# Consumer Perceptions and Attitudes Towards Ultra-Processed Foods
## 3 Related Work  
### Consumer Attitudes Towards Ultra-Processed Foods and Their Influence on Purchase Intentions  
Understanding consumer attitudes towards UPFs is essential for both businesses and policymakers seeking to balance market demands with public health objectives. By analysing the psychological, social, and economic factors that drive UPF consumption, this study aims to provide insights into how consumer decision-making processes align with broader health and sustainability trends. The findings will help guide targeted marketing approaches, regulatory frameworks, and consumer education programmes designed to promote healthier food choices while addressing the realities of modern consumption patterns. [PERSON] et al. [31] explored consumer behaviour (intention and consumption) toward convenience-processed foods by applying the SEM technique with nine input constructs and two output constructs to test a model using a dataset of 426 Italian consumers. Four input constructs belonged to the group of belief factors, while the remaining five were classified as personal trait factors. Although convenience foods are not always ultra-processed, they often overlap with UPFs due to industrial processing, extended shelf life, and the inclusion of preservatives or artificial additives. The study reveals that six out of the ten hypotheses were supported, while the remaining three--related to value for money, taste, healthiness (from the belief factors group), and monetary resources (from the personal traits group)--were not supported. The hypothesis regarding the influence of intention on consumption was confirmed. To examine changes in consumer behaviour, including fast-food consumption and online purchasing patterns resulting from the pandemic, [PERSON] et al. [32] adopted the value-attitude-behaviour (VAB) model and designed two models: a first-order and a second-order constructs model to predict buying intention among 325 young people who live in Bangladesh and consume fast food. The first model analysed the relationships between seven input constructs--convenience, food quality, novelty seeking, subjective norms, and self-identification--and three output constructs: cognitive attitude, affective attitude, and buying intention. In the second-order model, utilitarian and hedonic values were considered higher-order reflective constructs. Utilitarian value was represented by convenience and food quality, while novelty seeking and subjective norms were interpreted as hedonic values. The study found that both higher-order constructs positively influenced cognitive and affective attitudes toward online fast-food purchasing. These attitudes, along with self-identity and subjective norms, were strongly and positively correlated with behavioural intention, whereas the role of food quality was found to be statistically insignificant. Using the theory of consumption values, [PERSON] [33] investigated how consumers rank food choice values using a dataset of 256 completed questionnaires from Mexican consumers. The questionnaire was designed to measure seven food choice values along with selected psychographic constructs, including safety and sustainability, weight control, convenience, basic sensory attributes, traditionalism, emotional value, novelty of functional food, self-control, self-assessment of diet quality, and health consciousness. For data analysis, in addition to classical statistical methods, the author introduced decision trees (DTs) as an innovative analytical tool to better understand consumer choices. The results empirically validated food choice value metrics and revealed the underlying motives influencing snack and beverage choices. [PERSON] et al. [34] examined the relevance of nine factors influencing consumer acceptance of UPF products in Spain. This study proposed a measurement scale incorporating quality, time savings, price, effortless preparation, convenience, hedonicism, marketing strategies, purchase intention, and satisfaction.