Promoting Sustainable Lifestyle Habits: “Real Food” and Social Media in Spain

  Citation: Segovia-Villarreal, M.; Rosa-Díaz, I.M. Promoting Sustainable Lifestyle Habits: “Real Food” and Social Media in Spain. Foods 2022,11, 224. https:// doi.org/10.3390/foods11020224 Academic Editors: Juan-Antonio Mondéjar-Jiménez and María-Almudena Soriano-Pérez Received: 12 December 2021 Accepted: 11 January 2022 Published: 14 January 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). foods Article Promoting Sustainable Lifestyle Habits: “Real Food” and Social Media in Spain María Segovia-Villarreal 1and Isabel María Rosa-Díaz 2,* 1Department of Financial Economics and Accounting, Faculty of Business Sciences, University Pablo de Olavide, 41004 Sevilla, Spain; [email protected] 2Department of Business Administration and Marketing, Faculty of Economics and Business Sciences, University of Seville, 41018 Sevilla, Spain *Correspondence: imr[email protected] Abstract: Obesity and state of being overweight are beginning to be treated as global epidemics. In this context, health professionals are increasingly acting as expert opinion leaders that use social media to connect with the public, in order to promote healthy lifestyles and provide specific recommendations for different product categories, including fresh, processed, and ultra-processed meat products. This study investigates how exposure to content created by health professionals, and posted on social media, influences consumers’ attitudes. For this purpose, the collaboration of one relevant nutritionist influencer in Spain has been obtained. The online survey created has provided 4.584 responses , received from followers (from May to June 2019). After applying a partial least squares path modeling approach, the results suggest that trust in the content shared, the perceived credibility of the professional sharing the information and the informative value, determine the strength with which consumers acquire more knowledge about endorsed products, develop a favorable predisposition towards them, prefer them over their options, and modify their behaviour by purchasing them, instead of their usual foods. The link is stronger, in the case of trust and influencer’s credibility, than for informative value. However, the latter has an indirect effect on the attitude phases through the former. Keywords: real food; meat food; healthy properties; social media; consumer perceptions; marketing in foods 1. Introduction Chronic diseases, such as cardiovascular pathologies, certain types of cancers, overweight, obesity, and diabetes, are starting to be treated as global epidemics, whose main triggers are unhealthy diets, sedentary lifestyles, and stress [ 1 – 3 ]. This is why interest in health consciousness, which refers to the degree to which individuals are concerned with their health, is such a popular topic nowadays [1,4,5]. Previous research claims that several factors, for instance the desire for hedonic pleasure, may guide food choices and contradict the motivation of eating healthy, because they usually lead to less healthy food choices, including ultra-processed meat products. However, this relationship becomes weaker when consumers have greater health consciousness. This is because consumers with high health consciousness engage in more elaborate decision making, by relying on prior health knowledge and beliefs, when evaluating properties of food [ 3 , 4 ]. Nevertheless, consumers find themselves feeling overwhelmed, as a result of the saturation of health consciousness information shared by institutions, health professionals, companies, and the general public [5,6]. Researchers have studied consumers’ perceptions about the reliability of the source of food information and found that they prefer professional and objective sources in this context [ 5 ]. However, the content of the information disclosed is not always easily understandable for people who do not master this area of knowledge. At the same time, Foods 2022,11, 224. https://doi.org/10.3390/foods11020224 https://www.mdpi.com/journal/foods Foods 2022,11, 224 2 of 21 consumers are also confronted with nutrition and health claims shared by companies in the marketing campaigns of their products, from commercials to packaging. Nutrition and health claims are statements in any message, conveyed in text or image, that establish, suggest, or imply that a food has beneficial nutrition properties [6]. As opposed to information disclosed by scientific and official sources, nutrition and health claims are usually easily comprehensible, thus increasing their chances of attracting consumers’ attention. Consequently, while more consumers are concerned about health consciousness, a rise in the use of nutrition and health advertising messages has occurred in recent years, as an effective marketing strategy to respond to the new demands. Yet, consumers are beginning to distrust nutrition and health claims, due to serious cases of manipulation in food labelling or misleading advertising [ 6 ]. Therefore, the need for new strategies to promote healthy eating is clear [ 3 ]. These new strategies should focus on consumers’ attitudes towards the associations between food and health in decision making but also considering the aforementioned challenges [ 3 , 4 ]. Taking advantage of the great range of possibilities, offered by the numerous social media (SM) platforms available, many health professionals are creating SM profiles to share their knowledge with the general public [ 7 ]. Nutritionists share reliable, professional information online about food items’ properties, regarding health, in a way that is easily understandable for people who are not experts in this area. This has the potential to influence consumer behaviour towards healthy food products. In Spain, several nutritionists are taking part in this strategy and causing a real impact on their followers’ behaviour and decisions as consumers [ 8 – 13 ]. This trend is this movement is known as “Real Food” or “Real Fodding” (initiated in that country by the nutritionist Carlos Ríos, at the beginning of 2017, which promotes the consumption of real food, good-processed food fresh, minimally processed food, or food which industrial or handcrafted processing has not worsened the quality of the natural properties of the specific food) against the consumption of ultra-processed food, which cope supermarket shelves and most occidental diets. This issue takes on special importance in this context, since certain tendencies have been identified among Spanish consumers to associate meat products with unhealthy foods, undervaluing their beneficial health properties. However, at the same time, they are increasing their consumption of ultra-processed meat products. When this research started, Carlos Ríos had around 500,000 followers on his Instagram account. Now, as the research reaches the end, he has nearly one-and-a-half million. So, it can be stated that the trend is still growing and expected to have more influence over consumers, at the same time as the nutritionists become social media influencers. The importance of this rising trend can also be observed in the wide variety of articles in newspapers and magazines covering the topic [8–13]. For this research, the nutritionist Carlos Ríos has collaborated with us. He promotes healthism, which is the pursuit of specific food choices to enhance physiological function and reduce disease risk. This is achieved by raising health consciousness, through instructional materials about healthy food properties, shared on SM [ 5 ]. Due to the wide range of food-related products in supermarkets worldwide, the influencer pairs these suggestions with specific product recommendations. It is to be expected that followers report improvements in their overall health after following the influencer’s guidelines, displayed on his SM accounts, and that they also recommend and advocate for the trend in their environment. Moreover, since the influencer shares useful and hands-on information, regarding specific food products, followers of this trend will take into account the knowledge that they garnered to make more conscious decisions as consumers. The striking success seems to result from the decoupling from brands’ promotional efforts, the vast references used to base the information provided in influencer-generated content, fact that the person behind the trend is a professional in the health sector who creates visually appealing and easily accessible information content, and possibility of interaction, so that followers can keep in touch with and receive support from the influencer, as well as from other followers. His most popular way of sharing knowledge is usually by Foods 2022,11, 224 3 of 21 going to the main supermarket chains in Spain and explaining the quality of each product by a disclosure of the ingredients, located on the reverse of every food, instead of the nutrition and health claims located on the front of the packaging. Based on all that has been stated, the present research aims at testing the impact that exposure to content advocating health consciousness may have on consumer behaviour, in terms of awareness, knowledge, liking, preference, purchase intention, and purchase of food-related products linked to the real food content being shared on SM. For doing so, this study addresses preliminary explanations as to how this relationship occurs, by analyzing the role that some variables, such as informative value, trust, and influencer’s credibility, may have in determining the strength of this link. A quantitative study, articulated by an online survey, is selected as a way to assist large data collection. The answers from the 4.584 respondents were analyzed by employing the partial least squares structural equation modeling technique (PLS-SEM), through the SmartPLS 3 computer pack. 2. Theoretical Background 2.1. Consumer Behaviour, Social Media Influencers, and Health Consciousness According to consumer behaviour theory, when a strong need is recognized, consumers search for information and evaluate alternatives before making the final decision of performing a purchase, in order to minimize the post-purchase cognitive dissonance that results from inadequate choices [ 14 ]. A few decades ago, this process of information search was mainly limited to consumers’ knowledge, collected from their own experience, plus feedback from family, friends, and neighbours, which consumers consider more reliable than companies’ promotional efforts [ 15 ]. Nowadays, SM impacts decision making by creating farther connections that allow for the gathering of more trustworthy information and opinions from other participants in social networks [16,17]. Power and Phillips-Wren (2011) defined SM as “web-based and mobile technologies that enhance human communication and create dynamic, interactive dialogues”. When consumers become users of SM, they experience the feeling of being able to know more about products and services, as well as their availability, price, location, and desired attributes [ 15 , 18 ]. This means that they can expand their social environment, and it is usually expected that when this happens, it has an impact on the consumers’ decision process [19]. Traditionally, individuals have taken on different roles, when engaging in interpersonal communications. On the one hand, opinion leaders can influence others’ attitudes and behaviours, using their actions and other interpersonal tools. On the other hand, followers are usually fascinated about opinion leaders and frequently ask them for advice, which will be more likely to be accepted than the advice of non-opinion leaders [ 19 ]. With the introduction of SM, users joining social networks started adopting such roles, as would be done in any kind of social relationship [20,21]. Social media influencers are electronic opinion leaders that can increase the influence of the information they receive and transmit to others [ 21 ]. According to Freberg et al. (2011) social media influencers “represent a new type of independent third-party endorser who shape audience attitudes through blogs, tweets, and the use of other SM”. In this sense, the influencer-generated content of social media influencers is considered to be more authentic and in direct contact with potential consumers than brand-generated ads [ 22 ]. Twitter studies suggest that consumers may accord social media influencers a similar level of trust as they hold for their friends [23]. Usually, social media influencers use their abilities to create visually appealing content, in which a particular product, service, or brand is portrayed, and their characteristics are highlighted in a way that resembles a personal recommendation. Followers of the social media influencers will then have access to all the content posted by the influencer, and the information gathered will affect their consumer decision process to an extent that will depend on variables such as trust on the influencer, age, disposable income, or personal interest [15,20,21]. Foods 2022,11, 224 4 of 21 Consumers usually look for information on SM to get an expert opinion about the massive supply of products that they find in the market, especially in those cases when they simply do not have the background to be able to discern the best products for their needs. In this context, social media influencerdevelopment has shown a professionalization of the sector, which means that experts from different areas of knowledge have created an account on SM platforms to share their expertise. One such example is the rise of health sector-related professionals, such as nurses, gynaecologists, paediatricians, and nutritionists, entering SM to share their knowledge with their followers [ 7 ]. This is the case that we aim to explore in this research, especially its connection with consumer behaviour, as a result of gaining information related to health consciousness on SM. 2.2. Theoretical Framework and Model Previous studies already recognized the important role of information garnered through SM in analyzing consumer behaviour nowadays [ 14 , 24 – 28 ]. Most of the authors studied this link by focusing on the behavioural attitudes of the consumers’ decision process, since they are easily noticed and can be measured. However, from feeling a need to buy something, other complex mechanisms take place in the mind of the consumer, such as liking or preferring the product over other alternatives, that are not considered in those approaches [ 15 ]. Moreover, just some of the previous research considers relevant variables that could explain the link between exposure to SM content and behaviour, such as trust in the person sharing the information or information quality [20,21,24]. Based on this literature review, and taking into account the aforementioned purpose of this study, the two most complete frameworks for adopting a holistic approach in the analysis of the exposure to content generated by nutritionists, and its effect on consumer behaviour, could result from the combination of the models used by Duffett (2017) [ 24 ], who considers cognitive, affective, and behavioural attitudes, not just behavioural ones, and Lou and Yuan (2018) [ 20 ], who takes into account informativeness, credibility, and trust in the content shared, as a way to explain the link. Duffett (2017) [ 24 ] uses the framework of the multicomponent model of attitude phases according to Barry (1987) [ 29 ]. The reasons for selecting it in this particular research are twofold. First, it is a suitable way to keep a balance between cognitive, affective, and behavioural responses to SM communications. Previous studies focusing on purchase intentions did not consider the impact that content may have on other stages of the consumers’ decision process, in terms of attitudes [ 15 , 18 , 20 , 21 ]. Second, by testing multiple dependent variables, both researchers and companies will be able to identify hidden problems and reaching effects of each relationship for further analysis. According to Duffett (2017) [ 24 ], consumers move through attitude phases: awareness of the brand’s existence (cognitive attitude), knowledge of the brand’s offers (cognitive attitude), liking the brand by having a favourable predisposition to it (affective attitude), displaying preference toward the brand when compared to others (affective attitude), conviction that purchase of the brand would be sensible (behavioural attitude), and the final purchase of the brand (behavioural attitude). These six phases, which are successive and not necessarily equidistant, will be the variables used to measure the effect of content on followers’ behaviours and attitudes as consumers. However, in this research study, instead of measuring the impact on brands, the focus is on products, in general, as a way of assessing the effect of the content on increasing the health consciousness of followers towards healthy food products, in general, as a whole. Building on this approach to understanding consumers’ attitudes, the underlying mechanisms that explain SM’s effect on consumers were integrated in the model, as a way to provide more understanding of the complete phenomenon. The variables, proposed by Lou and Yuan (2018) [ 20 ], serve to provide figures, as to explain some of the determinants of the stated relationship. These variables are influencer-generated content informativeness, as well as trust and influencer’s credibility, measured through the perceived expertise, trustworthiness, attractiveness, and similarity of the influencer-generated content posted Foods 2022,11, 224 5 of 21 on their profile. Lou and Yuan (2018) [ 20 ] also suggested that informative value could have an indirect effect over consumer behaviour, through trust and influencer’s credibility. Based on the literature review and purpose of the study, a model can be depicted to guide this part of the research. The model, shown in Figure 1, portrays the relationship that exposure to real food content on SM, through consumers’ perceived informative value of influencer generated content, as well as trust on it and influencer’s credibility, may have on the different attitudes of the consumer. Additionally, everything that has been stated can be summarized in the following hypotheses: Hypothesis 1 (H1). Trust in non-branded influencer-generated content on social media and influencer’s credibility positively affects consumers’ attitude phases (cognitive, affective, and behavioural). Hypothesis 2 (H2). The informative value of influencer-generated content on social media positively affects consumers’ attitude phases (cognitive, affective, and behavioural). Hypothesis 3 (H3). The informative value of influencer-generated content on social media has a positive influence over the degree of trust that consumers place over the influencer-generated content on social media and the influencer’s credibility. Figure 1. Theoretical model. Foods 2022,11, 224 6 of 21 3. Materials and Methods 3.1. Case Selection In order to achieve the objectives of the research, the case of the nutritionist Carlos Ríos, who has succeeded on SM as an influencer, was selected, due to the fact that the percentage of branded content in his profile is extremely low; therefore, the effect of non-branded content could be properly analyzed. This influencer started a trend that became popular in Spain, and other Spanish-speaking regions, by using his expertise and rising influence over other users on SM. Hence, this case seems to fit well with the objectives of this study, namely studying the influence that non-branded, influencer-generated content on SM may have on followers’ attitudes, regarding awareness, knowledge, liking, preference, purchase intention, and purchase of real food and good processed food products. Similarly, once this relationship has been tested, an assessment will be made of the changes in attitudes promoted by the perceived trust in the content generated by the influencer, credibility of the influencer, and informative and entertaining value of the content shared. 3.2. Procedure, Measurement, and Sample Selection An online survey was designed, in line with the objectives of this research and based on the work of some of the authors from the literature review. As explained previously, the main variables of this study are exposure to non-branded influencer-generated content on SM, awareness, knowledge, liking, preference, purchase intention, purchase, informative and entertainment value of influencer-generated content, trust of non-branded influencer-generated content on SM, and influencer’s credibility. To be able to measure all of these variables through the survey method, we used different scales, proposed by Duffett (2017) [ 24 ] and Lou and Yuan (2018) [ 20 ]. The former included a series of questions in his data collection process, aimed at understanding the link between the multicomponent model of attitude phases, from awareness to purchase, and the exposure to branded, influencer-generated content on SM. In our case, we selected and adapted some of these questions so as to fit our objectives and our specific case. For the measurement of informative and entertainment value of influencer-generated content, trust of non-branded influencer-generated content, and influencer’s credibility, we decided to use the tools proposed in the study of Lou and Yuan (2018) [20]. All of the questions adapted from Lou and Yuan (2018) [ 20 ] were anchored by sevenpoint semantic differential scales, except for the entertainment value, while those from Duffett (2017) [ 24 ] were simply formulated using a seven-level Likert scale, which goes from strongly disagree to strongly agree, with the statement proposed in each case [ 29 , 30 ]. They were all displayed following a single positive direction in order to make it easier for the respondent. The use of seven-point semantic differential scales allowed us to capture an acceptable range of variation in the answers, without compromising the simplicity of the survey. Both of these measurement approaches were proven adequate for measuring the variables in previous studies, and the analysis of the measurement model was satisfactory in both of them. The questions included in the survey, as shown to respondents (both in English and in the original language, Spanish), are listed in Appendix A. Once the objectives and case were selected, and the survey was designed using Google Forms, data collection took place. It started in May 2019 and ended at the beginning of June 2019 . In order to carry out a successful and assertive data collection process, we decided to focus on reaching respondents through SM. Moreover, it would not be relevant to consider data about changes in consumers’ decision process of people who did not know the real food trend, because the consumers’ decision process would not be altered at all, due to the lack of new information linked to non-branded, influencer-generated content on SM about the real food. So, we were interested in getting as many answers as possible from people following the real food trend, either through the main social media influencer, Carlos Ríos, or through any other influencer who gave information about it frequently. Therefore, two filter questions were included in the survey, to be able to discern answers from people who knew the movement and whose changes in consumers’ decision Foods 2022,11, 224 7 of 21 process could be studied. Not only that but we also contacted Carlos Ríos to ask him to distribute the survey amongst his followers, in order to reach the objective population. Finally, he agreed, and we were able to incorporate very precise and representative data from the population. There are many ways in which we could measure the research population, as proposed by previous authors. They stated that the number of followers that an influencer has does not reflect the actual active engagement in the information shared. The fact that people follow an influencer but do not see or interact with the content may mean that they are not getting the information shared in non-branded, influencer-generated content about the real food and, consequently, their consumer behaviour would not be affected. Hence, other indicators should be considered, such as the number of likes in the content posted on the different social media platforms [ 21 , 24 , 31 ]. Thus, a few figures could be displayed in this study, although we are going to make it simple and share only two figures. A total of 800,000 is the number of followers that Carlos Ríos had in June 2019, although it changes every day, while the number of likes in the content, shared during that same month, oscillates between 13,800 and 31,400. The final sample consisted of a total of 4595 answers, from which 4584 went beyond the filter questions; so, depending on which figure we consider, we would be talking about a 0.57% or between a 14.6% and a 33.2% representation rate. From these 4584 respondents, apart from their rating of the indicators for each of the nine variables, we obtained information about their age, gender, nationality, level of education, and social strata, to be able to provide a demographic depiction of our sample, which will be displayed in Section 4.1. Moreover, four questions were included at the end of the survey that will serve us for the discussion and implication of results. They were about their perceptions, as active SM users and consumers, of the industry and how well it is adapting to the challenges posed by the real food guidelines, when talking about healthy eating. This was motivated by the fact that on SM, followers of the real food trend are continuously sharing discomfort about going to the supermarket and finding a lack of supply of products that fall within the real food guidelines, which would imply a misunderstanding or disregard of this situation by companies from the sector. 3.3. Data Analysis Once data collection took place, a partial least squares (PLS) path modeling approach was adopted and articulated by employing the SmartPLS 3 computer pack to perform both measurement validation and structural modeling [ 32 ]. Moreover, PLS path modeling is also recommended over CB-SEM for testing complex models with many latent variables, as in this case that we have nine latent variables [33,34]. Regarding the sample size of this study, it meets the condition imposed by PLSSEM of being at least 10 times the greatest number of structural paths predicting a specific construct. The latent variables in the current model all have reflective measurements (the latent variables precede the indicator). In this manner, the indicators represent effects of the latent constructs and are highly correlated [ 34 ]. For this reason, in the use of the selected computer pack for this research, SmartPLS 3, the consistent PLS algorithm and consistent bootstrapping options have been selected. These options perform corrections of reflective constructs’ correlations to make results consistent with a factor-model. 4. Results 4.1. Socio-Demographic and Consumer-Related Characteristics of the Sample With respect to the main characteristics observed in our sample, Table 1provides a comprehensive overview of respondents’ socio-demographic and consumer-related variables included in the survey. Foods 2022,11, 224 8 of 21 Table 1. Socio-demographic and consumer-related characteristics of the sample. Variable Percentage% Gender Female 87.8 Male 11.9 Age Below 18 4 From 19 to 25 34 From 26 to 35 40 From 36 to 45 15 From 46 to 55 6 From 56 to 65 1 66 or above 0 Nationality Spain 95.8 Other 4.2 Level of Education Primary education or below 0.7 Secondary education (first stage) 5.2 Secondary education (second stage) 11.3 Higher education 82.7 Income Level/Social Strata Low 3.9 Medium-low 20.9 Medium 61.5 Medium-high 13 High 0.7 The socio-demographic factors suggest that the respondents were mainly Spanish young females, with a high level of education (82.7%) and perception of belonging to the medium social strata, meaning a moderate amount of income within the context of Spain. 4.2. Descriptive Analysis of the Study Variables The descriptive data of the variables included in our study are shown in Appendix B. Its analysis allows several conclusions to be drawn. First, looking at the awareness phase, the vast majority of respondents agreed with the fact that the content shared by real food influencers made them rethink the way to buy and consume food, and found the content was also useful for being aware of alternatives to ultra-processed food and started paying attention to those. Nevertheless, only 91% of respondents clearly remember the content posted, of which 43% strongly agreed. Overall, followers do become more aware of alternatives to the ultra-processed food, according to the real food trend. Moving onto the second attitude phase, knowledge, 98% of respondents agreed with the statement, and 70% of them chose the highest level of agreement. This allows us to assert that the knowledge garnered through non-branded influencer-generated contents on SM is being incorporated in the decision-making process of real food followers. Focusing now on the liking phase, the great majority of respondents begin to value real food and good-processed food more after encountering real food content on SM, at the same time as they started to develop a critical view of ultra-processed food. In this case, the number of respondents choosing the highest level of agreement is remarkable, as 72.6% and 71.4% of respondents, respectively, said that they strongly agreed with the liking-related statements. Then, talking about developing a positive attitude towards products related to the real food trend, the preference phase would be a step further than liking. In this case, 96% of respondents asserted that the content encouraged them to prefer real food and good-process food, at the same time as they become more reluctant to believe everything that is broadcasted in ultra-processed food’s marketing campaigns. The main reason is that Foods 2022,11, 224 9 of 21 they have the knowledge, derived from non-branded influencer-generated contents on SM, about the real food trend that allows them to discern whether or not these products are actually worth, in terms of health facts, rather than promotional efforts. Around 60% of respondents opted for the highest level of agreement in both preference statements. Following this line of reasoning, once consumers are aware of a product, know enough about it, and like it over other alternatives, it is only right to think that an intention towards purchasing the product will start emerging in the mind of the consumers. When considering both purchase intention, as well as the actual Purchase of the product, the level of agreement with the statement declines. It may be due to the fact that other variables will come into play (for instance, the level of engagement with making an important change in their diets) and will largely differ from one consumer to another. Finally, when talking about the last attitude phase, purchase, the tendency observed in purchase intention repeats itself; that is, the percentage of respondents agreeing with the statements proposed is not as high as for the first attitude phases. In the next sections, we proceed to test some exogenous variables that could help understand this link between non-branded, influencer-generated content on SM about the real food trend and the different attitude phases of consumers who are followers of the trend. 4.3. Measurement Model Validation Measures related to internal consistency and convergent validity needed to assess the measurement model in this research (all constructs are reflective) are included in Table 2. First, most of the items’ loadings are almost equal to or higher than 0.7 (the factor loading for every item should be 0.6 or higher) [ 35 ]. When analyzing the average variance extracted AVE (for further testing convergent validity), all constructs have a value higher than the threshold of 0.5, which represents the minimum threshold for AVE. Therefore, we can assert that, overall, the constructs have an acceptable convergent validity level. Table 2. Measurement model assessment. Construct Indicator aWeight Loadings AVE bComposite Reliability Informative Value (IV) IV1 1.000 1.000 1.000 1.000 Trust (T) + Influencers’ Credibility (IC) T1 0.180 0.803 0.613 0.917 T2 0.182 0.816 T3 0.174 0.779 T4 0.192 0.858 IC1 0.180 0.804 IC2 0.176 0.787 IC3 0.137 0.711 Awareness (AW) AW1 0.308 0.689 0.503 0.801 AW2 0.325 0.728 AW3 0.356 0.798 AW4 0.272 0.709 Knowledge (KN) KN1 1.000 1.000 1.000 1.000 Liking (LK) LK1 0.579 0.816 0.615 0.761 LK2 0.534 0.751 Preference (PR) PR1 0.528 0.855 0.750 0.857 PR2 0.541 0.877 Purchase Intention (PI) PI1 0.684 0.730 0.513 0.780 PI2 0.508 0.662 Foods 2022,11, 224 16 of 21 Acknowledgments: We would like to specially acknowledge Carlos Ríos and the “Real Fooding” team, led by Julian Romero, who, disinterestedly, listened to our interest in studying the phenomenon they were contributing to in social media, and kindly agreed to share our survey with their followers, so as to reach a higher and more sharpened audience. Thanks, also, to Yeray Vidal from “nofitsireal” for also sharing our research with his followers, allowing us to gather a greater variety of opinions. We hope this research will give recognition to the nutrition training that you offer every day, for free, to all social media users. Finally, we appreciate the support from the University of Seville for the feedback received for this research. Conflicts of Interest: The authors declare no conflict of interest. Appendix A Table A1. Variables considered in this research, with respective questions included in the survey, as displayed for the respondents (in English, as well as in the original language, Spanish). Variable Measurement (English) Medida (Spanish) Awareness The content created by the influencer on social media related to health and real food prompts me to rethink the way I buy and consume food in my diet. Los contenidos creados por el influencer en redes sociales relacionados con la salud y la comida real me incitan a replantear la forma de comprar y consumir alimentos en mi dieta. The content created by the influencer on social media related to health and real food is effective in raising awareness of real food alternatives and good processed foods. Los contenidos creados por el influencer en redes sociales relacionados con la salud y la comida real son efectivos para darme a conocer las alternativas de comida real y buenos procesados. The content created by the influencer on social media related to health and real food leads me to direct my attention to products considered real food and good processed ones. Los contenidos creados por el influencer en redes sociales relacionados con la salud y la comida real hacen que dirija mi atención hacia productos considerados comida real y buenos procesados. I can recall several pieces of content created by the influencer on social media related to health and real food. Puedo recordar varios contenidos creados por el influencer en redes sociales relacionados con la salud y la comida real. Knowledge User-created content on social media related to health and real food allows me to incorporate useful new information into my process of evaluating alternatives as a consumer. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me permiten incorporar nueva informaciónútil en mi proceso de evaluación de alternativas como consumidor. Liking User-created content on social media related to health and real food leads me to value products considered real food and good processed ones. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me llevan a valorar los productos considerados comida real y buenos procesados. Preference User-created content on social media related to health and real food leads me to develop a more critical view towards products that do not contribute to the supply of real and good processed food. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me llevan a desarrollar una visión más crítica hacia los productos que no contribuyen al suministro de comida real y buenos procesados. User-created content on social media related to health and real food leads me to prefer products considered real food and good processed ones. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me llevan a preferir productos considerados comida real y buenos procesados. User-created content on social media related to health and real food stimulates my preference for products related to real food and good processed ones even when marketing campaigns for products related to ultra-processed ones seem to be better than those for the former. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real estimulan mi preferencia por productos relacionados con la comida real y los buenos procesados incluso cuando las campañas de marketing de productos relacionados con los ultra-procesados parecen ser mejores que las de los anteriores. Foods 2022,11, 224 17 of 21 Table A1. Cont. Variable Measurement (English) Medida (Spanish) Purchase Intention User-created content on social media related to health and real food prompts me to want to buy products that appear in them or that fall within the parameters offered to categorize products related to real food and good processed ones. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me incitan a desear comprar productos que aparecen en ellos o que entran dentro de los parámetros que se ofrecen para categorizar los productos relacionados con la comida real y los buenos procesados. User-created content on social media related to health and real food prompts me to want to not buy products that appear in them or that fall within the parameters offered to categorize ultra-processed related products. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me incitan a desear no comprar productos que aparecen en ellos o que entran dentro de los parámetros que se ofrecen para categorizar los productos relacionados con los ultra-procesados. Purchase I tend to buy products related to user-created content on social media related to health and real food. Suelo comprar productos relacionados con los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real. I use quite a few of the products related to user-created content on social media. Uso bastantes de los productos relacionados con los contenidos creados por el usuario en redes sociales. User-created content on social media related to health and real food contributes to my loyalty to brands that supply products related to real food and good processed food. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real contribuyen a fomentar mi lealtad hacia las marcas que suministran productos relacionados con la comida real y los buenos procesados. I tend to take into account the information that appears in user-created content on social media related to health and real food to make decisions in my purchasing processes. Suelo tener en cuenta la información que aparece en los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real para tomar decisiones en mis procesos de compra. Trust I find user-created content on social media related to health and real food to be: honest or dishonest. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me resultan: honestos o deshonestos. I find user-created content on social media related to health and real food to be: trustworthy or untrustworthy. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me resultan: dignos de confianza o poco dignos de confianza. I find user-created content on social media related to health and real food to be: credible or not credible. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me resultan: convincentes o no convincentes. I find user-created content on social media related to health and real food: convincing or unconvincing. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me resultan: convincentes o no convincentes. Informative Value of Influencer- Generated Content I find user-created content on social media related to health and real food: relevant to inform me about real food and good processed vs. ultra-processed or not relevant. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me resultan: relevantes para informarme sobre la comida real y los buenos procesados frente a los ultra-procesados o no relevantes. Influencer’s Credibility I find user-created content on social media related to health and real food to be: trustworthy or untrustworthy. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me resultan: fiables o no fiables. I find user-created content on social media related to health and real food: appealing or unattractive. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me resultan: atractivos o no atractivos. I find the user-created content on social media related to health and real food close and inviting to interact with the user or other followers of the user or I find it: distant and I find it inappropriate to interact with the user or other followers of the user. Los contenidos creados por el usuario en redes sociales relacionados con la salud y la comida real me resultan cercanos y me invitan a interactuar con el usuario u otros seguidores del mismo o me resultan: distantes y me parece inadecuado interactuar con el usuario u otros seguidores del mismo. Foods 2022,11, 224 18 of 21 Appendix B Table A2. Descriptive analysis of the study variables. Variable Measurement Agreement or Disagreement (7-Point Semantic Differential Scales) % Respondents Awareness The content created by the influencer on social media related to health and real food prompts me to rethink the way I buy and consume food in my diet. 7 6 5 4 to 1 63.5 24.8 8.6 3.1 Content created by the influencer on social media related to health and real food is effective in raising awareness of real food alternatives and good processed foods. 7 6 5 4 to 1 71.6 21.4 4.9 2 The content created by the influencer on social media related to health and real food leads me to direct my attention to products considered real food and good processed ones. 7 6 5 4 to 1 67.8 23.5 6.4 2.3 I can recall several pieces of content created by the influencer on social media related to health and real food. 7 6 5 4 to 1 43.4 30.9 16.7 9 Knowledge User-created content on social media related to health and real food allows me to incorporate useful new information into my process of evaluating alternatives as a consumer. 7 6 5 4 to 1 69.5 23.3 5.2 1.9 Liking User-created content on social media related to health and real food leads me to value products considered real food and good processed ones. 7 6 5 4 to 1 72.6 20.6 4.8 2 User-created content on social media related to health and real food leads me to develop a more critical view towards products that do not contribute to the supply of real and good processed food. 7 6 5 4 to 1 71.4 20.6 5.5 2.4 Preference User-created content on social media related to health and real food leads me to prefer products considered real food and good processed ones. 7 6 5 4 to 1 59.7 24 12.2 4.1 User-created content on social media related to health and real food stimulates my preference for products related to real food and good processed ones even when marketing campaigns for products related to ultra-processed ones seem to be better than those for the former. 7 6 5 4 to 1 60.5 25.4 9.8 4.4 Purchase Intention User-created content on social media related to health and real food prompts me to want to buy products that appear in them or that fall within the parameters offered to categorize products related to real food and good processed ones. 7 6 5 4 to 1 44.5 28.1 17.5 9.9 User-created content on social media related to health and real food prompts me to want to not buy products that appear in them or that fall within the parameters offered to categorize ultra-processed related products. 7 6 5 4 to 1 45.1 24.2 14.5 16.2 Foods 2022,11, 224 19 of 21 Table A2. Cont. Variable Measurement Agreement or Disagreement (7-Point Semantic Differential Scales) % Respondents Purchase I tend to buy products related to user-created content on social media related to health and real food. 7 6 5 4 to 1 31.3 29.6 23.9 15.1 I use quite a few of the products related to user-created content on social media. 7 6 5 4 to 1 36.1 30.8 20.5 12.5 User-created content on social media related to health and real food contributes to my loyalty to brands that supply products related to real food and good processed food. 7 6 5 4 to 1 43.3 32.1 16.1 8.5 I tend to take into account the information that appears in user-created content on social media related to health and real food to make decisions in my purchasing processes. 7 6 5 4 to 1 52.6 29.7 11.7 6 Trust I find user-created content on social media related to health and real food to be: honest (7) or dishonest (1). 7 6 5 4 to 1 55.3 30.7 10.2 3.9 I find user-created content on social media related to health and real food to be: trustworthy (7) or untrustworthy (1). 7 6 5 4 to 1 54.3 32.9 9.6 3.2 I find user-created content on social media related to health and real food to be: credible (7) or not credible (1). 7 6 5 4 to 1 56.9 32 8.5 2.6 I find user-created content on social media related to health and real food: convincing (7) or unconvincing (1). 7 6 5 4 to 1 55.3 30.9 10.5 3.4 Informative Value of Influencer- Generated Content I find user-created content on social media related to health and real food: relevant to inform me about real food and good processed vs. ultra-processed (7) or not relevant (1). 7 6 5 4 to 1 59.9 28.4 9.2 2.6 Influencer’s Credibility I find user-created content on social media related to health and real food to be: trustworthy (7) or untrustworthy (1). 7 6 5 4 to 1 51.1 33.1 12.1 3.7 I find user-created content on social media related to health and real food: appealing (7) or unattractive (1). 7 6 5 4 to 1 44.7 34.4 15.6 5.4 I find the user-created content on social media related to health and real food: close and inviting to interact with the user (7) or other followers of the user or I find it: distant and I find it inappropriate to interact with the user or other followers of the user (1). 7 6 5 4 to 1 42.6 27.2 18.6 11.6 Foods 2022,11, 224 20 of 21 References 1. Cavaliere, A.; De Marchi, E.; Banterle, A. Does consumer health-orientation affect the use of nutrition facts panel and claims? An empirical analysis in Italy. Food Qual. Prefer. 2016,54, 110–116. [CrossRef] 2. World Health Organization. Obesity and Overweight. 2005. Available online: http://www.who.int/dietphysicalactivity/ publications/facts/obesity/en/ (accessed on 14 April 2019). 3. Saba, A.; Sinesio, F.; Moneta, E.; Dinnella, C.; Laureati, M.; Torri, L.; Bendini, A. Measuring consumers’ attitudes towards health and taste and their association with food-related life-styles and preferences. Food Qual. Prefer. 2019,73, 25–37. [CrossRef] 4. Buhrau, D.; Ozturk, T.C. Motivating healthy eating: The role of presentation format and health consciousness. Food Qual. Prefer. 2018,64, 167–171. [CrossRef] 5. Jeong, J.Y.; Kim, H.C. Korean mothers’ food choice behavioral intent for children: An examination of the interaction effects of food type, household income, and healthism. Food Qual. Prefer. 2020,81, 103835. [CrossRef] 6. Klopˇciˇc, M.; Slokan, P.; Erjavec, K. Consumer preference for nutrition and health claims: A multi-methodological approach. Food Qual. Prefer. 2020,82, 103863. [CrossRef] 7. González Olivas, R. “Marketing de Influencia en el Sector Salud: La Figura del Influencer”. DiarioFarma. Available online: https://www.diariofarma.com/2019/07/18/marketing-de-influencia-en-el-sector-salud-la-figura-del-influencer (accessed on 18 July 2019). 8. Campillo, S. “La Ciencia Detrás del Movimiento Real Food, ¿EstáAvalado por Estudios o es Solo una Moda?”. Vitónica. Available online: https://www.vitonica.com/alimentos/la-ciencia-detras-del-movimiento-real-food-esta-avalado-por-estudios-o-es- solo-una-moda (accessed on 14 May 2018). 9. Carpallo, S. “QuéDebes Saber de la ‘Comida Real’, la Dieta de la que Todos Hablan”. El País, SModa. Available online: https:// smoda.elpais.com/belleza/que-debes-saber-de-la-comida-real-la-dieta-de-la-que-todos-hablan/ (accessed on 14 August 2018 ). 10. Díaz Madurga, L. “Realfooding: Volver a Comer Como lo Hacían tus Abuelos”. Gastroactitud. Available online: https: //www.gastroactitud.com/pista/realfooding-volver-a-comer-como-lo-hacian-tus-abuelos/ (accessed on 30 April 2019). 11. Heidemeyer, P. “¿Quées el “Realfooding”? Bezzia. Available online: https://www.bezzia.com/que-es-el-realfooding/ (accessed on 21 July 2019). 12. Ortí, A. “Por quécasi Medio Millón de Personas Siguen en Instagram a este Nutricionista de Huelva.” El País, Buena Vida. Available online: https://elpais.com/elpais/2018/11/30/buenavida/1543582333_914196.html (accessed on 5 December 2018). 13. Ruiz De La Prada, S. “‘Realfooding’: El Movimiento que Arrasa en Internet y que Debes Conocer”. Hapers’ Bazaar. Available online: https://www.harpersbazaar.com/es/belleza/dieta-ejercicios-adelgazar-belleza/a23304101/dieta-comida-realfooding- movimiento-comida-real-que-es/ (accessed on 15 October 2018). 14. Lin, M.; Choudhury, A.H. Using website information to reduce postpurchase dissonance: A mediated moderating role of perceived risk. Psychol. Mark. 2021. [CrossRef] 15. Baalbaki, A.M.; Azzam, N.J.; El-Kassar, A.N. The influence of social media behaviour of university students in Lebanon on their purchasing habits: The mediating effect of e-Word-of-Mouth. Mark. Brand. Res. 2017,4, 303. 16. Al-Damat, A.M.; Al-Damat, O.A. Impact of Social Support Resources on Post- Purchase Dissonance: Evidence from Jordan. Int. J. Bus. Soc. Sci. 2019,10, 53–62. 17. Power, D.J.; Phillips-Wren, G. Impact of social media and Web 2.0 on decision-making. J. Decis. Syst. 2011 ,20, 249–261. [CrossRef] 18. Malik, F.; Asif, M.; Wali, S. Role of Social Media on Consumer Preferences. City Univ. Res. J. 2016,6, 256–268. 19. Cao, P.; Meister, S.; Klante, O. How social media influence apparel purchasing behaviour. Mark. Rev. St. Gallen 2014 ,31, 77–86. [CrossRef] 20. Lou, C.; Yuan, S. Influencer Marketing: How Message Value and Credibility Affect Consumer Trust of Branded Content on Social Media. J. Interact. Advert. 2018,19, 1–45. [CrossRef] 21. Magno, F.; Cassia, F. The impact of social media influencers in tourism. Anatolia 2018,29, 288–290. [CrossRef] 22. Talavera, M. Making the Market for Influencer Marketing. AdWeek 2015. Available online: http://adweek.it/1cNbFwq (accessed on 6 March 2019). 23. Swant, M. Twitter Says Users Now Trust Influencers Nearly as Much as Their Friends. AdWeek 2016. Available online: http://www.adweek.com (accessed on 22 March 2019). 24. Duffett, R.G. Influence of social media marketing communications on young consumers’ attitudes. Young Consum. 2017 ,18, 19–39. [CrossRef] 25. Gensler, S.; Völckner, F.; Liu-Thompkins, Y.; Wiertz, C. Managing brands in the social media environment. J. Interact. Mark. 2013,27, 242–256. [CrossRef] 26. Iyiola, O.; Akintunde, O. Perceptions as influencer of consumer choice behaviour: The case of tourism in Nigeria. J. Mark. Dev. Compet. 2011,5, 27–36. 27. Kumar, V.; Bhaskaran, V.; Mirchandani, R.; Shah, M. Practice prize winner—Creating a measurable social media marketing strategy: Increasing the value and ROI of intangibles and tangibles for hokey pokey. Mark. Sci. 2013,32, 194–212. [CrossRef] 28. Murphy, K. The Influence of Content Generation on Brand Attitude and Purchase Intention within Visual Social Media. Master’s Thesis, Dublin Business School, Dublin, Ireland, 2014. 29. Barry, T.E. The development of the hierarchy of effects: An historical perspective. Curr. Issues Res. Advert. 1987,10, 251–295. Foods 2022,11, 224 21 of 21 30. Voss, K.E.; Spangenberg, E.R.; Grohmann, B. Measuring the hedonic and utilitarian dimensions of consumer attitude. J. Mark. Res. 2003,40, 310–320. [CrossRef] 31. Freberg, K.; Graham, K.; McGaughey, K.; Freberg, L.A. Who are the social media influencers? A study of public perceptions of personality. Public Relat. Rev. 2011,37, 90–92. [CrossRef] 32. Hair, J.F.; Sarstedt, M.; Hopkins, L.; Kuppelwieser, V.G. Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. Eur. Bus. Rev. 2014,2, 106–121. [CrossRef] 33. Henseler, J.; Ringle, C.M.; Sarstedt, M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 2015,43, 115–135. [CrossRef] 34. Hair, J.F.; Risher, J.J.; Sarstedt, M.; Ringle, C.M. When to use and how to report the results of PLS-SEM. Eur. Bus. Rev. 2019,31, 2–24. [CrossRef] 35. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981,18, 39–50. [CrossRef] 36. Cohen, J. Statistical Power Analysis for the Behavioral Sciences, 2nd ed.; Laurence Erlbaum: Mahwah, NJ, USA, 1988. 37. Malthouse, E.C.; Haenlein, M.; Skiera, B.; Wege, E.; Zhang, M. Managing customer relationships in the social media era: Introducing the social CRM house. J. Interact. Mark. 2013,27, 270–280. [CrossRef] 38. Matthews-King, A. “Western Diet now Killing More Than Smoking and High Blood Pressure, Study Suggests”. Independent. Available online: https://www.independent.co.uk/news/health/western-diet-fat-salt-fruit-veg-fibre-cancer-heart-disease- obesity-diabetes-a8853696.html (accessed on 4 April 2019). 39. Mitelu t , , A.C.; Popa, E.E.; Drăghici, M.C.; Popescu, P.A.; Popa, V.I.; Bujor, O.-C.; Ion, V.A.; Popa, M.E. Latest Developments in Edible Coatings on Minimally Processed Fruits and Vegetables: A Review. Foods 2021,10, 2821. [CrossRef] [PubMed] 40. Monteiro, C.A.; Cannon, G.; Levy, R.B.; Moubarac, J.C.; Louzada, M.L.C.; Rauber, F.; Khandpur, N.; Cediel, G.; Neri, D.; Martinez-Steele, E.; et al. Ultra-processed foods: What they are and how to identify them. Public Health Nutr. 2019 ,22, 936–941. [CrossRef] 41. Duplaga, M.; Grysztar, M. Nutritional Behaviors, Health Literacy, and Health Locus of Control of Secondary Schoolers in Southern Poland: A Cross-Sectional Study. Nutrients 2021,13, 4323. [CrossRef] [PubMed] 42. Monteiro, C.A.; Moubarac, J.C.; Levy, R.B.; Canella, D.S.; Louzada, M.L.; Cannon, G. Household availability of ultra-processed foods and obesity in nineteen European countries. Public Health Nutr. 2017,21, 18–26. [CrossRef] 43. Talens, P.; Cámara, M.; Daschner, A.; López, E.; Marín, S.; Martínez, J.A.; Morales, F.J. Informe del ComitéCientífico de la Agencia Española de Seguridad Alimentaria y Nutrición (AESAN) sobre el impacto del consumo de alimentos “ultra-procesados” en la salud de los consumidores. Revista ComitéCientífico AESAN 2020,31, 49–76. 44. Consumption Report of the Spanish Ministry of Agriculture, Fisheries and Food. 2018. Available online: https://www.mapa.gob. es/images/es/20190807_informedeconsumo2018pdf_tcm30-512256.pdf (accessed on 2 January 2022). 45. Consumption Report of the Spanish Ministry of Agriculture, Fisheries and Food. 2020. Available online: https://www.mapa.gob. es/es/alimentacion/temas/consumo-tendencias/informe-anual-consumo-2020-v2-nov2021-baja-res_tcm30-562704.pdf (accessed on 2 January 2022).