Evaluating Product Information : an Analysis of the Effects of Information Type, On-/off-pack Information, and Information Resistance on Consumers’ Intention to Choose a Product and Intention to Exercise

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Evaluating Product Information

An Analysis of the Effects of Information Type, On-/off-pack

Information, and Information Resistance on Consumers’

Intention to Choose a Product and Intention to Exercise

Angela Bonanno 11713453 Master’s Thesis

Graduate School of Communication Master’s Programme Communication Science

Nadine Bol 31-01-2019

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Abstract

This study investigates the effects that integrating exercise information into food labels produces on consumers’ intention to choose a product and to exercise. Issues of information resistance and strategies to resist persuasion are addressed to further investigate the role of exercise information, and the implications of relocating such information on a secondary platform (off-pack) than product packaging (on-pack). We theorise that the auxiliary role of exercise information in increasing consumers’ food- and exercise-related intentions is minimised by consumers’ resistance to the information provided. We also predict that relocating exercise information off-pack would reduce information resistance and therefore increase consumers’ intention to choose a product and to exercise. We tested our prediction with one experimental study (N = 341) where two product types (low- and high-fat products) were used. We found that exercise information displayed on high-fat products increased consumers’ intention to choose them, as opposed to exercise information displayed on products low in fat. As for intention to exercise, in all conditions – except the nutrition information condition – participants had greater intentions to exercise after exposure to high-fat products. The obtained insights into the compensating mechanisms triggered after

exposure to exercise information on high-fat products carry theoretical and practical implications for researchers, marketers, and product and app developers, and should contribute to both maximise the benefits of food labels and promote a healthy lifestyle.

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Introduction

In the attempt to inform people about products, promote healthier food choice, and reduce obesity rates, nutrition labels have been made mandatory for packaged goods in most developed countries (Elshiewy & Boztug, 2018). Such labels provide food-related information about nutrients (carbohydrates, fats, fiber, and protein) and calories to guide consumers during the buying process. However, while some studies have shown that nutrition labels lead to better food choices (Campos, Doxey, & Hammond, 2011; Hersey, Wohlgenant, Arsenault, Kosa, & Muth, 2013), others have shown their inefficacy in educating consumers into healthy behaviours (Elshiewy & Boztug, 2018; Sacks, Rayner, & Swinburn, 2009). Such discrepancy might be caused by the complexity of nutrition information, which would prevent consumers from interpreting product information effectively and from making thoughtful food choices (Hawley et al., 2012; Kelly et al., 2009; Watson et al., 2014). For this reason, studies have emphasised the need for an auxiliary text – next to nutrition information – to guide consumers (Hawley et al., 2012). Given the link between food and exercise (Olivares et al., 2004), and the exercise-related implications of the calories displayed on food labels (Van Kleef, Van Trijp, Paeps, & Fernández-Celemín, 2007), research has started to investigate whether integrating exercise information into food labels helps consumers interpret food labels.

Exercise information is expressed in terms of energy balance, i.e., energy-in/energy-out ratio (Appendix A, Figure 1A). This implies exposing consumers to labels containing information on the amount and type of physical activity (PA) to undertake (energy-out) in order to burn the calories contained in a product (energy-in). While studies on the inclusion of exercise information on food labels highlighted its benefits for consumers (Campos et al., 2011; Van Kleef et al., 2007), others showed that some consumers might resist to it (Van Kleef et al., 2007). Building upon the mixed findings for both nutrition and exercise

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information, the present study will first attempt to define the role of information type with respect to consumers’ intention to choose a product and to exercise (RQ1). The choice of addressing consumers’ intention stems from the fact that most studies on food labels test consumers’ preference for label types (see Hawley et al., 2012; Kelly et al., 2009). Nevertheless, preference is often biased by familiarity and social desirability (Hawley et al., 2012Kelly et al., 2009). Intention – which is the strongest predictor of behaviour enactment (Ajzen, Czasch, & Flood, 2009) – will provide more consistent and real-life results (Sacks et al., 2009).

In the attempt to explain the mixed findings for exercise information, issues of

information appropriateness and consequent information resistance have emerged (Van Kleef et al., 2007). Information resistance is defined as “the act of withstanding influence”

(Knowles & Linn, 2004, p. 4), and refers to the fact that consumers might counter, refute, doubt or contest the information shown (Van Reijmersdal et al., 2016). In the study by Van Kleef et al. (2007), participants negatively reacted to exercise information on packaged goods, claiming that it generates guilt, and – most importantly – does not belong to food packaging (Van Kleef et al., 2007). The implicit association between exercise information and the product packaging has led to the investigation of secondary platforms where exercise

information should be transferred. Van Kleef et al. (2007) suggested that off-pack information should be preferred to on-pack. While on-pack relates to displaying information on product packaging, off-pack relates to offering product information on a different platform, for example a mobile app (Van Kleef et al., 2007). However, at present little research has been conducted on off-pack information (Campos et al., 2011). For this reason, this study will test the effect of different information types (i.e. nutrition, exercise, nutrition plus exercise, no information) on consumers’ intention to choose a product and to exercise (RQ1), by

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investigating the role of information resistance in such a relationship (RQ2), and by exploring platform-related implications (i.e., on-/off-pack information; RQ3).

Not only does the present study contribute to the existing knowledge from a

theoretical perspective (to our knowledge, no studies have investigated intention to exercise with respect to food labels), but it also shifts the methodological perspective. Most of the studies so far mentioned adopted a qualitative approach (Hawley et al., 2012; Van Kleef et al., 2007), whereas this study will employ a quantitative approach. The emphasis on exercise information and on-/off-pack information will extend the body of research currently existing (Campos et al., 2011), and hopefully provide greater understanding of the underlying

mechanisms of information resistance. These aspects are essential for consumers, marketers, and society as a whole, in that they will contribute to maximise the benefits of food labels and promote a healthy lifestyle.

From preference to intention: A theoretical shift

In the attempt to explain the remarkable yet contrasting insights on the effectiveness of food labels in guiding consumers towards healthier food choices (see Campos et al., 2011;

Elshiewy & Boztug, 2018; Hersey et al., 2013; Hawley et al., 2012; Kelly et al., 2009; Sacks et al., 2009), previous research has addressed the complexity of nutrition information (Hawley et al., 2012; Kelly et al., 2009; Watson et al., 2014). In the present study, we suggest a further explanation for the inconsistency, which implies a theoretical shift. A great number of

research investigating the function of nutrition information on food labels has explored which label types work better for consumers. This implies asking consumers about their label preference. However, preference for one label type does not necessarily relate to stronger intentions to choose a product (Hawley et al., 2012). In other words, consumers might prefer

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one label type to the other, but this does not provide any information on the extent to which the product information included in such labels influences their behaviour.

In order to provide more real-life insights into consumer behaviour (see Elshiewy & Boztug, 2018; Sacks et al., 2009; Watson et al., 2014), a shift in focus from consumers’ preference for one label type is needed. This choice is supported by two biases characterising label preference (i.e., familiarity bias and social desirability bias; Hawley et al., 2012; Kelly et al., 2009). In one study on labelling systems (Hawley et al., 2012), participants preferred Traffic Light (TL) label system to Guideline Daily Amount (GDA) system (Appendix A, Figures 2A and 3A), purely because they were more accustomed to the TL label system. Such findings highlight how familiarity bias – i.e., the tendency for respondents to choose an option based on how familiar with that option they are (Hawley et al., 2012) – prevented the

obtaining of insights about the role of food labels. A further study on consumers’ acceptability of different food labelling systems (Kelly et al., 2009) showed that participants asked about their label preference provided what they perceived to be the most acceptable and reasonable answers (i.e., social desirability bias; Fisher, 1993), leaving out crucial aspects related to the actual function of food labels. In order to minimise such biases, in our study we measure participants’ intention. This latter is the dominant antecedent to behaviour enactment within the theory of planned behaviour (TPB; Ajzen, Czasch, & Flood, 2009), which suggests that people are more likely to perform a given behaviour, if their intentions are strong. We specifically investigate consumers’ intention to choose a product and their intention to exercise. A first explanation for such a choice is given by the link between food and exercise (Olivares et al., 2004). A second explanation is represented by the possibility of introducing a further type of information – next to nutrition information – into food labels (Campos et al., 2011; Van Kleef et al., 2007) to help consumers interpret product information (Hawley et al.,

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2012; Kelly et al., 2009; Watson et al., 2014). With reference to this last point, our study specifically explores the implications of adding exercise information on food labels.

Exercise information on food labels: Potential implications

Consumers confronted with product calories receive information on their ideal caloric intake (energy-in), and on the benefits of having a balanced lifestyle, which usually implies exercising (energy-out; Van Kleef et al., 2007). Such a link between eating and exercising habits has motivated researchers to investigate the role of exercise information. Their findings suggest that emphasising the implications of extra calorie intake in relation to exercise enables participants to better understand the information displayed on packaged goods (Campos et al., 2009; Van Kleef et al., 2007). Three reasons support these findings. First, the message

conveyed by the energy-in/energy-out ratio (i.e., exercise information) is perceived as realistic and practical, two features which often do not belong to nutrition information (Hawley et al., 2012; Kelly et al., 2009; Watson et al., 2014). This seems to fulfil researchers’ and marketers’ need for capitalising the potential of food labels (Campos et al., 2011), and consumers’ need for less complex and easier-to-understand information on food packaging (Hawley et al., 2012; Kelly et al., 2009; Watson et al., 2014). Second, exposing participants to exercise information makes them realise that becoming overweight is not only a consequence of an unbalanced diet, but also of lack of exercise (Van Kleef et al., 2007). Third – and in line with the previous point – participants argue that exposure to exercise information makes them mindful about their exercise habits (Van Kleef et al., 2007).

At present, little research has been conducted on the impact of exercise information on consumers’ intention to choose a product and to exercise (Hawley et al., 2012; Van Kleef et al., 2007). Given the potential auxiliary role of exercise information in the interpretation of nutrition information addressed above (Hawley et al., 2012; Kelly et al., 2009; Watson et al.,

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2014), we hypothesise that integrating exercise information into food labels will increase consumers’ intention to choose a product, compared to food labels lacking exercise

information (H1a). Additionally, considered the emphasis that exercise information puts on exercise habits – or lack thereof – (Van Kleef et al., 2007), we hypothesise that adding

exercise information to food labels will increase consumers’ intention to engage in exercising, as opposed to food labels lacking exercise information (H1b). H1 is included below.

H1: Compared to those exposed to nutrition information only (N) or no information at all (C), consumers exposed to labels containing exercise information (E or NE) will have:

a) Greater intention to choose a product; b) Greater intention to exercise.

Information resistance and consequences for exercise information: The role of on-/off-pack information

Next to the positive aspects of exercise information so far discussed (Campos et al., 2011; Van Kleef et al., 2007), studies have also revealed negative consequences of exposing consumers to such information (Van Kleef et al., 2007). To explain the mixed findings, aspects related to information resistance (Knowles & Linn, 2004) need to be addressed.

For persuasion to occur, individuals should accept the message conveyed; in other words, they should not resist the information provided (Knowles & Linn, 2004). Resistance usually occurs when a prospect of change is offered (Knowles & Linn, 2004). For instance, people who are reminded of their unhealthy behaviours (e.g., unbalanced diet or lack of exercise), are also faced with the possibility of changing such behaviours (e.g., adopting a balanced diet or engage in exercise). This puts pressure on them, triggering the development of strategies to resist persuasion (Zuwerink Jacks & Cameron, 2003). Such strategies

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correspond to two levels of resistance, i.e. affective and cognitive (Knowles & Linn, 2004; Van Reijmersdal et al., 2016). People might not like exercise information (affective

resistance) or not believe it (cognitive resistance). Similar patterns of reaction to information were observed in the study on distressing images on cigarette packaging conducted by Brown and West (2014). They found that when consumers are confronted with an unhealthy habit and are reminded of its bad consequences, they are very likely to develop defensive avoidance behaviours (see Tannenbaum et al., 2015). Consumers might therefore disengage from the information provided (i.e., ignore it) or derogate it (i.e., question its credibility; Tannenbaum et al., 2015).

Interestingly, all behaviours and types of reaction to information so far discussed are centred on the content of the information. When people do not like the information provided (affective resistance) or do not believe it (cognitive resistance), they react by ignoring it (disengagement) or questioning its credibility (derogation), respectively. This point is of crucial importance for the present work. In fact, the study by Van Kleef et al. (2007) revealed that some respondents found exercise information distressing. Again, respondents focused on the content of the information they were exposed to. These findings imply that information resistance extensively depends on information content. The content of exercise information we employ in this study (Appendix B, Table 1B) addresses consumers’ current behaviour (eating; energy in), and a suggested behaviour (exercising; energy-out). In other words, exercise information offers consumers a prospect of behaviour change, which might well trigger resistance (Knowles & Linn, 2004). We therefore hypothesise that exposing

consumers to exercise information will increase their resistance to such information; this will in turn result in decreased intention to choose a product (focus on current behaviour) and to exercise (focus on suggested behaviour). H2 is provided below.

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H2: Compared to those exposed to nutrition information only (N) or no information at all (C), consumers exposed to labels containing exercise information (E or NE) will show greater information resistance, which in turn will result in:

a) Decreased intention to choose a product; b) Decreased intention to exercise.

At this stage, it seems that providing exercise information is actually detrimental to consumers. Part of the study by Van Kleef et al. (2007) provides support for such a statement. In fact, consumers found exercise information not only distressing, but also inappropriate. If in the first case of exercise information being distressing, the focus is on the content of the information provided – as already discussed – in the second case that exercise information is inappropriate, the emphasis then becomes on where such information is displayed. As a matter of fact, participants explicitly stated that exercise information is not appropriate for food labels. In support of this, the definition for the adjective “appropriate” provided by Oxford Dictionary (n.d.) is “suitable […] in the circumstances”; this underlies that

appropriateness pertains to the circumstance, context, and situation in which something is presented.

While in the above section we referred to content-related defensive avoidance

behaviours (Tannenbaum et al., 2015) to explain consumers’ reaction to exercise information, a third type of such behaviour needs to be mentioned. In fact, an additional strategy people adopt to resist information is avoiding further exposure to it (e.g. by no longer looking at the product packaging); this carries major implications related to where such information is displayed. The study by Van Kleef et al. (2007) in fact suggest that the energy-in/energy-out ratio (i.e., exercise information) is more appropriate when presented off-pack (e.g., on a mobile app), rather than on-pack (e.g., on product packaging). Building upon the alleged

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effects of exercise information on consumers’ intention to choose a product (H1a) and to exercise (H1b), we hypothesise that such effects will be more pronounced when exercise information is displayed on a more appropriate platform (i.e., off-pack, rather than on-pack; H3). The interaction is included below.

H3: On-/off-pack information moderates the relationship between information type and intention to choose a product, and between information type and intention to exercise, such that compared to those exposed to nutrition information only (N) or no

information at all (C), consumers exposed to labels containing exercise information (E or NE) will have:

a) Greater intention to choose a product when presented off-pack (app) than on-pack (on-packaging);

b) Greater intention to exercise when presented off-pack (app) than on-pack (packaging).

Considered the implications of defensive avoidance behaviours – with particular reference to the third type of behaviour (i.e. further exposure avoidance; Tannenbaum et al., 2015) – relocating the information to a different platform should reduce the likelihood that consumers avoid being exposed to exercise information (Van Kleef et al., 2007). In other words, consumers’ resistance to exercise information should be minimised if such information is presented off- rather than on-pack. Building upon H2 and H3, we lastly hypothesise that relocating exercise information off-pack will minimise consumers’ information resistance, thus resulting in increased intention to choose a product (H4a) and to exercise (H4b). The moderated mediation is summed up below.

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H4: Compared to those exposed to nutrition information only (N) or no information at all (C), consumers exposed to labels containing exercise information (E or NE) will show less information resistance off-pack than on-pack, which in turn will result in:

a) Increased intention to choose a product; b) Increased intention to exercise.

All hypotheses are visualised in Figure 1.

Method

Sample

363 participants started an online questionnaire. Two did not give their consent, and were excluded from the analysis. Two participants were excluded because they dropped out the questionnaire at the beginning. 17 participants completed only part of the questionnaire, and were therefore excluded. One participant was excluded in that he or she provided Fig. 1 Conceptual model.

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inaccurate answers to the open-ended questions (e.g., No, aaa). A final sample of 341 people took part to the online experimental study. 265 participants were recruited via Mechanical Turk by Amazon, and were paid €0.05on completion of the survey. 76 participants were recruited through the researcher’s personal network, online services the likes of SurveyCircle and Survey Tandem, and Facebook pages such as “Survey sharing 2018” and “Survey Exchange”. Convenience and snowball sampling techniques were used. The average age was 33 (M = 33, SD = 11.65); the age range was 18 to 78 years old. 58.1% were females, 41.9% males. The three most represented nationalities were American (36.7%), Indian (20.2%), and Italian (9.1%). Most participants held a Bachelor degree (52.8%).

Design and Procedure

A 2 x 4 x 2 mixed design, with on-pack/off-pack information (on-pack vs. off-pack) and information type (nutrition information vs. exercise information vs. nutrition plus exercise information vs. no information) as between-subjects variables, and product type as within-subjects variable (low-fat vs. high-fat) was used to test our proposed model.

The data was collected between November and December 2018. Participants were randomly assigned to one out of three low-fat products and one out of three high-fat products in a random order. Nutrition, exercise, and nutrition plus exercise information represented the treatment conditions. No information was the control condition.

Stimulus material

Nutrition information was retrieved from the smartphone app MyFitnessPal by Under Armour, and adapted to both on- and off-pack conditions. It included the features of TL labelling system (Hersey et al., 2013; Sacks et al., 2009; Appendix A, Figure 2A). The indications “low”, “medium”, and “high” refer to the recommended healthy range suggested

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by Penner (2018). “Low” means that the percentage of a given nutrient falls below the

recommended healthy range for that nutrient. The same logic applies to “medium” (within the range), and “high” (above the range). In the on-pack condition (Appendix C, Table 1C), nutrition information was displayed on four different boxes, one for calories (light-blue), and the remaining for carbs, fat, and protein. In the off-pack condition (Appendix C, Table 5C), it was displayed both in text and on a pie chart with the three aforementioned colours. Exercise information was created by taking into account male/female body weight, metabolic

equivalent of task (MET; Holtermann & Stamatakis, 2018), and the duration of the task. Gender-neutral activities (e.g., running, walking, stair climbing) were selected from the Compendium of Physical Activities (Ainsworth et al., 2011; Appendix B) for the sake of comparability. A detailed description of the creation of exercise information is included in Appendix B (Table 1B). In the on-pack condition (Appendix C, Table 2C), exercise information replaced the three boxes for nutrients. The light-blue box displaying calories remained unchanged. For the off-pack condition (Appendix C, Table 6C), it was displayed at the bottom of the screen, whereas a light-blue pie chart carrying information on calories only was included in the usual position. Nutrition plus exercise information was created by

combining feature of the two information types. In the on-pack condition (Appendix C, Table 3C), the text for exercise information was included below the boxes containing nutrition information. In the off-pack condition (Appendix C, Table 7C) it was placed below the usual pie-chart. The control condition consisted of an image of the product packaging for the on-pack condition (Appendix C, Table 4C). In the off-on-pack condition, the product on-packaging was displayed on the top-right part of the mobile screen (Appendix C, Table 8C).

The six products included in the present study were categorised in low-fat and high-fat based on the percentage of fat they contained. If such percentage exceeded the recommended threshold of 35%, products were labelled “high-fat”; products well below 20% of fat were

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labelled “low-fat” (Penner, 2018). The choice of including at least three products for each low- and high-fat category would enable participants to draw sharp distinctions between the two product types, and allow us to draw valid conclusions about the extent to which product type influences consumers’ choice. To allow for comparability between products and conditions, the layout (i.e., inclusion or exclusion of some elements), design (i.e., label colour), and part of the product information itself (i.e., percentage and grams of nutrients contained, amount of calories) were slightly modified (see Appendix C).

Measures

The measures presented below were computed by bearing in mind participants’ exposure to the within-subjects variable (i.e. product type).

Intention to choose a product. Drawing inspiration from purchase intention

measures (Davis & Warshaw, 1992; Van Reijmersdal, Fransen, Van Noort, Opree, Vandeberg, Reusch, Boerman, 2016), participants’ intention to choose a product was measured with a five-item scale (i.e., I intend to choose/would like to try/want to buy/will choose the product and I will look for the product in the supermarket). Participants were asked to rate each statement using a seven-point Likert scale (1 = Extremely unlikely, 7 = Extremely likely). To allow for a more real-life scenario, a short premise was included before the statements, which read “Imagine that you are doing groceries and that you might consider buying the product based on the product information”. A principal axis factoring analysis (Appendix D) revealed that all five items for Intention to choose a product loaded on one factor (Eigenvalue = 4.39), and 87.83% of the variance was explained by the latent construct. The scale was reliable (Cronbach’s α = .97), and computed into a mean scale of Intention to choose a product.

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Intention to exercise. Participants’ intention to exercise was measured with a

four-item scale (i.e., I have the intention/try/be determined/have the willingness to exercise after consuming the product), with statements taken from the scale measuring intention for exercise and healthy eating (Psouni, Hassandra, & Theodorakis, 2016). Participants were asked to rate each statement using a seven-point Likert scale (1 = Extremely unlikely, 7 = Extremely likely). Again, to confront participants with a real-life choice, we asked them to imagine they had to prepare a training schedule. A principal axis factoring analysis (Appendix D) revealed that all four constructs for Intention to exercise loaded on one factor (Eigenvalue = 3.72), which explained 92.90% of the variance. The scale was reliable (Cronbach’s α = .97), and computed into a mean scale of Intention to exercise.

Information resistance. Building upon the scales employed by Van Reijmersdal et al.

(2016), Information resistance was measured through a four cognitive resistance items (While looking at the product information, I contested/refuted/doubted/countered it) and four

affective resistance items (The product information was distressing/annoying and The product information made me feel unmotivated/guilty). Participants were asked to rate these

statements on a seven-point Likert scale (1 = Strongly disagree, 7 = Strongly agree). The principal axis factoring analysis (Appendix D) tested whether the four items for cognitive resistance, and the four items for affective resistance represented two distinct factors.

Although two factors had an Eigenvalue greater than one (Eigenvalue = 5.59, 69.93% of the variance explained; Eigenvalue = 1.15, 14.32% of variance explained), the scree plot showed only one factor after the point of inflexion (Appendix D, Figure 1D). Therefore, one reliable scale of information resistance was created (Cronbach’s α = .94). All factor loadings are reported in Appendix D (Table 4D).

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Manipulation check

Information type. To check for successful manipulation, participants were asked to

indicate whether they had seen calories, nutrients (i.e., carbs, fat, protein), and/or exercise information in relation to the products they were presented with. A new variable was created that indicated a correct (1) or incorrect (1) answer. For example, if participants were exposed to the nutrition information, they would check “calories” and “nutrients”; if they were shown exercise information, they were expected to check “calories” and “exercise advice”. In case they belonged to the nutrition plus exercise information condition, they would check all boxes. Those exposed to the control condition were expected to check “none of the above”. A Chi-square test showed that overall participants successfully recognised the type of

information they were confronted with, χ² (3) = 11.38, p = .010 (Table 1).

On-/off-pack information. To the question “The product information you looked at

was presented on/in” participants in the on-pack condition were expected to select “packaged products”, whereas those in the off-pack condition would select “a mobile application”. A Chi-square test indicated successful manipulation, χ²(2) = 9.92, p = .002. Participants were able to distinguish whether the product information was displayed on packaged goods or on a mobile application (Table 2).

Table 1 Comparisons of information type by stimulus recognition group

Information type n recognition of Correct

stimulus

Incorrect

recognition Chi-square test of independence

Nutrition information 94 33.8% 18.9%

χ²(3) = 11.38 p = .010

n = 341

Exercise information 81 19.7% 29.4%

Nutrition plus exercise

information 83 21.7% 28.0%

No information 83 24.7% 23.8%

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Table 2 Comparisons of on-/off-pack information by stimulus recognition group

On-/off-pack information _SampleOverall recognition of Correct

stimulus

Incorrect

recognition Chi-square test of independence

On-pack information 175 54.5% 28.6% χ²(2) = 9.92 p = .002 n = 341 Off-pack information 166 45.5% 71.4% Total 341 100% 100% Statistical analyses

To test for successful randomisation, Chi-square tests and F-tests were conducted with experimental condition as independent variable and gender, nationality, and educational level (Chi-square), and gender (F-test) as dependent variables.

To test the main effect of information type on intention to choose a product (H1a) and intention to exercise (H1b), and the interaction between information type and on-/off-pack information on intention to choose a product (H3a) and intention to exercise (H3b), a mixed ANOVA with information type and on-/off-pack information as between-subjects variables, intention to choose a product and intention to exercise as dependent variables, and product type (low-/high-fat product) as within-subjects variable was conducted.

A simple mediation model (Hayes, 2016) with the PROCESS macro (Model 4;

Appendix E, Figure 1E) was used to test the indirect effect of information type on intention to choose a product (H2a) and intention to exercise (H2b) through information resistance. To test the moderated mediations for intention to choose a product (H4a) and intention to exercise (H4b), PROCESS macro (Model 8; Appendix E, Figure 2E) was employed.

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Results

Randomisation check for gender, nationality, educational level, and age

There were no significant associations between the experimental conditions on the one hand, and gender, χ²(7) = 5.01, p = .659, nationality, χ²(350) = 367.41, p = .251, educational level, χ²(28) = 22.78, p = .744, and age, F(7, 332) = 0.10, p = .998, on the other hand, meaning that participants were evenly distributed across conditions with respect to the aforementioned variables.

Effects on Intention to choose a product

Main effect. Contrary to our expectations, there was no significant main effect of

information type on consumers’ intention to choose a product, F(3, 333) = 0.40, p = .752. Participants exposed to exercise information did not significantly differ from those exposed to nutrition information (M difference = -0.07, SE = .21, p = 1.000, 95% CI [-0.63, 0.49]), or no

information (M difference = -0.20, SE = .22, p = 1.000, 95% CI [-0.78, 0.38]). The same applied for

participants exposed to nutrition plus exercise information. These did not significantly differ from participants in the nutrition information condition, M difference = -.08, SE = .21, p = 1.000,

95% CI [-.64, .48], and in the control condition, M difference = -.21, SE = .22, p = 1.000, 95% CI

[-.79, .37]. H1a was therefore not supported. However, therewas a small, but significant interaction effect between information type and product type, F(3, 333) = 6.48, p < .001, Partial η2 = .06. Participants exposed to exercise information had greater intention to choose

high-fat products (M = 4.51, SE = .20), than low-fat ones (M = 4.16, SE = .18). The same applied to those in the control condition, whose intention to choose high-fat products (M = 4.57, SE = .19) was greater than their intention to choose low-fat products (M = 4.52, SE = .18). However, the inverse pattern was observed for those exposed to nutrition information only, and to the combination of nutrition and exercise information. The former (nutrition

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information) scored higher on intention to choose low-fat products (M = 4.83, SE = .17), than high-fat ones. The same held for the latter (nutrition plus exercise; M = 4.59, SE = .18).

Mediation. The indirect effect of information resistance was not significant for

nutrition information, β = 0.01, SE = .06, 95% CI [-0.11, 0.12], for exercise information, β = 0.07, SE = .06, 95% CI [-0.04, 0.19], for nutrition plus exercise information, β = 0.02, SE = .06, 95% CI [-0.10, 0.14]. H2a was therefore not supported. However, there was a significant direct effect of information resistance on intention to choose a product (b-path), β = .25, SE = .05, p < .001.

Moderation. The hypothesised interaction between information type and on-/off-pack

information was not significant, F(3, 333) = 1.00, p = .393. H3a was not supported. However, a small, but significant three-way interaction between information type, on-/off-pack

information, and product type was found F(3) = 2.72, p = .044, Partial η2 = .02 (Table 3).

Participants in the exercise information condition had greater intention to choose low-fat products when the information was displayed on-pack (M = 4.69, SE = .25), than off-pack (M = 3.63, SE = .26). The same applied to those exposed to nutrition plus exercise information, whose intention to choose low-fat products was greater when the information was displayed on-pack (M = 4.72, SE = .25), compared to off-pack (M = 4.46, SE = .25). The same pattern was found for participants exposed to exercise information about high-fat products. However, those exposed to nutrition plus exercise information had greater intention to choose high-fat products when the information was displayed off-pack (M = 3.85, SE = .27, than on-pack (M = 4.33, SE = .28). The profile plot showed that participants’ intention to choose a low-fat product was quite stable when product information was displayed on-pack (Figure 2). However, when these participants were presented product information off-pack, their

intention to choose a low-fat product varied considerably with respect to information type. In particular, those in the off-pack nutrition information condition had the greatest intention to

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choose low-fat products (M = 5.04, SE = .25), whereas those in the off-pack exercise information condition had the lowest intention to choose low-fat products (M = 3.63, SE = .26). Also, the greatest difference in intention to choose low-fat products was found between those exposed to exercise information on-pack (M = 4.69, SE = .25), and off-pack (M = 3.63, SE = .26). As for participants’ intention to choose a high-fat product, there was not a

considerable difference between on- and off-pack information condition. Participants’ intention to choose high-fat products was considerable for those exposed to both on- and off-pack exercise information (Figure 3).

Fig. 2 Profile plot for the three-way interaction between product type, information type,

and on-/off-pack information on intention to choose a product. The values reported refer to low-fat products.

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Table 3 Differences across conditions for the three-way interaction of information type, on-/off-pack

information, and product type on intention to choose a product

Product type Information type On-/off-pack information M SE

Low-fat product

Nutrition information on-pack 4.61 .23

off-pack 5.04 .25

Exercise information on-pack 4.69 .25

off-pack 3.63 .26

Nutrition plus exercise information on-pack 4.72 .25

off-pack 4.46 .25

No information on-pack 4.57 .25

off-pack 4.47 .25

High-fat product

off-pack 3.86 .27

off-pack 4.39 .28

off-pack 3.85 .27

off-pack 4.22 .28

Fig. 3 Profile plot for the three-way interaction between product type, information type, and on-/off-pack

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Moderated mediation. The interaction between information type and on-/off-pack

information on the mediating role of information resistance between information type and intention to choose a product was not significant. Participants exposed to exercise information off-pack did not have greater intention to choose a product (M = 0.02, SE = .07, 95% CI [-0.13, 0.16]), compared to those exposed to the same information on-pack (M = 0.12, SE = .09, 95% CI [-0.52, 0.30]) because of reduced information resistance. Participants in the nutrition plus exercise condition did not have greater intention to choose a product when exposed to information off-pack (M = 0.02, SE = .07, 95% CI [-0.13, 0.17]), than on-pack (M = 0.02, SE = .08, 95% CI [-0.15, 0.19]) because of minimised information resistance. H4a was not supported.

Effects on intention to exercise

Main effect. Contrary to our predictions, there was no significant main effect of

information type on consumers’ intention to exercise, F(3, 333) = .48, p = .696. Participants exposed to exercise information did not significantly differ from those exposed to nutrition information (M difference = -.07, SE = .25, p = 1.000, 95% CI [-.74, .60]), or no information (M difference

= -.20, SE = .26, p = 1.000, 95% CI [-.49, .90]). The same applied for participants exposed to nutrition plus exercise information. These did not significantly differ from participants in the

nutrition information condition (M difference = -.02, SE = .25, p = 1.000, 95% CI [-.69, .65]), and in

the control condition (M difference = .25, SE = .26, p = 1.000, 95% CI [-.43, .94]). Hence, Hb1 was

not supported. However, there was a small, but significant interaction between information type and product type on intention to exercise, F(3, 333) = 3.02, p = .030, Partial η2 = .03.

Participants in all conditions – except the nutrition information condition – showed greater intention to exercise when shown high-fat products, than low-fat ones (Table 4).

Fig. 15 Moderated mediation and direct effects for Intention to choose a product. ***Indicates significant

results.

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Table 4 Differences across conditions regarding the interaction effect of product type and information type Product type Low-fat High-fat Information type M SD M SD Nutrition information 4.32 1.70 4.02 1.91 Exercise information 3.91 1.92 4.28 1.86

Nutrition plus exercise

information 4.04 1.90 4.23 1.91

No information 3.84 1.85 3.91 1.94

Mediation. The indirect effect of information resistance was not significant for those

exposed to nutrition information, β = 0.02, SE = .10, 95% CI [-0.18, 0.22], exercise

information β = 0.14, SE = .11, 95% CI [-0.7, 0.35], and nutrition plus exercise information β = 0.04, SE = .11, 95% CI [-0.18, 0.25]. H2b was not supported.

Moderation. The interaction between information type and on-/off-pack information

hypothesised in the present study was also not significant, F(3, 333) = 1.47, p = .222.

Participants receiving exercise information off-pack (M = 3.75, SE = .27), did not have greater intention to exercise, compared to those receiving the same information on-pack (M = 4.42, SE = .26). H2b was hence not supported. Yet, a small, but significant three-way interaction effect for product type, information type, and on-/off pack information was found, F(3, 333) = 3.66, p = .013, Partial η2 = .03 (Table 5). In particular, when exposed to low-fat products,

participants’ intention to exercise when shown nutrition information, nutrition plus exercise information, or no information did not differ considerably with respect to on-/off-pack information (Figure 5). However, for the same product type, the difference in intention to exercise after exposure to exercise information either on- or off-pack was indeed substantial. Participants exposed to exercise information for low-fat products had greater intention to exercise when the information was shown on-pack than off-pack. Exposing participants to high-fat products revealed other patterns with reference to on-/off-pack information and

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information type. Particularly, for high-fat products, on-pack information triggered greater intention to exercise for those exposed to nutrition information and exercise information, compared to those exposed to the same information types off-pack (Figure 6).

Table 5 Differences across conditions for the three-way interaction of information type, on-/off-pack

information, and product type on intention to exercise

Product type Information type On-/off-pack information M SE

Low-fat product

off-pack 4.37 .28

off-pack 3.58 .30

off-pack 4.07 .28

off-pack 3.87 .29

High-fat product

off-pack 3.46 .28

off-pack 3.92 .30

off-pack 4.36 .29

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Moderated mediation. The interaction between information type and on-/off-pack

information on the mediating role of information resistance between information type and intention to exercise was not significant. Participants exposed to exercise information off-pack did not have greater intention to exercise (M = 0.05, SE = .14, 95% CI [-0.23, 0.33]), compared to those exposed to the same information on-pack (M = 0.23, SE = .16, 95% CI [-Fig. 6 Profile plot for the three-way interaction between product type, information type, and

on-/off-pack information on intention to exercise. The values reported refer to high-fat products.

Fig. 5 Profile plot for the three-way interaction between product type, information type,

and on-/off-pack information on intention to exercise. The values reported refer to low-fat products.

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0.10, 0.54]) because of reduced information resistance. Participants in the nutrition plus exercise condition did not have greater intention to choose a product when exposed to

information off-pack (M = 0.04, SE = .15, 95% CI [-0.25, 0.33]), than on-pack (M = 0.04, SE = .16, 95% CI [-0.28, 0.36]) because of minimised information resistance. H4b was not supported.

Discussion

The general aim of our study was to acquire greater understanding of the role of exercise information included on food labels. Shifting the focus onto consumers’ intention to choose a product and to exercise, we integrated the notion of information resistance (Knowles & Linn, 2004) to explain the mixed results found in literature investigating exercise

information (Campos et al., 2011; Van Kleef et al., 2007). We also suggested a solution to mitigate consumers’ resistance to exercise information, which consists in dislocating the information off-pack (Van Kleef et al., 2007).

Building upon previous literature addressing the potential auxiliary role of exercise information (Hawley et al., 2012; Kelly et al., 2009; Watson et al., 2014), we hypothesised that labels including exercise information would lead to increased intention to choose a product and to exercise, compared to those lacking such an information. In line with theory investigating resistance and persuasion (Knowles & Linn, 2004; Tannebaum et al., 2015), we predicted that exercise information would decrease consumers’ intention to choose a product and to exercise because of greater resistance to such information. Evidence for this effect has been shown in literature addressing consumers’ emphasis on (distressing) information content (Van Kleef et al., 2007). Based on issues of information appropriateness found in Van Kleef et al. (2007), we hypothesised that transferring exercise information off-pack would decrease consumers’ information resistance and therefore result in increased intention to choose a product and to exercise. These assumptions were tested through an online experimental study

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in which two product types (i.e, three low-fat products and three high-fat products) were employed.

Interesting points emerged when taking into account product type. Exercise

information displayed on high-fat products increased consumers’ intention to choose them, as opposed to exercise information displayed on products low in fat. Such findings can be explained by the licensing effect (Khan & Dhar, 2006; Septianto, 2017). Exposing consumers to a virtuous act (e.g., knowing the type and amount of physical activity to perform), licenses them to indulge in a less virtuous behaviour (e.g., choosing high-fat products over low-fat ones; Khan & Dhar, 2006). Our study revealed that consumers exposed to exercise

information tended to choose the less healthy option (i.e., high-fat products) because they knew how to compensate such a choice (i.e., by exercising). The same logic applied when intention to exercise was measured. In all conditions – except the nutrition information condition – participants had greater intentions to exercise after exposure to high-fat products.

Other findings pertaining to the inclusion/exclusion – next to exercise information – of on- and off-pack nutrition information emerged for both low- and high-products. Consumers’ intention to choose low-fat products was stable when exercise information or nutrition plus exercise information was displayed on-pack. However, their intention to choose low-fat products decreased when exercise information was presented off-pack, compared to on-pack. These findings partly explain how the lack of information about nutrients prevents consumers from making healthy food choices (Miller & Cassady, 2012). As for the combination of nutrition plus exercise information, consumers showed greater intention to choose low-fat products when such information was presented off-pack. In order to interpret the findings for off-pack information, further investigation on the role of on-/off-pack information is needed (see Campos et al., 2011). As for intention to exercise, the same pattern was observed after exposure to low- and high-fat products for exercise information and nutrition plus exercise

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information. In the off-pack information condition, participants receiving nutrition plus exercise information had greater intention to exercise, compared to those exposed to exercise information only. However, the opposite happened when the information was presented on-pack; participants’ intention to exercise decreased when shown nutrition plus exercise information, as opposed to exercise information only. This provides potential support for the benefits of relocating exercise information off-pack, and for the need to combine nutrition and exercise information addressed in literature.

Our study is the first to use a quantitative approach to investigate the implications of integrating exercise information into food labels. It is also the first to include complete exercise information, which takes into account average body weight and gender, and type, amount and duration of the task to perform. Our work extends the body of research on on-/off-pack information currently existing. Considered the proposed theoretical shift in

measuring intention, our study provides more real-life insights into consumer behaviour with respect to their food- and exercise-related intentions.

Limitations and future research

This study has several limitations. First, part of the stimulus material was adapted for the purpose of the study. This might have impacted participants’ level of resistance to product information, causing misbelief, doubting, counter-arguing (Van Reijmersdal et al., 2016). Future research might consider including real (yet still comparable) stimulus material to neutralise potential resistance.

Second, the self-reported measures used in the present study to measure intentions (Davis & Warshaw, 1992; Rijmersdal et al., 2016) might have been biased by social desirability. Future research should consider measuring less biased constructs such as

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Bagchi, & Ford, 2004). Additional research should attempt to extend the scales currently existing for intention to exercise (e.g., Psouni et al., 2016).

Third, our study might have produced different results in a more ecologically valid environment (e.g., supermarket).

Theoretical and practical implications

This study adds to the literature in several ways. First, it provides plausible

explanations for the inconsistent findings for exercise information, by integrating strategies to resist to persuasion (Zuwerink Jacks & Cameron, 2003) and defensive avoidance behaviours (Tannenbaum et al., 2015). Second, it yields interesting insights into the compensating mechanisms triggered after exposure to high-fat products and exercise information, which further underline the link between eating and exercising (Olivares et al., 2004).

For marketers, product developers, and app developers, layout of food labels, type of information displayed, and additional features on product packaging and mobile apps (e.g., health claims, goal-setting, progress-tracking; De Bruijn et al. 2017; Rothman, Sheeran, & Wood, 2009) require special attention. Presenting relevant product information in a clear and understandable way is essential to enable consumers to make healthy food choices, and raise awareness on the consequences of unhealthy eating and lack of exercise. Further aspects related to health literacy and to how consumers visualise product information (Mackert, Champlin, Pasch, & Weiss, 2013) will provide revealing insights on consumer behaviour and will potentially enable experts to design ad hoc content for a personalised consumer

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Appendix A

Fig. 1 Example of the energy-in/energy-out ratio (Van Kleef et al.,

2007).

Fig. 2 Example of the Traffic Light (TL) label system (Hersey et al.,

2013).

Fig. 1A Example of the energy-in/energy-out ratio (Van Kleef

et al., 2007).

Fig. 2A Example of the Traffic Light (TL) label system (Hersey

et al., 2013). Such a label system distinguishes good (green), medium (yellow), and harmful (red) amount of fat, saturated fat, sugars, and salt with respect to the recommended daily amount.

Fig. 3A Example of the Guideline Daily Amount (GDA) label

system (Hersey et al., 2013). Such a label system provides information on the extent to which the calories, sugars, fat, saturates, and salt contained in the product add up to the recommended daily amount.

Fig. 3 Example of the Guideline Daily Amount (GDA) label system

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Appendix B

Description of the creation of exercise information

Data concerning the average female/male body weight was retrieved from a study on German population – the second most represented country in the Netherlands after Dutch population (Huberts & De Coningh, 2018) – published in the website wissen.de (2012). This was

justified by inconsistent values found for the Dutch population. The Compendium of Physical Activities (Ainsworth et al., 2011) was used to retrieve MET values. It includes a list of activity categories (e.g., bicycling, home activities, running, and walking) associated to MET values. These latter were used – together with body weight – to calculate the amount and type of physical activity to perform in order to burn calories (Table 1B).

Table 1B Texts and equation used to create exercise information

Product Exercise information

(men) Exercise information (women)

Danone Greek yoghurt Oikos plain

(80 cal) Twix fun size

(80 cal)

In order to burn 80 cal., a man should climb the stairs at a slow pace for 15 minutes

In order to burn 80 cal., a woman should walk at a brisk pace for 15 minutes

Eden Foods organic kidney beans

(150 cal) Lay’s chips classic

(150 cal)

In order to burn 150 cal., a man should walk at a fast pace for 15 minutes.

In order to burn 150 cal., a woman should run at a slow pace for 15 minutes

Quaker maple oatmeal (190 cal) Ahoy chocolate chips

(190 cal)

In order to burn 190 cal., a man should engage in cross country running for 15 minutes

In order to burn 190 cal., a woman should run at a brisk pace for 15 minutes

Note: Equation: MET * weight in Kg = calories/hour

By dividing by 2, calories/half an hour; by dividing by 4, calories/15 minutes. In the table, we considered (MET*weight)/4.

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Appendix C Layout

On the one hand, elements not related to nutrition information per se (e.g., health claims, product quality certifications) were removed from the on-pack condition. The same applied to features displayed in the mobile app (e.g., serving size, percent of daily goals). On the other hand, information about the recommended daily amount was integrated into the off-pack condition for the sake of comparability to the on-pack condition.

Design

The colour of the boxes pertaining to calories typical of the on-pack condition was changed into light blue to distinguish them from the boxes referring to nutrients. The same changes were made for off-pack condition displaying exercise information. Since no nutrient-related data was included on the pie chart, this latter only contained calorie-related information displayed in light blue.

Product information

The amount of calories of some low- or high-fat products were adapted to their counterpart, so that the two products displayed the same values. The percentage of low-fat products that had 0% fat was changed into 1%. This allowed such a percentage to be displayed in the pie chart within the off-pack condition – in compliance with the layout of TL system – and made such information comparable to the on-pack condition.

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Table 1C On-pack nutrition information

Low-fat products High-fat products

(80 cal) Twix fun size (80 cal)

(150 cal) Lay’s chips classic (150 cal)

Quaker maple oatmeal

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Table 2C On-pack exercise information

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Table 3C On-pack nutrition and exercise information

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Table 4C On-pack no information (control)

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Table 5C Off-pack nutrition information

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Table 6C Off-pack exercise information

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Table 7C Off-pack nutrition and exercise information

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Table 8C Off-pack no information (control)

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Appendix D

Principal axis factoring analysis for Intention to choose a product

KMO and Bartlett's tests were carried out to assess, respectively, whether the sample was adequate and whether the assumption of sphericity (i.e. the variances of the differences between all combinations of related groups are equal) would hold. The sample was adequate (KMO = .91), and the test of sphericity was significant (p <.001). The principal axis factoring analysis showed one factor (Eigenvalue = 4.39). All the five items related to Intention to choose healthy products loaded on one factor (Table 1D). The scree plot showed one

component after the point of inflexion. Overall, the factor explained 87.83% of the variance. The item I want to buy the product had the strongest association (factor loading .958).

Table 1D Factor loadings based on a principal axis factoring analysis for five items from intention to

choose a product measures (N = 341)

Item Intention to choose a product

I want to buy the product .958

I will choose the product .939

I intend to choose the product .914

I will look for the product in the supermarket .902

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Principal axis factoring analysis for Intention to exercise

KMO and Bartlett's tests were carried out to assess, respectively, whether the sample was adequate and whether the assumption of sphericity (i.e. the variances of the differences between all combinations of related groups are equal) would hold. The sample was adequate (KMO = .83), and the test of sphericity was significant (p <.001). The principal axis factoring analysis showed one factor (Eigenvalue = 3.72). All the five items related to Intention to choose healthy products loaded on one factor (Table 2D). The scree plot showed one

component after the point of inflexion. Overall, the factor explained 92.90% of the variance. The item I am determined to exercise after consuming the product had the strongest

association (factor loading .972).

Table 2D Factor loadings based on a principal axis factoring analysis for four items for intention to

exercise (N = 341)

Item Intention to exercise

I am determined to exercise after consuming the product .972

I will exercise after consuming the product .956

I will try to exercise after consuming the product .940

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Principal axis factoring analysis for cognitive and affective resistance

KMO and Bartlett's tests were carried out to assess, respectively, whether the sample was adequate and whether the assumption of sphericity (i.e. the variances of the differences between all combinations of related groups are equal) would hold. The sample was adequate (KMO = .90), and the test of sphericity was significant (p <.001). The principal axis factoring analysis showed two factors with an Eigenvalue greater than one (Eigenvalue = 5.59,

Eigenvalue = 1.15). The Oblimin rotation (which assumes constructs to be related to each other) also showed two factors. Four items related to cognitive resistance loaded on the first factor; four items concerning affective resistance loaded on the second factor (Table 3D). Nevertheless, the scree plot (Figure 1D) showed only one component after the point of inflexion. The item While looking at the product information, I contested it had the strongest association (factor loading -.95). The item The product information made me feel unmotivated had a factor loading equal to .90.

Table 3D Factor loadings based on a principal axis factoring analysis with oblimin rotation for four

items from cognitive resistance measures, and four items for affective resistance measures (N = 341)

Cognitive resistance Affective resistance

While looking at the product information, I contested it -.949

While looking at the product information, I refuted it -.910

While looking at the product information, I countered it -.903

While looking at the product information, I doubted it -.657

The product information made me feel unmotivated .902

The product information was distressing .885

The product information made me feel guilty .866

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Table 4D Factor loadings based on a principal axis factoring analysis for eight items for resistance (N

= 341)

Resistance

While looking at the product information, I refuted it .855

While looking at the product information, I doubted it .845

The product information was annoying .834

While looking at the product information, I countered it .833

The product information made me feel unmotivated .812

The product information was distressing .812

The product information made me feel guilty .788

While looking at the product information, I contested it .777

Fig. 1D Scree plot from the principal axis factoring analysis with cognitive and

affective resistance.

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Appendix E

Fig. 10 PROCESS macro, Model 4: Mediation (Hayes, 2016).

Fig. 11 PROCESS macro, Model 8: Moderated mediation (Hayes,

2016).

Fig. 1E PROCESS macro, Model 4: Mediation (Hayes, 2016).

Fig. 2E PROCESS macro, Model 8: Moderated mediation