanotechnology reports a mix of optimism about the benefits of nanoscience and anxiety about its potential risks associated with nanofood (Wilkinson et al. 2007), while coverage in the United States tends to be more positive overall in tone (Friedman and Egolf 2011; Gaskell et al. 2005; Stephens 2005). Similarly, news stories in the Netherlands and Denmark have predominantly covered the positive and beneficial aspects of nanofood (Kjærgaard 2008; Te Kulve 2006). Given the fact that empirical studies have shown that the tone of media coverage of nanofood can shape public acceptance of nanofood (Gaskell et al. 2005), public attitudes to media messages might be a factor influencing consumers’ attitude toward nanofoods in Singapore. Hence, we propose the following hypotheses:

Hypothesis 6a: Attention to food safety news is positively associated with attitude toward nanofood applications.

Hypothesis 6b: Attention to food safety news is positively associated with intention to purchase nanofood.

Hypothesis 7a: Attention to nanonews is positively associated with attitude toward nanofood applications.

Hypothesis 7b: Attention to nanonews is positively associated with intention to purchase nanofood.

Protection Motivation and Nanofoods

Protection motivation is the term used to refer to individuals’ motivations to engage in protective, adaptive behaviors when confronted with messages that may put them at “disease.” PMT was developed to explain and predict the effects of potential threats on health attitudes and behaviors (Rogers 1975). PMT is organized along two cognitively mediated processes: threat appraisal and coping appraisal (Floyd, Prentice-Dunn, and Rogers 2000). Each process has two components. Threat appraisal evaluates (1) severity of the potential threat, the degree to which an individual believes they will be harmed if they experience the threat and (2) vulnerability to the threat, the perceived likelihood or probability that the individual believes they will experience the potential threat. The process of threat appraisal is dependent upon both features: as both threat severity and vulnerability increase, there is an expected increase in the individuals’ motivation to protect themselves from the potential threat.

Coping appraisal, often referred to as efficacy appraisal, also has two components. Coping appraisal evaluates (1) response efficacy or the degree that a behavior would be efficacious in diminishing a potential threat and (2) self-efficacy or the degree to which an individual feels capable of performing a behavior to diminish a potential threat. Like threat appraisal, coping appraisal is also dependent on these two components and PMT notes that as both response efficacy and self-efficacy increase, so too should protection motivation. The culmination of both threat and coping appraisals is referred to as “protection motivation,” which is theorized as a primary antecedent of intention, and ultimately of behavior. Figure 1 provides a visual organization of PMT.

Previous studies have demonstrated that some members of the public are wary of nanofood and would place such consumer products somewhere between the range of “safe” and “unsafe.” This means that some members of the public view nanofoods as a potential threat, while others do not. Similarly, coping appraisal regarding the response- and self-efficacious use of nanolabels is likely to be different among the population. While untested in this area, we believe that threat and coping appraisal are likely to have significant bearing on how people come to feel both about nanofood purchase intentions and labeling and governance options regarding nanofoods. In this case, where the “jury is still out” regarding nanofoods and public sentiments, it is best to attempt to maximize our scholarly understanding of how people come to make sense of nanofoods. Thus, we propose a research question along with our hypotheses to guide our inquiry:

Research Question: What influence do threat and coping appraisals have on (a) attitudes of nanofood applications and (b) purchase intentions regarding nanofood?

This is the first study to evaluate the role of protection motivation toward nanofood purchase intentions and attitudes toward nanofood applications. As we expect that individuals are likely to process threat and efficacy in distinct ways, we choose to maintain threat and coping appraisals as distinct concepts in order to evaluate their individual roles in cognitive outcomes, as will be further explicated in the Method section of this paper.

Demographics and Sociographics

Past studies demonstrate inconsistent results regarding the influence of demographics and sociographics on attitudes and purchase intentions toward nanofoods and nanotechnology. Contextual and sample population differ drastically between studies and are likely to sway over the observed differences between similar measures. For example, Ho and colleagues (2010) found that age and gender did not predict public support for federal funding of nanotechnology, but religiosity was negatively associated with public support of nanotechnology. Siegrist and colleagues (2008) similarly found that age and gender did not influence nanotechnology perceptions. However, in a cross-cultural study, support for government funding of nanotechnology was negatively predicted by age and religiosity in the United States but not in Singapore (Liang et al. 2015). With regard to food decisions, Worsley, Wang, and Hunter (2013) found that women more consistently consider the nutritional and technological aspects of food products than men. Higher income has also been found to positively influence consumers’ attitudes toward nanofood (Yue et al. 2015). Men have more positive attitudes toward nanofood as compared to women (Yue et al. 2015). Religiosity has also been found to negatively influence acceptance for uses of technology in food products while heightening desires for labeling of food technologies (Chern et al. 2003; Yue et al. 2015). In our study, demographic variables (such as age and gender) and sociographic variables (such as level of education, household income, and religiosity) are used as control variables.

Method

A pretested survey questionnaire¹ (N = 1,001) was conducted online through the professional survey company Qualtrics, Singapore. Participants were asked to complete a short questionnaire evaluating antecedent items pertaining to various independent variables in the study detailed below. After completing this questionnaire, the participants were asked to view the front and back of a hypothetical food package, in this case a box of cereal. The back of the box of cereal contained general information about nanotechnology in food and was designed to be balanced in its risk and benefit portrayal,² similar to other studies where individuals assess a product containing nanoparticles (Cummings 2013). The visual images of the box of cereal can be viewed in Appendix A. Following the viewing of the nanofood, respondents were asked to complete another short questionnaire that evaluated our dependent variables including perceptions of the nanofood as well as cognitive outcomes including purchase intentions, nanofood labeling preferences, and governance options.

Sample Measures

Respondents were recruited from all geographic regions of Singapore to provide a representative sample of the country’s citizens based on quota sampling using the demographic variables gender, age, and monthly household income. Our final sample matched well with recent census targets with respondents ranging from twenty-one to sixty-four years old (M = 37.92, standard deviation [SD] = 10.68). Among them, 51.6 percent were female, median education level was “degree” (equivalent of a bachelor degree in the United States). The median monthly household income ranged from US$6,000 to US$6,999 (US$4,300–US$5,000). Our response rate, defined by the number of completed questionnaires divided by the number of qualifying panelists invited to participate, was 30.8 percent, falling within respectable parameters for online surveys (Bosnjak, Das, and Lynn 2016; Iyengar and Hahn 2009). Attention filter questions were set within the survey questionnaire to ensure that respondents were attentive to questions and the associated response options before reporting their individual responses. Respondents who completed the survey were rewarded by Qualtrics with points that they can exchange for various items, such as cash or gift cards.

Independent Variables

Besides the demographic and sociographics sample selection variables, we also included a host of independent variables that have been used in previous studies to predict how members of the public form attitudes and make purchase intentions regarding nanotechnology and nanofoods.

Religiosity, the degree to which people feel that religious beliefs guide their daily decision-making (Brossard et al. 2008), was measured using one item in which respondents were asked to indicate on a seven-point scale (1 = “no guidance at all,” 7 = “a lot of guidance”) whether their religion prohibits them from eating food with nano-ingredients (M = 4.24, SD = 1.29).

Technocratic belief, the sentiment that technology is a means for improving society, was measured by asking respondents to indicate on a seven-point scale (1 = “strongly disagree,” 7 = “strongly agree”) how much they agree with the following statements: (a) “Technology should be used to increase food safety (e.g., shelf life),” (b) “Technology should be used to increase food quality (e.g., taste and color),” (c) “We should use technology to improve our daily life,” and (d) “Our leaders should use technology to solve problems in society.” The four items were averaged to create a composite index, with higher scores indicating higher technocratic belief (M = 5.27, SD = 1.04, Cronbach’s α = .82).

Deference to scientific authority (Ho et al. 2008), or trust in scientific uses for decision-making, was measured using three items on a seven-point scale (1 = “strongly disagree,” 7 = “strongly agree”) asking respondents how much they agree with the following statements: (a) “Scientists know best what is good for the public,” (b) “Scientists should move ahead with research even if it displeases some people,” and (c) “Scientists should do what they think is best, even they have to persuade people that it is right.” The items were averaged to form a composite index, with higher scores indicating higher deference to scientific authority (M = 4.60, SD = 1.19, Cronbach’s α = .86).

Trust in regulatory agencies was measured by asking respondents to indicate on a seven-point scale (1 = “strongly disagree,” 7 = “strongly agree”) how much they trust the information about food safety provided by (a) “Regulatory bodies (e.g., Agri-food & Veterinary Authority and National Environmental Agency)” (similar to the United States Food and Drug Administration and Environmental Protection Agency respectively), (b) “Scientists,” and (c) “Food companies.” These three items were summed and averaged to form a composite index, with higher scores indicating higher trust in regulatory agencies (M = 4.91, SD = 0.86, Cronbach’s α = .69).

Preference for natural products was measured by four items on a seven-point scale (1 = “strongly disagree,” 7 = “strongly agree”) asking respondents how much they agree with the following statements: (a) “I prefer to buy natural products,” (b) “To me the naturalness of the food that I buy is an important quality,” (c) “I prefer to avoid food products with additives,” and (d) “I do not mind paying a premium for natural products.” The four items were averaged to create a composite index, with higher scores indicating higher preference for natural products (M = 5.22, SD = 1.03, Cronbach’s α = .83).

Scientific knowledge was measured by five dichotomous items (1 = “true” (T); 2 = “false” (F)) asking respondent the following statements: (a) “Lasers work by focusing sound waves (F),” (b) “The center of the earth is very hot (T),” (c) “Antibiotics kill viruses as well as bacteria (F),” (d) “Electrons are smaller than atoms (T),” and (d) “All radioactivity is man-made (F).” For each item, the correct answer was recorded into “1,” while the incorrect answer was recoded into “0.” Responses which fell into the “I don’t know” categories were recoded as “0.” These scores for all the items were summed, with higher scores indicating higher level of scientific knowledge (M = 3.05, SD = 1.40, KR-20 = .56).

Threat appraisal was measured by summing two variables—threat severity and threat vulnerability. Threat severity was measured using two items on a seven-point scale (1 = “strongly disagree,” 7 = “strongly agree”): (a) “Nano-ingredients in food are healthy” and (b) “Nano-ingredients in food are safe.” These items were reverse coded. Threat vulnerability was measured by asking respondents to indicate on a seven-point scale (1 = “strongly disagree,” 7 = “strongly agree”) how much they agree with the following statements: (a) “New human health problems caused by nano-ingredients in food will affect me” and (b) “New environmental problems caused by nano-ingredients in food will affect me.” All four items were averaged to create a composite index, with higher scores indicating higher threat appraisal (M = 4.22, SD = 0.80, Cronbach’s α = .58).

Coping appraisal was measured by summing two variables—response efficacy that nanolabels are efficacious, and self-efficacy to be able to appropriately use nanolabels when making decisions. Response efficacy was measured using two items on a seven-point scale (1 = “strongly disagree,” 7 = “strongly agree”) asking the respondents how much they agree with the following statements: (a) “Nanolabels on food products show that the food is safe for consumption” and (b) “Nanolabels on food products help me to make an informed decision.” Self-efficacy was measured by asking the respondent to indicate on a seven-point scale (1 = “strongly disagree”, 7 = “strongly agree”) how much they agree on the following statements: (a) “I am able to use nanolabels on food products to make food choices” and (b) “It is easy to use nanolabels on food products to make food choices.” These items were averaged to form a composite index, with higher scores indicating higher coping appraisal (M = 4.47, SD = 1.06, Cronbach’s α = .86).

Attention to food safety news was measured by asking respondents to indicate on a seven-point scale (1 = “strongly disagree,” 7 = “strongly agree”) how much attention they pay to: (a) “new stories about food safety on TV,” (b) “new stories about food safety on print newspapers,” (c) “news stories about food safety on online news,” (d) “information about food safety on blogs (e.g., Blogspot, Wordpress),” (e) “information about food safety on Wikis (e.g., Wikipedia, Wiktionary),” and (f) “information about food safety on social networking sites (e.g., Facebook, Twitter, YouTube).” These six items were averaged to create a composite index, with higher scores indicating higher attention to food safety news (M = 4.69, SD = 1.06, Cronbach’s α = .81).

Attention to nanonews was measured using six items on a seven-point scale (1 = “strongly disagree,” 7 = “strongly agree”) asking the respondents how much attention they pay to (a) “new stories about nanotechnology on TV,” (b) “new stories about nanotechnology on print newspapers,” (c) “news stories about nanotechnology on online news,” (d) “information about nanotechnology on blogs (e.g., Blogspot, Wordpress),” (e) “information about nanotechnology on Wikis (e.g., Wikipedia, Wiktionary),” and (f) “information about nanotechnology on social networking sites (e.g., Facebook, Twitter, YouTube).” These six items were averaged to create a composite index, with higher scores indicating higher attention to food safety news (M = 4.05, SD = 1.38, Cronbach’s α = .92).

Dependent Variables

Attitude toward nanofood applications was measured by asking the respondents to indicate on a seven-point scale (1 = “strongly disagree,” 7 = “strongly agree”) how much they agree with the following statements: (a) “Nanotechnology should be used to increase food safety (e.g., shelf life),” (b) “Nanotechnology should be used to increase food quality (e.g., taste and color),” and (c) “Nanotechnology should be used to increase food nutrition.” These items were averaged to form a composite index, with higher scores indicating favorable attitude toward nanofood applications (M = 4.52, SD = 1.29, Cronbach’s α = .92). Table 2 summarizes the means and SD of the control, independent, and dependent variables.

Intention to purchase was measured using one item on a seven-point scale (1 = “strongly disagree,” 7 = “strongly agree”) asking the respondents how much they agree with the following statement: (a) “I would be willing to buy food products with nano-ingredients.” Higher scores indicate greater intention to purchase food products with nano-ingredients (M = 4.09, SD = 1.29). Descriptive statistics for independent and dependent variables are reported in Table I below.

Table 1.

Descriptive Statistic of Independent and Dependent Variables.

Variables	M	SD
Control variables
Age	37.92	10.68
Sex	51.6 percent female	—
Education	Median = 8.00	1.32
Household income	Median = 7.00	3.01
Religiosity	4.24	1.92
Independent variables
Technocratic belief	5.27	1.04
Deference to scientific authority	4.60	1.19
Trust in regulatory agencies	4.91	.86
Preference for natural product	5.22	1.03
Scientific knowledge	3.05	1.40
Attention to food safety news	4.69	1.06
Attention to nanonews	4.05	1.38
Threat appraisal	4.22	.80
Coping appraisal	4.47	1.06
Dependent variables
Attitude toward nanofood applications	4.52	1.29
Intention to purchase	4.09	1.29

Note: For reference, items appear in this table in the same order as in the Method section. SD = standard deviation.

Analytic Approach

Ordinary least squares hierarchical regression analyses were conducted to test our hypotheses and research questions. The variables were entered into the regression model according to their assumed causal order, with each variable and its dimensions entered into separate blocks, as well as the novel addition of protection motivation input as the final block. All control variables (demographic variables) were included in the first block, followed by the sociographic variables (educational level, household income, and religiosity) in the second block. Values predispositions of science and technology variables (technocratic belief and deference to scientific authority) were entered in the third block. Values predispositions of food variables (trust in regulatory agencies and preference for natural products) were entered in the fourth block, and scientific knowledge was entered in the fifth block. Next, media attention variables (attention to food safety news and attention to nanonews) were entered in the sixth block. Finally, PMT variables (threat appraisal and coping appraisal) were entered in the final block.

Results

Table 2 reports the final models predicting the two dependent variables. Across all dependent variables, age was not significantly related to attitude toward nanofood applications but negatively associated with purchase intention (β = −.08, p < .001). Likewise, gender was not significantly associated with any of the dependent variables. The demographic variables accounted for little of the total variance observed across dependent variables including attitude toward nanofood applications (0.7 percent) and intention to purchase nanofood (1.9 percent).

Table 2.

Hierarchical Regression Models Predicting Attitude toward Nanofood Applications and Intention to Purchase.

Variables	Attitude Toward Nanofood Applications (β)	Intention to Purchase (β)
Block 1: Demographics
Age	−0.02	−0.08***
Gender	0.00	−0.04
Incremental R ² (%)	0.70*	1.90***
Block 2: Sociographics
Education	0.03	0.04
Household income	0.02	0.04
Religiosity	−0.05^†	−0.06*
Incremental R ² (%)	1.40***	1.00*
Block 3: Value predispositions—science and technology
Technocratic belief	0.30***	0.10***
Deference to scientific authority	0.09**	0.05
Incremental R ² (%)	24.40***	11.60***
Block 4: Value predispositions—food
Trust in regulatory agencies	−0.01	0.04
Preference for natural product	−0.09**	−0.10***
Incremental R ² (%)	1.60***	4.00***
Block 5: Knowledge
General scientific knowledge	0.01	−0.03
Incremental R ² (%)	0.10	0.60**
Block 6: Protective motivation
Threat appraisal	−0.27***	−0.43***
Coping appraisal	0.27***	0.29***
Incremental R ² (%)	16.00***	28.50***
Block 7: Media attention
Attention to food safety news	0.07	0.01
Attention to nanonews	0.09**	0.13***
Incremental R ² (%)	1.40***	1.30***
Total R ² (%)	45.60	48.90

Note: *p < .05.

**p < .01.

***p < .001.

^† p < .1.

Among sociographics, educational level and household income were not related to any of the dependent variables. Religiosity was partially associated with attitude toward nanofood applications (β = −.05, p < .1) and negatively associated with the intention to purchase nanofood (β = −.06, p < .05). The sociographics block accounted for smaller variance for both the attitude toward nanofood applications (1.4 percent) and intention to purchase (1.0 percent).

Concerning value predispositions of science and technology, technocratic belief was positively associated with the attitude toward nanofood applications (β = .30, p < .001) and intention to purchase nanofood (β = .10, p < .001). Therefore, Hypotheses 1a and 1b were supported. Meanwhile, deference to scientific authority was positively related to attitude toward nanofood applications (β = .09, p < .01) but did not significantly influence the intention to purchase nanofood. Therefore, only Hypothesis 2a was supported. The third block, composed of variables that represent value predispositions toward science and technology, accounts for much more of the observed variance in attitudes toward nanofood applications (24.4 percent) but lesser in purchase intentions (11.6 percent).

For attitudinal predispositions variables of food, trust in regulatory agencies was not associated with any of the dependent variables, rejecting Hypotheses 3a and 3b. Notably, preference for natural product was negatively related to attitude toward nanofood applications (β = −.09, p < .01) and intention to purchase nanofood (β = −.10, p < .001). Hypotheses 4a and 4b were supported. This block accounted for lesser variance in attitude toward nanofood applications (1.6 percent) and purchase intention (4.0 percent).

Scientific knowledge was not related to intention to purchase nanofood and attitude toward nanofood applications. Therefore, Hypotheses 5a and 5b were rejected. Scientific knowledge accounted for very little variance across all dependent variables: intention to purchase nanofood (0.6 percent) and attitude toward nanofood applications (0.1 percent).

For the media attention variables, attention to food safety news did not display any significant relationship with all the dependent variables. Hence, Hypotheses 6a and 6b were rejected. Conversely, attention to nanonews was positively associated with attitude toward nanofood applications (β = .09, p < .01) and intention to purchase nanofood (β = .13, p < .001), lending support for Hypotheses 7a and 7b. The media attention block accounted for significant variance in attitude toward nanofood applications (1.4 percent) and intention to purchase nanofood (1.3 percent).

To answer Research Question 1, threat appraisal and coping appraisal were entered in the last block of the regression model. The result showed that threat appraisal was negatively related to attitude toward nanofood applications (β = −.27, p < .001) and the intention to purchase nanofood (β = −.43, p < .001). Coping appraisal was positively related to attitude toward nanofood applications (β = .27, p < .001) and intention to purchase nanofood (β = .29, p < .001). The protection motivation block accounted for the large variance in attitude toward nanofood applications (16 percent) and intention to purchase nanofood (28.5 percent).

Discussion

As nanotechnology-enabled food products continue to be developed and disseminated for public consumption, and as public awareness and concern increases, it is increasingly vital for stakeholders, risk communicators, and policy makers to maximize understanding of how public attitudes are formed and what factors influence decision-making. This study used national survey data to improve the predictive capability of health and risk decisions among the public regarding attitudes and purchase intentions of nanotechnology-enabled food products. Data were evaluated among Singaporeans, a group noted to be among the biggest future market for nanofoods (Helmut Kaiser Consultancy 2004). The empirical models reported in this paper provide valuable insights into factors influencing various aspects of how members of the public make decisions about nanotechnology-enabled foods. To date, our models provide the best predictive evaluations of purchase intentions regarding nanofoods (48.9 percent) and attitudes toward nanofood applications (45.6 percent) that we’ve seen when compared to previous models that have also attempted to explain and predict similar attitude and intention outcomes.

The results showed that age was negatively related to purchase intentions. This implies that younger generations have higher intention to purchase food containing nano-ingredients. Gender and household income, however, played no significant role across the board and all together, demographics and sociographics held little sway over explaining the variance observed within the sample. Education, household income, and religiosity also saw small influences. Together, these blocks provide little explanation of the observed variance of dependent measures. This bodes well for sentiments in the field of health and risk communication to continue to move away from simple demographic predictions of cognitive outcomes to more robust and granular assessments of value predispositions and motivations as more influential factors.

Value predispositions to science and technology demonstrated strong explanatory power regarding purchase intentions (11.6 percent) and attitudes toward nanofoods (24.4 percent). As hypothesized, technocratic belief was positively related to purchase intentions and attitudes toward nanofoods. However, deference to scientific authority positively related to attitude toward nanofood applications but not intention to purchase. Interestingly, trust in regulatory agencies to manage nanofood risks was not a significant factor for either dependent measure. As hypothesized, preference for natural products was negatively related to purchase intentions and attitudes toward nanofoods.

General scientific knowledge did not predict either attitudes or intentions to purchase nanofoods. While it may seem like a reasonable assumption that general scientific knowledge would ease concerns about uses of technology in food products, we note that the rejection of Hypothesis 5a and 5b actually supports the debunking of the “deficit model” of science communication that suggests that greater knowledge and familiarity with science is related to improved acceptance. As noted previously, studies demonstrate mixed findings regarding the role of general scientific knowledge in predicting other forms of support for nanotechnology including general technology acceptance and support for funding of nanotechnology research (Lee, Scheufele, and Lewenstein 2005; Ho et al. 2010). The lack of influence of general scientific knowledge on dependent variables may also highlight the importance of contextual knowledge regarding scientific applications in predicting attitudes (Sturgis and Allum 2004).

In the media attention block, we noted that attention to food safety news bore no significant impact on any dependent measures. However, media attention to nanotechnology news was a significant factor for all dependent measures, being positively related to purchase intentions and attitudes toward nanofoods. Noting that attention to food safety was not a factor, but attention to nanotechnology news was impactful, may suggest that the exotic character and novelty of the “nano” in nanofoods may trump typical predictors when it comes to health and risk decision-making about consumer products that employ emerging technologies with low familiarity among the public.

In evaluating our research question, there is little doubt that the PMT concepts of threat and coping appraisal had strong and consistent effects on purchase intentions and attitudes toward nanofood. Higher perceptions that nanofoods are a threat were coupled with strong negative purchase intentions and also strong negative attitudes toward nanofoods. We recommend that future study in this area question and investigate what antecedent factors best predict threat and coping perceptions and evaluate the potential for latent mediator and moderator variables that may be influential.

Coping appraisal proved to be potentially most interesting and demonstrative in this case of nanofoods. Those with high efficacy beliefs reported higher intentions to purchase nanofoods and held more positive attitudes toward nanofoods. This group is likely to feel that they have the personal means to use labels to make informed risk decisions and are the most likely group to perceive nanolabels as serving a “right to be informed” function and not a “do not buy” caution. Cumulatively, PMT concepts were the strongest influence on purchase intentions, while attitudes toward nanofoods were best predicted by value predispositions about science and technology.

We feel that this work also contributes to the larger arena of applied social science of science research. Our novel approach and application of PMT find value in assessing and identifying the influences of threat and efficacy appraisals as separate concepts rather than conflating them into one “protection motivation” variable. Being able to granularly note the influence of coping appraisal as distinct from threat appraisal provides greater opportunity to theorize about how the public comes to make sense and evaluate unfamiliar phenomena like nanofoods. Investigating perceptions in this manner may be of value to future researchers who desire to identify publics based on their threat and coping predilections.

In the field of health and risk communication, it is well-documented that risk perceptions do not always reflect the actual risk of a potential hazard and that risks are often communicated as social constructs that can be perceived even if there is little or no actual technical risk (Slovic, Fischoff, and Lichtenstein and Roe 1981; Sjöberg 2001). Given all of these considerations, this study offers a novel and more robust account of public perceptions of nanofoods. The findings we report demonstrate that, to date, antecedent value predispositions of science and technology coupled with threat and coping appraisal may be the best indicators yet for predicting how members of the public come to make sense of emerging technological products that are uncertain in their risk profile.

As debates around labeling and governance of nanofoods continue around the world, it may be of value to further explore these themes and triangulate such findings with other modes of social scientific inquiry and among other societies to confirm and compare results. We also note that subsequent study could examine potential interrelationships among these and other consequential variables using pathway modeling or other multi-equation methods. This will be critical for ensuring that health communication initiatives and public engagement are appropriately informed with robust understanding of the complex relationships among values, knowledge, media attention, and protection motivation.

Footnotes

Appendix A

Acknowledgment

The authors would like to thank the continued research support of Nanyang Technological University, Singapore, as well as the assistance of our research team and support staff who assisted with the data collection for this project.

Author Contribution

All authors contributed equally to this work.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

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