According to Ajzen, TPB suggests that intention most directly influences behavioral performance; intention refers to the “tendency to try to perform a behavior” (29), and the greater the intention to perform a behavior, the greater the likelihood that the action will be carried out. A review of the theory of planned behavior and the rational behavior approach suggests that intention explains between 18 and 23% of the variance across a wide range of behaviors (31), particularly health behaviors (40). In healthy dietary practices, researches have demonstrated that intentions exert a positive influence on eating behavior (41, 42).

In studies using the TPB framework, the assessment of attitudinal constructs and behavioral outcomes adheres to the logically prescribed chronological sequence dictated by theoretical postulates (43). Due to difficulties in contacting respondents in the days immediately following the distribution of the questionnaire to assess their functional food consumption behavior, administration of both behavioral and attitudinal measurements was necessary. However, dietary choices remain relatively stable over short periods of time, so the simultaneous or delayed measurement of consumption behavior does not yield substantial differences (44). Therefore, data derived from retrospective behavioral surveys can be used as a valid proxy for predicting future behavior (45). In this study, a retrospective behavioral survey was employed to measure behavioral constructs. Thus, the following hypothesis is proposed:

Health consciousness refers to a person’s willingness to take action for their health (46). Empirical evidence consistently shows that health-conscious consumers prioritize wellness-oriented products and have a stronger intention to purchase health-promoting goods and services (28). Specifically regarding functional foods: Chen identified the health-oriented consumers hold significantly more positive attitudes towards them (47). Cranfield et al. found that perceived health status was associated with attitudes towards functional foods among women, and individuals who were aware of the strong link between the nutritional benefits of functional foods and their personal health were more likely to consume such products (5). This finding implies that consumers’ health consciousness positively influences their attitudes towards functional foods. Thus, the following hypothesis is proposed:

In the TPB framework, attitude is recognized as a determinant of intention. Attitude refers to one’s positive or negative perceptions of performing a particular action (29). It is often cited as the most robust predictor of the intention to engage in healthy eating practices (12, 24, 48–50). Carrillo et al. demonstrated that consumers’ attitudes can serve as a reliable predictor of spending on functional foods (12). Patch et al. also revealed that attitudes were the primary determinant of Australian consumers’ intention to consume foods fortified with omega-3 fatty acids (51). Our study suggests that individuals with positive attitudes towards functional foods are more likely to incorporate them into their diets. Thus, the following hypothesis is proposed:

Subjective norms refer to an individual’s perception of the social support they receive from important significant others, such as family members, friends, or colleagues, when deciding whether to perform a specific behavior (29). Previous studies confirmed their predictive validity in health contexts. For example, O’Connor demonstrated a significant influence on the adoption of health products (24). Patch et al. reported that family and friends play a crucial role in introducing new foods to individuals, while dietitians were regarded as reliable information sources. In contrast, food companies and scientists were found to be the least trusted among the information providers (52). China exhibits an acquaintance-based cultural characteristic, where individual behaviors are significantly shaped by social influences (14). Thus, the following hypothesis is proposed:

Perceived behavioral control is defined as an individual’s subjective assessment of their ability to control a particular behavior, including how easy or difficult they perceive it to be (29). This construct exerts a dual influence, acting directly on behavioral enactment and indirectly via behavioral intentions. Empirical evidence demonstrates its critical role in food-related decision-making processes (29). For instance, reduced perceived difficulty increases the likelihood of online purchasing (53). Studies focusing on functional foods emphasize the importance of PBC factors. For example, Marimuthu found that perceived convenience was the main factor influencing young mothers’ decisions to administer herbal food supplements to their children (54). Nolan-Clark et al. revealed that some consumers had challenges interpreting dairy nutrition labels due to limited time and insufficient skills (55). Lalor et al. further reported that price was one of the main influences on the purchase of healthy foods (56). In our study, we follow the original hypothesis of the TPB model, and posit that consumers are more likely to consume functional foods when they have the requisite conditions to do so. Thus, the following hypotheses are proposed:

Trust refers to “a psychological state characterized by the willingness to accept vulnerability based on positive expectations of other’s intentions or actions” (57). Functional foods are considered to have health-promoting properties in addition to providing adequate nutrition (4). However, crucially, consumers require confidence in the tangible health benefits of regular consumption before they will adopt them (58). This study considers three dimensions of trust: personalized, institutional, and public trust in technology (59). “Personalized trust” refers to consumers’ confidence in food products from short supply chains and small-scale production systems. This trust is built and sustained through consumers’ in-depth knowledge of food origins and production processes. In contrast, large-scale supply systems predominantly rely on “institutionalized trust” (60), which is defined as the acceptance and perception that the system is benevolent, competent, reliable, and accountable (61). Public trust in technology manifests as confidence in food processing methods and associated health benefits (16). Empirical evidence has shown that trust is critical to consumers’ food purchase decisions (58, 59) Trust in technology has been shown to influence both perceived risk and perceived benefit (62); while trust in food organizations and systems affects consumer preferences and product acceptance (63, 64). These findings suggest that trust positively influences consumers’ intentions towards functional foods. Thus, the following hypothesis is proposed:

This study adopts a quantitative approach utilizing primary data gathered via an online survey. The data were analyzed using structural equation modeling (SEM). In order to obtain stable parameter estimates and standard errors, the sample size should be sufficiently large. According to research by Schumacker and Lomax, samples of between 250 and 500 are generally sufficient (65). Given China’s large population and vast size, the sample size for this study was increased to 1,000. After excluding responses from participants under the age of 18, 1,011 valid data were collected from Chinese adult consumers during the empirical study.

The participants were recruited and randomly selected from an external data collection agency. Gender, age, and income quotas reflecting the composition of the Chinese population were used to ensure a national representative sample. The sample included 581 male participants (57.5%); 25.5% were aged between 40 and 49 years, and 23.7% were aged between 18 and 20 years. The majority of respondents were well educated, with 420 (41.5%) having completed high school or vocational senior high school, and 330 (32.7%) having a college diploma or above. Table 1 summarizes some of the sociodemographic characteristics of the sample. Due to the retrospective, anonymous nature of this study and the fact that no personally sensitive information was collected, our Institutional Review Board waived the need for informed consent.

The questionnaire commenced with a brief description of the term “functional foods” used in this study. The term was defined in this study as a food product that, in addition to its usual nutritional value, has a specific effect on maintaining or promoting health or reducing the risk of disease (10). The questionnaire comprises two parts. The first part contained sociodemographic information about the respondents, including age, gender, education level, occupation, and monthly household per capita income. The second part was the expanded theory of planned behavior scale, which measured the variables of the TPB model according to Ajzen (66) outline for constructing a standardized TPB questionnaire with reference to the items commonly used in previous studies to formulate the items for the two additional variables.

Consumer purchasing behavior toward functional foods was evaluated using three items measuring consumption frequency (BEH1), duration (BEH2) and percentage of dietary intake (BEH3). Each item used a distinct 5-point ordinal scale (66, 67). Purchase intention was captured through four items addressing intention, expectation, trial and planning to consume regularly (INT1–INT4). Attitudes were evaluated using four items addressing perceived benefits, pleasantness, value and the goodness of consumption (ATT1–ATT4). Subjective norms were measured using four items reflecting the perceived beliefs, expectations, endorsement and understanding of acquaintances (SN1–SN4). Perceived behavioral control was measured using three items concerning consumption control, including one reverse-scored item (PBC1–PBC3). Health consciousness was assessed using three items concerning self-perception, willingness to sacrifice and essential knowledge (HC1–HC3). These items were selected from the 11 items of the Health Consciousness Scale developed by Ophuis (46). Trust was measured using three items concerning the nutritional adequacy of functional foods, the regulatory authorities and the producer integrity (TR1–TR3) (16). All constructs except behavior used a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Appendix shows the details of variable constructs and items.

Initial analyses using SPSS 25.0 explored data and confirmed the normality of distributions. Subsequently, a two-stage procedure in AMOS 24.0 was used for confirmatory factor analyses (CFA) and SEM. CFA verified the validity of the measurement model (68), while SEM examined the hypothesized causal pathways (69). The internal consistency of each scale was assessed using Cronbach’s alpha coefficient. Convergent validity of the measures were evaluated using composite reliability (CR) and average variance extracted (AVE). The structural model testing hypotheses about functional food purchase behavior was assessed using multiple goodness-of-fit indices: χ²/df < 3, RMSEA< 0.05, and GFI, AGFI, CFI, and IFI and TLI all greater than 0.9 (69, 70). Statistical significance was determined at α = 0.05 for all path coefficients.

The results of the standardized factor loadings, Cronbach’s alpha, C. R., and AVE values, which reflect the reliability and validity of the scale, are shown in Table 2. The Cronbach’s alpha values for the seven variables ranged from 0.628 to 0.789, all of which were close to or above the acceptable threshold of 0.7, indicating good internal consistency of the scale. AVE is a key metric used to evaluate convergent validity. It is calculated as the mean of the squared factor loadings. While factor loadings ideally exceed 0.7, empirical studies often achieve a value of at least 0.6. Therefore, an acceptability threshold of 0.36 for AVE has been established (71). In this study, AVE values ranged from 0.354 to 0.556, all of which met or approached this benchmark. Similarly, CR evaluates internal consistency by aggregating indicator reliability. Higher CR values indicate stronger indicator coherence, with established thresholds designating the following: CR values of at least 0.70 indicate excellent reliability (72), values between 0.60 and 0.69 are considered acceptable for exploratory studies (73), and values below 0.60 necessitate revising the scale to ensure adequate measurement. Contemporary practice emphasizes the contextual interpretation of these benchmarks (74). Our questionnaire produced CR values ranging from 0.630 to 0.790, satisfying the minimum criterion of 0.60. Together, the Cronbach’s alpha, AVE and CR results confirm that the measurement model has adequate convergent validity and internal consistency. The questionnaire data in this study successfully passed the reliability and validity tests, validating its suitability for subsequent analytical procedures.

Seven indicators were selected to test the fit of the model for the aforementioned research hypotheses using AMOS software. As can be seen in Table 3, the value of χ²/df is 2.796 (< 3), which is ideally fitted; the RMSEA is 0.042 (< 0.05), which is ideally fitted; the GFI, AGFI, CFI, and IFI, TLI are all greater than 0.9, and the results are therefore well fitted. Overall, the seven indicators fulfill the corresponding reference standard, and the model demonstrates a good fit.

Table 4 summarizes the results of the structural equation modeling analysis. A significant positive correlation was found between health consciousness and consumer attitude, as evidenced by a standardized path coefficient of 0.921, which was statistically significant at the 0.05% level. Attitude, perceived behavioral control, and trust were all positively correlated with the intention to purchase functional foods. The respective standardized path coefficients were 0.751, 0.148, and 0.115, respectively, all of which were significant at the 0.05% level. Attitude was found to be the strongest predictor of the intention to purchase functional foods. Perceived behavioral control was also positively related to consumption behavior, as indicated by a standardized path coefficient of 0.841, which was statistically significant at the 0.05% level. However, subjective norms were not significantly positively related to the purchase of functional foods, nor was intention significantly positively related to consumption behavior. These findings support hypotheses H2, H3, H5, H6, and H7, which suggest positive correlations between health consciousness and attitude, and between attitude, perceived behavioral control and trust, and intention. There was also a significant positive correlation between perceived behavioral control and consumption behavior. However, hypothesis H4 was not supported, indicating that the positive correlation between subjective norms and the intention to purchase functional foods is not significant. Similarly, hypothesis H1 was not supported, indicating that there is no significant positive correlation between intention and consumption behavior.

This study aims to explore the decision-making influences on Chinese consumers’ consumption of functional foods by introducing health consciousness and trust into the theory of planned behavior, a social psychological theory, to construct a theoretical framework. A questionnaire was administered to 1,011 respondents, and structural equation modeling was used to test the research hypotheses. Most expectations were confirmed, confirming the applicability of the expanded theory of planned behavior in explaining and predicting the intention and consumption behavior towards functional foods among the Chinese population. Finally, the implications, future studies, and limitations of this study are discussed.

We obtained several significant findings. First, health consciousness was found to substantially influence attitudes towards functional foods, as evidenced by a standardized regression coefficient (β = 0.921, p < 0.001, see Table 4). This robust association, with a value below the multicollinearity threshold of 1, is consistent with previous studies (75). This relationship likely stems from two interrelated mechanisms. The first is health-focused information processing: individuals with heightened health consciousness actively seek nutritional information and critically evaluate health claims, which is consistent with previous research (5). Secondly, value recognition: health-conscious consumers demonstrate a greater appreciation of the nutritional benefits of functional foods, resulting in more favorable attitudes towards them. Furthermore, attitudes were found to be the most important determinant of intention to purchase functional foods (β = 0.751, p < 0.001, see Table 4). This finding is consistent with previous research (47). Consumers are significantly more likely to purchase functional foods when they fully recognize their nutritional value and are aware of their strong associations with health (5). Therefore, a more positive consumer attitude towards functional foods can be achieved by changing individuals’ perceptions of the importance of diet for health, and by actively demonstrating and publicizing the health benefits of functional foods.

Second, subjective norms had no significant effect on consumption intentions in the context of functional foods (β = 0.118, p = 0.222, see Table 4) in this study. This finding contradicts theoretical expectations and some prior empirical findings (14, 24). However, this lack of influence is consistent with comprehensive meta-analytic evidence indicating that subjective norms have limited predictive value with regard to food consumption behaviors (41). Patch et al. also demonstrated that subjective norms did not significantly impact Australians’ intentions to consume foods enriched with omega-3 fatty acids (51). Possible reasons for this are that, on the one hand, the decision to consume functional foods is more dependent on the internal factors of the individual consumer, such as their own health priorities, health needs, and level of nutritional knowledge. Consequently, when purchasing functional foods, consumers are more likely to pay attention to objective information, such as the actual efficacy and ingredients of the products, rather than the opinions of others. On the other hand, the regulatory system for functional foods in China is currently not robust and gaps and ambiguous areas in the regulations exist. In particular, the lack of effective regulation of live e-commerce has led to several chaotic phenomena in the current functional food market, such as false propaganda, exaggerated effects, uneven product quality, and other issues, which have led to general scepticism of functional foods (14). This distrust of the market weakens the influence of subjective norms (e.g., peer recommendations, social pressure, etc.) on consumers’ purchase intentions. Consequently, subjective norms did not have a significant effect on purchase intention in this study.

Third, perceived behavioral control is an important predictor of functional food consumption intentions (β = 0.148, p = 0.002, see Table 4) and behaviors (β = 0.841, p < 0.001, see Table 4), this aligns with foundational Theory of Planned Behavior (TPB) postulates and corroborates prior empirical work (49, 76). If consumers have a more positive perception of a product in terms of self-efficacy, convenience, and price perception, their consumption behavior will be significantly facilitated. It may be beneficial to increase product availability to increase the consumption of functional foods by Chinese consumers. This is consistent with Marimuthu’s findings on the convenience-driven decision-making of young mothers (54), as well as with Lalor et al.’s emphasis on price sensitivity in the adoption of healthy foods (56). Notably, while PBC has a stronger direct effect on behavior (β = 0.841) than on intention (β = 0.148), this discrepancy underscores an important insight: consumers may intend to consume functional foods based on attitude, social influence or trust, but they only translate these intentions into action when practical barriers are surmounted.

Fourth, trust shows a significant positive relationship with consumers’ intention to purchase functional foods (β = 0.115, p < 0.001, see Table 4). This finding is consistent with previous studies (16, 63, 77, 78), which indicate that higher safety and lower risks enhance consumers’ willingness to purchase healthy foods perceived as nutritionally superior to other options. Consumers’ intention to purchase functional foods increases with trust; the key challenge in functional food development is to provide consumers with solid assurances so that they believe in the efficacy and safety of functional foods (79). The current mistrust of Chinese consumers towards functional foods not only hinders the consumption of these foods by individuals, but also limits the healthy development of the functional food industry.

Fifth, our analysis reveals that there is no statistically significant relationship between consumers’ intentions to purchase functional foods and their actual consumption behavior (β = 0.002, p = 0.973, see Table 4). This finding contradicts previous research on health behaviors (31), revealing a significant discrepancy between intentions and behavior within China’s functional food market. Although consumers may express positive intentions regarding their consumption, the ability to translate these intentions into action appears to be critically dependent on external constraints. A possible reason for this is that consumers may have ideas about consuming functional foods; however, for various reasons, including information, external factors, and complex decision-making, it is difficult to directly translate these ideas into actual consumption behavior. The minimal impact of intention on consumption behavior, combined with the substantial influence of PBC, indicates that strategies that focus solely on enhancing intention are insufficient. To bridge this intention-behavior gap, systematic interventions are required to eliminate environmental barriers.

Based on these findings, several recommendations have been made to improve Chinese consumers’ intentions to consume functional foods and improve their behavior.

In this study, attitude is the strongest factor influencing the intention to consume functional foods, while health consciousness positively influences attitude. Based on this, on the one hand, it is recommended that consumer education be strengthened. Professionals can explain the composition, efficacy, and applicable population of functional foods to correct consumer misconceptions by organizing health lectures and science popularization activities. Popular science articles and videos should be published using new internet-based media to present scientific evidence and latest research results on functional foods and to raise public awareness. There is a need for targeted nutrition education for specific groups, which in turn will improve the knowledge and attitudes of the target groups towards functional foods (55). On the other hand, given that consumers cannot assess the health benefits of a food product solely by its appearance, health claims have become the most important means of direct dialogue between food manufacturers and consumers (80). Therefore, a health labeling campaign is proposed, which would require enterprises to transform scientifically validated health claims into legally binding quality commitment clauses.

This study shows that trust is a key factor influencing Chinese consumers’ purchases of functional foods. Regaining the trust of consumers frustrated by market disruptions is a top priority. To this end, it is crucial to strengthen the supervision of the entire production and distribution chain and rebuild the ecology of market confidence (81). In the production chain, implementing “Good Manufacturing Practice” (GMP) certification requires enterprises to establish a comprehensive traceability system spanning from the procurement of raw materials to the manufacture of finished products. At the distribution stage, supervision over online and offline sales channels must be enhanced and false advertising must be investigated. To address issues in live-streaming platforms, reference can be made to the practice of the Shanghai Municipal Health Commission and the Shanghai Patriotic Health Campaign Committee Office in establishing an internet “Negative Behavior List,” which prohibits the dissemination of false or erroneous health science and technology information and exaggerated claims about disease treatment efficacy (82).

This study indicates that perceived behavioral control influences consumers’ purchase intentions and behavior. Emphasizing that the product is suitable for a specific group of people so that consumers feel that the product can meet their needs and increase their confidence in purchasing it is pivotal to improving consumer self-efficacy and control in the consumption of functional foods. In product packaging and advertising, the composition of the product ingredients, specific effects, correct use of the product, and related precautions should be presented in detail so that consumers can clearly understand the process of using the product and its expected results, thereby reducing uncertainty. In terms of price, it is important to regulate the market price mechanism, curb the phenomenon of inflated prices through market research, and develop a reasonable price range so that consumers can experience the cost-effectiveness of the product and rest assured of the worth of the purchase. In addition, a government subsidy scheme could be implemented for food enterprises or consumers to incentivize the development and launch of affordable functional foods. This approach would enable low-income groups to benefit from functional foods and participate seamlessly in the market, thereby enhancing food security and nutritional equity.