Psychological and sociodemographic contexts of attitudes towards new genomic techniques (NGT) foods and products in Poland.

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Learn more: PMC Disclaimer | PMC Copyright Notice Sci Rep . 2026 Apr 12;16:17002. doi: 10.1038/s41598-026-48713-x Psychological and sociodemographic contexts of attitudes towards new genomic techniques (NGT) foods and products in Poland Jagoda Różycka 1, 2, 5, # , Łukasz Jach 1, 5, # , Monika Stojek 1, 2, 3, 5, # , Marek Marzec 4, 5, ✉ Author information Article notes Copyright and License information 1 Institute of Psychology, University of Silesia, Katowice, Poland 2 Trauma, Health and Eating (Thrive) Lab, Institute of Psychology, University of Silesia in Katowice, Katowice, Poland 3 Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA USA 4 Faculty of Natural Sciences, University of Silesia, Katowice, Poland 5 Research Center for New Genomic Techniques, University of Silesia, Katowice, Poland ✉ Corresponding author. # Contributed equally. Received 2025 Aug 10; Accepted 2026 Apr 9; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13230753  PMID: 41968167 Abstract New Genomic Techniques (NGTs) offer promising opportunities to improve agricultural productivity and sustainability; however, their public acceptance remains uncertain. Guided by the Tripartite Attitude Model, this study tested hypotheses concerning psychological and demographic predictors of attitudes toward NGT food products. This study examined demographic and psychological (i.e., cognitive, affective, and behavioral) factors influencing attitudes toward NGT food products in a Polish sample ( N = 850; aged 18–88). Participants provided information on their expectations regarding NGT foods, their opinions on the changes that the introduction of NGT foods would bring, their willingness to try NGT products, and their opinions on the effectiveness of encouragement to the consumption of NGT products, along with assessments of conspiracy beliefs, attitudes toward science, food neophobia, food technology neophobia, disgust sensitivity, consumer awareness, and political orientation. Results revealed that older participants showed lower willingness to try NGT foods compared to younger groups. Moreover, positive attitudes toward science, openness to new foods, and subjective consumer awareness were positive predictors of favorable attitudes toward NGT foods. In contrast, food technology neophobia and conspiracy beliefs were negative predictors of these attitudes. Our findings emphasize the importance of psychological and sociodemographic contexts in shaping consumer acceptance of innovative food technologies, highlighting the need for targeted communication strategies to address skepticism and enhance trust. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-026-48713-x. Keywords: Attitudes towards science, Conspiracy beliefs, Consumer attitudes, Food technology neophobia, Genome-edited foods, New genomic techniques (NGTs) Subject terms: Genetics, Psychology, Psychology Introduction One of the most significant contemporary challenges facing science is ensuring sufficient food production for a growing global population. The world’s population is expected to reach 10 billion by 2050 and continue increasing thereafter 1 . Climate change further intensifies the pressure on food production systems, necessitating continuous efficiency improvements. Extreme weather events, such as droughts and floods, can devastate crops, leading to yield losses of up to 90% 2 . Additionally, shifting climatic conditions facilitate the migration of pathogens into new regions, where native plants may lack resistance to them 3 . Furthermore, increasingly stringent regulations are being implemented to enforce sustainable agricultural practices. While these regulations aim to mitigate environmental impact, they may also challenge maintaining high productivity levels. Currently, plant-based food production remains the foundation of global agriculture, either through direct human consumption or as feed for livestock 4 . For decades, developing improved crop varieties has been a central focus of agricultural research. In the early 20th century, this process accelerated with the introduction of mutagenesis techniques. These methods, which involve exposing plant material to physical or chemical factors to induce random mutations, have played a crucial role in crop improvement 5 . While many induced mutations are unfavorable, some confer beneficial traits such as increased yield, enhanced quality, or greater resistance to biotic (e.g., fungi, bacteria, viruses, insects) and abiotic stresses (e.g., drought, salinity, extreme temperatures, heavy metals). Mutagenesis has contributed to the development of nearly 3,500 new plant varieties worldwide 6 . However, its major limitation lies in the random nature of mutations, necessitating extensive labor and development of large populations, often comprising thousands of individuals, for effective selection and testing. Biotechnological tools were developed to enhance precise traits through genetic modification, thereby overcoming these limitations. However, genetically modified organisms (GMOs) often contain genetic material from unrelated species, raising concerns and controversies regarding their cultivation and consumption 7 . Consequently, GMO cultivation remains restricted in several regions, including the European Union (EU). Nevertheless, ongoing legislative discussions in the EU are considering the approval of specific new genomic techniques (NGTs) for food and feed production. NGTs encompass a variety of advanced methods that enable precise genome editing by introducing targeted modifications at specific DNA locations 8 . Some of these techniques allow for highly specific alterations, even at the single-nucleotide level, without permanently incorporating foreign genetic material into organism 9 . As a result, organisms modified using these approaches are indistinguishable from those with naturally occurring mutations 10 . NGTs thus combine the advantages of classical mutagenesis, by inducing small genetic changes, with the precision of genetic engineering, enabling the rapid development of improved crop varieties. Given the urgent need to accelerate breeding programs and enhance agricultural productivity, NGTs offer a promising and less controversial alternative to traditional GMOs. Although the technologies described are widely used, they remain controversial in public opinion. Consumers are increasingly interested in learning about food sources and how food production affects the environment and food safety. In addition to regulatory hurdles, consumer acceptance has often been listed as a primary obstacle to the broad adoption of genome editing in plant breeding and agriculture 11 . Due to the public novelty of NGTs, people may lack awareness of those technologies and their potential benefits. Thus, it is important to investigate the demographic and psychological factors associated with attitudes towards new solutions for the food industry, as it may inform the most effective way to introduce them to the food market and consumers. Attitudes are predispositions to respond consistently favourably or unfavourably toward a given object or concept 12 . Attitudes toward food attributes shape consumers’ food choices 13 and are associated with several different factors. Given the relative novelty of this technology, information about attitudes toward NGT foods is limited, as evidenced by a small number of studies below. However, we might be able to apply findings from research on attitudes toward GMOs to predict attitudes toward NGT foods. Understanding consumers’ attitudes is a crucial step in assessing public acceptance of NGT foods, as attitudes are commonly viewed as key predictors of behavioral intentions and decision-making 14 , 15 . Accordingly, the present study is grounded in the tripartite model of attitudes, which conceptualizes attitudes as comprising three interrelated components: cognitive, affective, and behavioral 16 , 17 . According to this model, attitudes toward an object are formed through individuals’ beliefs and evaluations (cognitive component), emotional responses (affective component), and behavioral tendencies or intentions (behavioral component). Moreover, demographic characteristics may also shape attitudes toward foods produced using novel genomic technologies. For example, the case study on acceptance of genome-edited food in Nigeria 18 showed that women declared more hesitation toward consuming NGT foods than men did, and less educated people were less aware of the new technology in agriculture. Furthermore, research also shows that older people tend to be more skeptical about new types of food 19 – 21 . Taken together, these findings suggest that gender, education level, and age may contribute to systematic differences in attitudes towards NGT foods. Beyond demographics, psychological issues play a central role in shaping consumer attitudes. Prior research demonstrates that consumer choices can be influenced by conspiracy beliefs 22 as well as trust in institutions and scientific knowledge 23 . Stronger beliefs in conspiracy theories reduce people’s willingness to consume GMO foods 24 .Conversely, exposure to official and credible information has been shown to decrease conspiracy beliefs and increase willingness to consume GMOs. Importantly, knowledge moderates these relationships – higher levels of objective knowledge weaken the negative association between conspiracy beliefs and attitudes towards GMOs. In contrast, self-assessed (subjective) knowledge can intensify the negative effects of conspiracy beliefs 25 . These findings highlight the relevance of trust, particularly trust in scientific experts and information sources, for understanding public responses to novel food technologies – especially when individuals have limited factual knowledge 26 , 27 . According to previous research, trust in scientific experts is influenced by female gender, white race, high levels of education, and a more liberal political orientation 28 – 35 . Moreover, consumers are more likely to trust and purchase healthy products when trust concerns are addressed, and credibility is built 36 . Another important set of psychological contexts involves food neophobia and food technology neophobia, defined as reluctance to try unfamiliar foods or foods produced using modern technologies 37 , 38 . These tendencies are closely linked to anxiety toward novelty and technological uncertainty 39 . Food neophobia, disgust sensitivity, and anxiety are core psychological drivers of resistance to unfamiliar or technologically novel foods 40 . Anxiety and low trust in technology predict resistance to modern food processes 41 . However, these reactions are modifiable. Consumers’ fear of novel food technologies can be significantly reduced, thereby boosting consumer acceptance and valuation 41 . Education and exposure to novel foods may play an important role 38 . In summary, food neophobia and food technology neophobia are closely linked to emotional responses such as anxiety, disgust, and distrust, which influence consumer resistance to novel foods and modern food technologies. Relatedly, disgust sensitivity represents another affective factor relevant to attitudes toward NGT foods. Disgust serves an evolutionary protective function by motivating the avoidance of potential pathogens and contaminants 42 , 43 . Mechanisms of disgust are linked to the behavioral immune system, which increases the likelihood of avoiding infection and disease by isolating oneself from their sources 44 . Although disgust is primarily triggered by biological threats, similar emotional and behavioral responses can be elicited in moral and technological contexts 45 , 46 . Individuals who oppose GM food tend to exhibit higher disgust sensitivity, and that disgust predicts support for restrictive food policies even after controlling explicit risk-benefit evaluations 47 , 48 . Given that NGT foods may be subjectively perceived as similar to GM food, disgust sensitivity may likewise play a role in shaping public attitudes toward NGT applications. Consumer knowledge further contributes to attitudes toward novel food technologies by influencing levels of food neophobia and technology-related anxiety 37 , 49 . Importantly, it appears that consumer decision-making is guided not only by what the individuals objectively know, but also by what they believe they know – a phenomenon often described as the objective-subjective knowledge gap 50 . Research on GMOs indicates that higher objective knowledge is associated with more positive attitudes, whereas higher subjective knowledge is often linked to more negative attitudes. Individuals with low objective knowledge, but high subjective knowledge exhibited stronger opposition to GMOs 51 , 52 . On the contrary, other studies suggest that providing information alone does not always increase willingness to consume GM or gene-edited foods 53 . This apparent paradox implies that acceptance is shaped by multiple factors, including perceived safety, benefits, labeling practices, and trust in developers, and that communication strategies must address not only information deficits but also overconfidence and misinformation. At present, comparable evidence for NGT foods remains limited. Environmental and ethical considerations also influence public acceptance of genomic technologies. Recent research shows that consumers are more supportive of the applications that enhance animal welfare (e.g., disease resistance), environmental sustainability, and human health, whereas applications aimed solely at increasing productivity are viewed less favorably 54 . Notably, genetic modification tends to elicit more negative reactions than gene editing, even when similar benefits are presented. These findings suggest that perceived purpose and ethical framing are critical determinants of public attitudes. Finally, people’s socioeconomic position and political ideology shape trust in science, openness to biotechnology, and perception of risks versus benefits. Income and political affiliation have been shown to predict GMO attitudes in some contexts 55 . On the other hand, Fernbach et al. stated that political extremity and perceived knowledge, not economic status, strongly predict anti-GMO sentiment 50 . These findings highlight that attitudes toward biotechnology are influenced not only by material conditions but also by deeper cognitive and ideological frameworks. From the policy perspective, understanding these psychosocial factors is essential for developing effective communication strategies and science-based decision-making models that encourage acceptance of beneficial agricultural innovations 56 , 57 . Current study Based on the tripartite model of attitudes, the present study examines the cognitive, affective, and behavioral components of attitudes towards NGT foods. In the context of novel food technologies, attitudes are shaped by a combination of knowledge-related and belief-based evaluations, emotional reactions to novelty and perceived uncertainty, and intentions to engage with or avoid NGT foods. The cognitive component in the present study includes attitudes toward science, conspiracy beliefs, consumer awareness, opinions about NGT foods, and perceived consequences of NGT applications in food production. These variables reflect how individuals interpret, evaluate, and make sense of scientific information related to NGT foods. The affective component is represented by emotional responses that are particularly salient in food-related decision-making, namely disgust sensitivity and anxiety toward new foods and new food technologies. These emotional reactions capture intuitive, affect-laden responses to NGT foods that may operate independently of, or precede, deliberate cognitive evaluations. Finally, the behavioral component of attitudes is operationalized through willingness to try NGT foods, reflecting individuals’ readiness to engage with products derived from novel genomic technologies. Consistent with the tripartite model, this behavioral intention is expected to be shaped by the interplay between cognitive evaluations and affective responses. Building on prior research on GMOs and novel foods 24 , attitudes toward science are treated as an indicator of generalized trust in scientific authority, whereas food and technology neophobia reflect affective resistance to change. Conspiracy beliefs may undermine the credibility of scientific information and reduce acceptance of NGT foods. Perceived consumer awareness reflects an individual’s subjective sense of control and competence. Additionally, disgust sensitivity is included as an additional emotional driver influencing food-related attitudes and behavioral intentions. The purpose of our study was to examine attitudes toward NGT foods based on demographic and psychological factors, identify the psychosocial correlates of attitudes toward NGT products, and define the most relevant psychological variables shaping attitudes towards NGT foods. Based on this theoretical framework and results of the studies conducted so far, we propose the following hypotheses: H1: Women will show more favorable expectations than men, whereas older participants will show lower willingness to try NGT foods compared to younger participants. H2: More positive attitudes toward science will predict more favorable attitudes toward NGT foods and greater willingness to try NGT products. H3: Higher conspiracy beliefs will predict less favorable attitudes toward NGT foods and lower willingness to try them. H4: Higher food neophobia and food-technology neophobia will negatively predict attitudes and willingness to try NGT products. H5: Higher objective and subjective consumer awareness will positively predict favorable attitudes toward NGT foods and willingness to try them. Materials and methods Participants & procedure We collected data via the survey platform “Ariadna” ( https://panelariadna.com/ ), which is the biggest independent nationwide research panel in Poland and enables online CAWI research on anonymous samples of Polish Internet users. For their participation, “Ariadna” respondents receive points that could be exchanged for prizes. We planned to research a quota sample of Poles [50% men and 50% women evenly distributed in the groups of young adults (aged 18–34), middle adults (aged 35–54), and late adults (aged 55 and more)]. Nine hundred and fifteen people agreed to participate in our study. However, some of them completed the survey unreliably (e.g., in a time shorter than 5 min or by selecting the same answer in all responses). Ultimately, we analyzed data collected in a sample of 850 Polish participants (402 men and 448 women) aged from 18 to 88 ( M = 48.86, SD = 16.23). Twenty-six of the respondents had primary education, 434 had secondary education, and 390 had higher education. Men and women did not differ in age [ t (848) = 0.46, p =.65, Cohen’s d = 0.03] and education [χ 2 (2) = 5.45, p =.07, Cramer’s V = 0.08]. For further analyses, we divided participants into three groups: young adults (aged 18–34, n = 194), middle adults (aged 35–54, n = 309), and late adults (aged 55 and older, n = 347). Distinguished groups were homogenous in terms of gender [χ 2 (2) = 2.87, p =.24, V = 0.06] and education [χ 2 (2) = 6.02, p =.20, V = 0.06]. Of the participants, 731 (86.0%) reported no allergies, 778 (91.5%) reported no diagnosed eating disorders, 749 (88.1%) reported including meat in their daily diet, and 808 (95.1%) reported including animal-derived products in their diet. Only 80 (9.4%) participants reported having heard of New Genomic Techniques before. The participants were informed of the nature of the study. Informed consent was obtained from all participants. Participants then provided information about their demographic characteristics and read a short, neutrally worded piece of information describing new genomic technologies and NGT foods (see Supplementary data 1). Then, participants provided information about their expectations for NGT foods compared to currently available non-NGT foods, their opinions on the changes that the introduction of NGT foods would bring, their willingness to try different NGT foods, and their opinions on the effectiveness of encouraging the consumption of NGT products. Subsequently, participants provided information about their conspiracy beliefs, attitudes towards science, food neophobia, food technology neophobia, disgust, subjective consumer awareness, objective consumer awareness, and political beliefs. The study was approved by the Ethics Committee of the University [hidden for peer review]. Measures Participants completed a demographic questionnaire including items on age, gender, level of education, place of residence (categorized by size), and sociodemographic status. They also provided additional background information relevant to the study. This included declarations of political orientation [7-point scale ranging from “definitely left-wing” to “definitely right-wing”. We asked about economic beliefs and social beliefs; however, these beliefs were strongly correlated ( r =.81, p <.01); therefore, we averaged their scores], presence of food allergies (yes/no), and history of eating disorders (no diagnosis; past diagnosis, currently recovered; current diagnosis). Dietary habits were measured through yes/no questions regarding the consumption of meat and animal-derived products (e.g., dairy, eggs, and honey). Finally, prior awareness of NGTs was measured with a binary item (yes/no). To measure conspiracy beliefs, we used Generic Conspiracist Beliefs Scale (GCBS 58 ; the Polish version 59 :). The GCBS has 15 items (e.g., “The government is involved in the murder of innocent citizens and/or well-known public figures and keeps this a secret”) and participants respond on a scale from 1 ( Disagree ) to 5 ( Agree ). We averaged the responses to get an overall score (McDonald’s ω = 0.95). The descriptive statistics of all the measures used are provided in Table 1 . Table 1. Descriptive statistics of variables measured in the current study. Variable Mean (SD) Overall Men Women Young adults Middle adults Late adults General attitudes towards NGT food 3.97 (0.70) 3.94 (0.73) 4.00 (0.67) 3.98 (0.62) 3.99 (0.70) 3.94 (0.74) Perceived consequences of NGT 4.38 (1.26) 4.38 (1.32) 4.37 (1.21) 4.39 (1.29) 4.34 (1.29) 4.40 (1.35) Willingness to try NGT food 4.16 (1.55) 4.18 (1.55) 4.14 (1.54) 4.41 (1.31) 4.28 (1.52) 3.91 (1.65) Opinions about the effectiveness of sources of encouragement GovC 4.02 (1.69) 4.04 (1.74) 4.01 (1.64) 4.03 (1.57) 4.10 (1.63) 3.94 (1.79) EUC 4.08 (1.69) 4.10 (1.75) 4.07 (1.64) 4.19 (1.55) 4.06 (1.70) 4.05 (1.76) Pol 3.02 (1.67) 3.09 (1.73) 2.96 (1.61) 3.23 (1.73) 3.08 (1.70) 2.85 (1.63) Sci 4.58 (1.66) 4.48 (1.72) 4.67 (1.60) 4.70 (1.47) 4.59 (1.65) 4.51 (1.77) Fam 3.69 (1.68) 3.71 (1.71) 3.68 (1.66) 3.87 (1.55) 3.77 (1.63) 3.52 (1.79) Rel 4.60 (1.62) 4.51 (1.68) 4.68 (1.56) 4.85 (1.40) 4.59 (1.56) 4.46 (1.77) AttPri 4.72 (1.70) 4.74 (1.71) 4.70 (1.69) 4.96 (1.57) 4.73 (1.61) 4.59 (1.83) GAv 4.60 (1.62) 4.57 (1.66) 4.55 (1.58) 4.84 (1.47) 4.54 (1.54) 4.42 (1.74) Com 3.73 (1.68) 3.65 (1.68) 3.79 (1.67) 3.95 (1.62) 3.80 (1.65) 3.53 (1.72) WKBr 4.34 (1.66) 4.30 (1.68) 4.37 (1.65) 4.51 (1.58) 4.41 (1.56) 4.18 (1.78) Psychological and lifestyle variables PolOr 3.93 (1.22) 4.04 (1.29) 3.83 (1.14) 4.02 (1.23) 4.02 (1.01) 3.81 (1.30) SubCA 4.86 (1.19) 4.82 (1.25) 4.90 (1.12) 4.78 (1.17) 4.93 (1.15) 4.85 (1.22) ObjCA 6.69 (2.34) 6.27 (2.24) 7.08 (2.36) 6.70 (2.47) 6.62 (2.30) 6.61 (2.30) ConBe 3.03 (0.84) 3.02 (0.87) 3.03 (0.81) 3.10 (0.74) 3.10 (0.86) 2.92 (0.87) FNApp 4.78 (1.31) 4.73 (1.31) 4.82 (1.32) 4.91 (1.22) 4.88 (1.30) 4.62 (1.36) FNAvo 3.81 (1.48) 3.80 (1.30) 3.83 (1.39) 3.83 (1.33) 3.64 (1.28) 3.96 (1.34) FTechN 4.57 (1.08) 4.50 (1.08) 4.64 (1.08) 4.39 (0.91) 4.54 (1.07) 4.71 (1.17) AttTSc 3.23 (0.73) 3.29 (0.77) 3.18 (0.70) 3.14 (0.61) 3.20 (0.75) 3.32 (0.77) DisMor 5.46 (1.07) 5.40 (1.09) 5.51 (1.04) 4.95 (0.95) 5.39 (1.05) 5.81 (1.01) DisSex 4.17 (1.45) 3.74 (1.40) 4.56 (1.37) 3.91 (1.27) 4.05 (1.49) 4.42 (1.46) DisPath 4.67 (1.12) 4.60 (1.12) 4.60 (1.12) 4.61 (1.05) 4.63 (1.10) 4.74 (1.16) Open in a new tab Effects of gender and age were partialled out. CovC = Government campaigns, EUC = The European Union Campaigns, Pol = Politicians, Sci = Scientists, Fam = Famous people, Rel = Relatives, AttPri = Attractive prices, Gav = Good availability, Com = Commercials, WNBr = Well-known brands, PolOr = Political orientation, SubCA = Subjective consume awareness, ObjCA = Objective consume awareness, FNApp = Food neophobia – approach, FNAvo = Food neophobia avoidance, FTechN = Food technology neophobia, AttTSC = Attitudes towards science, DisMor = Moral disgust, DisSex = Sexual disgust, DisPath = Pathogen disgust. We measured attitudes towards science using the Views of Science Questionnaire 60 . Participants were asked how much they agreed (1 = strongly disagree ; 5 = strongly agree ) with 16 items corresponding to their attitudes to scientific methods (e.g., “People who doubt in the fundamentals of science are in fact unable to grasp them.”), the role of scientists as experts (e.g., “Scientists’ work is more useful than the work of priests, philosophers, or artists.”), and the functions that science performs in everyday life (e.g., “The discoveries of scientists make us feel less and less anxious about our future.”). We averaged the responses to get an overall score (ω = 0.93). Participants’ disgust was measured using our Polish translation of the Three Domain of Disgust Scale 61 . This tool consists of 21 items and measures three dimensions of disgust: pathogen (e.g., “Stepping on dog poop.”; ω = 0.83), sexual (e.g., “Hearing two strangers having sex.”; ω = 0.88), and moral (e.g., “Shoplifting a candy bar from a convenience store.”; ω = 0.87). Participants respond on a scale from 1 ( Not at all disgusting ) to 7 ( Extremely disgusting ). We averaged the responses to get an overall score for each scale. To measure anxiety towards food, we used an alternative Food Neophobia Scale (FNS-A) 62 . The tool consists of 8 items and measures two factors: Approach (e.g. “New food means new adventure for me”, ω = 0.90) and Avoidance (e.g. “I don’t trust new food”; ω = 0.84). Participants respond on a scale from 1 (strongly disagree) to 7 (strongly agree). We averaged the responses to get an overall score of each scale. Anxiety towards new technology was measured by the 13-item Food Technology Neophobia Scale (FTNS) 36 . All items were rated on a scale from 1 (strongly disagree) to 7 (strongly agree). The higher the score, the higher the anxiety towards new technology. Example items are: “New food technologies are something I am uncertain about” and “New products using new food technologies can help people have a balanced diet”. We averaged the responses to get an overall score (ω = 0.94). Opinions about NGT products were measured with a set of tools created for the current study. To assess participants’ expectations about NGT foods compared to currently available non-NGT foods, a scale was developed consisting of eight items ( General attitudes towards NGT ). Respondents rated their agreement with each statement on a 7-point Likert scale (1 = strongly negative perception; 7 = strongly positive perception). The items referred to perceived nutritional value, taste, health impact, environmental sustainability, price, and availability of NGT-based products, as well as the potential of NGT to improve food qualities and expand cultivation into previously unsuitable regions (e.g., due to salinity, drought, or extreme temperatures). Higher scores reflected more favorable evaluations of NGT-derived food products. Confirmatory factor analysis with diagonally weighted least squares ( DWLS ) estimator revealed that the factor solution was justified (Bartlett’s test of sphericity χ 2 (28) = 3538, p <.01; overall MSA = 0.89) and scale had a good fit: χ 2 / df = 1.52, CFI = 0.996, TLI = 0.994, RMSEA = 0.025 (90% C.I. : 0.000 − 0.042), SRMR = 0.046; all factor loadings p s < 0.01; ω = 0.86. However, item related to prices had negative factor loading ( b = −0.30, SE = 0.04); therefore, we decided to remove it from the scale. The final, 7-item version of the scale had satisfactory reliability (ω = 0.89) and a good fit: χ 2 / df = 1.43, CFI = 0.998, TLI = 0.996, RMSEA = 0.022 (90% C.I. : 0.000 − 0.043), SRMR = 0.042. Moreover, the model fit did not change when we tested multigroup invariance across gender [Δs CFI in consecutive testing configural, metric, and scalar invariance < 0.010] and age group [Δs CFI in consecutive testing configural, metric, and scalar invariance < 0.010]. Factor loadings and descriptive statistics are shown in Table 2 . We averaged the responses to get an overall score. Table 2. Descriptive statistics and factor loadings of items of the scales designed for the current study. Scale Item M (SD) b SE z General attitudes toward NGT food scale Nutrition properties 4.33 (1.29) Taste 4.17 (1.26) 0.95 0.05 18.38* Health 4.19 (1.35) 1.00 0.05 18.32* Environmental sustainability 4.43 (1.44) 1.00 0.06 18.21* Availability 4.44 (1.28) 0.48 0.04 13.66* Cultivation area 5.00 (1.44) 0.85 0.05 17.43* Improvement of food quality 4.49 (1.45) 0.87 0.05 17.30* Perceived consequences of NGT Food problems solving 4.55 (1.52) Food availability for poor people 4.33 (1.53) 0.91 0.04 21.56* Decreasing chemicals 4.45 (1.57) 1.06 0.05 22.37* Fighting with overweight and obesity 4.05 (1.52) 0.91 0.04 21.58* Better life for the allergic 4.60 (1.44) 0.93 0.04 21.74* Lower influence on the environment 4.15 (1.59) 1.01 0.05 22.12* Increasing biodiversity 4.49 (1.49) 0.90 0.04 21.48* Willingness to try NGT food Bakery products 4.32 (1.77) Fresh products 4.42 (1.76) 0.95 0.02 39.45* Sweets 4.16 (1.77) 0.96 0.02 39.88* Beverages 4.32 (1.72) 0.97 0.02 40.11* Alcohol drinks 3.98 (1.83) 0.86 0.02 37.82* Snacks 4.06 (1.79) 0.94 0.02 39.52* Fat products 4.32 (1.73) 0.96 0.02 39.94* Food for children 3.71 (1.76) 0.90 0.02 39.24* Cereal products 4.45 (1.72) 0.96 0.02 39.94* Ready-made meals 4.11 (1.77) 0.97 0.02 40.07* Fast food 3.90 (1.81) 0.91 0.02 39.15* Objective consumer awareness Item 1: Which digits do product barcodes start with to indicate that they were produced in Poland? (correct answer: 590) 64.1% Item 2: What is the reference daily intake value(RDI) for adults? (correct answer: 2000 kcal) 53.4% 0.87 0.20 4.49* Item 3: Which of the following grains does NOT contain gluten? (correct answer: corn) 67.6% 1.06 0.19 5.55* Item 4: How many letters does the nutritional value scale consist of? (correct answer: 5) 45.9% 0.86 0.19 4.55* Item 5: Which of the following substances is NOT a sweetener? (correct answer: gelatin) 86.1% 1.29 0.23 5.54* Item 6: Which number printed on eggs indicates they come from barn (litter) farming? (correct answer: 2) 32.6% 1.20 0.22 5.44* Item 7: What is the substance found in milk known as lactose? (correct answer: sugar) 37.6% 1.14 0.22 5.12* Item 8: A product labeled “Best before: 11.2025”: (correct answer: should be consumed by the end of November, but later consumption is acceptable) 32.6% 0.69 0.18 3.91* Item 9: Consumption of which of the following substances is recommended for health reasons? (correct answer: fiber) 80.9% 0.54 0.19 2.78* Item 10: Organic products are: (correct answer: organic farm products or their processed forms produced using natural methods) 40.1% 1.20 0.23 5.12* Item 11: The BIO label on food products means: (correct answer: food produced organically, using only natural methods) 34.7% 1.13 0.22 5.16* Item 12: Food labeled “sugar-free” is food that: (correct answer: has no added sugar but may contain sweeteners) 47.2% 0.59 0.17 3.43* Item 13: “Light” food products are: (correct answer: products with reduced calories or reduced fat or reduced sugar) 46.5% 1.00 0.20 4.94* Open in a new tab Note. * p <.01. Numbers in the M ( SD ) column for Objective consumer awareness show the percentage proportion of correct answers among participants. To examine participants’ perceptions of the societal and environmental benefits of introducing NGT food products, a 7-item scale (Perceived consequences of NGT) was constructed. Respondents evaluated each statement on a 7-point Likert scale (1 = strongly disagree; 7 = strongly agree). The items covered perceived advantages of NGT-based food, such as addressing global hunger, improving food access for low-income populations, reducing the use of agricultural chemicals, supporting dietary needs (e.g., for individuals with allergies), mitigating obesity, minimizing environmental impact, and promoting biodiversity. Higher scores indicated a stronger belief in the positive consequences of NGT-based food production. Confirmatory factor analysis with DWLS estimator revealed that the factor solution was justified (Bartlett’s test of sphericity χ 2 (21) = 4051, p <.01; overall MSA = 0.91) and scale had a good fit [χ 2 / df = 1.20, CFI = 0.999, TLI = 0.999, RMSEA = 0.015 (90% C.I. : 0.000 − 0.038), SRMR = 0.032; all factor loadings p s < 0.01] and reliability (ω = 0.92). Moreover, the model fit did not change when we tested multigroup invariance across gender (Δs CFI in consecutive testing configural, metric, and scalar invariance < 0.010) and age group (Δs CFI in consecutive testing configural, metric, and scalar invariance < 0.010). Factor loadings and descriptive statistics are shown in Table 2 . We averaged the responses to get an overall score. Intentions to consume NGT food products were assessed via 11-items scale ( Willingness to try NGT foods ). Participants rated their willingness to try eleven categories of food products (e.g., bakery products, fresh products, sweets, beverages, alcohol drinks, snacks, fat products, food for children, cereal products, ready-made meals, and fast food) if these products contained NGT-derived ingredients. In the second part, participants rated their willingness to serve such products to others in their household. Each item was rated on a 7-point Likert scale (1 = definitely would not try; 7 = definitely would try). Higher scores indicated stronger behavioral intentions to consume NGT-based products across various food categories. Confirmatory factor analysis with DWLS estimator revealed that the factor solution was justified (Bartlett’s test of sphericity χ 2 (55) = 10916, p <.01; overall MSA = 0.96) and scale had a good fit [χ 2 / df = 1.17, CFI = 1.000, TLI = 0.999, RMSEA = 0.014 (90% C.I. : 0.000 − 0.028), SRMR = 0.036; all factor loadings p s < 0.01] and reliability (ω = 0.97). Moreover, the model fit did not change when we tested multigroup invariance across gender (Δs CFI in consecutive testing configural, metric, and scalar invariance < 0.010) and age group (Δs CFI in consecutive testing configural, metric, and scalar invariance < 0.010). Factor loadings and descriptive statistics are shown in Table 2 . We averaged the responses to get an overall score. To measure the perceived influence of external factors on the willingness of similar others to consume NGT-based food products, we presented the participants ten items describing different factors, collected in the Approaches to NGT introduction inventory. Participants indicated the extent to which each factor - such as social campaigns, opinions of scientists or celebrities, product availability, price, or brand recognition - could, in their opinion, motivate people like themselves to consume NGT-based food products. Responses were given on a 7-point Likert scale (1 = definitely would not encourage; 7 = definitely would encourage). Higher scores reflected greater perceived persuasive potential of external factors in shaping dietary choices related to NGT products. Consumer awareness regarding food products was assessed using two complementary tools: one subjective and one objective. Subjective Consumer Awareness was measured with a single-item self-assessment. Participants rated their own level of consumer knowledge regarding food and nutrition on a 7-point Likert scale (1 = very low consumer awareness; 7 = very high consumer awareness). This item captured the respondent’s self-perceived ability to make informed food choices. On the other hand, Objective Consumer Awareness was assessed using a 14-item multiple-choice quiz designed to evaluate factual knowledge about food labeling, nutrition, and food categories. Each item required respondents to select one correct answer from four options. Sample questions were: “Which of the following cereals is gluten-free?” (Correct answer: corn)”, “Which number printed on eggs indicates barn farming?” (Correct answer: 2), “Which substance is not a sweetener?” (Correct answer: gelatine), and “What is the recommended daily caloric intake (RDI) for an average adult?” (Correct answer: 2000 kcal). Correct answers were scored 1 and incorrect answers were scored 0. Confirmatory factor analysis with weighted least squares mean and variance adjusted ( WLSMV ) estimator revealed that the factor solution was justified (Bartlett’s test of sphericity χ 2 (91) = 1.31, p <.01; overall MSA = 0.61) but the scale had a relatively poor fit: χ 2 / df = 2.06, CFI = 0.820, TLI = 0.788, RMSEA = 0.035 (90% C.I. : 0.028 − 0.043), SRMR = 0.068] However, one item [“To classify a product as high-protein based on its composition:” (Correct answer: “At least 20% of the energy value of a food product should come from protein.”)] had a factor loading of p =.70; therefore, we removed it from the scale. The modified scale still had a relatively poor fit: χ 2 / df = 2.40, CFI = 0.803, TLI = 0.764, RMSEA = 0.041 (90% C.I. : 0.033 − 0.049), SRMR = 0.073] and the reliability of the scale was poor (ω = 0.53). On the other hand, all factor loadings’ p s were < 0.01 (see Table 2 ). Therefore, we decided to include the collected scores in our analyses; however, we were aware that the interpretation of collected results should be made with great caution, both due to poor fit and low scale reliability. Data analysis Data were coded and analyzed using JASP software (version 0.95.1.0). We examined participants’ expectations compared to currently available non-NGT foods in two steps. In the first step, we included sociodemographic and lifestyle variables; therefore, we ran a 2 (gender) × 3 (age group) ANCOVA analysis with three covariates (e.g., political orientation and subjective and objective consumer awareness). In the second step, we extended the previous model with eight psychological covariates (e.g., conspiracy beliefs, attitudes towards science, food neophobia dimensions, food technology neophobia, and disgust dimensions). We performed analogous, two-stage analyses for opinions on the changes that the introduction of NGT foods would bring and willingness to try NGT foods. Then, we examined participants’ opinions on the effectiveness of various methods for encouraging the consumption of NGT products. To achieve this goal, we ran a 2 (gender) × 3 (age group) × 10 (method of encouraging) Mixed Model ANOVA. Finally, we examined the correlations between respondents’ opinions on the effectiveness of various methods for encouraging the consumption of NGT products and their political orientation, as well as their subjective and objective consumer awareness, conspiracy beliefs, attitudes towards science, food neophobia, food technology neophobia, and disgust. Results Expectations regarding NGT foods compared to currently available non-NGT foods The ANCOVA analysis including sociodemographic and consumer awareness variables, conducted in the first step, did not reveal effects of gender [ F (1, 841) = 0.33, p =.57], age group [ F (2, 841) = 0.70, p =.50], and their interaction [ F (2, 841) = 0.49, p =.62]. Similarly, we did not find the effect of objective consumer awareness [ F (1, 841) = 0.41, p =.52]. On the other hand, we revealed effects of subjective consumer awareness [ F (1, 841) = 34.22, p <.01, η 2 p = 0.04, β = 0.20] and political orientation [ F (1, 841) = 9.62, p <.01, η 2 p = 0.01, β = −0.11]. In the second step, we ran ANCOVA analysis with psychological covariates added (e.g., conspiracy beliefs, attitudes towards science, two food neophobia dimensions, food technology neophobia, and three disgust dimensions). We did not find effects of gender [ F (1, 833) = 1.64, p =.20], age group [ F (2, 833) = 0.73, p =.48], or their interaction [ F (2, 833) = 0.65, p =.53]. We observed effects of subjective consumer awareness [ F (1, 833) = 28.23, p <.01, η 2 p = 0.03, β = 0.17] and objective consumer awareness [ F (1, 833) = 5.50, p =.02, η 2 p = 0.01, β = 0.07]; however, there was no effect of political orientation [ F (1, 833) = 0.19, p =.66, η 2 p = 0.01]. Among psychological covariates, we revealed effects of approaching new food [ F (1, 833) = 29.29, p <.01, η 2 p = 0.03, β = 0.20], avoiding new food [ F (1, 833) = 11.83, p <.01, η 2 p = 0.01, β = 0.13], food technology neophobia[ F (1, 833) = 53.87, p <.01, η 2 p = 0.06, β = −0.26], and attitudes towards science [ F (1, 833) = 86.13, p <.01, η 2 p = 0.09, β = 0.30]; however, we did not find effects of conspiracy beliefs [ F (1, 833) = 1.76, p =.19] or any type of disgust [ F s(1, 833) ≤ 1.00, p s ≥ 0.31]. Opinions on the changes that the introduction of NGT foods would bring The ANCOVA analysis including sociodemographic and consumer awareness variables revealed effects of political orientation [ F (1, 841) = 14.92, p <.01, η 2 p = 0.02, β = −0.13], subjective consumer awareness [ F (1, 841) = 16.66, p <.01, η 2 p = 0.02, β = 0.14], and objective consumer awareness [ F (1, 841) = 4.18, p <.04, η 2 p = 0.01, β = −0.07]. On the other hand, we did not find effects of gender [ F (1, 841) = 0.11, p =.74], age group [ F (2, 841) = 0.30, p =.74], or their interaction [ F (2, 841) = 0.76, p =.47]. In the second step, we run ANCOVA analysis with psychological covariates added. We revealed effects of subjective consumer awareness [ F (1, 833) = 12.40, p <.01, η 2 p = 0.02, β = 0.10], approaching new food [ F (1, 833) = 32.59, p <.01, η 2 p = 0.04, β = 0.19], avoiding new food [ F (1, 833) = 17.89, p <.01, η 2 p = 0.02, β = 0.15], food technology neophobia [ F (1, 833) = 108.32, p <.01, η 2 p = 0.12, β = −0.35], and attitudes towards science [ F (1, 833) = 172.45, p <.01, η 2 p = 0.17, β = 0.40]. On the other hand, we did not find effects of gender [ F (1, 833) = 0.93, p =.34], age group [ F (2, 833) = 0.13, p =.88], or their interaction [ F (2, 833) = 0.75, p =.47]; neither did we find effects of objective consumer awareness [ F (1, 833) = 0.02, p =.88], conspiracy beliefs [ F (1, 833) = 0.88, p =. 35] or any type of disgust [ F s(1, 833) ≤ 0.93, p s ≥ 0.34]. Willingness to try NGT foods The ANCOVA analysis including sociodemographic and consumer awareness variables revealed effects of age group [ F (1, 841) = 10.43, p <.01, η 2 p = 0.02], political orientation [ F (1, 841) = 18.16, p <.01, η 2 p = 0.02, β = −0.18], and subjective consumer awareness [ F (1, 841) = 21.76, p <.01, η 2 p = 0.03, β = 0.16]. On the other hand, we did not find effects of gender [ F (1, 841) = 0.62, p =.43], objective consumer awareness [ F (2, 841) = 0.33, p =.57], or an interaction of gender and age [ F (2, 841) = 1.56, p =.21]. A post-hoc analysis with Bonferroni-Holm correction revealed that young adults ( M = 4.45, SE = 0.11) and middle adults ( M = 4.28, SE = 0.09) were more willing to try NGT foods than late adults [ M = 3.88, SE = 0.08, t s(841) ≥ 3.36, p s < 0.01, Cohen’s d s ≥ 0.27]. Subsequently, we run ANCOVA analysis with psychological covariates added. We revealed effects of age group [ F (1, 833) = 8.55, p <.01, η 2 p = 0.02], subjective consumer awareness [ F (1, 833) = 17.62, p <.01, η 2 p = 0.02, β = 0.12], approaching new food [ F (1, 833) = 53.36, p <.01, η 2 p = 0.06, β = 0.25], avoiding new food [ F (1, 833) = 29.29, p <.01, η 2 p = 0.03, β = 0.20], food technology neophobia [ F (1, 833) = 135.72, p <.01, η 2 p = 0.14, β = −0.39], and attitudes towards science [ F (1, 833) = 103,51, p <.01, η 2 p = 0.11, β = 0.31]. On the other hand, we did not find effects of gender [ F (1, 833) = 0.31, p =.58], objective consumer awareness [ F (1, 833) = 0.90, p =.34], conspiracy beliefs [ F (1, 833) = 0.83, p =. 35], any type of disgust [ F s(1, 833) ≤ 1.66, p s ≥ 0.20], or an interaction of gender and age group [ F (2, 833) = 1.61, p =.20]. A post-hoc analysis with Bonferroni-Holm correction revealed that young adults ( M = 4.36, SE = 0.09) and middle adults ( M = 4.28, SE = 0.07) were more willing to try NGT foods than late adults [ M = 3.92, SE = 0.07, t s(841) ≥ 3.48, p s < 0.01, d s ≥ 0.28]. Opinions on the effectiveness of sources of encouragement to the consumption of NGT products We aimed to compare respondents’ opinions on individual sources of encouragement to consume NGT foods, in the context of gender and age groups (step 1), and to investigate the lifestyle and psychological correlates of these opinions (step 2). Therefore, in the first step, we conducted 2 (gender) × 3 (age group) × 9 (source of encouragement) mixed model ANOVA. Since the sphericity was violated [Mauchly’s W = 0.16, approximated χ 2 (44) = 1.55, p <.01], we applied Greenhouse-Geisser correction. We revealed main effect of age [ F (2, 844) = 3.32, p =.04, η 2 p = 0.01] and main effect of source of encouragement [ F (5.53, 4667.41) = 244.47, p <.01, η 2 p = 0.23]; however, we did not find the main effect of gender [ F (1, 844) = 0.29, p =.59]. A post-hoc analysis with Bonferroni-Holm correction revealed that young adults ( M = 4.31, SE = 0.10) rated sources of encouragement to the consumption of NGT products higher than late adults [ t (844) = 2.52, p =.04, d = 0.19]. Attractive prices were rated higher than other sources [ t s(844) ≥ 3.29, p s < 0.01, d s ≥ 0.08]; relatives, good availability, and scientists were rated higher than other sources except prices [| t s(844)| ≥ 5.30, p s < 0.01, | d s| ≥ 0.14], well-known brands were rated higher than remaining sources [| t s(844)| ≥ 6.25, p s < 0.01, | d s| ≥ 0.16], EU campaigns and government campaigns were rated higher than commercials [ t (844) = 6.08, p <.01, d = 0.16], famous people [ t (844) = 6.74, p <.01, d = 0.19], and politicians [ t (844) = 18.36, p <.01, d = 0.59]. Rates of commercials and famous people were higher than rates of politicians [| t s(844) ≥ 14.51|, p s < 0.01, | d s| ≥ 0.40]. Moreover, we revealed interaction of gender and source of encouragement [ F (5.53, 4667.41) = 2.25, p =.04, η 2 p < 0.01]; however, a post-hoc analysis with Bonferroni-Holm correction did not reveal any gender differences in rates of sources of encouragement [| t s(844)| ≤ 1.75|, p s = 1.00] and differences in rates among men and women reflected those observed in main effect of sources of encouragement. We did not find interactions of age and source of encouragement [ F (5.53, 4667.41) = 1.53, p =.12], gender and age [ F (2, 844) = 0.68, p =.51], or gender and age, and source of encouragement [ F (11.06, 4667.41) = 1.79, p =.05]. In the second step, we correlated opinions about the effectiveness of sources of encouragement with lifestyle and psychological variables (see Table 3 ). Step 1 analyses revealed effects of gender and age; therefore, in correlation analyses, we partialled out their effects. Attitudes towards science and approach to new food correlated positively with opinions about the effectiveness of all sources of encouragement; moreover, correlations between attitudes towards science and opinions about the effectiveness of sources of encouragement were the highest among all observed. These opinions also correlated positively with subjective consumer awareness, except opinions about the effectiveness of politicians. Moreover, we observed positive correlations of opinions about the effectiveness of politicians with new food avoidance and sexual disgust. Additionally, people with higher moral disgust had more positive opinions about the effectiveness of scientists, relatives, attractive prices, and good availability, while people with higher pathogen disgust had more positive opinions about the effectiveness of famous people. Regarding negative links, food technology neophobia correlated negatively with all sources of encouragement, and more conservative political orientation correlated negatively with opinions about almost all sources of encouragement except politicians. Objective consumer awareness correlated negatively with opinions about the effectiveness of government campaigns, the EU campaigns, politicians, famous people, and commercials (however, the tool for measuring objective consumer awareness had low reliability and poor fit indicators, so the collected results should be treated with caution); conspiracy beliefs correlated negatively with opinions about effectiveness of government campaigns, the EU campaigns, scientists, relatives, attractive prices, good availability, and well-known brands. Finally, new food avoidance correlated negatively with opinions about effectiveness of good availability, and attractive prices, and sexual disgust and sexual disgust correlated negatively with opinions about effectiveness of scientists, good availability, and well-known brands. Table 3. Correlations of opinions about the effectiveness of sources of encouragement with lifestyle and psychological variables. GovC EUC Pol Sci Fam Rel AttPri GAv Com WKBr PolOr − 0.16** − 0.19** − 0.05 − 0.22** − 0.12** − 0.12** − 0.16** − 0.15** − 0.10** − 0.14** SubCA 0.14** 0.13** 0.04 0.17** 0.09** 0.18** 0.16** 0.20** 0.14** 0.16** ObjCA − 0.08* − 0.08* − 0.21** 0.04 − 0.12** 0.01 0.02 0.02 − 0.12** 0.00 ConBe − 0.09* − 0.14** 0.01 − 0.17** 0.00 − 0.10** − 0.12** − 0.14** 0.00 − 0.10** FNApp 0.23** 0.24** 0.10** 0.27** 0.19** 0.28** 0.25** 0.24** 0.20** 0.24** FNAvo − 0.02 − 0.02 0.13** − 0.06 0.07 − 0.06 − 0.09* − 0.09* 0.04 − 0.03 FTechN − 0.31** − 0.33** − 0.21** − 0.35** − 0.27** − 0.31** − 0.31** − 0.35** − 0.27** − 0.33** AttTSc 0.40** 0.41** 0.34** 0.42** 0.37** 0.34** 0.36** 0.37** 0.33** 0.37** DisMor 0.04 0.02 − 0.02 0.09** 0.01 0.13** 0.10** 0.13** 0.02 0.09** DisSex − 0.04 − 0.06 0.13** − 0.09** 0.05 − 0.04 − 0.10** − 0.07* 0.02 − 0.08* DisPath − 0.01 − 0.04 0.04 0.01 0.08.* 0.02 0.00 0.02 0.05 0.02 Open in a new tab Note. * p <.05, ** p <.01. Effects of gender and age were partialled out. CovC = Government campaigns, EUC = The European Union Campaigns, Pol = Politicians, Sci = Scientists, Fam = Famous people, Rel = Relatives, AttPri = Attractive prices, Gav = Good availability, Com = Commercials, WNBr = Well-known brands, PolOr = Political orientation, SubCA = Subjective consume awareness, ObjCA = Objective consume awareness, FNApp = Food neophobia – approach, FNAvo = Food neophobia avoidance, FTechN = Food technology neophobia, AttTSC = Attitudes towards science, DisMor = Moral disgust, DisSex = Sexual disgust, DisPath = Pathogen disgust. Discussion The primary goal of the study was to examine attitudes towards NGT foods based on demographic and psychological factors and to identify the most relevant variables shaping attitudes toward NGT foods. Our results indicate that while demographic factors like age play a role, the most potent predictors are psychological: specifically, trust in science, technology-specific neophobia, and subjective consumer awareness. With respect to demographic variables, H1 was partially supported. We did not find the effects of gender on expectations and opinions of NGT products or the willingness to try them. However, we did confirm the effects of age on the willingness to try NGT foods, such that young and middle-aged adults reported greater willingness to try NGT products than older adults. Guided by the tripartite model of attitudes 16 , 17 , our hypotheses regarding the psychological predictors were partially supported. Positive attitudes toward science emerged as the strongest predictor across all three attitudinal components (H2): positive expectations (cognitive), favourable opinions (affective–evaluative), and willingness to try NGT foods (behavioral intention). However, contrary to our hypotheses, conspiracy beliefs did not emerge as a predictor of expectations regarding NGT foods, opinions about these foods, and the willingness to try NGT products (H3). It is possible that general distrust framed through conspiracy thinking may be less relevant than more specific trust in science and scientific institutions when evaluating NGTs. Additionally, the generic nature of the conspiracy belief measure used in this study did not fully capture technology-specific distrust or skepticism directly related to NGT applications. Affective components were reflected primarily in food neophobia and food technology neophobia. Consistent with H4, a lower anxiety toward new technology (technology neophobia) was associated with more positive NGT attitudes. However, a counterintuitive finding emerged regarding food neophobia: both the tendency to approach new foods and the tendency to avoid them were significant positive predictors of NGT attitudes. This counterintuitive finding suggests that NGTs may not be categorized by Polish consumers as traditional “novel foods,” which are typically evaluated based on sensory properties or natural origins. Instead, individuals with high avoidance tendencies (neophobia) might perceive NGTs as “scientifically controlled” interventions. In this view, the technological nature of the food might actually mitigate the perceived risks usually associated with unknown, “natural” novel foods, as the scientific framework provides a sense of predictability and safety. Furthermore, in the Polish socioeconomic context, the perceived utility of NGTs - such as their potential for sustainability or enhanced food quality - may outweigh the innate neophobic response. Rather than reflecting a simple contradiction, this co-occurrence suggests that NGT acceptance is filtered through a unique lens where technological legitimacy overrides traditional food-related anxieties. The behavioral component of attitudes - operationalized as willingness to try NGT foods - was more predicted by subjective consumer awareness, rather than objective consumer awareness. This supports H5 and indicates that behavioral intentions may depend more on a consumer’s confidence in their understanding than on the information alone. This is consistent with previous research suggesting that simply providing technical information does not necessarily increase acceptance of GM or gene-edited foods 52 . Thus, strengthening the subjective sense of consumer awareness may be more vital for translating evaluations into behavior than factual education alone On the other hand, the objective consumer awareness tool had low reliability and poor fit indices, so conclusions regarding objective consumer awareness should be treated with caution until more reliable data is collected. The most relevant predictors of attitudes towards NGTs were attitudes toward science, the tendency to approach new types of food, and subjective consumer awareness; on the other hand, food technology neophobia was a strong negative predictor of these attitudes. Since trust in science emerged as an important predictor of more favourable attitudes toward NGTs while conspiracy beliefs did not, there is a potential to build credibility around NGTs by addressing trust concerns. Therefore, the potential engagement of scientific knowledge in the public discussion about NGTs might impact the latter’s acceptance 35 . In this way, the public perception of NGT foods may be similar to that previously reported for COVID-19 vaccines 62 , 63 , where also scientific discoveries aimed at improving the health of the global population were met with both favorable and skeptical reception. Past research on both, food and food technology neophobia, has highlighted the importance of consumers’ perceptions of food in choices that they make around novel foodstuff 64 , which has also been shown in our study. Paradoxically, our results indicated that both the tendency to approach new foods and the tendency to avoid new foods were significant predictors of NGT attitudes. This result is in contrast to many past studies showing that the anxiety of novelty is a barrier to introducing controversial food categories 38 , 65 , 66 . However, it may be a promising findingResearch on attitudes toward nanotechnology in food production shows that public evaluations of emerging food technologies are often ambivalent, reflecting the coexistence of perceived benefits and concerns, and that both attitudes can change in response to information and contextual cues 67 – 76 . Importantly, ambivalence does not simply precede acceptance or rejection but represents a stable response to complex and unfamiliar technologies. This pattern closely parallels attitudes toward NGT foods, which similarly evoke competing approach- and avoidance-oriented motivations related to sustainability, innovation, safety, and ethics. Evidence from the nanotechnology literature suggests that increasing acceptance of NGT products may require not only strengthening positive attitudes but also explicitly addressing and managing both approaches by acknowledging mixed evaluations and supporting trust-based public engagement 77 . Consumer awareness was positively associated with positive expectations and opinions about NGT foods. Interestingly, researchers have found that consumers’ willingness to consume GM and gene-edited foods was not affected by providing information on the technology and its health and environmental benefits 53 . Therefore, it may be more important to strengthen consumers’ confidence in their food awareness, along with providing objective information about NGTs (However, please note that the objective consumer awareness data in the current study were collected using a tool with low reliability and poor fit.). Overall, these results are in line with various previous studies 35 , 37 , 78 and highlight the interplay of certain cognitive and affective components in behavioral aspects of attitudes toward NGTs. Contrary to our hypothesis, we did not observe more favorable expectations of NGT foods among women compared to men; in fact, we found no gender differences in attitudes toward NGT products in our sample. The lack of gender differences is somewhat contrary to past literature, as a gender gap was observed in the study of GM food, where women consumers had a more negative attitude toward GM foods than male consumers when considering whether GM foods are healthy or not 63 . Studies have also demonstrated that women were generally less likely to buy GM food 64 and had a less positive attitude towards gene technology 65 . Similarly, the case study of NGT foods acceptance in Nigeria 18 showed that women were less likely to buy and eat genome-edited food, even though it was not GMOs. Such differences in our results might be associated with changing gender roles in Poland. Female and male food-related habits can be conceptualized as socially constructed 79 – 81 and reflected in food choices, practices, and knowledge. However, it is possible that the role of affective and cognitive factors is much more pronounced than the socially constructed gender expectations. Public trust and food-related discourse in Poland appear to be influenced by media narratives and European Union (EU) messaging. Following Poland’s accession to the EU in 2004, significant modernization in both food production and societal structures, including the empowerment of women, can be observed. Educated women may exhibit greater trust in institutions and a higher openness to scientifically grounded innovations, thus eliminating gender differences seen in some other studies. Age appears to be an important demographic factor influencing food preferences and behaviors. In our research, older adults were less likely than younger or middle-aged adults to try NGT foods in such products as sweets, soft drinks, snacks, fast food, and prepared meals. Moreover, they had less favorable views than other age groups about encouragement from politicians, celebrities, relatives, advertisements, famous brands, and even the level of accessibility. This may be partly explained by the generational differences in exposure to and familiarity with modern technologies among Polish adults – while younger and middle-aged adults may be more immersed in the modern technological world older adults might be less familiar with novel food products and contemporary food production processes 21 , 77 . It should be underlined that most of the discussed research concentrated on GM rather than NGT, which limits the conclusions. Overall, the results highlight the dynamic interplay between cognitive (trust in science, awareness), affective (neophobia, anxiety), and behavioral (willingness to try) components of attitudes toward NGT foods. Rather than reflecting simple acceptance or rejection, attitudes toward NGT products appear to be structured by ambivalence, suggesting that public engagement strategies should focus not only on improving knowledge but also on acknowledging mixed feelings and supporting trust-based, reflective decision-making processes. Conclusions This study represents the first known attempt to explore the psychosocial components of attitudes toward NGT foods in Poland, offering insights into the role of affective and cognitive factors in the choices that people might make about NGTs. These findings suggest that it may be particularly important to address the trust in science, anxiety around new foods and technologies, and the subjective consumer awareness in tailoring public communication - both through mass media and government channels – around NGTs in Poland. This aligns with the findings of Adeboye et al. 18 , who demonstrated that genetic educational initiatives are largely ineffective without targeted approaches, and emphasized the need for increased public dialogue, transparent labeling, and trust-building efforts involving health professionals. Similarly, Firoozzare et al. 35 concluded that consumer trust and willingness to purchase health-related food products significantly increase when credibility concerns are addressed. Taken together, these results underscore the potential of well-designed, evidence-based informational campaigns to enhance public acceptance of novel food technologies. Limitations It is important to acknowledge key limitations of this study, which warrant caution when generalizing its findings. First, the survey was administered online, thereby restricting the sample primarily to well-educated, internet-savvy adults. This sampling bias may limit the representativeness of the results. Moreover, collecting data using online survey platforms carries the risk of collecting responses that do not reflect the actual characteristics of the individuals being surveyed. On the other hand, we screened our dataset and we removed from the analyses data that appeared to be provided in an unreliable manner (e.g., surveys completed too quickly or containing long strings of identical responses). Second, the use of cross-sectional data constrains the ability to draw causal inferences between the independent and dependent variables identified in the regression analysis. A longitudinal design would be more appropriate for establishing causal relationships. On the other hand, our study concerned issues that have not been explored so far, especially in the Polish sample; therefore, the information we collected can be treated as a guide for further investigations focused on more specific issues. Third, this study did not examine trust in scientists in the context of general interpersonal trust - that is, trust in other people within society. Such a comparison could have provided a more contextualized understanding of the specificity of trust in scientists, allowing us to determine whether relatively low or high trust in scientists stems from the general level of social capital or from more specific attitudes toward expert knowledge and scientific institutions. The absence of this comparison limits the interpretation of the findings and makes it more difficult to assess whether trust in scientists is an autonomous category or one embedded within a broader social climate (e.g., trust in public institutions or other professional groups). Therefore, future research should consider trust in scientists both at a general level and in the specific area of food 82 . Fourth, most study participants had not previously heard of NGT foods, so their attitudes toward this technology were shaped primarily by the limited information we provided (see Supplementary Material 1). Therefore, there was a risk that their positive or negative attitudes toward NGT foods and the underlying NGT technology were influenced by the way we described NGT in the information we provided. However, we attempted to present NGT technology and NGT foods in a neutral manner, referring exclusively to evidence-based data on these topics. The responses collected from participants do not indicate any overt bias, suggesting that we prepared the introductory material neutrally. This is evidenced by the descriptive statistics presented in Table 1 , where all means for general attitudes toward NGT foods, perceived consequences of NGT, and willingness to try NGT foods (from 3.91 to 4.41) are close to the midpoint of the scale (4.00), and the highest standard deviation is 1.65. Fifth, our measures of subjective and objective consumer awareness may raise concerns. Subjective consumer knowledge was measured using a single-item scale with uncertain reliability. However, other studies show that single-item scales are valid and allow data collection from participants with little effort 83 – 85 . On the other hand, our objective consumer awareness measure (a quiz with one correct and four incorrect answers) was characterized by poor reliability and poor model fit; therefore, the results collected using it and their interpretation should be taken with great caution. Finally, participants’ knowledge of NGTs was measured using custom-designed items, which, although tailored to the specific focus of the study, limits the ability to make cross-cultural or cross-study comparisons. In future research, it would be advisable to use standardized measurement tools, such as the question sets employed by Eurobarometer 2025 86 . It may allow for international comparability and enhance the validity and reliability of scientific knowledge assessments. The use of such standardized instruments could also reduce the risk of measurement bias and increase the methodological transparency of the study. Finally, we used ANCOVA to analyse the relationships between the dependent variables and the continuous and categorical independent variables. Although this approach allowed us to discover numerous significant effects, ANCOVAs with continuous covariates can obscure the relative importance of the predictors, especially when they are correlated, and some may argue that regression analysis would be more appropriate in this case. Furthermore, our data are available in an open repository; therefore, they can be reanalysed to focus on any relationships between the variables we examined. Future studies Future studies should focus on identifying effective strategies to improve expectations and attitudes toward NGTs, particularly among more sceptical groups such as older adults. Experimental research could test tailored messages designed to align with the values, concerns, and motivations of these populations. As Bearth et al. 87 suggest, consumer acceptance of NGTs is not solely driven by factual knowledge but is also shaped by affective responses, personal values, and the broader regulatory and societal context. Therefore, future interventions should take these psychological and contextual factors into account, aiming to foster acceptance through more personalized and value-sensitive communication approaches. Supplementary Information Below is the link to the electronic supplementary material. Supplementary Material 1 (49.3KB, docx) Author contributions Conceptualization: ŁU, JR, MS, MM; Investigation: ŁU, JR, MS; Writing – original draft: ŁU, JR, MS, MM; Writing – review & editing: ŁU, JR, MS, MM; Funding acquisition: MM. All authors read and approved the manuscript. Funding This study was financed by the Research Centre for New Genomic Techniques, University of Silesia in Katowice. Data availability The data supporting the findings of this study are openly available in the Open Science Framework (OSF) at https://osf.io/pdbfr/, DOI: 10.17605/OSF.IO/PDBFR. Declarations Competing interests The authors declare no competing interests. Ethics approval and consent to participate The study was approved by the Departmental Ethics Committee (This study was approved by the University of Silesia Ethics Committee (document of approval number: KEUS551/07.2024, Katowice, Poland). All procedures in the present study were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Jagoda Różycka, Łukasz Jach and Monika Stojek contributed equally to this work. References 1. United Nations. World Population Prospects 2019: Highlights. UN. (2019). 2. Dietz, K.-J., Zörb, C. & Geilfus, C.-M. Drought and crop yield. Plant Biol. 23 , 881–893 (2021). [ DOI ] [ PubMed ] [ Google Scholar ] 3. Singh, B. K. et al. Climate change impacts on plant pathogens, food security and paths forward. Nat. Rev. Microbiol. 21 , 640–656 (2023). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 4. Yang, X. et al. Diversifying crop rotation increases food production, reduces net greenhouse gas emissions and improves soil health. Nat. Commun. 15 , 198 (2024). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 5. Animasaun, D. A. & Oguntoye, E. O. Mutagenesis in crop improvement: Methods and applications. J. Crop Improv. 38 , 156–178 (2024). [ Google Scholar ] 6. Jain, S. M. Major mutation-assisted plant breeding programs supported by FAO/IAEA. Plant Cell Tissue Organ Cult. 82 , 113–123 (2005). [ Google Scholar ] 7. Linnhoff, S., Volovich, E., Martin, H. M. & Smith, L. M. Millennials’ attitudes toward genetically modified foods. Int. J. Agric. Resour. Gov. Ecol. 13 , 371–389 (2017). [ Google Scholar ] 8. Bohle, F. et al. Where does the EU-path on new genomic techniques lead us?. Front. Genome Ed. 6 , 1377117 (2024). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 9. Marzec, M. & Hensel, G. More precise, more universal and more specific RNA-guided endonucleases. FEBS J. 286 , 4657–4660 (2019). [ DOI ] [ PubMed ] [ Google Scholar ] 10. Drake, J. W., Charlesworth, B., Charlesworth, D. & Crow, J. F. Rates of spontaneous mutation. Genetics 148 , 1667–1686 (1998). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 11. Paleologo, M. et al. Public perception of new plant breeding techniques. Public. Underst. Sci. 33 , 795–812 (2024). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 12. Fishbein, M. & Ajzen, I. Belief, attitude, intention, and behavior (Addison-Wesley, 1975). 13. Cicia, G., Furno, M. & Del Giudice, T. Consumers’ values and food retailer choice. Agric. Econ. 9 , 3 (2021). [ Google Scholar ] 14. Bagozzi, R. P. Attitudes, intentions, and behavior. J. Pers. Soc. Psychol. 41 , 607–627 (1981). [ Google Scholar ] 15. Michaelidou, N. & Hassan, L. Advances in attitude and behavioural decision-making models. J. Mark. Manag. 30 , 519–528 (2014). [ Google Scholar ] 16. Rosenberg, M. J. et al. Attitude organization and change (Yale Univ. Press, 1960). 17. Eagly, A. H. & Chaiken, S. The psychology of attitudes . Harcourt Brace (1993). 18. Adeboye, S. E. et al. Consumer awareness of genome-edited food in Nigeria. J. Agric. Food Sci. 22 , 118–132 (2024). [ Google Scholar ] 19. Frewer, L., Scholderer, J. & Lambert, N. Consumer acceptance of functional foods. Br. Food J. 105 , 714–731 (2003). [ Google Scholar ] 20. Bruhn, C. M. Enhancing consumer acceptance of new processing technologies. Innov. Food Sci. Emerg. Technol. 8 , 555–558 (2007). [ Google Scholar ] 21. Tańska, M., Babicz-Zielińska, E. & Chaillot, A. Elderly attitudes towards unfamiliar food. Handel Wewnętrzny . 366 , 368–376 (2017). [ Google Scholar ] 22. Allred, N. & Bolton, L. E. Conspiracy beliefs and consumption. J. Consum. Res. 51 , 656–678 (2024). [ Google Scholar ] 23. Deng, H. & Hu, R. Crisis of trust in scientists and GMO attitudes. Br. Food J. ahead of print (2019). 24. Du, Z., Xiao, Y. & Xu, J. Information exposure and GMO attitudes in China. Front. Psychol. 13 , 955541 (2022). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 25. Renn, O. & Levine, D. Credibility and trust in risk communication. In Communicating risks to the public (Springer, (1991). 26. Frewer, L. J. et al. Trust in food-related risk information. Risk Anal. 16 , 473–486 (1996). [ DOI ] [ PubMed ] [ Google Scholar ] 27. Norris, P. Institutional explanations for political support. In Critical citizens (Oxford Univ. Press, (1999). 28. Slovic, P. Trust, emotion and science. Risk Anal. 19 , 689–701 (1999). [ DOI ] [ PubMed ] [ Google Scholar ] 29. LaVeist, T. A. et al. Medical mistrust and satisfaction with care. Med. Care Res. Rev. 57 , 146–161 (2000). [ DOI ] [ PubMed ] [ Google Scholar ] 30. Newton, K. & Norris, P. Confidence in public institutions. In Disaffected democracies (Princeton Univ. Press, (2000). 31. Pescosolido, B. A. et al. Public confidence in physician authority. J. Health Soc. Behav. 42 , 1–16 (2001). [ PubMed ] [ Google Scholar ] 32. Kehoe, S. M. & Ponting, J. R. Value congruence and trust in health policy actors. Soc. Sci. Med. 57 , 1065–1075 (2003). [ DOI ] [ PubMed ] [ Google Scholar ] 33. Calnan, M. W. Public trust in health care. Qual. Saf. Health Care 13 , 92–97 (2004). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 34. Neufeld, S. J. & Cinnamon, J. L. Farm parents’ attitudes to safety experts. Rural Sociol. 69 , 532–551 (2004). [ Google Scholar ] 35. Firoozzare, A. et al. Awareness and trust in healthy food decisions. Food Qual. Prefer . 121 , 105275 (2024). [ Google Scholar ] 36. Cox, D. N. & Evans, G. Food technology neophobia scale. Food Qual. Prefer. 19 , 704–710 (2008). [ Google Scholar ] 37. Siddiqui, S. A. et al. Avoiding food neophobia. Sustainability 14 , 10391 (2022). [ Google Scholar ] 38. Vidigal, M. C. T. R. et al. Food technology neophobia in Brazil. LWT 60 , 832–840 (2015). [ Google Scholar ] 39. Tuorila, H. & Hartmann, C. Consumer responses to novel foods. Curr. Opin. Food Sci. 33 , 1–8 (2020). [ Google Scholar ] 40. Okello, R. et al. Food technology neophobia in Uganda. Appl. Food Res. 2 , 100053 (2022). [ Google Scholar ] 41. Ortega, D. L., Lin, W. & Ward, P. S. Acceptance of gene-edited foods in China. Food Qual. Prefer. 95 , 104374 (2022). [ Google Scholar ] 42. Rozin, P., Haidt, J. & McCauley, C. R. Disgust. In Handbook of emotions (Guilford Press, (1993). 43. Haidt, J. & Joseph, C. The moral mind. In The innate mind Vol. 3 (Oxford Univ. Press, (2008). 44. Schaller, M. Disgust and the behavioral immune system. Evol. Behav. Sci. 8 , 251–256 (2014). [ Google Scholar ] 45. Olatunji, B. O. et al. Three Domains Disgust Scale Assessment 19 , 205–225 (2012). [ DOI ] [ PubMed ] [ Google Scholar ] 46. Haidt, J. The righteous mind . Vintage (2013). 47. Scott, S. E., Inbar, Y. & Rozin, P. Moral opposition to GM food. Perspect. Psychol. Sci. 11 , 315–324 (2016). [ DOI ] [ PubMed ] [ Google Scholar ] 48. Chinn, S. & Hasell, A. Disgust and GM food attitudes. JCOM 20 , A05 (2021). [ Google Scholar ] 49. Hwang, H. & Nam, S.-J. Knowledge and responses to GM foods. GM Crops Food 12 , 146–157 (2021). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 50. Fernbach, P. M. et al. Extreme opponents of GM foods. Nat. Hum. Behav. 3 , 251–256 (2019). [ DOI ] [ PubMed ] [ Google Scholar ] 51. Brossard, D. & Nisbet, M. C. Deference to scientific authority. Int. J. Public Opin. Res. 19 , 24–52 (2006). [ Google Scholar ] 52. McFadden, B. R. & Lusk, J. L. Knowledge and beliefs about GM food. FASEB J. 30 , 3091–3096 (2016). [ DOI ] [ PubMed ] [ Google Scholar ] 53. Paudel, B. et al. Acceptance of gene-edited foods. Agribusiness 39 , 623–645 (2023). [ Google Scholar ] 54. Naab, F. Z. et al. Public perceptions of genomic technologies in animals. BioTech 10 , 28 (2021). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 55. Lang, J. T. & Hallman, W. K. Trust and GM food. Risk Anal. 25 , 1241–1252 (2005). [ DOI ] [ PubMed ] [ Google Scholar ] 56. Araki, M. & Ishii, T. Social acceptance of genome editing. Trends Plant Sci. 20 , 145–149 (2015). [ DOI ] [ PubMed ] [ Google Scholar ] 57. Ishii, T. & Araki, M. Consumer acceptance of genome-edited crops. Plant. Cell Rep. 35 , 1507–1518 (2016). [ DOI ] [ PubMed ] [ Google Scholar ] 58. Brotherton, R. et al. Generic Conspiracist Beliefs Scale. Front. Psychol. 4 , 279 (2013). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 59. Siwiak, A. et al. Polish adaptation of conspiracist beliefs scale. Pol. Psychol. Bull. 50 , 259–269 (2019). [ Google Scholar ] 60. Jach, Ł. Views of science questionnaire. Curr. Issues Pers. Psychol. 9 , 66–83 (2021). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 61. De Kock, H. L. et al. Alternative food neophobia scale. Food Qual. Prefer . 101 , 104626 (2022). [ Google Scholar ] 62. Jach, Ł. Scientistic worldview and COVID-19 attitudes. Curr. Issues Pers. Psychol. 11 , 11–28 (2023). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 63. White, T. M. et al. Trust in COVID-19 vaccine science. Vaccine X . 21 , 100576 (2024). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 64. Zamparo, G. et al. Food neophobia and attitudes. Br. Food J. 125 , 2275–2293 (2023). [ Google Scholar ] 65. Giordano, S. et al. Neophobia and food technologies. Int. J. Gastron Food Sci. 11 , 1–19 (2018). [ Google Scholar ] 66. Boccia, F. & Sarno, V. Socially responsible food behavior. Food Res. Int. 121 , 91–96 (2019). [ DOI ] [ PubMed ] [ Google Scholar ] 67. Prochaska, J. O. & DiClemente, C. C. Stages of change model. J. Consult. Clin. Psychol. 51 , 390–395 (1983). [ DOI ] [ PubMed ] [ Google Scholar ] 68. Prochaska, J. O. et al. How people change. Am. Psychol. 47 , 1102–1114 (1992). [ DOI ] [ PubMed ] [ Google Scholar ] 69. Prochaska, J. O. et al. Measuring processes of change. J. Consult Clin. Psychol. 56 , 520–528 (1988). [ DOI ] [ PubMed ] [ Google Scholar ] 70. Miller, W. R. & Rose, G. S. Motivational interviewing theory. Am. Psychol. 64 , 527–537 (2009). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 71. Sparks, P. et al. Ambivalence about food choice. Br. J. Health Psychol. 6 , 53–68 (2001). [ DOI ] [ PubMed ] [ Google Scholar ] 72. Halkier, B. Consuming ambivalences. J. Consum. Cult. 1 , 205–224 (2001). [ Google Scholar ] 73. Gillebaart, M. et al. Self-control and food conflict. J. Pers. 84 , 789–798 (2016). [ DOI ] [ PubMed ] [ Google Scholar ] 74. Norris, C. J. et al. Ambivalence toward food. Appetite 140 , 309–317 (2019). [ DOI ] [ PubMed ] [ Google Scholar ] 75. Kuijer, R. G. & Tunley, M. K. Ambivalence and self-compassion. Br. J. Health Psychol. 30 , e12806 (2025). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 76. Fischer, A. R. H. et al. Attitudinal ambivalence and nanotechnology. Public. Underst. Sci. 22 , 817–831 (2013). [ DOI ] [ PubMed ] [ Google Scholar ] 77. Białek-Dratwa, A. et al. Dietary trends among Polish women. Front. Nutr. 10 , 1219704 (2023). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 78. Cattaneo, C. et al. Attitudes toward food by-products. Int. J. Food Sci. Technol. 54 , 679–687 (2019). [ Google Scholar ] 79. Butler, J. Variations on sex and gender. In Essays on the politics of gender (Univ. of Minnesota Press, (1987). 80. Przygoda, J. & Chrisler, J. C. Definitions of gender and sex. Sex. Roles . 43 , 553–569 (2000). [ Google Scholar ] 81. Fausto-Sterling, A. Gender/sex and identity. J. Sex. Res. 56 , 529–555 (2019). [ DOI ] [ PubMed ] [ Google Scholar ] 82. McCright, A. M. et al. Political ideology and trust in science. Environ. Res. Lett. 8 , 044029 (2013). [ Google Scholar ] 83. Allen, M. S. et al. Single-item measures. Eur. J. Psychol. Assess. 38 , 1–5 (2022). [ Google Scholar ] 84. Bergkvist, L. & Rossiter, J. R. Single- vs multiple-item measures. J. Mark. Res. 44 , 175–184 (2007). [ Google Scholar ] 85. Fisher, G. G. et al. Single-item measures in research. J. Occup. Health Psychol. 21 , 3–23 (2016). [ DOI ] [ PubMed ] [ Google Scholar ] 86. European Commission. European citizens’ knowledge and attitudes towards science and technology. Publications Office. (2025). 87. Bearth, A. et al. Acceptance of genome editing in agriculture. Food Res. Int. 178 , 113982 (2024). [ DOI ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials Supplementary Material 1 (49.3KB, docx) Data Availability Statement The data supporting the findings of this study are openly available in the Open Science Framework (OSF) at https://osf.io/pdbfr/, DOI: 10.17605/OSF.IO/PDBFR. Articles from Scientific Reports are provided here courtesy of Nature Publishing Group ACTIONS View on publisher site PDF (1.6 MB) Cite Collections Permalink RESOURCES Similar articles Cited by other articles Links to NCBI Databases Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top

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