Abstract
Encouraging people to adopt a healthy diet is believed to reduce the prevalence of obesity. However, a deeper understanding of consumers' psychology regarding healthy dieting is required for this intervention to be effective. To date, knowledge remains limited on the motivations preceding healthy dietary adoption among adult consumers in the Czech Republic, which is undoubtedly facing a high prevalence of obesity among other EU member states. Most importantly, few studies have modeled the food choice motives as primary antecedents of healthy dietary adoption intentions. Therefore, the current study proposes and tests a research model that explains the motivational factors for adopting healthy diets. Data were collected through an online survey involving 161 university students and analyzed using partial least squares structural equation modeling (PLS-SEM) procedures. The results reveal that food choice motives explain healthy dietary adoption intentions satisfactorily. Notably, the natural content and weight control motives positively and significantly affect healthy dietary adoption intentions. The study offers relevant contributions to the science of consumer motivation regarding healthy dieting and practical means to health promotion.
1 Introduction
Obesity remains a major public health problem in Europe (Janssen et al. 2020; Marques et al. 2018), spawning cardiovascular disease, osteoarthritis, mental illness and life-threatening diseases like type 2 diabetes and cancer (Dixon 2010). Among EU member states, the Czech Republic recorded the highest adult obesity rate at 19% in 2019, and it is forecast to reach 35% by 2030 (MZČR 2019; OECD – European Observatory on Health Systems and Policies 2021). Landovská (2021) substantiates the severity of obesity in the country as its estimated social costs amounted to 1.5 billion euros in 2018 alone. The incidence of the COVID-19 pandemic further stressed the importance of responding to the obesity problem as it is linked to higher morbidity and mortality (Popkin et al. 2020).
Counteracting the obesity epidemic becomes even more challenging with the economic growth and increasing urbanization in many areas across the globe. People increasingly adopt sedentary lifestyles and transition diets favoring high-calorie and processed food (Hruby – Hu 2015). External cues in the food service domain are likewise becoming more salient to consumers. The increased availability, accessibility, and palatability of calorie-dense food engender psychological signals that hamper consumers' ability to regulate food intake (Bilman et al. 2017). In addition, away-from-home consumption has increased, and frequent visits to fast food restaurants have led to poor diet quality and increased obesity risk among adult consumers (Larson et al. 2011).
In the Czech Republic, more than 50% of adult consumers (i.e. those older than 20 years) are overweight and obese (World Health Organization 2013). They fall behind the recommended daily intake of fruit and vegetables and exceed the recommended intake of high-sugar or sweetened beverages (OECD – European Observatory on Health Systems and Policies 2021). Lean et al. (2006) suggest that obesity cases can be mitigated by encouraging people to consume healthy food and perform adequate physical activity. Enforcing health-promoting policies in communities, schools, and worksites could also strengthen individual-level initiatives toward obesity prevention (Johnson et al. 2006). However, for health-promoting interventions to be effective, there is a need to delve deeper into consumers' psychology regarding healthy lifestyle adoption. Previous studies argue that healthy lifestyle adoption precisely related to the choice or intake of healthy food is driven by various motivations (Marty et al. 2021; Steptoe et al. 1995; Sun 2008). Steptoe et al. (1995), through their food choice questionnaire (FCQ), conceived nine motives influencing food choice: health, mood, convenience, sensory appeal, natural content, price, weight control, familiarity, and ethical concern.
Nevertheless, knowledge remains limited regarding Czech consumers' motivations to adopt healthy diets following the COVID-19 pandemic. Consumer behavior studies on healthy diet adoption still largely represent western developed countries (Wang – Scrimgeour 2021). Moreover, the literature pays little regard to modeling the food choice motives as antecedents of healthy dietary behaviors (Ahmad et al. 2020; Dowd – Burke 2013; Sun 2008). Some applications of the food choice concept include consumers' consumption of organic food (Honkanen et al. 2006), traditional food (Pieniak et al. 2009), genetically modified food (Chen 2011), ethnic food (Ahmad et al. 2020), and sustainable food (Verain et al. 2021). Scholars argue that more validation studies are required to better understand the influence of food choice motives on consumer behavior outcomes regarding food consumption (Ahmad et al. 2020; Sun 2008). Furthermore, Verain et al. (2022) emphasize the need to conduct context-specific studies as the motives' relative importance on food choice exhibits high contextual variability. Socio-demographic differences (such as pertaining to age, income, education, family background, etc.; Konttinen et al. 2021; Vorage et al. 2020) and cultural differences (Honkanen – Frewer 2009) variously affect motives on food choice.
Therefore, to address the previously mentioned research gaps, this work anchors on the concept of food choice motives (Steptoe et al. 1995) and examines their influence on behavioral intentions among university students in the Czech Republic to adopt a healthy diet following the COVID-19 pandemic. To date, no studies have explicitly looked into Czech university students' motives for adopting healthy diets. University students constitute a significant part of the adult population in the Czech Republic, experiencing high overweight and obesity cases (OECD – European Observatory on Health Systems and Policies 2021). Prior studies have reported that university students are exposed to unhealthy lifestyles, hence the prevalence of overweight and obesity cases (Peltzer et al. 2014; Telleria-Aramburu – Arroyo-Izaga 2022). Meanwhile, higher education institutions are important avenues for promoting healthy eating behaviors (Sepúlveda et al. 2007); hence, investigating university students' healthy diet adoption behavior is imperative in designing effective health-promoting interventions.
By employing the food choice questionnaire (FCQ), this study measures nine core food choice motives and examines what motives influence healthy diet adoption intentions. Theoretically, the study uncovers the mechanisms of food choice motives impacting healthy diet adoption intentions from a new contextual perspective on university students in the Czech Republic. Practically, the study provides insights into what actions to pursue to induce relevant motivations that effectively steer individuals toward a healthier lifestyle and consequently halt the ballooning incidence of obesity in the country.
2 Literature review and hypotheses development
2.1 The concept of food choice motives
The pioneering work by Steptoe et al. (1995) has developed a multidimensional measure of motivational factors influencing people's dietary choices, commonly known as the food choice questionnaire (FCQ). They elucidated a conceptual understanding of nine health and non-health motives steering food selection. These include health, mood, convenience, sensory appeal, natural content, price, weight control, familiarity, and ethical concern. Since then, several scholars have tested the robustness of the FCQ and explored relevant motives underlying people's food consumption. Consumer psychology maintains that motivation is essential for performing a behavior (de Ridder 2012). Hence, the concept of food choice motives has been linked to other theories (e.g., the theory of planned behavior), developing alternative frameworks that better explain diverse contexts related to food consumption (Ahmad et al. 2020; Dowd – Burke 2013; Sun 2008). In this study, food choice motives were modeled as direct antecedents of intentions among Czech university students to adopt a healthy diet (Fig. 1).
The research model. Source: authors
Citation: Society and Economy 2023; 10.1556/204.2023.00004
The research model. Source: authors
Citation: Society and Economy 2023; 10.1556/204.2023.00004
The research model. Source: authors
Citation: Society and Economy 2023; 10.1556/204.2023.00004
2.2 Hypotheses development
2.2.1 Health and healthy diet adoption intentions
Health motives relate to people's concerns about improving or maintaining overall health, and they shape decisions toward consuming health-promoting food (Glanz et al. 1998; Steptoe et al. 1995). Sun (2008) stresses that an individual manifesting concern over developing diet-related diseases activates health motivations which subsequently drive healthy eating behavior. Previous studies reported similar findings indicating the importance of health motives in decisions related to the consumption of sustainably sourced food (Dowd – Burke 2013), traditional food (Almli et al. 2011; Pieniak et al. 2009), and functional food (Žeželj et al. 2012), and practicing a healthy diet in general (Michaelidou et al. 2012; Pearcey – Zhan 2018; Piggford et al. 2008). However, it is argued that health concerns among young adults are still less; thus, health-driven food consumption can be dismissed (Ahmad et al. 2020; Honkanen – Frewer 2009). With these opposing findings in the literature, the current study postulates the following:
Health motives positively influence intentions to adopt a healthy diet
2.2.2 Mood and healthy diet adoption intentions
People's mood influences the type of food they consume (Leigh Gibson 2006). Extant evidence suggests that a stressful or negative emotional state induces unhealthy food consumption behavior, denoted as “emotional eating” (Evers et al. 2010; Sproesser et al. 2013; Taut et al. 2012). Meanwhile, AlAmmar et al. (2020) expounded that the mood and food intake have a corresponsive relationship. Mood influences food choice, and food intake affects mood modulation. Adequate consumption of health-promoting food (e.g., vegetables, fruit, protein, and nuts), water, and low-caffeine beverages promote a positive mood (AlAmmar et al. 2020). Arab et al. (2019) also reported that vegetable-based, glycemic load–based, ketogenic, and paleo diets could promote better mood states. Although the intake of unhealthy food affects positive mood modulation as well, it is less influential than consuming healthy food (AlAmmar et al. 2020; Wagner et al. 2014). As the literature emphasizes the corresponsive effect between mood and food, the study addresses the role of mood as an antecedent of healthy diet adoption. Therefore, the study postulates the following:
The mood motive positively influences intentions to adopt a healthy diet
2.2.3 Convenience and healthy diet adoption intentions
The convenience motive relates to the time, effort, and skills required to prepare and consume certain food (Piggford et al. 2008; Steptoe et al. 1995). The extant literature shows the negative link between convenience and healthy dietary behavior (Glanz et al. 1998; Michaelidou et al. 2012; Verstraeten et al. 2014). It is perceived that healthy food is challenging to access and takes longer time and effort to prepare. Hence, time-constrained individuals (e.g., students and employees) often favor away-from-home consumption, such as in fast food restaurants (Monsivais et al. 2014; Piggford et al. 2008). During the COVID-19 pandemic, convenience has also been found to be influential in people's consumption of convenience food as working parents, with their added responsibilities at home, strive to be productive while working remotely (Shen et al. 2020). Hence, the study posits that:
The convenience motive negatively influences intentions to adopt a healthy diet
2.2.4 Sensory appeal and healthy diet adoption intentions
Sensory appeal influences consumers' decisions about what and when to eat and drink (Pearcey – Zhan 2018). Unsurprisingly, consumers favor pleasant and tasty food (Papies et al. 2021). The more attractive a dish is in terms of appearance, taste, and aroma, the more inclined a consumer is to consider the dish superior and to eventually select it. Past studies have largely considered the impact of sensory appeal on dietary choices among consumers with diverse demographics, except for people with food neophobia (Allès et al. 2017; Pearcey – Zhan 2018). Given these, the following pertinent hypothesis is formulated:
The sensory appeal motive positively influences intentions to adopt a healthy diet
2.2.5 Natural content and healthy diet adoption intentions
Nowadays, several food products are being processed and added with several additives to enrich and lengthen their shelf life. Román et al. (2017) argue that food naturalness remains a significant factor in food choice, especially among consumers who are deeply concerned about health. These consumers often desire natural, fresh, and less processed food. On the contrary, a few studies, such as by Schlup and Brunner (2018) and Jaeger et al. (2021), dismiss the relevance of the natural content motive in food neophobic consumers' food intake decisions. This study posits the following:
The natural content motive positively influences intentions to adopt a healthy diet
2.2.6 Price and healthy diet adoption intentions
Price is a major factor influencing food selection and consumption decisions (Choe – Kim 2019). Food consumption decisions are closely associated with consumers' budget; hence, food price becomes a vital factor in deciding the quantity and quality of the food purchased. High-quality food products, sometimes healthy ones, generally have higher market prices. One way or another, this potentially dissuades consumers from purchasing healthy food products (Daly et al. 2021; Van Doorn – Verhoef 2015). Meanwhile, another study revealed that customers are willing to pay higher prices for healthy food, thereby challenging the idea of the price motive being influential in healthy food choices (de-Magistris – Gracia 2016). With these findings, this study postulates the following:
The price motive negatively influences intentions to adopt a healthy diet
2.2.7 Weight control and healthy diet adoption intentions
Consumers who are deeply concerned about their weight tend to follow healthy diets (Glanz et al. 1998; Vainio et al. 2016). People tend to suppress eating behavior to lose weight (de Ridder 2012), attain a good physique, achieve sound health, and recover from illnesses (Burnette et al. 2020). However, more recent evidence from the work by Pearcey and Zhan (2018) indicates the influence of weight control factors on students' choice of healthy food for reasons related to their hectic lifestyle, availability, accessibility, and the price of healthy food in schools. Meanwhile, Vorage et al. (2020) argue that the weight control motivation only influences consumers' attraction to functional food (i.e., with added health benefits) but not actual consumption. Despite these opposing views, this work posits the following:
The weight control motive positively influences intentions to adopt a healthy diet
2.2.8 Familiarity and healthy diet adoption intentions
The familiarity motive refers to consumers' proximate cognizance of food products, and consuming these familiar foods engenders more satisfying feelings over having novel alternatives (Steptoe et al. 1995). Knaapila et al. (2015) reveal that the aversion to consuming novel foods is associated with a decreased consumption of vegetables and contributes to a decline in the quality of dietary choices. However, Pearcey and Zhan (2018) assert that the effect of food familiarity may differ depending on demographic groups. The authors observe that younger generations are more open and curious about new foods, thus dismissing the effect of food familiarity. With these findings, the following is postulated:
The familiarity motive negatively influences intentions to adopt a healthy diet
2.2.9 Ethical concerns and healthy diet adoption intentions
Western diets have been associated with sustainability issues relating to high environmental load, animal-welfare issues, and social justice (Jaeger et al. 2021; van de Kamp et al. 2018). Some evidence shows that consumers nowadays have developed greater sustainability and ethical concerns about the food they purchase, as evidenced by the availability of ethical food products in the market (De Canio – Martinelli 2021). Sun (2008) claims that the ethical concern in parallel with health consciousness is one of the most important motives contributing to healthy eating, especially among women (Piggford et al. 2008). However, the review by Jaeger et al. (2021) argues that ethical concern as a food choice motive is the least relevant among other motives conceptualized by Steptoe et al. (1995). With the contrasting findings in the literature, this work hypothesizes the following:
The ethical concern motive positively influences intentions to adopt a healthy diet
3 Methodology
3.1 Questionnaire design
The survey questionnaire was formulated online using Google Forms. It consisted of two major sections: i) assessment of the motives and intentions to adopt a healthy diet, and ii) demographic characteristics of the respondents. The food choice questionnaire (FCQ) developed by Steptoe et al. (1995) was adapted to measure constructs of food choice motives. A four-point scale (1 = not at all important; 4 = very important) was utilized to assess the importance of motives' measurement items. The study also adapted the question items from Ahmad et al. (2020) to measure behavioral intentions, gauged using a five-point Likert scale (1 = strongly disagree; 5 = strongly agree). The survey questionnaire was translated into the Czech language and underwent a back-translation procedure to ensure the translation quality of the measurement items. Two professors fluent in Czech and English were closely involved in this procedure. Moreover, before its final distribution, the survey questionnaire was pre-tested on ten Czech undergraduate students to check for its comprehensibility and identify errors and other issues.
3.2 Sampling and data collection procedure
The study recruited a convenience sample from a pool of university undergraduate students attending economics and management courses. Its use in the study remains apt as the sample still captures young adult consumers (18–26 years old). This population is facing a high prevalence of obesity, has a higher chance of developing diet-related diseases, and is more likely to gain weight than other age groups (Berger 2018; Munt et al. 2017; Poobalan – Aucott 2016).
The online survey link was sent to 250 students, but only 180 completed the survey. After data screening, only 161 responses were found to be valid, which is still sufficient for studies employing structural equation modeling analysis. Hair Jr et al. (2017: 24) argue that the minimum sample size should be “10 times the largest number of structural paths directed at a particular construct in the structural model”, so a sample of more than 90 was required in the current study. Concurrently, power sample analysis was performed using G*Power (version 3.1.9.7), and it revealed a minimum sample size of 114, at f2 (medium effect) = 0.15, power = 0.80, and
Demographic characteristics of the respondents (n = 161)
| Variable | Frequency (n = 161) | Percentage |
| Gender | ||
| Male | 57 | 35.4 |
| Female | 104 | 64.6 |
| Age (in years) | ||
| 18–25 | 118 | 73.29% |
| 26–35 | 27 | 16.77% |
| 36–45 | 16 | 9.94% |
| Employment Status | ||
| Unemployed | 75 | 46.6 |
| Self-employed | 22 | 13.7 |
| Employed | 64 | 39.8 |
| Income Level | ||
| up to CZK 20,000 | 32 | 19.9 |
| CZK 20,000–CZK 40,000 | 60 | 37.3 |
| 40 0001 CZK and more | 69 | 42.9 |
| Marital Status | ||
| Single | 98 | 60.9 |
| Married, registered partnership | 23 | 14.3 |
| Living with partner, not married | 40 | 24.8 |
Source: authors' field survey, June–December 2021.
Furthermore, it should be noted that the sample characteristics may not be sufficient to represent the population of interest in the study (i.e., the young adult population) and may limit the generalizability of the findings. However, using the study sample may still be relevant in investigations in a theory-testing stage (Ashraf – Merunka 2017), similar to the nature of the current study.
3.3 Data analysis
Partial least squares structural equation modeling (PLS-SEM) was employed to assess the variable relationships specified in this study's research model. PLS-SEM has demonstrated robust explorative and predictive capacity for structural models with low sample sizes and non-normal data (Hair Jr et al. 2017). Therefore, given the sample size, data characteristics, and nature of the current study, PLS-SEM is the most suitable for data analysis. The procedure explicitly followed the guidelines of Hair Jr et al. (2017), developed for measurement and structural model assessment.
4 Results
4.1 Common method bias assessment
Podsakoff et al. (2003) stress the urgent need to pay attention to method biases in behavioral studies, especially when predictor and criterion variables are derived from the same source, sample, and other context-specific influences surrounding the measures used in the research. The authors assert that method biases give rise to measurement errors, affecting the validity of inference regarding parameter relationships. Harman's single-factor test was performed to diagnose this issue in the study. The result shows that the first factor extracted has only a 17.29% cumulative variance, lower than the normal 50% threshold value (Leong et al. 2021). This suggests that common method bias is not a serious concern in the current study. Meanwhile, procedural remedies such as anonymizing responses and assuring the clarity of question items were carried out to keep common method bias at a minimum (Kock et al. 2021).
4.2 Measurement model assessment
Reliability and validity tests were carried out to assess the measurement model. Measurement items that were not loading sufficiently (
A summary of the results of the construct reliability and validity assessments
| Construct | English Translation | Loadings | CA | CR | AVE |
| Intention to adopt a healthy diet (INT) | 0.556 | 0.9032 | 0.7019 | ||
| INT1 | I intend to consume healthy foods regularly. | 0.850 | |||
| INT2 | I expect to eat healthy foods in future. | 0.872 | |||
| INT3 | I am willing to consume healthy foods if they are available. | d | |||
| INT4 | I plan to eat healthy foods in future. | 0.914 | |||
| Food Choice Motives | |||||
| Please indicate the importance of the following statements toward adopting a healthy diet or eating healthy food. | |||||
| Health (HLT) | 0.839 | 0.883 | 0.603 | ||
| HLT1 | Contains a lot of vitamins and minerals | d | |||
| HLT2 | Is nutritious | 0.787 | |||
| HLT3 | Is high in protein | d | |||
| HLT4 | Is good for my skin, teeth, hair, nails, etc. | 0.702 | |||
| HLT5 | Is high in fibre and roughage | 0.729 | |||
| HLT6 | Keeps me healthy | 0.846 | |||
| Mood (MOD) | 0.795 | 0.866 | 0.686 | ||
| MOD1 | Helps me cope with stress | d | |||
| MOD2 | Makes me feel good | d | |||
| MOD3 | Cheers me up | 0.884 | |||
| MOD4 | Keeps me awake/alert | d | |||
| MOD5 | Helps me relax | 0.881 | |||
| MOD6 | Helps me to cope with life | 0.707 | |||
| Convenience (CONV) | 0.702 | 0.868 | 0.767 | ||
| CONV1 | Is easy to prepare | d | |||
| CONV2 | Can be cooked very simply | d | |||
| CONV3 | Takes no time to prepare | d | |||
| CONV4 | Can be bought in shops close to where I live or work | 0.836 | |||
| CONV5 | Is easily available in shops and supermarkets | 0.913 | |||
| Sensory Appeal (SENS) | 0.702 | 0.823 | 0.610 | ||
| SENS1 | Smells nice | 0.780 | |||
| SENS2 | Looks nice | d | |||
| SENS3 | Has a pleasant texture | 0.700 | |||
| SENS4 | Tastes good | 0.856 | |||
| Natural Content (NCON) | 0.870 | 0.919 | 0.791 | ||
| NCON1 | Contains no additives | 0.879 | |||
| NCON2 | Contains natural ingredients | 0.895 | |||
| NCON3 | Contains no artificial ingredients | 0.894 | |||
| Price (PRICE) | 1.000 | 1.000 | 1.000 | ||
| PRICE1 | Is not expensive | 1 | |||
| PRICE2 | Is cheap | d | |||
| PRICE3 | Is good value for money | d | |||
| Weight Control (WCONT) | 0.876 | 0.918 | 0.790 | ||
| WCONT1 | Is low in calories | 0.896 | |||
| WCONT2 | Helps me control my weight | 0.912 | |||
| WCONT3 | Is low in fat | 0.857 | |||
| Familiarity (FAM) | 0.472 | 0.787 | 0.650 | ||
| FAM1 | Is what I usually eat | d | |||
| FAM2 | Is familiar | 0.874 | |||
| FAM3 | Is similar to the food I ate when I was a child | 0.733 | |||
| Ethical concern (ETIC) | 0.598 | 0.822 | 0.700 | ||
| ETIC1 | Comes from countries I approve of politically | 0.737 | |||
| ETIC2 | Has the country of origin clearly marked | d | |||
| ETIC3 | Is packaged in an environmentally friendly way | 0.925 | |||
Note: d – dropped because factor loading below 0.7; CA – Cronbach's alpha; CR – composite reliability; AVE – average variance extracted.
Source: authors' processing from SMART-PLS 3 Version.
Similarly, the measurement model exhibits sufficient discriminant validity, satisfying the conditions of the Fornell–Larcker criterion and heterotrait-monotrait ratio correlations (HTMT) criterion. As shown in Table 3, the square root AVE (in bold) is greater than the values of inter-construct correlations (Fornell – Larcker 1981). Meanwhile, HTMT values (in italics) are less than 0.80–0.90 (Hair Jr et al. 2017), dismissing potential discriminant validity issues. Given that all reliability and validity requisites were satisfied, the structural model assessment followed.
Results of the discriminant validity assessment using the Fornell–Larcker criterion and HTMT ratios
| CONV | ETIC | FAM | HLT | INT | MOD | NCON | PRICE | SENS | WCONT | |
| CONV | 0.876 | 0.203 | 0.249 | 0.098 | 0.151 | 0.093 | 0.121 | 0.407 | 0.327 | 0.144 |
| ETIC | 0.143 | 0.837 | 0.071 | 0.521 | 0.274 | 0.361 | 0.553 | 0.202 | 0.212 | 0.412 |
| FAM | 0.138 | 0.026 | 0.806 | 0.185 | 0.158 | 0.231 | 0.227 | 0.113 | 0.220 | 0.189 |
| HLT | 0.065 | 0.382 | 0.091 | 0.777 | 0.362 | 0.270 | 0.511 | 0.146 | 0.208 | 0.394 |
| INT | 0.121 | 0.212 | −0.103 | 0.327 | 0.896 | 0.136 | 0.402 | 0.074 | 0.135 | 0.338 |
| MOD | 0.006 | 0.255 | 0.148 | 0.205 | 0.135 | 0.828 | 0.185 | 0.068 | 0.329 | 0.205 |
| NCON | 0.044 | 0.420 | −0.088 | 0.447 | 0.359 | 0.163 | 0.889 | 0.145 | 0.114 | 0.253 |
| PRICE | 0.341 | 0.173 | 0.078 | 0.142 | 0.071 | 0.050 | 0.136 | 1.000 | 0.162 | 0.209 |
| SENS | 0.223 | 0.081 | 0.137 | 0.141 | 0.118 | 0.242 | 0.082 | 0.151 | 0.781 | 0.147 |
| WCONT | 0.115 | 0.287 | 0.050 | 0.343 | 0.326 | 0.188 | 0.240 | 0.192 | 0.113 | 0.889 |
Note: square root of AVE (diagonal in bold), HTMT ratios (in italics).
Source: authors' processing from SMART-PLS 3 Version.
4.3 Structural model assessment and hypotheses testing
In the assessment of the structural model, the coefficient of determination (R2) and the predictive relevance (Q2) scores were evaluated (Table 4). The R2 for healthy diet adoption intentions was 0.232, suggesting that food choice motives (i.e., health, mood, convenience, sensory appeal, natural content, price, weight control, familiarity, and ethical concern) describe 23.2% of the variance intention. Meanwhile, the model demonstrated sufficient predictive relevance as Stone–Geisser's Q2 scores and Q2-Predict scores were greater than 0 (Ahmad et al. 2020; Allah Pitchay et al. 2021; Hair Jr et al. 2017).
A summary of the results of the structural model assessment
| Direct Effects | ß | t-value | P-value | Interval Estimate | Remark | ||
| 2.5% | 97.5% | ||||||
| HLT → INT | 0.156* | 1.923 | 0.055 | −0.01 | 0.31 | H1+ | Not Supported |
| MOD → INT | 0.039 | 0.491 | 0.623 | −0.22 | 0.16 | H2+ | Not Supported |
| CONV→ INT | 0.104 | 1.359 | 0.174 | −0.08 | 0.24 | H3− | Not Supported |
| SENS →INT | 0.048 | 0.472 | 0.637 | −0.21 | 0.20 | H4+ | Not Supported |
| NCON → INT | 0.229*** | 2.691 | 0.007 | −0.07 | 0.40 | H5+ | Supported |
| PRICE → INT | −0.057 | 0.707 | 0.479 | −0.21 | 0.11 | H6− | Not Supported |
| WCONT → INT | 0.217*** | 2.840 | 0.005 | 0.07 | 0.37 | H7+ | Supported |
| FAM → INT | −0.131 | 1.388 | 0.165 | −0.26 | 0.16 | H8− | Not Supported |
| ETIC → INT | −0.023 | 0.310 | 0.757 | −0.17 | 0.12 | H9+ | Not Supported |
| Assessment | INT | ||||||
| R2 | 0.232 | ||||||
| Adjusted R2 | 0.187 | ||||||
| Stone–Geisser's Q2 | 0.150 | ||||||
| Q2-Predict | 0.106 | ||||||
Notes: *** significant at 0.01; ** significant at 0.05; *significant at 0.10.
Source: authors' processing from SMART-PLS 3 Version.
A non-parametric bootstrapping procedure with 5,000 subsamples was performed to test the hypotheses in the study. The results reveal that at a 5% significance level, only the motives relating to natural content (NCON; β = 0.229, t = 2.691, P > 0.01) and weight control (WCONT; β = 0.217, t = 2.840, P > 0.01) have a positive and significant influence on intention (INT) to adopt a healthy diet. Hence, H5 and H7 are accepted. Moreover, there was no sufficient evidence to confirm the relationship between the motives of health (HLT), mood (MOD), convenience (CONV), sensory appeal (SENS), price (PRICE), familiarity (FAM), and ethical concern (ETIC) in shaping healthy diet adoption intentions (INT). Therefore, H1, H2, H3, H4, H6, H8, and H9 are not supported.
5 Discussion
The study adopts the concept of nine food choice motivations by Steptoe et al. (1995) to explain intentions to adopt a healthy diet (i.e., eating healthy food) among adult consumers in the Czech Republic. The results reveal that natural content has a positive and significant influence on adoption intentions toward a healthy diet. This corroborates previous claims suggesting that concerns about foods' natural content induce the selection of relatively healthy food (Chen 2007; Phan – Chambers 2016). Its relevance may be attributed to consumers' perception that healthy food intake allows them to benefit from natural contents and associated health-promoting benefits (Korzen et al. 2011; Saher 2006). Moreover, as access to information is now significantly improved, consumers have become more conscious about the food they choose to eat, especially regarding food nutrition and safety (Gagic et al. 2014).
Meanwhile, weight control's positive and significant effect on healthy dietary adoption intentions confirms claims from previous studies (Glanz et al. 1998; Pearcey – Zhan 2018; Vainio et al. 2016). Evidence shows that individuals who desire to lose weight demonstrate high self-monitoring behaviors (Nothwehr – Peterson 2005). They are also likely to consume more fruits, vegetables, and low-fat food (Lowry et al. 2000), and adhere to weight loss diets (Cruwys et al. 2020; Forestell 2018). Consumers may have also placed high importance on weight management and desired to improve diet quality, especially as physical activity was significantly reduced during the COVID-19 pandemic (Ingram et al. 2020; Marty et al. 2021). As most physical classes were discontinued at the height of the pandemic, students at home could better adhere to healthy dietary patterns and weight loss endeavors.
Surprisingly, health motives did not significantly influence healthy dietary adoption intentions. This finding contends several studies asserting that health reasons drive healthy food intake (Glanz et al. 1998; Pearcey – Zhan 2018; Piggford et al. 2008; Sun 2008; Wardle et al. 2004; Žeželj et al. 2012). Prior studies highlight that younger individuals take health-related concerns lightly (Ahmad et al. 2020; Honkanen – Frewer 2009). Hence, following this contention, the study sample may have perceived that they were still healthy. Thus, proneness to obesity and other diseases could be dismissed, and there was no need for them to adhere to a strictly healthy diet at once.
Furthermore, the postulated relationships of mood, sensory appeal, convenience, price, familiarity, and ethical concern motives toward healthy dietary adoption intentions were not found to be significant in the study. As for mood, although prior evidence shows that the intake of healthy foods is a good mood booster (Arab et al. 2019), its effects may only be felt in the long term (AlAmmar et al. 2020). The study's sample may have perceived this similarly; thus, their efforts to alter mood favored short-term solutions such as consuming sugary and fatty foods (Macht 2008). Meanwhile, the sensory appeal of healthy food (i.e., fruit and vegetables) is not commonly the top priority and thus may not always correspond to consumption (Appleton et al. 2019; Arce et al. 2021). Agovi et al. (2022) argue that some vegetables exhibit negative sensory properties (e.g., bitterness), which are detrimental to their acceptability among consumers.
Prior studies report a negative relationship between convenience and healthy dietary behavior (Michaelidou et al. 2012; Piggford et al. 2008; Verstraeten et al. 2014). As fast-paced lifestyles have become today's norm, more people are consuming fast and convenient food (Jacob et al. 2020; Liu – Chen 2021; Popkin et al. 2012). However, the result of the current study suggests differently. Convenience is not perceived as a negating factor to eating healthy food. For contextual reasons, the study sample may have found healthy food accessible and available in the country. Additionally, circumstances induced by the pandemic potentially gave consumers time to prepare healthy meals. Furthermore, high food prices may be perceived as detrimental to healthy food consumption decisions, but the study's results reveal that they are of lesser importance to healthy dieting intentions. The sample may still be willing to pay premium prices for healthy food (de-Magistris – Gracia 2016), as the expected benefits outweigh the cost.
Meal options associated with healthy diets may not be as familiar as other alternatives highly promoted in today's increasingly obesogenic food environment. Despite this, the study dismisses their negative effect on consumers' desire to adopt a healthy diet plausibly due to their openness to consume novel food (Pearcey – Zhan 2018). Young adults are more open to new experiences and consume high servings of vegetables (Conner et al. 2017; Rodrigues et al. 2019). Finally, ethical concerns surrounding healthy food (e.g., fruit/vegetables) may have been unclear to our sample, thereby dismissing their effect on intentions to adopt a healthy diet. The stringent regulations and the upholding of high standards of food product safety and quality within European member states may have imbued trust among EU consumers and correspondingly reduced ethical concerns.
6 Conclusion
6.1 Theoretical contribution
The study offers the literature insights on the food choice motives (Steptoe et al. 1995) influencing healthy dietary adoption intentions. From a new contextual perspective considering Czech university students, the results reveal that food choice motives can explain healthy dietary adoption intentions. Notably, only the natural content and weight control motives demonstrated a positive and significant influence on healthy dietary adoption intentions. Health status perception, preference for mood-boosting solutions, sensory acceptability, access to or availability of healthy food, willingness to pay premium prices for healthy food, openness to consume healthy food, vague understanding of food-related ethical concerns, and the COVID-19 pandemic may have induced influences around the lesser importance of other food choice motivations. Although more validation studies are required to support the claims robustly, the current study offers initial evidence that the importance of food motives in explaining food selection and consumption-related behavior varies contextually. Finally, the study provides a relevant and timely understanding of Czech university students' psychology and behavior regarding healthy eating, which to date remains limited.
6.2 Practical contribution
The study offers important inputs for crafting health-promoting strategies and interventions to curb the immense obesity figures in the Czech Republic. Based on the study results and the confirmation by further studies, it is crucial to highlight food products' natural content and corresponding health benefits. Goal-activation pursuits for weight loss (e.g., goal priming) can also be followed to encourage people to eat healthy. Most importantly, the government can support these initiatives by developing policies that require or incentivize food businesses' marketing and promote healthy food products. Furthermore, healthcare and educational institutions can further strengthen health education campaigns so that it reinforces peoples' motivation to adopt a healthy diet and overall healthy lifestyle.
6.3 Limitations and future research directions
This study is not without limitations. First, caution is advised in generalizing the results due to the characteristics of the study sample, composed mainly of university students in the Czech Republic. Although obesity is prevalent in this demographic group, health knowledge and perceptions may vary in other generational cohorts (e.g., Gen X and Boomers), potentially engendering biases on perceptions, motivations, and healthy dietary adoption intentions. Future studies can examine intergroup differences in the impact mechanisms of food choice motives on healthy diet adoption. Moreover, future studies should validate the research model and utilize a more representative sample of the targeted population. Other variables such as age, gender, body mass index, income, education, the size of human settlements, country, and culture should also be scrutinized. Second, the study's use of the term “healthy” diet/food may have had different connotations for our respondents (e.g., intake of low-calorie food, intake of vegetables/fruits, minimal intake of sugary food, etc.). Future studies can resolve this issue by explicitly defining what is healthy and what is not. Lastly, the study has only captured behavioral intentions and not actual behavior. Although behavioral intention and actual behavior are closely related, consumer behavior scholars argue that gauging actual behavior is more appropriate. Therefore, future studies can assess actual healthy adoption among consumers and its antecedents, especially following the COVID-19 pandemic.
Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.
Acknowledgment
The authors are grateful to the project OP RDE Junior Grants of Tomas Bata University in Zlín, Reg. No. CZ.02.2.69/0.0/0.0/19_073/0016941 for financial support to carry out this research.
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