The devil is not as black as he is painted? On the positive relationship between food industry conspiracy beliefs and conscious food choices.

Previous research found that conspiracy beliefs were usually activated when individuals faced different types of psychological threats and that they led mainly to maladaptive individual and societal outcomes. In this research, we assumed that potential harmfulness of conspiracy beliefs may depend on the context, and we focused on the link between food industry conspiracy beliefs and conscious food choices. We hypothesized that food industry conspiracy beliefs may allow for a constructive attempt to protect oneself against real or imagined enemies (i.e., food industry companies) by conscious food choices (e.g., paying attention to how much the food products are processed). We tested this hypothesis among Polish participants (Study 1; N = 608; cross-sectional and Study 2; N = 790; experimental). Study 1 confirmed that context-specific conspiracy beliefs (but not general notions of conspiracy) are associated with adaptive consumer behaviors. Study 2 showed that inducing feelings of threat related to the possibility of purchasing food contaminated by a harmful bacteria (vs. control condition) increased food industry conspiracy beliefs, which were further positively linked to conscious food choices. We discuss the role of threat and conspiracy beliefs in adaptive consumer behaviors related to food choices.

Introduction

Extant literature points toward the phenomenon of responsible, conscious, and reflexive consumption, highlighting the fact that modern consumers are paying at least some degree of attention to such issues as ethics, product composition and origin [1], or the environmental impact of purchased goods [2-7]. Although some researchers provide evidence for that many product purchase decisions are unconscious and automatic [8, 9], others show that consumers’ choices are not motivated by brand awareness or image [10, 11] but rather by health, environmental, or social reasons [12-14]. The latter also applies to food products and has even turned into a form of social pressure, put by the consumers on the food industry, to include relevant information on the packaging [15, 16]. In this paper, we analyze the psychological concomitants of this phenomenon, focusing on the role of food industry conspiracy beliefs in conscious food choices. Specifically, we examine whether a conviction that food industry companies are secretly conspiring against consumers may translate into psychological mobilization in the form of paying attention to the quality of purchased food products.

Conspiracy beliefs and (mal)adaptive behaviors

Conspiracy beliefs are mostly framed in terms of beliefs in the existence of a “vast, insidious, preternaturally effective international conspiratorial network designed to perpetrate acts of most fiendish character” [17] (p. 14). By explaining how powerful and evil out-groups covertly influence or cause major world events, conspiracy beliefs usually lead to negative societal outcomes [18]. Previous research found, for example, that people who show a general tendency towards conspiracy theories are less willing to take part in conventional political activities (e.g., are less inclined to register to vote; [19, 20]). Different types of conspiracy beliefs were also positively correlated with anti-science attitudes [21], they were related to lower adherence to safety and self-isolation guidelines [22, 23], lower willingness to vaccinate against COVID-19 [24] or higher freeriding during the pandemic [23]. Conspiracy beliefs may also fuel extremism [25, 26] and lead to illegal actions, such as occupying buildings [27]. Moreover, previous research found conspiracy beliefs to predict prejudice, negative out-group attitudes, and violence [28, 29]. This is because adopting conspiratorial explanations is closely related to lower levels of trust, scapegoating, and projecting societal problems onto real or imagined enemies who can be blamed for individual or collective problems [30]. One may ask, however, whether conspiracy beliefs always must necessarily bring damaging consequences.

According to Krekó [31], there are situations when conspiracy beliefs could be useful and adaptive. For example, they may provide a sense of community for people with marginal views [32], open opportunities for political debate [33], or inspire people to mobilize toward collective goals with the intention to bring about social change [34]. It is worth noticing, however, that till now, mobilizing aspects of conspiracy beliefs were mainly explored in relation to group-level processes (e.g., collective action; [34]) with disregard to the individual perspective on this issue. At the same time, from an evolutionary perspective, higher suspicion, and sensitivity to clues of danger, associated with conspiracy beliefs, can be a sort of strategy that, while rising the frequency of false alarms, may decrease the probability of missing the threat by an individual (see signal detection model, [35]). As Robins and Post stated: “natural selection will favour animals that become sensitive to subtle clues of danger” [36] (p. 71).

In line with this logic, there are situations when conspiracy theories can be helpful in detecting different types of threat and further lead to mobilization and preparing strategies that can reduce the danger. In our work, we assume that this would refer to such conspiracy beliefs that draw our attention to potentially dangerous situations (e.g., poor food quality).

Food industry conspiracy beliefs and conscious food choices

Nowadays food safety has become a concern for many societies [37], with specific cases of food and water contamination fuelling the perceived risk of the possibility to consume a harmful product [38]. According to data gathered by the Lloyd’s Register Foundation [39], over 200 diseases (from diarrhoea to cancer) can be caused by unsafe food or water, containing harmful bacteria, viruses, parasites, chemical substances, or other contaminants. It is estimated that every year 600 million people become ill because of consuming unsafe products and 420 thousand die, especially in low and middle income countries [39]. Despite an increasing number of food safety regulations being introduced by local, as well as international organizations, such as the British Food Safety Act (predecessor to the EU regulations) [40] or the Food Safety System Certification 22000 [41], instances of large-scale food scandals still occur. Arguably the largest scandal of this kind involved the Peanut Corporation of America and broke out in 2009, when 9 people died and over 10 thousand fell ill after consuming peanuts containing salmonella [42]. The case not only led to a massive recall of over 4000 different products in the US, but it also inspired a debate on state responsibility in facilitating unsafe conditions in food industry [42]. Another example is the European Union, where more than 90,000 cases of Salmonella are recorded each year and the main risk of infection in humans is associated with the consumption of contaminated food [43].

Although this data remains worrisome, not everyone declares behaviors encompassed by conscious consumption as typical for their regular food choices. For instance, Grunert and colleagues [44] found that even moderately high levels of concern about sustainability in food production did not translate into a specific motivation to use sustainability labels. On the other hand, previous research, largely inspired by the Protection Motivation Theory, showed that high levels of fear drove change in terms of both behavior and attitude towards health; for example, it inclined individuals to eat healthier food and physically exercise [45-48]. Given that one characteristic of conspiracy beliefs is exaggerating the direct threat specific choices may entail, by drawing attention to their potential dangers [35], a food industry conspiracy belief may also positively predict adaptive behaviors, at least on the declarative level. Therefore, in the present research, we aimed to explore the role of food industry conspiracy beliefs in shaping attitudes and behaviors related to conscious consumption in the area of food choices.

We define food industry conspiracy beliefs as convictions that agents responsible for the production, distribution, and safety inspection intentionally conceal certain facts regarding food products to fulfil their secret goals. Among the most commonly known food conspiracies are the belief that fluoride was deliberately added to drinking water during the Cold War to weaken the American people and make them “susceptible to a Communist takeover” [49] (p. 1559) or the theory that a United Nations sustainable development plan–Agenda 21 –intentionally uses genetically modified foods to make people fall ill and, by that, to decrease world population [50]. However, it needs to be highlighted that our intention was not to verify the validity of these accusations, but to explore the psychological concomitants of conspiracy beliefs related to the food industry. In line with our theorizing, these include higher susceptibility to external threats and higher motivation to protect oneself from the potential negative effects of these agents’ actions by, for example, recurring to conscious food choices.

Overview of the current research

The aim of our research was to investigate the prevalence of food industry conspiracy beliefs as well as factors associated with these beliefs. Previous research found that conspiracy beliefs are usually activated when facing different types of psychological threat [51] and lead mainly to maladaptive individual and societal outcomes [30, 52]. In this work we claim that concomitants of conspiracy beliefs may depend on the context so that in some cases belief in conspiracy theories may lead not only to negative consequences for the self [20, 30], but paradoxically, be associated with adaptive, healthy, behaviors. We claim that this is a “side effect” of some types of conspiracy theories, which not only warn people against real or imaginary enemies, but draw their attention to potentially dangerous, specific situations and, thus, decrease the probability of missing a threat [31, 35]. Importantly, the positive relationship between conspiracy beliefs and adaptive consumer choices should be present only in the case of context-specific (i.e., food industry) conspiracy beliefs and not generic conspiracist ideation (i.e., a belief system which consists of a small number of generic, less specific, assumptions about the typicality of conspiratorial activity in the world; [53]).

In line with this logic, we assumed that food industry conspiracy beliefs (but not belief in general notions of conspiracy per se) should be associated with conscious food choices aimed at protecting one’s own health (Study 1 and Study 2). Additionally, we assumed that inducing feelings of threat related to the possibility of purchasing food contaminated with a harmful bacteria should strengthen food industry conspiracy beliefs which, in turn, should be correlated with conscious food choices (Study 2). We tested these predictions in two studies conducted in Poland. Both studies included more than 400 participants, which gave us a power of .80 for detecting even small associations between variables (for r = .14; [54]; G*Power yields a target of 395 participants).

Data for both studies was obtained via Pollster Institute–a Polish online research panel that has been previously used in academic studies (e.g., [22, 23]). Pollster has over 230,000 registered users. The studies were conducted on a non-probability, national quota sample of Poles representative for gender, age, settlement size and education. Quotas were based on the Central Statistical Office (GUS) data. Data was collected via Computer Assisted Web Interviews (CAWI). As a reward for taking part in the study, participants receive points that can be later monetized. Both studies were conducted in accordance with the Declaration of Helsinki and approved by the Research Ethics Committee of the Institute of Psychology, Polish Academy of Sciences (number of approval: 26/X/2020). Informed written consent was obtained from all subjects involved in the study. The data and code that support current findings and are necessary to replicate are openly available in Open Science Framework depository at https://osf.io/h4x5v/.

Study 1

In Study 1 (cross-sectional), we sought to establish the basic relationship between food industry conspiracy beliefs and conscious food choices. To this end, we analysed data from a nationally representative study that included food industry conspiracy beliefs, conscious food choices, generic conspiracy beliefs, and demographics (age, gender, education, and settlement size). We assumed that food industry conspiracy beliefs (but not generic conspiracist ideation) should be positively related to conscious food choices.

Method

Participants and procedure

Study 1 included a nationwide representative sample of Polish adults in terms of gender, age, completed level of education, and settlement size. The sample consisted of 603 respondents (329 women, 274 men), aged between 19 and 85 (M = 51.97, SD = 15.41). Data was collected on-line by a leading Polish online research panel that has been used in academic studies before [22, 23].

Measures

Food industry conspiracy beliefs (short scale). The scale was developed for the purpose of the current study and was based on the characteristics of previous tools measuring conspiracist ideation [18, 19]. Each item included three elements: an implied agent (1) secretly undertaking specific action (2) to obtain some type of gain (3). To fit the context of the study, the agent was always associated with food industry companies and the actions were harmful for the consumers. It was measured with four items, asking about participants’ beliefs about food industry conspiracies, using the following statements: “Food processing companies bribe quality controllers to hide the actual nutritional content of food products”, “Food processing companies pay scientists to fabricate evidence for the innocuousness of ingredients that are in fact toxic”, “Cases of food poisoning are being covered up so that food processing companies can keep on harming people with impunity”, “Food processing companies secretly stuff foods with harmful substances to earn more money”. Participants responded on a scale from 1 = I definitely disagree to 5 = I definitely agree. The scale showed high reliability, α = .93. Exploratory Factor Analysis with principal axis extraction (Oblimin rotation) provided a single factor solution explaining 81.98% of the variance.

Conscious food choices (short scale). The scale was developed for the purpose of the current study and was inspired by previous research on conscious consumption [4, 5, 7–9]. To adapt the scale to the conditions of the study, emphasis was placed on actions that can be undertaken while grocery shopping and that have been previously identified as conscious consumption. It was measured with three items, asking how much the respondents would be willing to do specific things during their next visit to a grocery shop, assessed by the following statements: “Before buying a food product, I will read the nutrition information displayed on the label”, “Before buying a food product, I will pay attention to the country of origin of the groceries that I will be buying”, “Before buying a food product, I will pay attention to how much the food products are processed”. Participants were asked to determine their willingness to do these things on a scale from 1 = I definitely will not do this to 5 = I will definitely do this. The measure was internally consistent, α = .89. Exploratory Factor Analysis with principal axis extraction (Oblimin rotation) provided a single factor solution explaining 82.47% of the variance.

General conspiracy beliefs. Measured with the Generic Conspiracist Beliefs scale ([53]; Polish adaptation [55]). A total of 15 statements was applied, such as “Certain significant events have been the result of the activity of a small group who secretly manipulate world events”, “New and advanced technology which would harm current industry is being suppressed”. Participants responded on a scale from 1 = definitely not true to 5 = definitely true. The scale demonstrated very good reliability, α = .95.

Covariates. In addition to age and gender (coded Female = 0, Male = 1), participants were asked to indicate the highest level of education they had attained thus far (1 = primary degree or no degree, 2 = vocational degree, 3 = high-school or post-secondary degree, 4 = university degree) and settlement size (1 = rural area, 2 = town up to 20 thousand residents, 3 = town between 20 and 99 thousand residents, 4 = town between 100 and 200 thousand residents, 5 = town between 200 and 500 thousand residents, 6 = city above 500 thousand residents). Both education and settlement size were explanatory variables of categorical level. Thus, we decided to use a dummy coding procedure to control for their effects while predicting the variables of the main interest. Primary degree and rural area were used as reference categories.

Statistical analyses

Data was analyzed with IBM SPSS 27. Pearson product-moment correlation coefficient (Pearson’s r) was used in correlation analyses. We also used hierarchical multiple linear regression analyses. Skewness and kurtosis analyses were conducted to assess the normality of the variables of interest. For food industry conspiracy beliefs skewness was -0.01 (SE = 0.10) and kurtosis was -0.44 (SE = 0.20), for conscious food choices skewness was -0.61 (SE = 0.10) and kurtosis was -0.08 (SE = 0.20), and for general conspiracy beliefs skewness was 0.10 (SE = 0.10) and kurtosis was -0.39 (SE = 0.20). There were no multicollinearity problems in our regression models, with all VIFs < 2.0 [56].

Results and discussion

Since Study 1 used a nationally representative sample of Poles, we first explored the agreement with the food industry conspiracy items (Fig 1) by calculating the average percentage score for each answer to all items. Around 31.1% of all participants agreed with the statements arguing that the food industry is involved in some kind of conspiracy.

Fig 1

Prevalence of food industry conspiracy beliefs in Poland.

Next, we computed correlations between the variables. Conscious food choices were positively related to food industry conspiracy beliefs but unrelated to general conspiracy beliefs. Both types of conspiracy beliefs (i.e., food industry conspiracy beliefs and general conspiracy beliefs) were positively correlated to each other. All means, standard deviations, and zero-order correlations can be found in Table 1. To investigate if there were any differences between genders (female = 0, male = 1), we computed an independent samples t-test for the main variables. There was no significant effect of gender (Food industry conspiracy beliefs, t(601) = 0.70, p = .483; Conscious food choices, t(601) = 1.76, p = .079; General conspiracy beliefs, t(601) = 0.07, p = .946).

Table 1

Means, standard deviations, and zero-order correlations (Study 1).

Measure	M	SD	1	2	3
1. Food industry conspiracy beliefs	2.99	1.05	-	.11**	.62***
2. Conscious food choices	3.66	1.04		-	.04
3. General conspiracy beliefs	2.75	0.94			-

Note. We also conducted correlation analyses using Spearman test. Results remained the same.

*p < .05.

**p < .01.

***p < .001.

We then performed a hierarchical multiple regression analysis to investigate whether food industry conspiracy beliefs (but not general conspiracy beliefs) would be positively related to conscious food choices when controlling for basic demographic variables (see Table 2). In Step 1, we introduced gender, age, education, and settlement size. We found a positive and significant effect of age on conscious food choices. In Step 2, we introduced food industry conspiracy beliefs and general conspiracy beliefs. Food industry conspiracy beliefs (but not general conspiracy beliefs) was a positive and significant predictor of conscious food choices. The positive effect of age remained significant.

Table 2

Predictors of conscious food choices (Study 1).

Variable		Step 1				Step 2
	B	95% CI	β	p	B	95% CI	β	p
		LL  UL				LL  UL
Gender (Female = 0, Male = 1)	-0.13	[-0.30, 0.04]	-.06	.130	-0.12	[-0.29, 0.04]	-.06	.148
Age	0.01	[0.01, 0.02]	.15	< .001	0.01	[0.004, 0.02]	.14	< .001
Vocational degree	-0.38	[-0.95, 0.19]	-.13	.187	-0.40	[-0.96, 0.17]	-.14	.172
High-school or post-secondary degree	-0.04	[-0.58, 0.50]	-.02	.886	-0.05	[-0.59, 0.49]	-.02	.860
University degree	0.02	[-0.52, 0.57]	.01	.935	0.03	[-0.51, 0.58]	.02	.909
Town up to 20 thousand residents	0.08	[-0.22, 0.38]	.02	.597	0.09	[-0.21, 0.38]	.03	.564
Town between 20 and 99 thousand residents	0.09	[-0.14, 0.31]	.04	.449	0.09	[-0.13, 0.32]	.04	.409
Town between 100 and 200 thousand residents	0.10	[-0.23, 0.42]	.03	.567	0.10	[-0.23, 0.43]	.03	.550
Town between 200 and 500 thousand residents	0.02	[-0.29, 0.32]	.004	.925	0.01	[-0.29, 0.32]	.004	.926
City above 500 thousand residents	0.12	[-0.15, 0.39]	.04	.377	0.13	[-0.14, 0.41]	.05	.329
General conspiracy beliefs					-0.02	[-0.13, 0.10]	-.02	.778
Food industry conspiracy beliefs					0.12	[0.02, 0.22]	.12	.018
R 2		.05				.06
Δ R 2						.01*
F		F(10, 592) = 3.12***				F(12, 590) = 3.29***

*p < .05.

**p < .01.

***p < .001.

Study 1 confirmed our prediction about the positive correlation between the endorsement of food industry conspiracy beliefs and conscious food choices. It also showed that context-specific conspiracy beliefs (but not general notions of conspiracy) could be associated with adaptive consumer behaviors. These preliminary results suggested that in some cases conspiracy beliefs might be associated with adaptive behavior. People with a higher level of food industry conspiracy beliefs were found to be more conscious consumers and pay more attention to the composition of the food and its origin when shopping. Additionally, we found that higher age predicted more conscious food choices. It seems that older, more life-experienced individuals focus more on conscious choices while purchasing food products.

Study 2

In Study 2, we aimed to replicate the pattern of results obtained in Study 1. Additionally, we aimed to examine the role of threat in boosting context-specific food industry conspiracy beliefs. Thus, we employed an experimental research design and tested a hypothesis that feelings of threat, related to the possibility of purchasing a food product that might contain a bacteria harmful to human health, would strengthen food industry conspiracy beliefs, which, in turn, would be associated with higher conscious food choices. We manipulated the feelings of threat with a short text about a case in which the Sanitary Inspectorate detected a harmful bacteria in many kinds of food products available for purchase in the most popular Polish supermarkets. As in Study 1, we controlled for basic demographics (age, gender, education, and settlement size) and general conspiracy beliefs to check whether the obtained effects are context-specific (i.e., related specifically to food issues).

One limitation of Study 1 was that we measured the crucial variables (e.g., food industry conspiracy beliefs and conscious food choices) with the use of short (four- and three-item) scales. Therefore, in Study 2 we examined whether the pattern of results obtained in Study 1 would conceptually replicate if we used better measurement tools. We operationalized the food industry conspiracy beliefs and conscious food choices with 14 and 9 items respectively. The conceptual principles applied while developing the tools remained the same as in Study 1, with some items including an implicit allusion to the action secretly undertaken by food industry companies for their own benefit. Still, both extended versions of the scales showed high reliability (listed below) and Exploratory Factor Analysis provided single factor solutions for both of them. Additionally, in Study 2 we also controlled for individual differences related to consumer choices (i.e., frequency of grocery shopping and respondents’ subjective financial situation).

As in Study 1, data for Study 2 was collected by an external research company, which has been used in academic studies before [22, 23], through Computer Assisted Web Interviews (CAWI). 790 respondents, aged between 18 and 83 (M = 47.44, SD = 15.97), participated in this study (419 women, 371 men). The sample was representative of Polish adults in terms of gender, age, completed level of education, and settlement size. Due to the experimental character of this study, we included an attention check–participants were asked about the content of the text that was used as a manipulation. Participants who failed the attention check (n = 25) were excluded from further analyses. This resulted in the final sample of 765 respondents (408 women, 357 men), aged between 18 and 83 (M = 47.47, SD = 15.97). When these participants were not excluded, the main pattern of results remained the same.

Participants were randomly assigned to one of two experimental conditions: threat (n = 386) and control (n = 379) by the research company. In both conditions, participants were exposed to a short, fabricated article, designed in such a way as to imitate an actual online article from a news portal. In the threat condition, it was an article about some food products that were withdrawn from stores due to the fact that sanitary authorities found a dangerous bacteria in them. In the control condition, they read an article providing advice on how to grow tomatoes at home. Afterwards, participants completed measures of conspiracy beliefs and conscious food choices. Then, they were asked to provide an answer to the attention check question. When the participants completed the questionnaire, they were debriefed and thanked.

Food industry conspiracy beliefs (full scale). Measured with 14 items regarding food conspiracy beliefs: “Food processing companies secretly stuff foods with harmful substances to earn more money”, “Nobody really knows what is inside of food products”, “Food processing companies use genetically modified ingredients without letting the consumers know”, “Cases of food poisoning are being covered up so that food processing companies can keep on harming people with impunity”, “Harmful substances added to foods by food processing companies make them look good on the outside, despite being spoiled”, “Food is stuffed with addictive substances to keep the customer loyal to it and to generate more profit”, “Food processing companies bribe quality controllers to hide the actual nutritional content of food products”, “Scientific evidence that some foods are harmful is being obscured by huge food processing companies”, “Food processing companies pay scientists to fabricate evidence for the innocuousness of ingredients that are in fact toxic”, “The real goal of food processing companies is high profit, regardless of the consequences for the consumers’ health and life”, “Food processing companies pay scientists to say that genetically modified food is healthy”, “Artificially modified food allows food processing companies to control population size”, “Food processing companies secretly add addictive substances to their products”, “Food processing companies manipulate the amount of sugar in their products to make the consumers addicted to them”. Participants responded on a scale from 1 = definitely disagree to 5 = definitely agree. The measure demonstrated high reliability, α = .96. Exploratory Factor Analysis with principal axis extraction (Oblimin rotation) provided a single factor solution explaining 63.65% of the variance.

Conscious food choices (full scale). Measured with nine items: “I will pay attention to the nutritional content of the food products that I will be buying”, “Before buying a food product, I will read the nutrition information displayed on the label”, “When choosing a food product, I will consider the nutrition information specified on the label”, “Before buying a food product, I will pay attention to how much the food products are processed”, “While shopping, I will use an app that will tell me which food products are healthy”, “Before buying a food product, I will pay attention to the country of origin of the groceries that I will be buying”, “I will buy groceries from local producers”, “I will shop for groceries only in trusted places”, “I will simply buy what I need, without analysing the nutritional content of the product (reverse coded item)”. Participants were asked to determine whether they will do what the statement says using a scale from 1 = I definitely will not do this to 5 = I will definitely do this. The scale showed good reliability, α = .89. Exploratory Factor Analysis with principal axis extraction (Oblimin rotation) provided a single factor solution explaining 56.10% of the variance.

General conspiracy beliefs. As in Study 1, we used the Generic Conspiracist Beliefs scale ([53]; Polish adaptation [55]). There were 15 statements and participants responded on a scale from 1 = definitely not true to 5 = definitely true. The measure was internally consistent, α = .95.

Covariates. We used the same demographic variables as in Study 1: gender, age, level of education, and settlement size, but this time we also added a question about the respondents’ subjective financial situation (1 = definitely bad, 2 = bad, 3 = rather bad, 4 = average, 5 = rather good, 6 = good, 7 = definitely good) and a question about the frequency of going grocery shopping (1 = never, 2 = once a month, 3 = few times a month, 4 = once a week, 5 = two-three times a week, 6 = few times a week, 7 = everyday). We followed the same procedure as in Study 1 to code dummy variables (i.e., level of education, and settlement size).

Data was analyzed with IBM SPSS 27. Mediation analyses were performed with Process v3.5 macro. Pearson product-moment correlation coefficient (Pearson’s r) was used in correlation analyses. We used hierarchical multiple linear regression analyses. Similarly, as in Study 1, skewness and kurtosis analyses were conducted to assess the normality of the variables of interest in Study 2. For food industry conspiracy beliefs skewness was -0.14 (SE = 0.09) and kurtosis was -0.32 (SE = 0.18), for conscious food choices skewness was -0.50 (SE = 0.09) and kurtosis was -0.04 (SE = 0.18), and for general conspiracy beliefs skewness was 0.10 (SE = 0.09) and kurtosis was -0.65 (SE = 0.18). There were no multicollinearity problems in our regression models, with all VIFs < 2.0 [56].

First, we computed correlations between the variables. Conscious food choices were positively related to food industry conspiracy beliefs. We also found a significant, albeit weaker, correlation between conscious food choices and general conspiracy beliefs. Importantly, both types of conspiracy beliefs (i.e., food industry conspiracy beliefs and general conspiracy beliefs) were positively related to each other.

We also found that shopping frequency, and subjective financial situation were significantly positively related to conscious food choices. Food industry conspiracy beliefs were significantly negatively related to subjective financial situation. We also found that general conspiracy beliefs were negatively related to subjective financial situation. All means, standard deviations and zero-order correlations can be found in Table 3. To investigate if there were any differences between genders (female = 0, male = 1), we computed an independent samples t-test for the main variables. The effect of gender on food industry conspiracy beliefs (t(763) = 1.17, p = .242) and general conspiracy beliefs (t(763) = 1.46, p = .146) was non-significant. In case of conscious food choices, women (M = 3.66, SD = 0.82) scored higher than men (M = 3.49, SD = 0.81), t(763) = 2.84, p = .005.

Table 3

Means, standard deviations, and zero-order correlations (Study 2).

Measure	M	SD	1	2	3	4	5
1. Food industry conspiracy beliefs	3.08	0.93	-	.18***	.62***	.07	-.13***
2. Conscious food choices	3.58	0.81		-	.09*	.14***	.10**
3. General conspiracy beliefs	2.72	0.96			-	-.07	-.14***
4. Shopping frequency	5.23	1.17				-	.09*
5. Subjective financial situation	4.40	1.10					-

Note. We also conducted correlation analyses using Spearman test. Results remained the same.

*p < .05.

**p < .01.

***p < .001.

Next, we computed a hierarchical regression analysis to investigate the effects of the experimental manipulation (threat vs. control) on food industry conspiracy beliefs (see Table 4). Experimental manipulation was coded: 0 = control condition and 1 = threat condition. To control for the socio-demographic variables, in Step 1 we included not only gender, age, education, settlement size, but also variables about the frequency of grocery shopping and the subjective financial situation. Age positively and significantly predicted food industry conspiracy beliefs. Subjective financial situation and higher level of education (vs. primary degree) were also significantly, albeit negatively, related to food industry conspiracy beliefs. Finally, we a found positive effect of living in town up to 20 thousand residents (vs. rural area) on conspiracy beliefs. In Step 2, we introduced variable coding experimental condition (threat vs. control). We found that experimental condition positively and significantly predicted food industry conspiracy beliefs: participants in the threat (vs. control) condition scored significantly higher on food industry conspiracy beliefs. The effects of age, place of residence, education and financial situation remained significant.

Table 4

Predictors of food industry conspiracy beliefs (Study 2).

Variable		Step 1				Step 2
	B	95% CI	β	p	B	95% CI	β	p
		LL  UL				LL  UL
Gender (Female = 0, Male = 1)	-0.11	[-0.24, 0.02]	-.06	.097	-0.12	[-0.25, 0.01]	-.07	.066
Age	0.01	[0.001, 0.01]	.10	.009	0.01	[0.001, 0.01]	.08	.031
Vocational degree	-0.28	[-0.74, 0.19]	-.08	.249	-0.29	[-0.76, 0.17]	-.09	.215
High-school or post-secondary degree	-0.47	[-0.89, -0.05]	-.25	.027	-0.49	[-0.91, -0.08]	-.26	.020
University degree	-0.63	[-1.05, -0.21]	-.34	.004	-0.65	[-1.07, -0.23]	-.35	.002
Town up to 20 thousand residents	0.33	[0.09, 0.56]	.10	.007	0.36	[0.12, 0.59]	.11	.003
Town between 20 and 99 thousand residents	0.10	[-0.08, 0.28]	.05	.275	0.12	[-0.06, 0.30]	.06	.182
Town between 100 and 200 thousand residents	0.06	[-0.19, 0.31]	.02	.649	0.07	[-0.18, 0.32]	.02	.564
Town between 200 and 500 thousand residents	0.09	[-0.16, 0.33]	.03	.500	0.10	[-0.15, 0.34]	.03	.434
City above 500 thousand residents	-0.17	[-0.38, 0.05]	-.06	.131	-0.14	[-0.35, 0.07]	-.05	.199
Shopping frequency	0.05	[-0.01, 0.11]	.06	.078	0.05	[-0.003, 0.11]	.07	.062
Subjective financial situation	-0.09	[-0.15, -0.03]	-.11	.003	-0.09	[-0.15, -0.04]	-.11	.002
Condition (control = 0; threat = 1)					0.26	[0.13, 0.39]	.14	< .001
R 2		.08				.09
Δ R 2						.01*
F		F(12, 752) = 5.09*				F(13, 751) = 6.01*

*p < .001.

Then we computed a hierarchical regression analysis to investigate the effects of the experimental manipulation (threat vs. control) on general conspiracy beliefs (see Table 5). Experimental manipulation was coded 0 = control condition and 1 = threat condition. Again, in Step 1 we introduced the socio-demographic variables: gender, age, education, settlement size, as well as variables about the frequency of grocery shopping and the subjective financial situation. We found that age and subjective financial situation were significantly negatively related to general conspiracy beliefs. In turn, shopping frequency and living in smaller towns (vs. rural area) positively and significantly predicted the dependent variable. In Step 2, we introduced variable coding experimental condition (threat vs. control). In line with our assumptions, we did not find a significant effect of the experimental condition on general conspiracy beliefs. Effects of age, shopping frequency, subjective financial situation, and living in smaller towns remained significant.

Table 5

Predictors of general conspiracy beliefs (Study 2).

Variable		Step 1				Step 2
	B	95% CI	β	p	B	95% CI	β	p
		LL  UL				LL  UL
Gender (Female = 0, Male = 1)	-0.09	[-0.23, 0.05]	-.05	.190	-0.10	[-0.23, 0.04]	-.05	.167
Age	-0.01	[-0.01, -0.003]	-.13	.001	-0.01	[-0.01, -0.003]	-.13	< .001
Vocational degree	-0.03	[-0.51, 0.45]	-.01	.911	-0.04	[-0.52, 0.45]	-.01	.884
High-school or post-secondary degree	-0.22	[-0.65, 0.21]	-.12	.312	-0.23	[-0.66, 0.20]	-.12	.293
University degree	-0.40	[-0.84, 0.03]	-.21	.069	-0.41	[-0.85, 0.02]	-.21	.063
Town up to 20 thousand residents	0.31	[0.07, 0.56]	.10	.011	0.33	[0.09, 0.57]	.10	.008
Town between 20 and 99 thousand residents	0.19	[0.01, 0.38]	.08	.043	0.20	[0.02, 0.39]	.09	.034
Town between 100 and 200 thousand residents	0.04	[-0.22, 0.30]	.01	.738	0.05	[-0.21, 0.31]	.02	.700
Town between 200 and 500 thousand residents	0.05	[-0.21, 0.30]	.01	.724	0.05	[-0.20, 0.31]	.02	.691
City above 500 thousand residents	-0.21	[-0.43, 0.02]	-.07	.067	-0.19	[-0.41, 0.03]	-.07	.084
Shopping frequency	0.07	[0.01, 0.12]	.08	.024	0.07	[0.01, 0.13]	.08	.021
Subjective financial situation	-0.13	[-0.20, -0.07]	-.15	< .001	-0.14	[-0.20, -0.07]	-.15	< .001
Condition (control = 0; threat = 1)					0.12	[-0.02, 0.25]	.06	.085
R 2		.08				.09
Δ R 2						.01
F		F(12, 752) = 5.66*				F(13, 751) = 5.47*

*p < .001.

Finally, we computed a hierarchical regression analysis to investigate the effects of the experimental condition, food industry conspiracy beliefs, and general conspiracy beliefs on conscious food choices (Table 6). The experimental manipulation was coded 0 = control condition and 1 = threat condition. In Step 1, we introduced the socio-demographic variables: gender, age, education, settlement size, as well as variables about the frequency of grocery shopping and the subjective financial situation. Gender was significant and negative predictor of conscious food choices. Age, shopping frequency, and subjective financial situation were positively related to conscious food choices. In Step 2, we introduced variable coding experimental condition (threat vs. control). We found that the effect of the experimental condition was non-significant. The effects of gender, age, shopping frequency, and subjective financial situation remained the same. In Step 3, we introduced food industry conspiracy beliefs and general conspiracy beliefs. We found that food industry conspiracy beliefs were a significant and positive predictor of conscious food choices, while the effects of the condition (threat vs. control) and of general conspiracy beliefs were non-significant. Effects of gender, age, shopping frequency, and subjective financial situation on the dependent variable remained significant.

Table 6

Predictors of conscious food choices (Study 2).

Variable		Step 1				Step 2				Step 3
	B	95% CI	β	p	B	95% CI	β	p	B	95% CI	β	p
		LL  UL				LL  UL				LL  UL
Gender (Female = 0, Male = 1)	-0.19	[-0.30, -0.07]	-.12	.001	-0.19	[-0.30, -0.08]	-.12	.001	-0.17	[-0.28, -0.06]	-.11	.003
Age	0.01	[0.01, 0.02]	.26	< .001	0.01	[0.01, 0.02]	.26	< .001	0.01	[0.01, 0.02]	.25	< .001
Vocational degree	-0.18	[-0.58, 0.23]	-.06	.390	-0.18	[-0.58, 0.22]	-.06	.381	-0.14	[-0.54, 0.26]	-.05	.483
High-school or post-secondary degree	-0.08	[-0.45, 0.28]	-.05	.651	-0.09	[-0.45, 0.28]	-.05	.636	-0.02	[-0.38, 0.34]	-.01	.918
University degree	-0.13	[-0.49, 0.24]	-.08	.496	-0.13	[-0.49, 0.23]	-.08	.483	-0.04	[-0.40, 0.33]	-.02	.842
Town up to 20 thousand residents	0.04	[-0.17, 0.24]	.01	.728	0.04	[-0.16, 0.25]	.02	.685	-0.01	[-0.21, 0.19]	-.01	.903
Town between 20 and 99 thousand residents	-0.03	[-0.19, 0.12]	-.02	.673	-0.03	[-0.19, 0.13]	-.02	.712	-0.05	[-0.21, 0.11]	-.03	.520
Town between 100 and 200 thousand residents	0.06	[-0.15, 0.28]	.02	.570	0.07	[-0.15, 0.28]	.02	.553	0.06	[-0.16, 0.27]	.02	.615
Town between 200 and 500 thousand residents	0.03	[-0.18, 0.24]	.01	.780	0.03	[-0.18, 0.25]	.01	.762	0.02	[-0.19, 0.23]	.01	.859
City above 500 thousand residents	0.02	[-0.17, 0.20]	.01	.851	0.02	[-0.16, 0.21]	.01	.810	0.05	[-0.14, 0.23]	.02	.623
Shopping frequency	0.07	[0.02, 0.11]	.10	.007	0.07	[0.02, 0.12]	.10	.007	0.06	[0.01, 0.11]	.08	.017
Subjective financial situation	0.09	[0.04, 0.14]	.13	< .001	0.09	[0.04, 0.14]	.12	< .001	0.11	[0.06, 0.16]	.15	< .001
Condition (control = 0; threat = 1)					0.05	[-0.06, 0.16]	.03	.377	0.01	[-0.10, 0.13]	.01	.804
General conspiracy beliefs									0.03	[-0.05, 0.11]	.04	.439
Food industry conspiracy beliefs									0.13	[0.05, 0.20]	.14	.002
R 2		.10				.10				.13
Δ R 2						.001				.03*
F		F(12, 752) = 6.99*				F(13, 751) = 6.51*				F(15, 749) = 7.24*

*p < .001

In order to perform a full test of our hypotheses, we conducted a mediation analysis using model 4 in Process 3.5 [57]. Significance was tested with bootstrapped 95% confidence intervals for the unstandardized indirect effects, constructed with 10,000 resamples. The analysis, displayed in Fig 2, examined whether food industry conspiracy beliefs mediated the path between the experimental condition (threat vs. control) and conscious food choices. As covariates we used general conspiracy beliefs, gender, age, education level, settlement size, shopping frequency, and subjective financial situation. We found that the experimental condition positively and significantly predicted food industry conspiracy beliefs, B = 0.19, SE = 0.05, 95% CI [0.09, 0.29], p < .001 and that, in turn, food industry conspiracy beliefs positively and significantly predicted conscious food choices, B = 0.13, SE = 0.04, 95% CI [0.05, 0.20], p = .002. The indirect effect of the experimental condition on conscious food choices via food industry conspiracy beliefs was positive and significant, B = 0.02, SE = 0.01, 95% CI [0.01, 0.05]. All effects remained the same when we computed these analyses without the covariates. Next, we conducted similar analyses with general conspiracy beliefs as a mediator: the experimental condition did not predict general conspiracy beliefs significantly, B = -0.05, SE = 0.05, 95% CI [-0.15, 0.06], p = .372, and general conspiracy beliefs was not a significant predictor of conscious food choices, B = 0.03, SE = 0.04, 95% CI [-0.05, 0.10], p = .439. The indirect effect of the experimental condition on conscious food choices via general conspiracy beliefs was also non-significant, B = -0.001, SE = 0.003, 95% CI [-0.01, 0.004].

Fig 2

Indirect effect of condition (threat vs. control) on conscious food choices via food industry conspiracy beliefs (Study 2).

Entries are unstandardized coefficients. Dotted line indicates total effect (not controlling for the third variable). *p < .05. **p < .01. ***p < .001.

In Study 2, we managed to replicate the pattern of results obtained in Study 1 with the use of better measurement tools. Specifically, we found a positive correlation between food industry conspiracy beliefs and conscious food choices. We also replicated the effect of age, suggesting that older individuals pay more attention to purchasing food consciously. However, we did not find a similar result for education. Moreover, Study 2 showed that inducing feelings of threat related to the possibility of purchasing food contaminated by a harmful bacteria (vs. control condition) increased food industry conspiracy beliefs, which were further positively correlated with conscious food choices.

In such a way, we found that inducing feelings of threat may indirectly strengthen adaptive consumer choices related to food purchasing behaviors via boosting context-specific conspiracy beliefs. In line with our predictions, these effects were not present in the context of generic conspiracist ideation, which did not increase after threat induction. Moreover, after accounting for the shared variance between food industry conspiracy beliefs and generic conspiracy ideation, only the former was found to predict conscious food choices.

General discussion

In two studies, we investigated the phenomenon of food industry conspiracy beliefs. Using a nationally representative sample, in Study 1 we established that a third of Poles endorsed this form of conspiracy beliefs. Previous studies showed that belief in conspiracy theories was usually associated with maladaptive individual and societal outcomes [18]. However, we argued that there were some exceptions to this rule and showed (Study 1 and Study 2) that in some cases conspiracy beliefs were in fact related to adaptive behaviors. Specifically, we showed that those who endorsed food industry conspiracy beliefs were found to be more conscious consumers (i.e., scored higher on conscious food choices). This seems to be in line with previous theorizing (e.g., [31]) emphasizing the mobilizing aspects of conspiracy beliefs and the role of higher suspicion and sensitivity to clues of danger that could decrease the possibility of missing insecure stimuli [35]. Additionally, it can be observed that while inducing context-specific threat (related to food content) increased the level of food industry conspiracy beliefs, it did not lead to a higher level of general conspiracy beliefs (Study 2). This evidence is yet another argument that food industry conspiracy beliefs, as measured in the present research, are qualitatively different from other, previously studied examples of conspiracy theories.

Importantly, in Study 2, we additionally demonstrated that a mere induction of feelings of threat (i.e., an article about a dangerous bacteria in food) did not directly change the consumers’ perspective on conscious food choices. Rather, our analysis indicated that threat induction directly increased only food industry conspiracy beliefs, which were further positively linked to conscious food choices. This is consistent with previous research showing that people endorse conspiracy theories particularly when they experience feelings of anxiety or uncertainty [58, 59]. According to Van Prooijen [58], feelings of threat fuel a sense-making process focused on finding alleged enemies who can be blamed for unpleasant psychological states. In such a way, conspiracy theories offer structured maps of meaning and give simple explanations for uncertain situations [59, 60]. They help to track the enemy responsible for a threatening situation (e.g., food industry companies). This process, however, does not lead to threat reduction, but instead, seems to exaggerate the danger [51, 58]: we feel threatened, we have enemies so we should be careful and ready to fight. Previous researchers analyzed this mechanism from the perspective of intergroup relations (see [30]). On the one hand, they emphasized positive links between conspiracy beliefs and maladaptive intergroup outcomes (e.g., out-group hostility in times of peace; [28, 61]), but on the other, they elaborated on the evolutionary value of conspiracy theories that have been able to instill fear and anger in perceivers in times of war [58]. Our research extended this work by showing that conspiracy beliefs may also lead to adaptive intraindividual outcomes (i.e., paying more attention to the food products we choose).

Future research would do well to test what type of conspiracy beliefs may evoke adaptive behaviors (vs. be associated only with maladaptive ones). It is possible that only such beliefs that are based on a real threat (e.g., food contamination) may in some cases be related to positive outcomes. Potentially fertile ground for future research would also be to investigate the possible maladaptive concomitants of food industry conspiracy beliefs. In fact, it is possible that an obsessive focus on this type of convictions could also evoke undesirable psychological effects in the long term (e.g., lead to eating disorders such as orthorexia nervosa; [62]). One of the limitations was low (but acceptable; [63]) average variance explained for food industry conspiracy beliefs and conscious food choices. These scales should be psychometrically tested and revised in the future research. Future research is also needed to better investigate other possible predictors of food industry conspiracy beliefs as well as conscious food choices. For example, it would be interesting to check whether variables usually linked to conspiracy beliefs (e.g., need for cognitive closure; [59] or defensive self-evaluation; [64] would serve as significant predictors of conspiracy thinking also in this case. Other limitation was the decision about the order of the scales. In Study 1, we decided that the order of the scales should be rotated to maximize the validity of the research. In Study 2, we decided that food industry conspiracy beliefs should be presented before conscious food choices, as its possible underpinning. Although the variables were positively related to each other in both cases, future research would do well to further explore the potential influence the order of these scales might have on the results. Additionally, data measuring conscious food choices relied on self-reported declarations, so verifying whether a similar increase would be noted in actual shopping behavior is needed. Given the findings of past research on consumer choices and implicit attitudes [7, 8], social and intangible attributes [65], as well as self-reported shopping behavior [66], we assume that the pattern of results obtained in the present studies would remain similar, though this would have to be verified in the future.

Also, future research would do well to better establish the causality of the observed relationships, for example, by experimentally manipulating the levels of food industry conspiracy beliefs. According to our predictions, boosting food industry conspiracy beliefs should lead to conscious food choices. On the other hand, we cannot exclude the possibility, that boosting conscious food choices may change the levels of food industry conspiracy beliefs. Future research is also needed to understand the influence of food industry conspiracy beliefs on consumer choices in a real shopping setting, with real products that can be inspected by the consumer before making a purchase decision. For example, it would be interesting to find out which aspects of conscious food choices (e.g., reading the nutrition information displayed on the label vs. using an app that with tell which food products are healthy) would be most popular among the consumers and which could be most effectively strengthened by food industry conspiracy beliefs. These issues require further empirical investigation. Similarly, given the novel character of the food industry conspiracy beliefs and the conscious food choices measurement tools, it would be beneficial to continue exploring the psychometric properties of these scales and to verify whether they would replicate in different cultural and economic contexts. One more issue was low R-squared in both Study 1 and Study 2 regression analyses [67]. These findings should be treated with caution and future studies should further analyze psychological concomitants of food industry conspiracy beliefs and conscious food choices.

The present research bears significant practical implications, as it points towards a psychological mechanism responsible for an increased willingness to pay more attention to the composition of purchased foods. Therefore, it could also be considered from the perspective of the broader concept of food integrity [68], which includes legal, moral, and ethical dimensions pertaining to the food supply and demand network. Identifying an efficient way of convincing individuals of the benefits of responsible consumption has been a burning issue in the last decades, especially given the general concern with global sustainability [69].

Importantly, although priming food-related threat may be a way to boost food industry conspiracy beliefs and, thus, increase conscious food choices, one should be aware of its potential shortcomings. In fact, previous research showed that feelings of threat [70] as well as conspiracy beliefs have negative consequences (e.g., lack of trust to government; [71] or antisemitic behaviours; [72]). Thus, one should remain cautious when employing this type of interventions. Still, materials elaborated for the purpose of this research could be analyzed by different entities, from local collectives or schools to international organizations, engaged in projects aimed at increasing people’s awareness regarding the implications of conscious food choices. This seems particularly relevant in times when population obesity is accompanied by enormous food waste.

Overall, the current results allowed us to understand the role of food industry conspiracy beliefs in shaping conscious consumer choices. We showed that by increasing the level of this particular conspiracy belief through context-specific, food-related threat, individuals may become more susceptible to cues of danger and show greater readiness to reconsider their food purchasing decisions. Importantly, our research demonstrated that food industry conspiracy beliefs differed from the general notions of conspiracy studied before. The novel approach to the topic of conspiracies adopted in this research not only paves the way for a practical application of its results, but also points towards a yet unexplored area of study related to conspiracy beliefs, that is their possible adaptive outcomes.

14 Mar 2022

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Reviewer #2: Partly

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Reviewer #1: 1. This paper is technically sound and consistant, approaching the research question with proper quantitative methods to demonstrate that food industry conspiracy belief is positively associated with consumers' conscious food choice.

2. The data analysis (Exploratory factor analysis and hierarchical regression using SPSS) is conducted properly and the procedure is well described. One recommendation is to refer to the communalities in the text, especially for study 2 which shows rather low (although still acceptable) average variance explained for food industry conspiracy beliefs and conscious food choices, to clarify whether all items are included in the construct.

3. The questionnaire, treatment and SPSS codes are available from the link on page 8. Full question items for general conspiracy beliefs is missing from the text and the shared data, and it would be better to be made available as well.

4. The quality of English is good enough.

As an additional comment, the practical implication(manuscript p.28) is not very clear, and it can be more specific about how the results should be interpreted and utilized. One concern is, boosting the level of food industry conspiracy means increasing consumers' distrust in or hostile view toward food companies, which is not generally desirable. While the association deserves investigation, I suppose that food industry conspiracy itself is not a "tool" to raise consumers' consciousness about food. This point should be acknowledged if the authors consider the same.

Reviewer #2: General comments:

The authors present the results from two studies with Polish consumers on their conspiracy beliefs about the food industry and how this relates to their conscious food choices. It is an interesting study field because, as the idiom in the title suggests, conspiracy believers are usually associated with maladaptive behaviour. Through both studies the researchers found a positive link between food industry conspiracy beliefs and conscious food choices.

Overall, the structure of the manuscript needs to be improved. Several of the specific comments below discuss some of the gaps or overlaps because of the structure. Subdividing study 1 and study 2 at the highest level creates repetition. More importantly, the fact that 2 constructs were measured in a different way in study 2 but still have the same name makes the interpretation of the results more difficult for the reader. The authors should consider a small change in the name of the variables. The change of measurement tools is not discussed in much detail. The reason behind this choice and the impact on the results should be addressed.

The first issue with the design of the study lies within the construct ‘conscious food choices’ and how it is interpreted. Not much information is provided on how the long version was developed, however for the short version the authors refer to a number of papers on socially responsible consumption. The items used to measure conscious food choices all refer to ‘I will pay attention to …’, which measures how informed consumers are when making their food choices. I would like the authors to add a discussion on why they assume adaptive behaviour based on this construct.

The second issue is the use of education and settlement size variables as dependent variables in the regression analysis. The authors do not mention any recoding of these variables so assuming they used the data as is, this is a wrong approach because these are not interval data.

Specific comments:

100: Throughout the manuscript it seems the authors only consider the food conspiracy beliefs in relation to food safety issues. Considering the definition of food conspiracy beliefs on line 128, I believe the broader concept of food integrity could be used here, which includes food safety but also authenticity. Irregularities with food products’ integrity do not only apply to food safety issues but can be food fraud or mislabelling (f.e. organic or country of origin labelling).

111: The authors should include at least one example from Europe or Poland.

136: The last sentence of this paragraph is unclear

191: It would be interesting to discuss the order of the questions in the questionnaire. Were the conspiracy beliefs asked before the conscious food choices, and if so why did the researches choose this order and how could it have affected the results?

204: The authors report a reliability measure for 4 items of the scale ‘food conspiracy beliefs’. Later on in the manuscript it is mentioned that this scale was measured using 4 items in study 1 and 14 items in study 2. It is important to make this difference clear in the methods section.

244: The authors chose to discuss both studies separately and make a ‘Results and discussion’ section for each of the studies. There is actually not much discussion of the results in that section, and there is another section ‘General discussion’ later on. I would suggest to restructure and rename the sections of the manuscript to make it easier to navigate as a reader and avoid repetition. Overall for both study 1 and study 2 I would be interested in more discussion of the results.

260: Table 1 shows the correlation matrix, including education and settlement size as variables. Can you provide more details about how these were measured and how they could be considered continuous variables?

268: Significant relationship between age and education and conscious food choices are found. Is this in line with your expectations?

274: Please discuss the R squared value of the regression model

274: Unclear what you mean with term ‘basic prediction’

291: general instead of generic

326: Explain in more detail how the items were designed. On line 298, the authors mention that the conceptual principles to develop the tools in study 1 still applied. This made me assume that the added items would follow the principles of line 193, being ‘Each item included three elements: an implied agent (1) secretly undertaking specific action (2) to obtain some type of gain (3). However, when reading the added items, this seems not to be the case.

348: In similar vein, explain how the nine items for the conscious food choices were developed. Overall, the use of the same construct names ‘food industry conspiracy beliefs’ and ‘conscious food choices’ throughout the paper, while measuring them differently is confusing. The authors should differentiate clearly.

370: Have the authors considered if they can accept participants that shop for groceries once a month or less as valid respondents for this study?

370: Was the data analysis carried out with the scale of the variable ‘frequency grocery shopping’ as such, or was this recoded to actual frequency?

381: The researches could elaborate more detailed about why they chose to use mediation analysis and how assumptions for mediation analysis were checked.

383: avoid the use of ‘basic variables’

385: use ‘correlation’ instead of ‘link’, and discuss here that this was not significant in study 1. Could the difference be related to the new way of measuring conscious food choice?

388: since including shopping frequency, I suggest using the term socio-demographic instead of demographic

388: Later on in the results, a significant effect of the treatment (threat vs control) is found. I would expect an explanation why you discuss the difference in socio-demographics without differentiating between those treatment groups. As opposed to study 1, there is difference in conscious food choices between males and females in study 2. Would the difference results be due to different way of measuring conscious food choices or because this study included the experimental manipulation?

392: Age is positively correlated to food conspiracy beliefs but negatively to general conspiracy beliefs, this is an interesting finding. Discuss by comparing to previous studies.

405: avoid the term items but use variables

414: Authors should discuss and interpret R squared of the final model.

434: Please rephrase ‘a significant negative effect of gender’; specify that you entered gender as a dummy variable

445: In study 1, education was significant, but in study 2 it turned out not to be. This difference should be discussed.

477: This paragraph is generalizing the results too much. There were difference between the results of study 1 and study 2 and they are not sufficiently reported and discussed.

486: The authors always refer to the number of respondents that endorse food conspiracy beliefs, based on the results of study 1. In study 2 they used better measurement for this variable, so it seems contradictory that they don’t use the results from the better measurement to give the reader an indication of the food conspiracy beliefs of Polish consumers. The ‘threat’ group could have been influenced by the message, however the control group was not. It would also be interesting to report the difference in mean value of the food conspiracy beliefs for the 2 treatment groups.

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28 Apr 2022

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April 27th, 2022

RE: Notification of decision: PONE-D-22-05042

Dear Professor Hans De Steur,

Thank you for your invitation to revise and resubmit our manuscript entitled “The devil is not as black as he is painted? On the positive relationship between food industry conspiracy beliefs and conscious food choices'' (PONE-D-22-05042). We are very grateful to you and the reviewers for the responses. In this letter, we outline the changes we have made to the paper regarding the minor revision that was requested. Also, we would like to kindly ask you to include our funding statement in the Acknowledgments section (final version of the manuscript) as this is explicitly required by our founding source (National Science Centre).

Thank you in advance!

Authors

Editor’s comments

E.1.1 Please include your full ethics statement in the ‘Methods’ section of your manuscript file. In your statement, please include the full name of the IRB or ethics committee who approved or waived your study, as well as whether or not you obtained informed written or verbal consent. If consent was waived for your study, please include this information in your statement as w well.

Thank you for this suggestion, we have now included an appropriate ethics statement on page 8, which now read as follows: “Both studies were conducted in accordance with the Declaration of Helsinki and approved by the Research Ethics Committee of the Institute of Psychology, Polish Academy of Sciences (number of approval: 26/X/2020). Informed written consent was obtained from all subjects involved in the study.”

Reviewer #1

R1.1. This paper is technically sound and consistant, approaching the research question with proper quantitative methods to demonstrate that food industry conspiracy belief is positively associated with consumers' conscious food choice.

We thank reviewer for their positive comments.

R1.2. The data analysis (Exploratory factor analysis and hierarchical regression using SPSS) is conducted properly and the procedure is well described. One recommendation is to refer to the communalities in the text, especially for study 2 which shows rather low (although still acceptable) for food industry conspiracy beliefs and conscious food choices, to clarify whether all items are included in the construct.

Thank you for pointing this out. We have now elaborated on this issue in the discussion section. Page 28 now reads:

“One of the limitations was low (but acceptable; [63]) average variance explained for food industry conspiracy beliefs and conscious food choices. These scales should be psychometrically tested and revised in the future research. Future research is also needed to better investigate other possible predictors of food industry conspiracy beliefs as well as conscious food choices. For example, it would be interesting to check whether variables usually linked to conspiracy beliefs (e.g., need for cognitive closure; [64] or defensive self-evaluation; [65] would serve as significant predictors of conspiracy thinking also in this case.”

R.1.2 The questionnaire, treatment and SPSS codes are available from the link on page 8. Full question items for general conspiracy beliefs is missing from the text and the shared data, and it would be better to be made available as well.

Thank you for pointing this out! General conspiracy beliefs scale is now available in the OSF folder, available through the link on page 8: https://osf.io/h4x5v/?view_only=d7fd112e8bcb470eb9ec4090882d0e2b

R.1.3 As an additional comment, the practical implication (manuscript p.28) is not very clear, and it can be more specific about how the results should be interpreted and utilized. One concern is, boosting the level of food industry conspiracy means increasing consumers' distrust in or hostile view toward food companies, which is not generally desirable. While the association deserves investigation, I suppose that food industry conspiracy itself is not a "tool" to raise consumers' consciousness about food. This point should be acknowledged if the authors consider the same.

Thank you for that comment. We agree with that, and we have now explained that concern in the discussion section.

Page 30 now reads: “Importantly, although priming food-related threat may be a way to boost food industry conspiracy beliefs and, thus, increase conscious food choices, one should be aware of its potential shortcomings. In fact, previous research showed that feelings of threat [71] as well as conspiracy beliefs have negative consequences (e.g., lack of trust to government; [72] or antisemitic behaviours; [73]). Thus, one should remain cautious when employing this type of interventions.”

Reviewer #2

R2.1. The authors present the results from two studies with Polish consumers on their conspiracy beliefs about the food industry and how this relates to their conscious food choices. It is an interesting study field because, as the idiom in the title suggests, conspiracy believers are usually associated with maladaptive behaviour. Through both studies the researchers found a positive link between food industry conspiracy beliefs and conscious food choices.

We thank the reviewer for their positive comments.

R2.2. Overall, the structure of the manuscript needs to be improved. Several of the specific comments below discuss some of the gaps or overlaps because of the structure. Subdividing study 1 and study 2 at the highest level creates repetition. More importantly, the fact that 2 constructs were measured in a different way in study 2 but still have the same name makes the interpretation of the results more difficult for the reader. The authors should consider a small change in the name of the variables. The change of measurement tools is not discussed in much detail. The reason behind this choice and the impact on the results should be addressed.

Thank you for your comment. We decided to subdivide Study 1 and 2 as they had different designs (i.e., Study 1 was cross-sectional, Study 2 was experimental). We believed they should not be merged to avoid confusion. We also changed the names of the scales in the method section by adding “short scale” (pp. 9-10) and “full scale” (pp. 15-17) to the previous measures’ labels. We used longer versions of our measurement tools to analyze the full spectrum of the variables of our main interest (i.e., conspiracy beliefs and conscious food choices). This is now clarified on page 14:

“One limitation of Study 1 was that we measured the crucial variables (e.g., food industry conspiracy beliefs and conscious food choices) with the use of short (four- and three-item) scales. Therefore, in Study 2 we examined whether the pattern of results obtained in Study 1 would conceptually replicate if we used better measurement tools. We operationalized the food industry conspiracy beliefs and conscious food choices with 14 and 9 items respectively. The conceptual principles applied while developing the tools remained the same as in Study 1, with some items including an implicit allusion to the action secretly undertaken by food industry companies for their own benefit. Still, both extended versions of the scales showed high reliability (listed below) and Exploratory Factor Analysis provided single factor solutions for both of them.”

In such a way, we extended the scales used in Study 1 with additional items referring to, for example, adding harmful, addictive substances (in the food industry conspiracy beliefs scale) and buying healthy food in local, trusted places (in the conscious food choices scale).

Moreover, we conducted additional analyses to find out whether the pattern of results would be similar when considering only the same items as in Study 1 (short version). The results remained the same (please find the details below and in the OSF folder).

Mediation Analyses Using Same Items as in Study 1 (Study 2)

In order to perform a full test of our hypotheses, we conducted a mediation analysis using model 4 in Process 3.5 [57]. Significance was tested with bootstrapped 95% confidence intervals for the unstandardized indirect effects, constructed with 10,000 resamples. The analysis, displayed in Fig 2, examined whether food industry conspiracy beliefs mediated the path between the experimental condition (threat vs. control) and conscious food choices. As covariates we used general conspiracy beliefs, gender, age, education level, settlement size, shopping frequency, and subjective financial situation. We found that the experimental condition positively and significantly predicted food industry conspiracy beliefs, B = 0.18, SE = 0.06, 95% CI [0.07, 0.29], p = .002 and that, in turn, food industry conspiracy beliefs positively and significantly predicted conscious food choices, B = 0.10, SE = 0.04, 95% CI [0.01, 0.18], p = .024. The indirect effect of the experimental condition on conscious food choices via food industry conspiracy beliefs was positive and significant, B = 0.02, SE = 0.01, 95% CI [0.001, 0.041]. All effects remained the same when we computed these analyses without the covariates. Next, we conducted similar analyses with general conspiracy beliefs as a mediator: the experimental condition did not predict general conspiracy beliefs significantly, B = -0.03, SE = 0.06, 95% CI [-0.14, 0.08], p = .550, and general conspiracy beliefs was not a significant predictor of conscious food choices, B = 0.04, SE = 0.04, 95% CI [-0.05, 0.13], p = .364. The indirect effect of the experimental condition on conscious food choices via general conspiracy beliefs was also non-significant, B = -0.001, SE = 0.004, 95% CI [-0.010, 0.005].

R2.3. The first issue with the design of the study lies within the construct ‘conscious food choices’ and how it is interpreted. Not much information is provided on how the long version was developed, however for the short version the authors refer to a number of papers on socially responsible consumption. The items used to measure conscious food choices all refer to ‘I will pay attention to …’, which measures how informed consumers are when making their food choices. I would like the authors to add a discussion on why they assume adaptive behaviour based on this construct.

Thank you for drawing attention to this issue. Indeed, the scale developed for the purpose of this research was inspired by past work on responsible consumption and it was our intention to use examples of behaviours that had been identified as such, for example checking the product’s ingredients, country of origin, or degree of processing. Still, while socially responsible consumption "can promote social causes consumers deem important" (Francois-Lecompte & Roberts, 2006, p. 51), in our studies, we were not interested in the social/environmental/political motives of food choices. Our focus was more on the individual's health. It seems that socially responsible consumption is a broader term than "conscious food choices." We believe that these constructs are related, but this needs further empirical investigation. In the case of adaptiveness, we argue that conscious food choices - made with an awareness and sensitivity to clues of potential danger or some kind of risks - are adaptive in the sense that they can prevent individuals from jeopardizing their health. Maladaptive, on the other hand, would be exposing yourself to the dangers of potential contamination of some product. In this sense, maladaptive means thoughtless, inconsiderate, which stands the opposite of "conscious choice."

The extended version of the scale (used in Study 2) was still based on the same principles as in Study 1, though it was extended to check if the results would replicate when we used a longer tool, hence it also included a wider variety of examples conscious shopping behaviours. Still, both scales formed a single factor in the Exploratory Factor Analysis. The phrase "I will pay attention to" we often used in our items is directly related to the term "conscious choices." In this way, we aimed to emphasize that food choices are made with awareness and attention and, thus, are conscious. Of course, in this case, we are aware that this measurement is only declarative and we acknowledge that it is a limitation and mention that in the the paragraph describing future directions. We see that the scale could be interpreted as reflecting how much the consumers are informed about the composition of the products they consider buying and believe it could translate into adaptive behavior for several reasons. First, past research on social and other intangible product attributes demonstrated that they did in fact influence actual product choice (Auger et al., 2010). Second, self-reported shopping behavior has been previously associated with actual decisions, though they dependent on the type of product (Moser, 2016). Third, research on implicit vs explicit attitudes towards brands showed that they were in fact positively associated [7, 8]. Based on these findings, we assume that the conscious food choices scale we developed would be positively associated with specific actions too, though it would have to be checked. We have now added a clearer explanation regarding that assumption in the Discussion section on p. 28-29, which reads:

“Additionally, data measuring conscious food choices relied on self-reported declarations, so verifying whether a similar increase would be noted in actual shopping behaviour is needed. Given the findings of past research on consumer choices and implicit attitudes [7, 8], social and intangible attributes [66], as well as self-reported shopping behaviour [67], we assume that the pattern of results obtained in the present studies would remain similar, though this would have to be verified in the future.”

R2.3. The second issue is the use of education and settlement size variables as dependent variables in the regression analysis. The authors do not mention any recoding of these variables so assuming they used the data as is, this is a wrong approach because these are not interval data.

Thank you. We used demographics as independent variables to check for their potential role in shaping food industry conspiracy beliefs and conscious food choices and, especially, to find out whether the pattern of results would stay the same after controlling for age, gender etc. These were not the variables of our main interest, but still potentially interesting. Importantly, when conducted analyses without these variables, the results remained the same.

Specific comments:

100: Throughout the manuscript it seems the authors only consider the food conspiracy beliefs in relation to food safety issues. Considering the definition of food conspiracy beliefs on line 128, I believe the broader concept of food integrity could be used here, which includes food safety but also authenticity. Irregularities with food products’ integrity do not only apply to food safety issues but can be food fraud or mislabelling (f.e. organic or country of origin labelling).

Thank you for your comment. We appreciate your suggestion, however, if we were to replace the concept of food conspiracy theories with food integrity, the entire theoretical background on which we base the main hypothesis would have to be different. The scale was developed to reflect the fundamental principles of conspiracy thinking, namely that some secret agents are plotting behind our back to obtain some kind of a gain and that the results of that secret action may be potentially threatening to us (Douglas et al., 2019). As far as we are aware, food integrity is a much broader concept including many specific issues, but it does not contain that element of conspiracy thinking we employed in the scale. Of course, it is an interesting insight to consider the results of our research from the perspective of food integrity and we have now elaborated on this idea in the discussion section on pages 30:

“The present research bears significant practical implications, as it points towards a psychological mechanism responsible for an increased willingness to pay more attention to the composition of purchased foods. Therefore, it could also be considered from the perspective of the broader concept of food integrity [69], which includes legal, moral, and ethical dimensions pertaining to the food supply and demand network. Identifying an efficient way of convincing individuals of the benefits of responsible consumption has been a burning issue in the last decades, especially given the general concern with global sustainability [70].”

111: The authors should include at least one example from Europe or Poland.

Thank you for that comment. We added some statistics from the European Union.

Page 5 now reads: “Another example is the European Union, where more than 90,000 cases of Salmonella are recorded each year and the main risk of infection in humans is associated with the consumption of contaminated food [43].”

136: The last sentence of this paragraph is unclear

Thank you for your comment! We have now rephrased this sentence to improve its clarity.

Page 6 now reads: “However, it needs to be highlighted that our intention was not to verify the validity of these accusations, but to explore the psychological concomitants of conspiracy beliefs related to the food industry. “

191: It would be interesting to discuss the order of the questions in the questionnaire. Were the conspiracy beliefs asked before the conscious food choices, and if so why did the researches choose this order and how could it have affected the results?

Thank you for your comment. Indeed, this issue requires explanation. Thus, we elaborated on it in the discussion section.

Page 28 now reads:

“Other limitation was the decision about the order of the scales. In Study 1, we decided that the order of the scales should be rotated to maximize the validity of the research. In Study 2, we decided that food industry conspiracy beliefs should be presented before conscious food choices, as its possible underpinning. Although the variables were positively related to each other in both cases, future research would do well to further explore the potential influence the order of these scales might have on the results.”

204: The authors report a reliability measure for 4 items of the scale ‘food conspiracy beliefs’. Later on in the manuscript it is mentioned that this scale was measured using 4 items in study 1 and 14 items in study 2. It is important to make this difference clear in the methods section.

Thank you for that comment. Scales used in Study 2 are extended versions of the measurement tools employed in Study 1. For the sake of clarity, we changed the names of the scales in the method section by adding “short scale” (pp. 9-10) and “full scale” (pp. 15-17) to the previous measures’ labels. It is described in the methods on pages 9 and 16

244: The authors chose to discuss both studies separately and make a ‘Results and discussion’ section for each of the studies. There is actually not much discussion of the results in that section, and there is another section ‘General discussion’ later on. I would suggest to restructure and rename the sections of the manuscript to make it easier to navigate as a reader and avoid repetition. Overall for both study 1 and study 2 I would be interested in more discussion of the results.

Thank you for that comment. The purpose of short discussion after each study’s results is more to summarize the study and provide initial directions of interpretation. Detailed discussion is in the General discussion section, and it focuses on particular aspects of both studies. We would prefer not to rename the sections, because we believe that its current version is more in line with previous papers on conspiracy beliefs (e.g., Marchlewska et al., 2021, Jolley & Douglas, 2014, Stojanov et al., 2020, Alsuhibani et al., 2022). Naturally, we will change it if you think it is necessary.

Moreover, the revised version of the manuscript includes a more detailed discussion. Specifically, we elaborated more on the limitations and future directions issues.

260: Table 1 shows the correlation matrix, including education and settlement size as variables. Can you provide more details about how these were measured and how they could be considered continuous variables?

Thank you for this comment. We explain they way of measurement of these variables in details on page 10 in section called “Covariates”. We agree that these variables are not continuous in nature, thus, requiring different than Pearson correlation coefficients. Please note, however, that we tested these associations using Spearman rank-order coefficient, finding nearly identical results. Thus, to ease the presentation of the results, we left Pearson's correlations coefficients. We did, however, added an additional footnote emphasizing that the correlation to categorical variables (i.e., education and settlement size) were essentially the same when rank-order correlation coefficient was applied.

Table 1 on page 12 now reads: Note. We also conducted correlation analyses using Spearman test. Results remained the same.

In order to be consistent we also provided footnote to Table 3.

Table 3 on page 20 now reads: Note. We also conducted correlation analyses using Spearman test. Results remained the same.

268: Significant relationship between age and education and conscious food choices are found. Is this in line with your expectations?

Thank you for this remark. Age and education were not our main variables of interest, we used them as covariates and we had no specific expectations related to demographic variables. However, as you noted, we found some interesting significant relationships and they should be reported in the discussion. Thus, we added new sentences to Study 1 and 2.

Page 13 now reads:

“Additionally, we found that higher levels of education and age predicted more conscious food choices. It seems that older, more life-experienced, and better-educated individuals focus more on conscious choices while purchasing food products.”

Page 26 now reads as follows:

“We also replicated the effect of age, suggesting that older individuals pay more attention to purchasing food consciously. However, we did not find a similar result for education.”

274: Please discuss the R squared value of the regression model

Thank you for that comment. We added further interpretation in the discussion.

p 29. now reads: “One more issue was low R-squared in both Study 1 and Study 2 regression analyses [68]. These findings should be treated with caution. Future studies should further analyze psychological concomitants of food industry conspiracy beliefs and conscious food choices.”

274: Unclear what you mean with term ‘basic prediction’

Thank you for that comment. The point of this phrase was to indicate predictions connected to our hypotheses, but to make it clearer we decided to delete word “basic”.

291: general instead of generic

Thank you for that comment. We have now changed the word accordingly.

326: Explain in more detail how the items were designed. On line 298, the authors mention that the conceptual principles to develop the tools in study 1 still applied. This made me assume that the added items would follow the principles of line 193, being ‘Each item included three elements: an implied agent (1) secretly undertaking specific action (2) to obtain some type of gain (3). However, when reading the added items, this seems not to be the case.

Thank you for this comment. Indeed, the same principles still applied in Study 2, but some of the items included an implicit allusion to the core elements of conspiracy theories, rather than an explicit one [29]. For example, the item “Food processing companies use genetically modified ingredients without letting the consumers know” contains an element of implied gain because if information is withheld there must be a reason for doing that. Similarly, if “Nobody really knows what is inside of food products” it is because someone is purposely not telling us that. To make the issue clearer, we have now added the following to the section introducing Study 1 (p. 14):

“The conceptual principles applied while developing the tools remained the same as in Study 1, with some items including an implicit allusion to the action secretly undertaken by food industry companies for their own benefit. Still, both extended versions of the scales showed high reliability (listed below) and Exploratory Factor Analysis provided single factor solutions for both of them.”

348: In similar vein, explain how the nine items for the conscious food choices were developed. Overall, the use of the same construct names ‘food industry conspiracy beliefs’ and ‘conscious food choices’ throughout the paper, while measuring them differently is confusing. The authors should differentiate clearly.

Thank you for this suggestion. We added “short scale” and “full scale” at the end of the scales’ name in methods section as suggested. We understand that using the same name can be confusing, however, both the short versions used in Study 1 and the long versions in Study 2 measure the same constructs and yield the same patterns of results. Scales used in Study 2 include the original items employed in Study 1. To demonstrate the validity of the construct we have now performed some additional analysis for Study 2 including only the original 4 items from Study 1. We included these analyses in OSF folder.

https://osf.io/h4x5v/?view_only=d7fd112e8bcb470eb9ec4090882d0e2b

370: Have the authors considered if they can accept participants that shop for groceries once a month or less as valid respondents for this study?

Thank you for that comment. Only 0.9% of respondents said that they went shopping once a month or never. However, we conducted additional analysis and found that the results did not change when we excluded these participants.

370: Was the data analysis carried out with the scale of the variable ‘frequency grocery shopping’ as such, or was this recoded to actual frequency?

The frequency of grocery shopping was coded as it was presented within the scale. We did not recode this variable to reflect the actual frequency as we did not have had such objective data.

381: The researches could elaborate more detailed about why they chose to use mediation analysis and how assumptions for mediation analysis were checked.

Thank you for this comment. We used mediation to examine whether the indirect effect of experimental condition on conscious food choices via food industry conspiracy beliefs.

The relationship of condition and conscious food choices exists through food conspiracy beliefs.

We checked the normality of the variables, linearity of the model, homoscedasticity, autocorrelation of the variables, collinerality, measurement error and if errors have homogeneous variance. All of the results were acceptable enough to use mediation analysis.

383: avoid the use of ‘basic variables’

Thank you for that comment. We have now refrained from using this term.

385: use ‘correlation’ instead of ‘link’, and discuss here that this was not significant in study 1. Could the difference be related to the new way of measuring conscious food choice?

Thank you for that comment. We have now changed “link” to “correlation” when possible. Conscious food choices scale was used in full version in Study 2, which in our belief might have resulted in such an outcome. Indeed, the correlation between conscious food choices and general conspiracy beliefs (r = .04, p = .388) was not significant in Study 1, but it was significant (r = .09, p = .017) in Study 2. Moreover, we conducted additional correlation analysis, employing only the items used in Study 1 for the conscious food choices scale, and this relationship was also not significant (r = .07, p = .060). Thus, it might be the case that the use of a longer, more complex measurement of conscious food choices has resulted in such an outcome, as you suggested in this comment.

388: since including shopping frequency, I suggest using the term socio-demographic instead of demographic

Thank you for that comment. We changed it where it was necessary.

388: Later on in the results, a significant effect of the treatment (threat vs control) is found. I would expect an explanation why you discuss the difference in socio-demographics without differentiating between those treatment groups. As opposed to study 1, there is difference in conscious food choices between males and females in study 2. Would the difference results be due to different way of measuring conscious food choices or because this study included the experimental manipulation?

Thank you for that comment. We had no specific hypothesis on the different effects of threat on the variables of main interest (e.g., conspiracy beliefs) among male vs. female participants. In other words, according to our knowledge, there is no theoretical justification for such.

For this reason, we would prefer to stick to the current version of the analytical section. However, we would be glad to add additional results in the supplementary file should you deem this appropriate.

392: Age is positively correlated to food conspiracy beliefs but negatively to general conspiracy beliefs, this is an interesting finding. Discuss by comparing to previous studies.

Thank you for that comment. This is an interesting finding, however, it only occurred in Study 2. On the contrary, Study 1 showed that age did not correlate significantly with food industry conspiracy beliefs or general conspiracy beliefs. Thus, with such inconsistencies between the studies, we would suggest treating these relationships between age, general conspiracy beliefs, and food industry conspiracy beliefs with caution, especially while the latter is the construct that – to our knowledge – has never been investigated before. It is possible that food industry conspiracy beliefs are characterized by some specificity related to age. For example, it is plausible that older individuals who have more experience with the food industry or with purchasing food over their lives may be more prone to believing in such theories. However, we do not have enough evidence to theorize about it.

We are certain that it requires more research, but we are not sure about discussing it in that manuscript. Of course, we would be happy to include a more detailed discussion of these issues in the manuscript, should you deem this appropriate

405: avoid the term items but use variables

Thank you for that comment. We changed it where it was necessary.

414: Authors should discuss and interpret R squared of the final model.

Thank you for that comment. We added interpretation in the general discussion section.

p 29. now reads: “One more issue was low R-squared in both Study 1 and Study 2 regression analyses [68]. These findings should be treated with caution. Future studies should further analyze psychological concomitants of food industry conspiracy beliefs and conscious food choices.”

434: Please rephrase ‘a significant negative effect of gender’; specify that you entered gender as a dummy variable

Thank you for that comment. We rephrased that statement.

Page 23 now reads: Gender was a significant and negative predictor of conscious food choices

We also added an information about the coding of this variable on page 10:

“In addition to age and gender (coded Female = 0, Male =1)”

445 : In study 1, education was significant, but in study 2 it turned out not to be. This difference should be discussed.

The zero-order relation between education to food industry conspiracy beliefs was indeed non-significant in Study 1 and significant in Study 2. We are sure that it requires more research and mentioned about it in discussion.

p. 29 now reads: “Another issue is that education was weakly and negatively related to food industry conspiracy beliefs (although this relation was non-significant in Study 1). This surely requires future research and better verification.”

477: This paragraph is generalizing the results too much. There were difference between the results of study 1 and study 2 and they are not sufficiently reported and discussed.

Thank you for that comment. We understand why this paragraph seemed overgeneralized. However, it is a short discussion, in which we aimed to summarize the results of Study 2 only. The results of both studies are precisely described and discussed in the General discussion.

Things that are mentioned in short discussion are also included in general discussion, where they are more widely talked over. The example of verse 497 discussed in general discussion on p. 26-27:

“However, we argued that there were some exceptions to this rule and showed (Study 1 and Study 2) that in some cases conspiracy beliefs were in fact related to adaptive behaviors. Specifically, we showed that those who endorsed food industry conspiracy beliefs were found to be more conscious consumers (i.e., scored higher on conscious food choices).”

In the General Discussion, we also highlighted some differences between Study 1 and Study 2. For example, page 28 says:

Other limitation was the decision about the order of the scales. In Study 1 we decided that the order of the scales should be rotated to maximize the validity of the research. In Study 2 we decided that food industry conspiracy beliefs should be presented before conscious food choices, as its possible underpinning. Although the variables were positively related to each other in both cases, future research would do well to further explore the potential influence the order of these scales might have on the results.

486: The authors always refer to the number of respondents that endorse food conspiracy beliefs, based on the results of study 1. In study 2 they used better measurement for this variable, so it seems contradictory that they don’t use the results from the better measurement to give the reader an indication of the food conspiracy beliefs of Polish consumers. The ‘threat’ group could have been influenced by the message, however the control group was not. It would also be interesting to report the difference in mean value of the food conspiracy beliefs for the 2 treatment groups.

Thank you for that comment. The whole sample was representative - with random assignment to conditions, but not in all groups. Thus, frequencies based on Study 2 would not be necessarily more reliable than those in Study 1. Due to the experimental manipulation conducted in Study 2, we restrained from adding frequencies for the whole sample (for those exposed to a threat material and those exposed to control material).

However, we conducted these analyses using independent t-test which are in line with regression analyses reported in the manuscript. We present them below:

Independent t-test Analysis of Main Variables Between Threat and Control Group

Variable Threat group Control group t(763) p

M SD M SD

Food industry conspiracy beliefs 3.21 0.93 2.95 0.91 -3.85 <.001

Conscious food choices 3.62 0.80 3.54 0.82 -1.35 .178

General conspiracy beliefs 2.75 0.98 2.68 0.93 -1.04 .298

References:

Alsuhibani, A., Shevlin, M., Freeman, D., Sheaves, B., & Bentall, R. P. (2022). Why conspiracy theorists are not always paranoid: Conspiracy theories and paranoia form separate factors with distinct psychological predictors. PloS one, 17(4), e0259053.

Auger, P., Devinney, T. M., Louviere, J. J., & Burke, P. F. (2010). The importance of social product attributes in consumer purchasing decisions: A multi-country comparative study. International Business Review, 19(2), 140-159.

Douglas, K. M., Uscinski, J. E., Sutton, R. M., Cichocka, A., Nefes, T., Ang, C. S., & Deravi, F. (2019). Understanding conspiracy theories. Political Psychology, 40, 3-35.

Francois-Lecompte, A., & Roberts, J. A. (2006). Developing a measure of socially responsible consumption in France. Marketing Management Journal, 16(2).

Jolley, D., & Douglas, K. M. (2014). The effects of anti-vaccine conspiracy theories on vaccination intentions. PloS one, 9(2), e89177.

Marchlewska, M., Górska, P., Malinowska, K., & Jarosław, K. (2021). Threatened masculinity: Gender-related collective narcissism predicts prejudice toward gay and lesbian people among heterosexual men in Poland. Journal of homosexuality, 1-16.

Moser, A. K. (2016). Consumers' purchasing decisions regarding environmentally friendly products: An empirical analysis of German consumers. Journal of Retailing and Consumer Services, 31, 389-397.

Stojanov, A., Bering, J. M., & Halberstadt, J. (2020). Does Perceived lack of control lead to conspiracy theory beliefs? Findings from an online MTurk sample. PloS one, 15(8), e0237771.

20 Jun 2022

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Additional Editor Comments:

Dear authors,

Given the concerns of one reviewer regarding the statistical analysis, I recommended major revision in order to allow you enough time to address these crucial concerns.

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Reviewer #2: No

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Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #2: Thank you to the authors for there extensive answer to my comments on the original manuscript. You have made additions and changes that have improved the manuscript. Most of the comments have clarified some of the issues I had with the paper.

I would still hope you can further clarify why education and settlement sizee, used as covariates are treated as continuous variables.

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Reviewer #2: No

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27 Jun 2022

Reviewer #2

Reviewer #2: Thank you to the authors for the extensive answer to my comments on the original manuscript. You have made additions and changes that have improved the manuscript. Most of the comments have clarified some of the issues I had with the paper.

I would still hope you can further clarify why education and settlement sizee, used as covariates are treated as continuous variables.

Once again, thank you for all your comments! We have now refrained from using education and settlement size as continuous variables and based on dummy coding procedure (Hutcheson & Sofroniou, 1999) that allowed us to use these variables in regression analyses.

Methods section now reads:

Both education and settlement size were explanatory variables of categorical level. Thus, we decided to use a dummy coding procedure to control for their effects while predicting the variables of the main interest (Hutcheson & Sofroniou, 1999). Primary degree and rural area were used as reference categories.

We have now reanalysed our data using dummy variables (both Study 1 & Study 2).

The results could be found in the main file.

26 Jul 2022

The Devil is not as Black as He is Painted? On the Positive Relationship Between Food Industry Conspiracy Beliefs and Conscious Food Choices

PONE-D-22-05042R2

Dear Dr. Marchlewska,

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Academic Editor

PLOS ONE

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1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

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Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #2: Yes

**********

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PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: Thank you for addressing my concerns and taking the time to make the changes in the analysis. The final manuscript is an interesting view on conspiracy beliefs in Poland.

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Reviewer #2: No

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29 Jul 2022

PONE-D-22-05042R2

The devil is not as black as he is painted? On the positive relations­­­­hip between food industry conspiracy beliefs and conscious food choices

Dear Dr. Marchlewska:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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