Food Preparation Videos: Villains or Heroes?
Investigating Effects of Unhealthy versus Healthy Food Preparation Videos.
Emma Bloemhof - 11249730 Master’s Thesis
Graduate School of Communication
Master’s programme Communication Science Supervisor: Bas van den Putte
Abstract
Food cues, like the sight or smell of food, can have impactful influences on people’s eating behavior because they can induce both psychological and physiological responses. Even though a lot of research has been conducted on food cues within the context of advertisement, research on social media food cues remains underexposed. Social media are flooded with videos glorifying the preparation of mostly energy-dense foods. The effects of these food preparation videos (FPVs) have not been explored yet. An online experiment (N = 225) resulted in the surprising finding that exposure to a healthy compared to an unhealthy FPV led to a more positive attitude towards eating and a higher desire to eat the cued food. It was supported that attitude mediated the relationship between exposure to an FPV and desire. Additionally, desire significantly predicted intention. However, it was also expected that nutrition information would influence the relationship between exposure and attitude but this could not be concluded. The results have implications for theory, (non) governmental and public health organizations.
Food Preparation Videos: Villains or Heroes?
Investigating the Effects of Unhealthy versus Healthy Food Preparation Videos. Obesity and being overweight are a problem in the Dutch society, as almost fifty percent of the population is overweight and this number has increased significantly during the last decade (CBS, 2017). Obesity and being overweight correspond to an increased risk of chronic diseases such as cardiovascular diseases, diabetes and some forms of cancer according to the World Health Organization (WHO, 2017). The current obesogenic
environment is often blamed for the high prevalence of obesity. There is a high omnipresence and easy accessibility of palatable energy-dense foods (Stok et al., 2015). People are
continuously exposed to properties of food like the sight or smell of palatable food. These so-called food cues can lead to a desire to eat and an increase in caloric-intake (e.g. Cornell, Rodin & Weingarten, 1989; Fedoroff, Polivy & Herman, 1997; Larsen, Hermans & Engels, 2012; Nederkoorn, Smulders & Jansen, 2000). For example, food advertisements (Emond, Lansigan, Ramanujam, Gilbert-Diamond, 2016; Halford et al., 2008) and food-related television shows (Bodenlos & Wormuth, 2013) have been linked to the consumption of unhealthy foods and weight gain. A potential, yet uninvestigated, source of obesity in our obesogenic environment is the trend of food preparation videos (FPVs) on social media.
Our society has become intrigued with watching FPVs on social media, such as Instagram and Facebook (Xposé, 2018). An FPV is a short video of a meal being prepared, fixated on a single spot and played back at a quicker pace than recorded (fast-motion), backed up by bright music (Green Buzz Agency, 2017). FPVs make cooking and eating seem
exciting, easy and almost sensual. According to Boland (2017) engagement scores on Facebook (i.e. likes, shares and comments) of the main publisher of FPVs, Buzzfeed Tasty (Tasty), are as high as 85 million a month. This is much higher than for example most news videos (Boland, 2017). Over the past years, FPVs have popped up all over the web,
continuously exposing people to the sight of energy-dense, alluring food (Slisz, 2016). This could have impactful effects on people’s eating behavior, potentially making FPVs a major threat for public health.
Prior research has focused almost exclusively on food advertising and on
environmental cues, showing mainly the influence of unhealthy food cues on eating behavior. On the other hand, less focus has been put on the difference between unhealthy and healthy food cues. This is an important distinction because according to Raghunathan, Naylor and Hoyer (2006) unhealthy compared to healthy foods are perceived differently. Unhealthy foods are intuitively perceived as tastier than healthy foods. Because past research showed that taste is a key predictor of food consumption (Glanz, Basil, Maibach, Goldberg & Snyder, 1998) it is likely that unhealthy FPVs have a different effect on eating than healthy FPVs.
Additionally, unhealthy food is perceived as more enjoyable than healthy food (Raghunathan et al., 2006). The difference in enjoyment is expected to cause differences in attitude towards the cued food. The current study aims to fill a gap in literature by comparing the effects of unhealthy versus healthy FPVs.
Even though FPVs have an enormous reach, they are often published without discussing health consequences regarding unhealthy eating. One potential strategy to
influence people’s decision-making regarding food is to provide nutrition information on how nutritious or calorie-dense the prepared meal is. According to Benelam (2009), presentation of nutrition information for unhealthy food can lead to a decrease in the perceived pleasure of eating. This could impact the effects of unhealthy versus healthy FPVs, which is why the current study investigates nutrition information as a potential moderator of the effects.
For the current study, the research question addressed is: To what extent do unhealthy compared to healthy FPVs have an effect on attitude towards eating the cued food, desire and intention to eat the cued food; and do these effects differ when nutrition information is present
versus absent? The outcomes of the research will contribute to scientific knowledge about unhealthy and healthy FPVs and the presentation of nutrition information. In addition, the outcomes will provide implications for government policy regarding obesity and overweight prevention and intervention. With the current knowledge about the influence of food
advertising on eating, the government has already applied prevention policies, reducing unhealthy marketing messages (Hawkes, 2007). For example, in Amsterdam recently a new law was applied, prohibiting unhealthy food advertisements in the metro targeted at children (NOS, 2017). If the current study shows that unhealthy FPVs have more negative effects than healthy FPVs, recommendations can be given for policies regarding the distribution of FPVs. For example, governments could limit the distribution of unhealthy FPVs or stimulate the distribution of healthy FPVs. Additionally the outcomes regarding nutrition information could provide implications on whether to present nutrition information with FPVs or not.
Theoretical Background Exposure to FPV & Desire
People are sensitive to food cues, like the sight or smell of food (Coelho, Jansen, Roefs & Nederkoorn, 2009). A model explaining why is the cue-reactivity model by Jansen (1998). The cue-reactivity model poses that when food is consumed, a metabolic response is induced (Coelho et al., 2009). This response becomes associated with food-related cues like the sight or smell of food (Jansen, 1998). These cues act as stimuli and lead to different responses, both psychological (e.g. cravings or desire to eat) and physiological (e.g. increased salivation or insulin release). These responses can arise even when actual food is not present. For example, there is an ever-growing body of food photography on social media, often of highly palatable and mainly unhealthy dishes (Spence, Okajima, Cheok, Petit & Michel, 2016). Spence et al. (2016) found that the mere sight of these online images can lead to an increased desire to eat. Thus, the principle that people are sensitive to food seems to transfer
to the online context. A large number of studies has shown that desire, in the current study self-defined as an urge to eat the cued food, was induced after being exposed to food cues (Bodenlos & Wormuth, 2013; Boyland & Halford, 2013; Coelho et al., 2009; Fedoroff, Polivy & Herman, 2003). A difference is expected between unhealthy and healthy food cues because of the perceived palatability. Palatability is the pleasurable evaluation of sensory factors like sight, taste and smell of food (Yeomans, 1998). The palatability of food can increase the release of dopamine, a neurotransmitter associated with enjoyment and reward, leading to actual desire to eat the food (Wansink, 2004). Several studies have shown that unhealthy food is generally seen as more palatable than healthy food (Stubbs & Whybrow, 2004; Talukdar & Lindsey, 2013). This suggests that more dopamine is released when exposed to unhealthy compared to healthy food. Because more dopamine is released, the desire to eat the cued food is expected to be higher for unhealthy FPVs than for healthy FPVs.
The difference between effects of unhealthy and healthy food cues on desire has not been widely studied. However, Page et al. (2011) investigated brain activity as a response to high and low- calorie food cues. They showed a series of 168 pictures (56 high-calorie, 56 calorie and 56 non-food) to the participants and found that high-calorie compared to low-calorie food cues led to a greater desire to eat the food. Additionally, a study focusing on the effects of unhealthy food cues has shown that an unhealthy food cue compared to a control (non-food) cue led to a higher desire to eat the particular food (Fedoroff et al., 1997). However, it must be noted that this was the case for restrained eaters. Altogether, previous research does seem to support the idea that an unhealthy food cue leads to a higher desire than a healthy food cue. Therefore, the following was hypothesized (see Figure 1):
H1a: Exposure to an unhealthy FPV leads to a higher desire to eat the cued food than exposure to a healthy FPV.
Exposure to FPV & Attitude
The fact that unhealthy and healthy foods are perceived differently is expected to have an effect on attitude. Attitude is the evaluation of a behavior (Ajzen, 1991), in the current study the attitude towards eating the cued food. According to the ‘unhealthy = tasty intuition’ (UTI: Raghunathan, Naylor and Hoyer, 2006) people intuitively connect unhealthy food with a good taste and perceive eating unhealthy food as enjoyable. On the contrary, healthy food is seen as tasteless and boring. Research showed that enjoyment positively influences attitude (Childers, Carr, Peck & Carson, 2001). Moreover, several studies showed that (perceived) taste of food is a major predictor of attitude towards eating the food (Brug, Lechner & De Vries, 1995; Koivisto & Sjöden, 1996; Roininen, Lähteenmäki & Tuorila 1999; Roininen & Tuorila, 1999). Because the UTI states that unhealthy food is intuitively perceived as tastier and more enjoyable than healthy food, it is expected that this will lead to a more positive attitude towards eating the cued food.
Previous research on the impact of food cues on attitude towards eating the cued food showed that an unhealthy food cue compared to a control cue positively influenced attitude towards the cued food (Fedoroff et al., 1997). Additionally, research in the context of advertising revealed that exposure to junk food advertisements led to more positive attitudes towards the cued food than exposure to healthy food advertisements (Dixon, Scully,
Wakefield, White & Crawford, 2007). In sum, theory and practice seem to support the idea that unhealthy compared to healthy food cues lead to a more positive attitude towards eating the cued food. Thus, the following was hypothesized (see Figure 1):
H1b: Exposure to an unhealthy FPV leads to a more positive attitude towards eating the cued food than exposure to a healthy FPV.
Attitude as a Mediator of the Exposure Effects on Desire
Exposure to an unhealthy compared to a healthy FPV is expected to differently affect desire and attitude. However, it is unknown through what mechanism this happens. Here, it is proposed that exposure to an unhealthy compared to a healthy FPV affects desire through attitude. Specifically, a more positive attitude as a result of exposure to an unhealthy
compared to a healthy FPV will lead to a higher desire. A model explaining the relationship between attitude and desire is the theory of self-regulation (TSR; Bagozzi, 1992). According to the TSR, desire is strongly predicted by attitude. Therefore, it is expected that the effect of exposure to an unhealthy compared to a healthy FPV on desire can be explained by a
difference in attitude.
No research has been conducted on this relationship within the context of food cues. However, research investigating the relationship in the context of food choice has shown that attitude explained as much as 61% of variance in desire to eat the food (Sparks, Hedderly & Shepherd, 1992). Also, Norman and Smith (1995) investigated the relationship in the context of dieting and found that attitude strongly correlated with desire. Additionally, research investigating components of playing a virtual golf game showed that attitudes strongly predicted desire to play the game (Han, Baek, Lee & Huh, 2014). Building on theory and research, the current study investigates whether a more positive attitude towards eating the cued food drives the effects of exposure to an unhealthy compared to a healthy FPV on desire. Thus, the following was hypothesized (see Figure 1):
H1c: A more positive attitude towards eating the cued food leads to a higher desire to eat the cued food.
H2: The effect of exposure to an unhealthy compared to a healthy FPV on desire to eat the cued food is mediated by attitude towards eating the cued food.
Nutrition Information Moderation of the Exposure to FPV Effects on Attitude
The previous argumentation showed the impact of exposure to an unhealthy compared to a healthy FPV on attitude. This relationship is arguably impacted by nutrition information. Nutrition information can be presented in several ways. Nan, Briones, Shen, Jiang and Zhang (2013) distinguished three different types of nutrition claims. First, ‘healthy claims’ generally state that a product is healthy. Second, ‘nutrient content claims’ describe nutrient components (e.g., low in fat and calories). Third, ‘general nutrition claims’ imply healthiness by using general words (e.g., wholesome and nutritious). According to Liu, Roberto, Liu and Brownell (2012), the most effective way of presenting nutrition information is a ‘traffic light’ labeling system (Liu et al., 2012). This system uses red, green and yellow traffic light symbols on packages to indicate the fat, saturated fat, sugar and salt levels in the product (i.e., nutrient content claim). Because it was proven most effective, the current study focuses on this type of nutrition information.
Currently, FPVs are not accompanied by nutrition information, even though they make excessive use of unhealthy ingredients such as butter, cheese and sauces to make it look exciting and tasty. This could make viewers unaware of how unhealthy or healthy the meal actually is. In the case of unhealthy FPVs this could be worrisome, because people tend to over consume unhealthy foods due to this unawareness (Raghunathan et al., 2006). A theory explaining why nutrition information possibly has an impact on the effects of exposure to an unhealthy compared to a healthy FPV on attitude is the expectancy disconfirmation theory (EDT; Van Raaij, 1991). According to the EDT, consumers form initial expectations
regarding the attributes of a product. In the case of FPVs, the attribute is the nutritional value of the meal. When nutrition information is presented and disconfirms the expectations
regarding the nutritional value, attribute dissatisfaction takes place, which negatively impacts attitude (Burton, Howlett & Tangari, 2009). On the other hand, when the information does
meet the expectations or is better than expected, a more positive attitude results. A study by Burton, Creyer, Kees and Huggins (2006) showed that consumers are not able to estimate nutritional value without menu labeling. Additionally, their study revealed that people underestimate calories, fat and saturated fat levels of unhealthy items (Burton et al., 2006). Therefore, it is likely that presenting of nutrition information in unhealthy FPVs negatively exceeds initial expectations, causing a more negative attitude. On the other hand, it is likely that a healthy FPV presents more favorable information than expected, leading to a more positive attitude. However, the EDT contradicts the tendencies of the UTI, in which the authors argued that when nutrition information is given, unhealthy meals are perceived even tastier (Raghunathan et al., 2006).
In practice, however, research in the context of menu labeling in restaurants seems to support the EDT. With respect to healthy food, several studies on the presentation of nutrition information have shown that favorable nutrition information leads to more favorable attitudes towards the food (Burton et al., 2009; Kozup, Creyer & Burton, 2003). Research by Burton et al. (2006) showed that the presence versus absence of nutrition information for a healthy meal increased attitude towards the meal. The opposite was found for unhealthy meals, the attitude decreased when nutrition information was presented.
While theory concerning nutrition information is contradicting, previous research seems to support the EDT rather than the UTI. Therefore, it may be carefully suggested that nutrition information influences the effect of exposure to an unhealthy compared to a healthy FPV on attitude. The presence of nutrition information for an unhealthy (healthy) FPV will negatively (positively) influence attitude. The following was hypothesized with regard to the moderating role of nutrition information (see Figure 1):
H3: The effect of exposure to an unhealthy compared to a healthy FPV on attitude is influenced by the presence or absence of nutrition information, in that the effects are weaker when nutrition information is present versus absent.
Desire & Intention
The main focus of the study is to see whether exposure to an unhealthy compared to a healthy FPV causes different eating behavior. An important predictor of behavior is intention, or the motivation to act (Ajzen, 1991). Intentions are formed based on people’s desire and subjective norm towards performing the behavior (Bagozzi, 1992). Subjective norm refers to the perceived social pressure to conduct a specific behavior or refrain from it (Ajzen, 1991). Even though the TSR poses that subjective norm predicts intention, Leone, Perugini and Ercolani (1999) found that subjective norm was only marginally significant. They tested the model with six data sets and found that desire was a significant predictor of intention. Additionally, Sheeran, Norman and Orbell (1999) found that intentions based on subjective norm are weaker predictors of behavior than those based on attitude. Therefore, subjective norm was used as a control variable in the current study but not included in the conceptual model. Because attitude is expected to directly have an impact on desire, and research has shown that desire strongly correlates with intention, it is expected that higher desire to eat the cued food should lead to a higher intention to eat the cued food.
Previous research in the context of dieting, has shown that variance in intention was explained by desire (Bagozzi & Kimmel, 1995). In the context of work, Fishbein and Stasson (1990) found that desire to attend a training was the strongest predictor of actual presence at the training. Theory and practice seem to support the idea that desire predicts intention. Therefore the following was hypothesized (see Figure 1):
H4: A higher desire to eat the cued food leads to a higher intention to eat the cued food.
Figure 1. Conceptual model of the effects of exposure to an unhealthy compared to a healthy
FPV on attitude, desire and intention, moderated by nutrition information.
Method Participants
A total of 314 participants participated in the experiment. They were recruited through non-probability sampling via the personal Facebook, LinkedIn and Snapchat network of the researcher. Additionally, the online experiment was distributed in specific groups, such as university groups and respondent groups. Sharing the survey with family and friends was encouraged. From this sample, those who did not agree to the informed consent, did not finish the experiment, failed the manipulation check, did not stay on the FPV page for at least 1 minute, were younger than 18 or were vegetarian, were excluded from further analysis (n = 89). An analysis with regard to the scores on the dependent variables was conducted to check for individuals that scored well above or below the majority of cases. Three cases altered the mean for attitude. These cases did not have an outlier score on desire or intention and
exclusion did not alter the significance of the results for attitude. For these reasons, the participants were not excluded from the research. In total, the sample consisted of 225 adults ranging between the age of 18 and 78 years old (M = 33.99, SD = 15.49, 57.8% female). Most of the participants were Dutch (85.0%). The majority (60.9%) of participants finished or currently was in university, followed by university of applied sciences (26.2%). The number of participants was slightly higher than the intended sample of 200.
Stimulus Materials
Exposure to an unhealthy or healthy FPV was manipulated by creating two different versions of an FPV. The FPVs showed the preparation of either a healthy or an unhealthy meal (low-calorie courgetti with homemade pesto or calorie-dense pasta pesto). The
manipulation was the healthiness of the recipe; the unhealthy recipe contained more calories, sugar and fat than the healthy FPV. The difference in healthy/unhealthy recipes was based on the fact that according to the World Health Organization, foods high in fat, sugar and energy can lead to obesity (WHO, 2017). The unhealthy recipe had 71.1 grams of fat, 7.4 grams of sugar and 1192 calories per serving (see Appendix Figure A2). In comparison, the healthy recipe had 32 grams of fat, 2 grams of sugar and 502 calories per serving (see Appendix Figure A2). The videos were shot from a top-view in the same kitchen with the same materials. In order to keep the videos as similar as possible, the recipes were prepared with almost healthy and unhealthy variants on ingredients. For example, the unhealthy FPV contained pre-fabricated pesto, a lot of cheese and a lot of oil whereas the healthy FPV contained homemade low-calorie pesto. Also, the length, music and font within the video were kept the same.
Additionally, nutrition information was manipulated by duplicating both videos and placing a traffic light nutrition label of the healthy and the unhealthy recipe on top, based on research by Liu et al. (2012) (see Appendix Figure A2). The nutritional values for each meal were calculated using an online recipe nutrition calculator from MyFitnessPal (2018).
Figure 2. Screenshot of the unhealthy FPV without nutrition information
Figure 4. Screenshot of the healthy FPV without nutrition information
Pretest and manipulation check
A pretest was conducted to assess whether the unhealthy and healthy FPV were seen as unhealthy or healthy and whether the unhealthy versus healthy nutrition information was seen as unhealthy or healthy. Respondents had to look at both FPVs and both nutrition information labels. Then they had to indicate for both videos and nutrition information labels whether they thought it was (A) healthy or (B) unhealthy. The participants ranged between the age of 22 and 29 (M = 24.8, SD = 2.20, N = 10). Of the participants, the majority was female (60.0%). All participants (100%) considered the healthy FPV to be healthy and almost all (90.0%) considered the unhealthy FPV to be unhealthy. Also, all participants (100%) saw the unhealthy nutrition information as unhealthy whereas the healthy nutrition information was seen as healthy (90.0%). The manipulations thus were successful.
Procedure
Participants were randomly assigned to one of the conditions after agreeing to the
informed consent, explaining the subject, goal, procedure and anonymity of this study. First, they were asked general questions regarding demographics: age, education, gender and vegetarian status (see Appendix B). Additionally, a control question regarding hunger was asked (see Appendix B). Question and answer orders for the dependent variables were randomized. Then, they were exposed to the FPV as if they would see it on a Facebook wall (see Figure 2 through 5). Next, the participants were asked questions regarding the
manipulations: desire to eat the cued food, attitude towards eating the cued food, intention to eat the cued food and subjective norm towards eating the cued food (see Appendix B). After filling out the questionnaire, the participants were debriefed and thanked for participating. Additionally they got the opportunity to ask questions through e-mail and were informed of the possibility to withdraw their response until seven days after filling out the questionnaire.
Design
The experiment used a 2 by 2 between-subjects factorial design with exposure to FPV as the first independent variable (2 levels, healthy and unhealthy) and nutrition information as the second independent variable (2 levels, present and absent) (see Table 1). This left four conditions (1) Unhealthy FPV without nutrition information (see Figure 2), (2) Unhealthy FPV with nutrition information (see Figure 3), (3) Healthy FPV without nutrition information (see Figure 4) and (4) Healthy FPV with nutrition information (see Figure 5).
Table 1
2x2 Between-subjects factorial design as employed in the current study
Exposure to FPV Nutrition information Unhealthy Healthy
Absent Group 1 Group 3
Present Group 2 Group 4
Measures
The dependent measures in the current study were observed on 7-point Likert scales. After watching the FPV, four different meals were presented with a title and a picture each followed by three measures (desire to eat the cued food, attitude towards eating the cued food, intention to eat the cued food). The pictures consisted of (1) The healthy FPV meal (courgetti with homemade pesto), (2) The unhealthy FPV meal (creamy pasta pesto with bacon), (3) An unhealthy meal (hamburger) and (4) A healthy meal (salad) (see Appendix Figure A1). Picture 3 and 4 were included to make it possible to conduct an additional analysis to establish whether exposure to FPV had an effect on attitude and desire to eat healthy or unhealthy in general or towards the cued food. All measures as presented in the questionnaire can be found in Appendix B.
Attitude towards eating the cued food. Attitude towards eating the cued food was measured by four statements on a 7-point bipolar scale, adapted from research by Olsen, Sijtsema & Hall (2010): “If I would eat this meal for dinner, I would feel:” ranging from 1 to 7 (unsatisfied/satisfied, unpleasant/pleasant, dull/ exciting, and very unhealthy/very healthy). Attitude towards food behavior is often measured through these items, because they cover positive feelings toward food (Shepherd & Raats, 1996; Tuu, Olsen, Thao, & Anh, 2008). The reliability of the scale was good for both cued foods: pasta (Cronbach’s = .78, M = 4.55, SD = 1.21) and courgetti (Cronbach’s = .85, M = 5.23, SD = 1.21). Attitude towards eating the cued food, attitude towards eating unhealthy and attitude towards eating healthy were
computed for each condition.
Desire to eat the cued food. Desire to eat the cued food was measured by three items adapted from research by Perugini and Bagozzi (2001). The items were: (1) “I desire to eat this meal over the next few days”, followed by a 7-point scale (false/true); (2) “My desire for eating this meal in the next few days can be described as…”, where the participants selected one of the following: (a) No desire, (b) Very weak desire, (c) Weak desire, (d) Moderate
desire, (e) Strong desire, and (f) Very strong desire; and (3) “I want to eat this meal over the
next few days”, followed by a 7-point scale (false/true). The reliability of the scale was good for both cued foods: pasta (Cronbach’s = .93, M = 3.50, SD = 1.48) and courgetti
(Cronbach’s = .94, M = 3.95, SD = 1.55). Desire to eat the cued food, desire to eat unhealthy and desire to eat healthy were computed for each condition.
Intention to eat the cued food. Intention to eat the cued food was measured by three items adapted from research by Perugini and Bagozzi (2001). The items were: (1) “I am planning to eat this meal over the next few days”, on a 7-point scale going from ‘very
unlikely’ to ‘very likely’; (2) “I intend to eat this meal over the next few days”, measured on a 7-point scale going from ‘completely disagree’ to ‘completely agree’; and (3) “I will eat this
meal over the next few days”, measured on a 7-point scale going from ‘completely disagree’ to ‘completely agree’. The reliability of the scale was good for both cued foods: pasta
(Cronbach’s = .96, M = 3.03, SD = 1.55) and courgetti (Cronbach’s = .97, M = 3.43, SD = 1.65). Intention to eat the cued food was computed for each condition.
Control variables. Five control variables were measured. Specifically, participants’ hunger on the moment of participation was taken into account. Hunger is the physiological response to feel the need to eat food (Cornell, Rodin & Weingarten, 1988). It could have an impact on the desire whether people feel hungry or satiated. Therefore, a Visual Analogue Scale (VAS) was used to determine hunger by rating the variable on a scale ranging from 0 to 10 (not hungry at all/extremely hungry) (Bodenlos & Wormuth, 2013). The overall mean of participants’ hunger scores was 4.10 (SD = 2.39). Furthermore, subjective norm was
measured by including both significant others and people respondents eat with as reference group (Ajzen, 1991) by using two statements adapted from research by Olsen et al. (2010): “People who are important to me would appreciate it if I eat this meal”, “People with whom I eat with regularly would appreciate it if I eat this meal”. These items were based on a 7-point scale ranging from 1 to 7 (Completely disagree/Completely agree). The reliability of the scale was good for both cued foods: pasta (Cronbach’s = .97, M = 3.71, SD = 1.67) and courgetti (Cronbach’s = .94, M = 4.24, SD = 1.62). Subjective norm towards eating the cued food was computed for each condition. Additionally, education was included because people with lower levels of education may eat more unhealthy, high-caloric foods than those with higher education levels (Public Library of Science, 2013). Also, age was assessed, because
nutritional needs change as people age (Raman, 2017). Therefore, the outcomes may be different for those from different ages. Finally, gender was included because women generally have more positive dietary beliefs and perform healthier behavior than men (Roininen &
Tuorila, 1999). Besides that, women have more negative attitudes toward high-fat foods and more positive attitudes towards low-fat foods than men (Roininen & Tuorila, 1999).
Manipulation check. The manipulation of nutrition information was checked with one question at the end of the questionnaire. It was presented with both nutrition labels in random order. The question was: “Have you seen one of these nutrition labels in the video?”. The answer options were ‘A’, ‘B’ and ‘Neither of them’.
Results Manipulation, Randomization and Confound checks
A chi-square test of independence was calculated to see if the respondents recalled whether they were exposed to nutrition information and if so, to which nutrition information. The test showed that there was a significant difference between the different conditions and the answers to the manipulation check, χ2 (6) = 273.24, p < .001 (one-sided). Of the
participants in the unhealthy absent condition, the majority (88.3%) said that they had not seen nutrition information. In the healthy absent condition, the majority said the same (94.7%). In the unhealthy present condition, the majority selected the unhealthy nutrition information (84.1%) compared to a majority in the healthy present (79.7%) selecting the healthy nutrition information. The manipulation was successful. Exclusion of the cases that incorrectly answered the manipulation check did not alter the significance of the results. It could be that participants were not consciously aware of the nutrition information but in fact they were exposed subconsciously. For this reason, in combination with the fact that the results did not differ, the participants were not excluded from the research.
To test for any differences between the four conditions with respect to the study variables, chi-square and analyses of variance were conducted. The results showed that the four conditions did not differ with respect to age F(3, 224) = 1.00, p = .392; gender χ2 (3) = 2.11, p = 0.275 (one-sided) and hunger scores F(3, 224) = 0.36, p = .781. Thus, the
randomization was successful. Analysis of correlations of the control variables with the dependent variables and mediator showed that only gender had a significant but weak correlation with attitude towards eating the cued food, r = .13, n = 225, p < .05. Therefore, gender was included as a covariate in the analyses regarding attitude.
Checking the descriptives of the dependent measures as presented in Table 2 showed that participants in the unhealthy condition had a more negative attitude, lower desire and lower intention than those in the healthy condition. Additionally, the descriptives showed small differences in means for the nutrition information absent and present conditions. Table 2
Mean scores for attitude towards eating the cued food, desire to eat and intention to eat the
cued food by condition
Measures Exposure to
FPV
Nutrition information
Attitude Desire Intention
Unhealthy Absent 4.70(0.97) 3.62(1.57) 3.17(1.56) Present 4.28(1.30) 3.29(1.58) 2.89(1.57) Total 4.52(1.14) 3.48(1.58) 3.05(1.57) Healthy Absent 5.27(1.26) 4.08(1.68) 3.55(1.76) Present 5.29(1.11) 4.19(1.51) 3.72(1.71) Total 5.28(1.18) 4.14(1.59) 3.64(1.73)
Note. The standard deviation for each mean is presented in parentheses.
Hypotheses Testing
In order to test H1a, H1b, H1c and H2, mediation analysis was conducted using Model 4 in the PROCESS bootstrapping approach by Hayes (2013). The model with 5,000 bootstrap
samples had exposure to FPV as independent variable, attitude as mediator, desire as dependent variable and gender as covariate.
With respect to H1a, the model revealed that the regression of desire on exposure to FPV, ignoring the mediator, was significant (see Table 3). Showing that desire was lower for exposure to an unhealthy FPV than for exposure to a healthy FPV. This means that the hypothesis was not supported by the data, exposure to an unhealthy compared to a healthy FPV did not lead to a higher desire.
With respect to H1b, the model revealed that exposure to FPV had a significant negative effect on attitude (see Table 3). The covariate gender had a significant positive impact on attitude, b = .33, p < .05, 95% CI [0.02, 0.64]. The results imply that exposure to FPV impacted attitude; exposure to an unhealthy FPV leads to a more negative attitude than exposure to a healthy FPV. Therefore, H1b was not supported by the data. Exposure to an unhealthy FPV did not lead to a more positive attitude towards eating the cued food than exposure to a healthy FPV.
With respect to H1c, the model revealed that attitude, controlling for exposure to FPV, had a significant positive effect on desire (see Table 3). Therefore, H1c was supported by the data. A positive attitude did lead to a higher desire.
With respect to H2, the model revealed that, controlling for attitude, exposure to FPV was no longer a significant predictor of desire (see Table 3). A Sobel test was conducted and found full mediation in the model (z = -4.19, p < .001). It was found that attitude fully mediated the relationship between exposure to FPV and desire. Therefore, H2 was supported by the data. The effect of exposure to an unhealthy compared to a healthy FPV on desire to eat the cued food was mediated by attitude towards eating the cued food.
Table 3
Overview of the results of the hypothesized relationships as analyzed with PROCESS
mediation model 4 C.I. Relationships b p LL UL 1 Exposure Desire -.66 .002 -1.08 -0.24 Exposure Attitude -.76 .000 -1.06 -0.45 Attitude Desire .87 .000 0.66 1.08 2
Exposure Attitude Desire -.004 .983 -0.42 0.41
Note. C.I. = 95% confidence interval; LL = lower level; UL = upper level. 1 = total effect with attitude; 2 = direct effect, controlling for attitude.
To investigate H3, whether the effect of exposure to FPV on attitude was influenced by the presence or absence of nutrition information, a moderated mediation analysis was conducted using PROCESS Model 7 (Hayes, 2013), to estimate the influence of nutrition information on the relationship between exposure to FPV and attitude within the established mediation. The model with 5,000 bootstrap samples had exposure to FPV as independent variable, gender as covariate, attitude as mediator, nutrition information as moderator and desire as dependent variable. There was no main effect of nutrition information on attitude, b = -.21, p = .19, 95% CI [-.53, .10] and no significant interaction effect between exposure to FPV and nutrition on attitude, b = -.49, p = .13, 95% CI [-1.12, .15]. The presence or absence of nutrition information did not influence the effect of exposure to FPV on attitude. Therefore, H3 was rejected by the data.
To investigate H4, a simple regression analysis was conducted with desire as independent variable and intention as dependent variable. The analysis revealed that desire significantly predicted intention, b = .84, t(223) = 23.01, p < .001. Desire explained a
significant proportion of variance in intention, R2 = .70, F(1, 223) = 529.64, p < .001. Therefore, H4 was supported by the data. A higher desire to eat the cued food leads to a higher intention to eat the cued food. An overview of the results is presented in Figure 6.
An additional analysis was conducted to check whether the relationships existed for the cued food, or for unhealthy and healthy food in general. A one-way analysis of variance was conducted with exposure to FPV as independent variable and attitude towards eating unhealthy, attitude towards eating healthy, desire to eat unhealthy and desire to eat healthy as dependent variables. However, no significant differences between exposure to the unhealthy and healthy FPV were found between conditions for attitude towards eating unhealthy, F(1, 223) = 1.13, p > .05, attitude towards eating healthy, F(1, 223) = 0.49, p > .05., desire to eat unhealthy, F(1, 223) = 0.59, p > .05 and desire to eat healthy, F(1, 223) = 0.40, p > .05. This seems to indicate that there was no different effect of exposure to an unhealthy compared to a healthy FPV on general attitude and desire to eat unhealthy/healthy, only towards the cued food.
Figure 6. Visual representation of significant and non-significant study results.
Note. The standardized regression coefficient between exposure to FPV and desire,
controlling for attitude, is in parentheses. * p < .05. ** p < .01. ***p < .001. Conclusion & Discussion
The aim of the current study was to investigate to what extent unhealthy compared to healthy FPVs have an effect on attitude, desire and intention to eat the cued food and whether these effects differ when nutrition information is present versus absent. Results of the online experimental study in which participants viewed either a healthy or unhealthy FPV with or
without nutrition information, led to four conclusions. First, contrary to H1a and H1b,
exposure to a healthy FPV leads to a more positive attitude towards eating and a higher desire to eat the cued food than exposure to an unhealthy FPV. Second, in line with what was
predicted in H1c and H2, the relationship between exposure and desire is mediated by
attitude. A positive attitude leads to a higher desire, which confirmed H1c. Moreover, attitude fully mediates the relationship between exposure to FPV and desire, which confirmed H2. This seems to indicate that the desire people feel for eating the cued food is completely dependent on their attitude towards the food, which can be influenced by the exposure to an FPV. Third, contrary to what was expected from H3, the absence or presence of nutrition information did not affect the effect of exposure to FPV and attitude. This seems to indicate that presentation of nutrition information has no impact on the relationship between exposure to FPV and attitude. Fourth, in agreement with what was predicted in H4, a higher desire leads to a higher intention to eat the cued food. Desire explained variance in intention, as expected from the TSR (Bagozzi, 1992). This seems to indicate that exposure to an FPV can lead to intention through attitude and desire.
To summarize, the results imply that exposure to an unhealthy compared to a healthy FPV has different outcomes on behavioral intention through the effect on desire and attitude. Exposure to a healthy compared to an unhealthy FPV leads to a higher desire because of a more positive attitude. Desire then influences intention. Additionally, this effect takes place regardless of the presence or absence of nutrition information.
The unexpected finding that exposure to a healthy FPV leads to a more positive attitude and higher desire than exposure to an unhealthy FPV is inconsistent with literature about the UTI (Raghunathan et al., 2006). An explanation for the effect on attitude could be that the foundations of the UTI do not transfer to the context of FPVs. The UTI focuses on enjoyment and taste of food. Raghunathan et al. (2006) argue that this is higher for unhealthy
food, mostly because of how unhealthy food is profiled in advertising. However, a main characteristic of FPVs is that they focus on enjoyment and on making cooking seem exciting and almost sensual (Green Buzz Agency, 2017). The enjoyable presentation of the preparation of the healthy meal potentially increased how enjoyable the meal itself was perceived,
influencing attitude. With respect to desire, palatability of the unhealthy food was expected to induce dopamine, leading to desire (Wansink, 2004). The healthy FPV contained more colorful ingredients, which is an important factor in how palatable a meal is perceived (Van der Laan et al., 2011). This could be a reason for the outcome regarding desire. In short, if the palatability of the healthy FPV was higher, this would lead to a higher amount of dopamine being released, resulting in a higher desire to eat the food.
Another surprising finding was that nutrition information did not impact the relationship between exposure to FPV and attitude. A potential explanation is that the nutrition information did not present new information to the participants. Most participants were highly educated and it is known that more educated people tend to have more
knowledge on health (Learning & Development Agency, 2015). As a result they may have known that the ingredients of the unhealthy FPV were unhealthy and those of the healthy FPV were healthy. If this was the case, the presentation of nutrition information probably did not trigger them and did not alter their attitude towards eating the food. Another explanation could be that nutrition information has an impact on a different type of attitude than exposure to FPV. Attitudes can be influenced by emotions or feelings that the behavior evokes (i.e. affective) and by a rational evaluation of consequences (i.e. cognitive; Boers, Zebregs, Hendriks & Van Den Putte, 2018; Shepherd & Raats, 1996; Tuu, Olsen, Thao & Anh, 2008). It is likely that exposure to an FPV has an influence on the affective attitude because FPVs focus on positive feelings by making cooking and eating highly enjoyable. On the other hand, it is likely that nutrition information affects the cognitive attitude. As nutrition information
presents facts and requires a more rational evaluation. However, in the current study, a more affective attitude was measured. This could be a reason for the lacking effect of nutrition information and distinguishing the affective and cognitive attitude within the same study is an interesting cue for future research.
Even though some of the results of the study were different from what was expected, the study still provides meaningful information about FPVs. It is clear that unhealthy and healthy FPVs differently affect people’s attitude, desire and intention. Healthy compared to unhealthy FPVs seem to lead to a higher intention to eat the cued food through desire and attitude. Therefore, a spread of healthy FPVs could have an impact on people their healthy eating behavior. Even though unhealthy FPVs resulted in significantly lower intention to eat the cued food than healthy FPVs, future research is necessary in order to see whether
intention predicts actual behavior. In the following section, limitations and implications for future research are given.
Limitations & Future Research
There were several limitations in this study that need to be noted. First, the results cannot be generalized to a broader context because they are based on convenience sampling. Convenience sampling is a type of nonprobability sampling where members of the target population meet some practical criteria (e.g. accessibility, proximity) (Etikan et al., 2016). This type of sampling does not make it possible to establish how well the sample represents the population. Additionally, the sample consisted of mainly highly educated people. It is likely they spend most of their time either studying or at an office job. The results could have been very different for another sample. For example manual workers need more energy than office workers, because they are more physically active (BBC, n.d.). For that reason, their attitude or desire towards the cued food could have been more leaning towards the energy-dense meal. In order to make the study more generalizable, future research could focus on
replicating the results with a representative sample, for example examining the effects between manual and office workers.
Second, it would be highly recommended to conduct the study again but with an unhealthy, healthy and a control condition. Currently, the research investigated the difference between unhealthy and healthy FPVs. However, no prior research was conducted on an effect of either unhealthy or healthy FPVs. A problem was that the study did not show change in the dependent measures because of exposure to an FPV, only differences between the conditions. It is a good idea to investigate whether an FPV on its own has a causal influence or if this influence is the same for exposure to a control condition. The exposure to an unhealthy FPV, healthy FPV and a control condition could potentially reveal the effects of and differences between FPVs.
Third, some important factors were not measured, such as nutrition knowledge and past behavior. Nutrition knowledge about differences between healthy and unhealthy food and about the health consequences could have influenced the outcomes of the study. Research showed that nutrition knowledge is significantly associated with healthy eating (Wardle, Parmenter & Waller, 2000). Especially women in the 26-45 year age group seem to have more negative attitudes towards consumption of high fat foods due to their nutrition
knowledge (Shepherd & Stockley, 1987). Wardle et al. (2000) found that people with more knowledge on nutrition, ate significantly less fat and more fruit and vegetables than those with lower knowledge. The sample potentially already had nutrition knowledge, causing their preference for the healthy FPV. Therefore, a measure of nutrition knowledge should be implemented in future research. Additionally, past behavior could have affected the results as this is known to have an impact on the appraisal of food (Leone, Perugini & Ercolani., 2004). It is likely that the sample was not completely homogeneous with regard to lifestyle or eating behavior. This could have influenced their attitude towards the cued food. For example, an
athlete probably has a different perception of junk food than a student who goes out a lot. Therefore, it would be wise to include a measure of lifestyle (i.e. past behavior) in future research.
Fourth, social desirability potentially biased the results. Social desirability is the tendency of participants to deny social undesirable traits and claim socially desirable ones, thereby putting the participant in a favorable light (Nederhof, 1985). Because the participants were shown both healthy foods (e.g. courgetti and salad) and unhealthy foods (e.g. pasta and hamburger) in the questionnaire, they could have filled out the survey with what they consider to be socially desirable answers. A study by Nederhof (1985) provided several methods of coping with social desirability. For future research it is recommended to use these methods to limit social desirability.
Implications
Besides the limitations, the findings of the current study have important implications. This study extends previous theory about food cues by investigating FPVs, also furthering research on comparing unhealthy and healthy food cues. Opposite to what was expected from theory, results showed healthy FPVs potentially have impactful effects on public health. Additionally, attitude completely mediated the relationship between exposure and desire. Therefore, attitude should be included in theory regarding food cue effects. Also, the findings revealed that the relationships, as expected from the TSR, are applicable in food cue
exposure. Finally, the study adds to literature about food cues by including the presentation of nutrition information. Food cue effects do not seem to be influenced by the presentation of nutrition information.
This research has two important practical implications for public health organizations. First, it is advisable to realize that attitude was very important in determining desire.
increasing palatability. They could do this by making enjoyable FPVs of highly palatable healthy meals. This enjoyment will positively influence attitude, which as a consequence will influence desire, intention and hopefully behavior. Second, healthy FPVs appear to have an effect on attitude, desire and intention to eat the cued food, not to healthy food in general. Therefore, a spread of FPVs in which various healthy meals are prepared could have a positive impact on the diversity of people’s eating behavior.
Even though the current study took the first steps in researching FPVs and their effects on people’s attitude towards eating, desire to eat and intention to eat the cued food, further research is necessary to convincingly claim positive or negative effects of FPVs. The
popularity of FPVs is ever increasing as they expand all-over different social media channels, potentially making them a contributor to the obesogenic environment. A main difference with other food cues is that people enjoy FPVs and voluntarily watch them, compared to
commercials or advertisements. Therefore, these potentially powerful FPVs deserve and require more attention in scientific research as well as from (non) governmental and public health organizations.
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Appendix A: Stimulus materials
Figure A1: pictures of (cued) food as presented to the participants.
Figure A2: nutrition labels as presented to the participants in the pretest and in condition 2
Appendix B: Measures Attitude. Measured for each picture in Figure A1.
Please have a look at the following image and answer the questions regarding it: If I would eat this meal for dinner, I would feel:
Unsatisfied Satisfied Unpleasant Pleasant
Dull Exciting
Unhealthy Healthy
Desire. Measured for each picture in Figure A1.
Please indicate your choice for the following statements:
False True
1 2 3 4 5 6 7
I desire to eat this meal over the next few days
I want to eat this meal over the next few days No desire Very weak desire Weak desire Moderate desire Strong desire Very strong desire 1 2 3 4 5 6 My desire for eating this meal over the next few days can be described as…
Intention. Measured for each picture in Figure A1. Please indicate your choice for the following statements:
False True
1 2 3 4 5 6 7
I am planning to eat this meal over the next few days
Completely disagree Completely agree
1 2 3 4 5 6 7
I intend to eat this meal over the next few days
I will eat this meal over the next few days
Subjective norm.
Please indicate your choice for the following statements:
Completely disagree Completely agree
1 2 3 4 5 6 7
People with whom I eat regularly would appreciate it if I eat this meal People who are important to me would appreciate it if I eat this meal
Hunger.
Please indicate how hungry you are right now:
Not hungry at all Extremely hungry
Nutrition information.
Random order pictures of the two nutrition labels.
Have you seen one of these nutrition labels in the video? o A
o B
o Neither of them
Demographic variables. Age.
What is your age (in numbers)?
Gender.
What is your gender? o Male
o Female o Other
Education.
What is your highest or current education? o No education
o Primary school o High school o MBO
o University of Applied Sciences o University
o Other, namely …..
Vegetarian status.
Would you consider yourself a full-time vegetarian? o Yes
o No
Country.
In which country have you lived for most of your life?
