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Effects of Confirmation Bias on Consumer Attitudes Toward GM

Paper Type: Free Essay Subject: Environmental Studies
Wordcount: 3063 words Published: 4th Sep 2017

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Literature Review: Evaluating the Effects of Confirmation Bias on Consumer’s Attitudes Toward Genetically Modified Foods

Genetically modified foods (GMFs) have been a part of American life for more than twenty years, with the USDA approving the first commercial crop in 1994 (Bruening & Lyons, 2000). Since then, genetically modified (GM) crops have boomed, with an estimated 70% of processed foods on grocery store shelves containing GM ingredients (Chrispeels, 2014). The United States Department of Agriculture has recognized many benefits of GM crops, including greater yields, increased nutritional value, and better seed quality (Fernandez-Cornejo et al, 2014). Given the current global food climate, with hunger and starvation still being prevalent in many countries, this is an important benefit.

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Since the introduction of GM crops into the food chain, a lot of questions have been asked regarding their safety and much research has been done in this regard. A 2014 meta-analysis of the previous ten years of data indicates that GMOs do not pose any direct threat to human health (Nicolia et al, 2014). Indeed, most scientists (Funk et al., 2015) and the World Health Organization (2015) believe that GM foods are safe to eat. Despite this data, only just over a third of Americans believe GMOs are safe for human consumption (Funk et al, 2015) and many will spend more for foods that they know are non-GMO (Fernandez-Cornejo et al., 2014). This indicates that GM foods continue to be a contentious issue, and it is one that is often played out on social media (Stevens et al., 2016).

Food safety is an inherently emotional issue (Anderson 2000), and contentious issues, particularly emotional ones, are often hyped up in the media (Stieglitz & Dang-Xuan, 2013). When consumers go to the media seeking information on the emotionally charged issue of GM food, they will find that much of information that is easily accessible to them is negative and centered more on popular opinion that scientific facts (Mahgoub, 2016; McCluskey, Swinnen, & Vandermoortele, 2015). The media’s negative portrayal of GM food has been linked to consumers’ negative perception of the products (Marques, Critchley, & Walshe, 2014; Vilella-Villa & Costa-Font, 2008).

Both public opinion and scientific data play a part in how governments and regulatory bodies develop their policies, highlighting the importance of understanding the evidence and what shapes consumer attitudes toward GMOs (Druckman & Bolsen, 2011; Page & Shapiro, 1983). Public opinion is formed from the attitudes of individuals (Katz, 1960). Hostility to GMOs can lead to limiting development of research about them (e.g. Ceccoli & Hixon, 2012) and restrict or ban the use of the technology (e.g. Siegrist, 2000). The success of GMO foods on the market depends on public opinion (Moschini et al, 2005).

Facebook is the most popular social media platform in the United States. Nearly 80% of online Americans use Facebook, and of those, 76% use it every day, and 55% visit it several times a day (Funk & Rainie, 2015). Many American adults (62%) get their news from Facebook and nearly a fifth (18%) do it often (Gottfried & Shearer, 2016). Facebook offers near-instantaneous access to news and information in user’s newsfeeds, offering a greater ease of selectivity over more traditional media sources (Westerwick et al, 2013). However, the selectivity is biased towards users’ preexisting beliefs and attitudes, and serves to limit the amount of information available to them through the use of their algorithm that provides messaging consistent with previous “likes” of the user, as well as web searches, thus increasing the effect of selective exposure (Bakshy et al., 2015; Pariser, 2011), and an effect to which most people may be unaware of (Powers, 2017). This leads to tailoring a news feed that is increasingly fragmented and polarized to the existing attitudes of the individual user (Westerwick et al, 2013).

Facebook also elicits quick responses from users by way of how information is presented and does not require the user to put much cognitive effort into assessing its veracity. Users will often accept the first message they encounter without doing any further investigation (Flanagin & Metzger, 2007; Chen et al, 2015), engaging in what Petty and Cacioppo (1986) termed “peripheral processing”. This is common in user assessment on online media (Fogg et al, 2003) and when making food-related decisions (Frewer et al., 1997). In this type of processing, people rely on simple cues (Andrews et al., 2011; Walters et al, 2012) and cognitive heuristics, such as confirmation bias, to evaluate information and form an attitude about it. This is particularly true when people want to decide about an issue that they do not know much about and are uncertain about the risks, benefits, and consequences (Tversky and Kanehan, 1975). With peripheral processing, no higher-order thinking, or central processing, goes into their formation of opinion. While engaged in peripheral processing, people will discredit the attitude incongruent information off-hand or will alter their perception of it so that it fits into their pre-existing schemas (Petty & Cacioppo, 1986; Festinger, 1957). People generally prefer messages that fit with their pre-existing beliefs, and regardless of how much importance they attach to an issue, they are not likely to spend much time looking for credible information (Westerwick et al, 2013).

The problem with engaging in peripheral processing when encountering messages on a platform like Facebook is that the credibility of the information they are accessing is often not verified (e.g., Moody, 2011) and people rarely verify the credibility of this information (Metzger, 2007). The information may be based on inferior data, is often driven by personal opinion (Ennals et. al, 2010), has no real standards for quality control or regulatory controls, and can be easily altered (Metzger et al, 2013).

As mentioned earlier, confirmation bias is a cognitive heuristic that may be utilized when people are engaged in peripheral processing. The confirmation bias is a tendency for people to pay more attention to and attribute greater importance to information that is congruent with what they believe while overlooking or discrediting information that does not fit their preexisting beliefs (Klayman and Ha, 1987). Confirmation bias with regards to media exposure is well documented, with the first instance noted over seventy years ago (Lazarsfeld et al., 1944), however, the effect of confirmation bias on user attitudes is not consistent across different types of messaging. Political messaging and confirmation bias are well documented, but this is not the case for health messaging. Westerwick et al. (2013) found that people are generally more likely to look for credible information sources when it comes to their health. Alternatively, confirmation bias may be more pronounced if media coverage about an issue is negative, as could also be the case with GM foods (Lusk et al, 2014; Slovic, 1987). Given the impact of food safety on one’s health, the question arises as to the role that confirmation bias has in consumer’s attitude formation toward GMOs, and this has not yet been adequately addressed by existing research. Research in this area would contribute to the knowledge of how to best design messaging to positively persuade public opinion regarding GMOs.

Purpose and Objectives

The purpose of this study is to examine the impact of attitudinally congruent and attitudinally non-congruent messaging concerning GMOs on how consumers self-evaluate GM foods under the Elaboration Likelihood framework. To accomplish this purpose the following objectives were constructed:

  1. Collect data on the pre-existing knowledge and beliefs of the audience about GMOs.
  2. Compare the perceptions of attitudinally congruent and attitudinally non-congruent GMO messaging.
  3. Compare the beliefs and attitudes of consumers pre and post-message exposure.


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